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  • 251. Tahvildari, Babak
    et al.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Alonso, Angel A.
    Hasselmo, Michael E.
    Switching between on and off states of persistent activity in lateral entorhinal layer III neurons2007Inngår i: Hippocampus, ISSN 1050-9631, E-ISSN 1098-1063, Vol. 17, nr 4, s. 257-263Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Persistent neural spiking maintains information during a, working memory task when a stimulus is no longer present. During I retention, this activity needs to be stable to distractors. More importantly, when retention is no longer relevant, cessation of the activity is necessary to enable processing and retention of subsequent information. Here, by means of intracellular recording with sharp microelectrode in in vitro rat brain slices, we demonstrate that single principal layer III neurons of the lateral entorhinal cortex (EC) generate persistent spiking activity with a novel ability to reliably toggle between spiking activity and a silent state. Our data indicates that in the presence of muscarmic receptor activation, persistent activity following an excitatory input may be induced and that a subsequent excitatory input can terminate this activity and cause the neuron to return to a silent state. Moreover, application of inhibitory hyperpolarizing stimuli is neither able to decrease the frequency of the persistent activity nor terminate it. The persistent activity can also be initiated and terminated by synchronized synaptic stimuli of layer II/III of the perirhinal cortex. The neuronal ability to switch On and Off persistent activity may facilitate the concurrent representation of temporally segregated information arriving in the EC and being directed toward the hippocampus.

  • 252. Tarjuelo-Gutierrez, J.
    et al.
    Rodriguez-Vila, B.
    Pierce, D. M.
    Fastl, T. E.
    Verbrugghe, P.
    Fourneau, I.
    Maleux, G.
    Herijgers, P.
    Holzapfel, Gerhard A.
    KTH, Skolan för teknikvetenskap (SCI), Hållfasthetslära (Inst.).
    Gomez, E. J.
    High-quality conforming hexahedral meshes of patient-specific abdominal aortic aneurysms including their intraluminal thrombi2014Inngår i: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 52, nr 2, s. 159-168Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In order to perform finite element (FE) analyses of patient-specific abdominal aortic aneurysms, geometries derived from medical images must be meshed with suitable elements. We propose a semi-automatic method for generating conforming hexahedral meshes directly from contours segmented from medical images. Magnetic resonance images are generated using a protocol developed to give the abdominal aorta high contrast against the surrounding soft tissue. These data allow us to distinguish between the different structures of interest. We build novel quadrilateral meshes for each surface of the sectioned geometry and generate conforming hexahedral meshes by combining the quadrilateral meshes. The three-layered morphology of both the arterial wall and thrombus is incorporated using parameters determined from experiments. We demonstrate the quality of our patient-specific meshes using the element Scaled Jacobian. The method efficiently generates high-quality elements suitable for FE analysis, even in the bifurcation region of the aorta into the iliac arteries. For example, hexahedral meshes of up to 125,000 elements are generated in less than 130 s, with 94.8 % of elements well suited for FE analysis. We provide novel input for simulations by independently meshing both the arterial wall and intraluminal thrombus of the aneurysm, and their respective layered morphologies.

  • 253.
    The, Matthew
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Statistical and machine learning methods to analyze large-scale mass spectrometry data2018Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Modern biology is faced with vast amounts of data that contain valuable information yet to be extracted. Proteomics, the study of proteins, has repositories with thousands of mass spectrometry experiments. These data gold mines could further our knowledge of proteins as the main actors in cell processes and signaling. Here, we explore methods to extract more information from this data using statistical and machine learning methods.

    First, we present advances for studies that aggregate hundreds of runs. We introduce MaRaCluster, which clusters mass spectra for large-scale datasets using statistical methods to assess similarity of spectra. It identified up to 40% more peptides than the state-of-the-art method, MS-Cluster. Further, we accommodated large-scale data analysis in Percolator, a popular post-processing tool for mass spectrometry data. This reduced the runtime for a draft human proteome study from a full day to 10 minutes.

    Second, we clarify and promote the contentious topic of protein false discovery rates (FDRs). Often, studies report lists of proteins but fail to report protein FDRs. We provide a framework to systematically discuss protein FDRs and take away hesitance. We also added protein FDRs to Percolator, opting for the best-peptide approach which proved superior in a benchmark of scalable protein inference methods.

    Third, we tackle the low sensitivity of protein quantification methods. Current methods lack proper control of error sources and propagation. To remedy this, we developed Triqler, which controls the protein quantification FDR through a Bayesian framework. We also introduce MaRaQuant, which proposes a quantification-first approach that applies clustering prior to identification. This reduced the number of spectra to be searched and allowed us to spot unidentified analytes of interest. Combining these tools outperformed the state-of-the-art method, MaxQuant/Perseus, and found enriched functional terms for datasets that had none before.

  • 254.
    The, Matthew
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi.
    Käll, Lukas
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi.
    Distillation of label-free quantification data by clustering and Bayesian modelingManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    In shotgun proteomics, the amount of information that can be extracted from label-free quantification experiments is typically limited by the identification rate as well as the noise level of the quantitative signals. This generally causes a low sensitivity in differential expression analysis on protein level. Here, we present a new method, MaRaQuant, in which we reverse the typical identification-first workflow into a quantification-first approach. Specifically, we apply unsupervised clustering on both MS1 and MS2 level to summarize all analytes of interest without assigning identities. This ensures that no valuable information is discarded due to analytes missing identification thresholds and allows us to spend more effort on the identification process due to the data reduction achieved by clustering. Furthermore, we propagate error probabilities from feature level all the way to protein level and input these to our probabilistic protein quantification method, Triqler. Applying this methodology to an engineered dataset, we managed to identify multiple analytes of interest that would have gone unnoticed in traditional pipelines, specifically, through the use of open modification and de novo searches. MaRaQuant/Triqler obtains significantly more identifications on all levels compared to MaxQuant/Perseus, including differentially expressed proteins. Notably, we managed to identify differentially expressed proteins in a clinical dataset where previously none were discovered. Furthermore, our differentially expressed proteins allowed us to attribute multiple functional annotation terms to both clinical datasets that we investigated.

  • 255.
    The, Matthew
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi.
    Käll, Lukas
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Genteknologi.
    Integrated identification and quantification error probabilities for shotgun proteomicsManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Protein quantification by label-free shotgun proteomics experiments is plagued by a multitude of error sources. Typical pipelines for identifying differentially expressed proteins use intermediate filters in an attempt to control the error rate. However, they often ignore certain error sources and, moreover, regard filtered lists as completely correct in subsequent steps. These two indiscretions can easily lead to a loss of control of the false discovery rate (FDR). We propose a probabilistic graphical model, Triqler, that propagates error information through all steps, employing distributions in favor of point estimates, most notably for missing value imputation. The model outputs posterior probabilities for fold changes between treatment groups, highlighting uncertainty rather than hiding it. We analyzed 3 engineered datasets and achieved FDR control and high sensitivity, even for truly absent proteins. In a bladder cancer clinical dataset we discovered 35 proteins at 5% FDR, with the original study discovering none at this threshold. Compellingly, these proteins showed enrichment for functional annotation terms. The model executes in minutes and is freely available at https://pypi.org/project/triqler/.

  • 256.
    The, Matthew
    et al.
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Käll, Lukas
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    MaRaCluster: A Fragment Rarity Metric for Clustering Fragment Spectra in Shotgun Proteomics2016Inngår i: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 15, nr 3, s. 713-720Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Shotgun proteomics experiments generate large amounts of fragment spectra as primary data, normally with high redundancy between and within experiments. Here, we have devised a clustering technique to identify fragment spectra stemming from the same species of peptide. This is a powerful alternative method to traditional search engines for analyzing spectra, specifically useful for larger scale mass spectrometry studies. As an aid in this process, we propose a distance calculation relying on the rarity of experimental fragment peaks, following the intuition that peaks shared by only a few spectra offer more evidence than peaks shared by a large number of spectra. We used this distance calculation and a complete-linkage scheme to cluster data from a recent large-scale mass spectrometry-based study. The clusterings produced by our method have up to 40% more identified peptides for their consensus spectra compared to those produced by the previous state-of-the-art method. We see that our method would advance the construction of spectral libraries as well as serve as a tool for mining large sets of fragment spectra. The source code and Ubuntu binary packages are available at https://github.com/ statisticalbiotechnology/maracluster (under an Apache 2.0 license).

  • 257.
    Tigerholm, Jenny
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Börjesson, Sara
    Division of Cell Biology, Department of Clinical and Experimental Medicine, Linköping University.
    Lundberg, Linnea
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Elinder, Fredrik
    Division of Cell Biology, Department of Clinical and Experimental Medicine, Linköping University.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Dampening of Hyperexcitability in CA1 Pyramidal Neurons by Polyunsaturated Fatty Acids Acting on Voltage-Gated Ion Channels2012Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, nr 9, s. e44388-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A ketogenic diet is an alternative treatment of epilepsy in infants. The diet, rich in fat and low in carbohydrates, elevates the level of polyunsaturated fatty acids (PUFAs) in plasma. These substances have therefore been suggested to contribute to the anticonvulsive effect of the diet. PUFAs modulate the properties of a range of ion channels, including K and Na channels, and it has been hypothesized that these changes may be part of a mechanistic explanation of the ketogenic diet. Using computational modelling, we here study how experimentally observed PUFA-induced changes of ion channel activity affect neuronal excitability in CA1, in particular responses to synaptic input of high synchronicity. The PUFA effects were studied in two pathological models of cellular hyperexcitability associated with epileptogenesis. We found that experimentally derived PUFA modulation of the A-type K (K-A) channel, but not the delayed-rectifier K channel, restored healthy excitability by selectively reducing the response to inputs of high synchronicity. We also found that PUFA modulation of the transient Na channel was effective in this respect if the channel's steady-state inactivation was selectively affected. Furthermore, PUFA-induced hyperpolarization of the resting membrane potential was an effective approach to prevent hyperexcitability. When the combined effect of PUFA on the K-A channel, the Na channel, and the resting membrane potential, was simulated, a lower concentration of PUFA was needed to restore healthy excitability. We therefore propose that one explanation of the beneficial effect of PUFAs lies in its simultaneous action on a range of ion-channel targets. Furthermore, this work suggests that a pharmacological cocktail acting on the voltage dependence of the Na-channel inactivation, the voltage dependences of K-A channels, and the resting potential can be an effective treatment of epilepsy.

  • 258.
    Tigerholm, Jenny
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    KA channels reduce dendritic depolarization from synchronized synaptic input: implication for neural processing and epilepsy2008Inngår i: BMC neuroscience (Online), ISSN 1471-2202, E-ISSN 1471-2202, Vol. 9, nr Suppl 1, s. P45-Artikkel i tidsskrift (Fagfellevurdert)
  • 259.
    Tigerholm, Jenny
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    KA channels suppress cellular responses to fast ripple activity – implications for epilepsy2009Inngår i: BMC neuroscience (Online), ISSN 1471-2202, E-ISSN 1471-2202, Vol. 10, nr Suppl 1, s. P226-Artikkel i tidsskrift (Fagfellevurdert)
  • 260.
    Tigerholm, Jenny
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Reversing Nerve Cell Pathology by Optimizing Modulatory Action on Target Ion Channels2011Inngår i: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 101, nr 8, s. 1871-1879Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In diseases of the brain, the distribution and properties of ion channels display deviations from healthy control subjects. We studied three cases of ion channel alteration related to epileptogenesis. The first case of ion channel alteration represents an enhanced sodium current, the second case addresses the downregulation of the transient potassium current K(A), and the third case relates to kinetic properties of K(A) in a patient with temporal lobe epilepsy. Using computational modeling and optimization, we aimed at reversing the pathological characteristics and restoring normal neural function by altering ion channel properties. We identified two key aspects of neural dysfunction in epileptogenesis: an enhanced response to synaptic input in general and to highly synchronized synaptic input in particular. In previous studies, we showed that the potassium channel K(A) played a major role in neural responses to highly synchronized input. It was therefore selected as the target upon which modulators would act. In biophysical simulations, five experimentally characterized endogenous modulations on the K(A) channel were included. Relative concentrations of these modulators were controlled by a numerical optimizer that compared model output to predefined neural output, which represented a normal physiological response. Several solutions that restored the neuron function were found. In particular, distinct subtype compositions of the auxiliary proteins Kv channel-interacting proteins 1 and dipeptidyl aminopeptidase-like protein 6 were able to restore changes imposed by the enhanced sodium conductance or suppressed K(A) conductance. Moreover, particular combinations of protein kinese C, calmodulin-dependent protein kinase II, and arachidonic acid were also able to restore these changes as well as the channel pathology found in a patient with temporal lobe epilepsy. The solutions were further analyzed for sensitivity and robustness. We suggest that the optimization procedure can be used not only for neurons, but also for other organs with excitable cells, such as the heart and pancreas where channelopathies are found.

  • 261.
    Tigerholm, Jenny
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Migliore, Michele
    Institute of Biophysics, National Research Council.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Integration of synchronous synaptic input in CA1 pyramidal neuron depends on spatial and temporal distributions of the input2013Inngår i: Hippocampus, ISSN 1050-9631, E-ISSN 1098-1063, Vol. 23, nr 1, s. 87-99Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Highly synchronized neural firing has been discussed in relation to learning and memory, for instance sharp-wave activity in hippocampus. We were interested to study how a postsynaptic CA1 pyramidal neuron would integrate input of different levels of synchronicity. In previous work using computational modeling we studied how the integration depends on dendritic conductances. We found that the transient A-type potassium channel KA was able to selectively suppress input of high synchronicity. In recent years, compartmentalization of dendritic integration has been shown. We were therefore interested to study the influence of localization and pattern of synaptic input over the dendritic tree of the CA1 pyramidal neuron. We find that the selective suppression increases when synaptic inputs are placed on oblique dendrites further out from the soma. The suppression also increases along the radial axis from the apical trunk out to the end of oblique dendrites. We also find that the KA channel suppresses the occurrence of dendritic spikes. Moreover, recent studies have shown interaction between synaptic inputs. We therefore studied the influence of apical tuft input on the integration studied above. We find that excitatory input provides a modulatory influence reducing the capacity of KA to suppress synchronized activity, thus facilitating the excitatory drive of oblique dendritic input. Conversely, inhibitory tuft input increases the suppression by KA providing a larger control of oblique depolarizing factors on the CA1 pyramidal neuron in terms of what constitutes the most effective level of synchronicity. Furthermore, we show that the selective suppression studied above depends on the conductance of the KA channel. KA, as several other potassium channels, is modulated by several neuromodulators, for instance acetylcholine and dopamine, both of which have been discussed in relation to learning and memory. We suggest that dendritic conductances and their modulatory systems may be part of the regulation of processing of information, in particular for how network synchronicity affects learning and memory.

  • 262.
    Tigerholm, Jenny
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm Brain Institute, Sweden.
    Petersson, Marcus E.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm Brain Institute, Sweden.
    Obreja, Otilia
    Eberhardt, Esther
    Namer, Barbara
    Weidner, Christian
    Lampert, Angelika
    Carr, Richard
    Schmelz, Martin
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm Brain Institute, Sweden.
    C-Fiber Recovery Cycle Supernormality Depends on Ion Concentration and Ion Channel Permeability2015Inngår i: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 108, nr 5, s. 1057-1071Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Following each action potential, C-fiber nociceptors undergo cyclical changes in excitability, including a period of superexcitability, before recovering their basal excitability state. The increase in superexcitability during this recovery cycle depends upon their immediate firing history of the axon, but also determines the instantaneous firing frequency that encodes pain intensity. To explore the mechanistic underpinnings of the recovery cycle phenomenon a biophysical model of a C-fiber has been developed. The model represents the spatial extent of the axon including its passive properties as well as ion channels and the Na/K-ATPase ion pump. Ionic concentrations were represented inside and outside the membrane. The model was able to replicate the typical transitions in excitability from subnormal to supernormal observed empirically following a conducted action potential. In the model, supernormality depended on the degree of conduction slowing which in turn depends upon the frequency of stimulation, in accordance with experimental findings. In particular, we show that activity-dependent conduction slowing is produced by the accumulation of intraaxonal sodium. We further show that the supernormal phase results from a reduced potassium current K-dr as a result of accumulation of periaxonal potassium in concert with a reduced influx of sodium through Na(v)1.7 relative to Na(v)1.8 current. This theoretical prediction was supported by data from an in vitro preparation of small rat dorsal root ganglion somata showing a reduction in the magnitude of tetrodotoxin-sensitive relative to tetrodotoxin - resistant whole cell current. Furthermore, our studies provide support for the role of depolarization in supernormality, as previously suggested, but we suggest that the basic mechanism depends on changes in ionic concentrations inside and outside the axon. The understanding of the mechanisms underlying repetitive discharges in recovery cycles may provide insight into mechanisms of spontaneous activity, which recently has been shown to correlate to a perceived level of pain.

  • 263.
    Tigerholm, Jenny
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm Brain Institute, Stockholm, Sweden.
    Petersson, Marcus
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm Brain Institute, Stockholm, Sweden.
    Obreja, Otilia
    Anaesthesiology, Universitaetsmedizin Mannheim, Univ. of Heidelberg.
    Lampert, Angelika
    Inst. of Physiol. and Pathophysiology, Friedrich-Alexander-Uni versität Erlangen-Nürnberg.
    Carr, Richard
    Anaesthesiology, Universitaetsmedizin Mannheim, Univ. of Heidelberg.
    Schmelz, Martin
    Anaesthesiology, Universitaetsmedizin Mannheim, Univ. of Heidelberg,.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm Brain Institute, Stockholm, Sweden.
    Modeling activity-dependent changes of axonal spike conduction in primary afferent C-nociceptors2014Inngår i: Journal of Neurophysiology, ISSN 0022-3077, E-ISSN 1522-1598, Vol. 111, nr 9, s. 1721-1735Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Action potential initiation and conduction along peripheral axons is a dynamic process that displays pronounced activity dependence. In patients with neuropathic pain, differences in the modulation of axonal conduction velocity by activity suggest that this property may provide insight into some of the pathomechanisms. To date, direct recordings of axonal membrane potential have been hampered by the small diameter of the fibers. We have therefore adopted an alternative approach to examine the basis of activity-dependent changes in axonal conduction by constructing a comprehensive mathematical model of human cutaneous C-fibers. Our model reproduced axonal spike propagation at a velocity of 0.69 m/s commensurate with recordings from human C-nociceptors. Activity-dependent slowing (ADS) of axonal propagation velocity was adequately simulated by the model. Interestingly, the property most readily associated with ADS was an increase in the concentration of intra-axonal sodium. This affected the driving potential of sodium currents, thereby producing latency changes comparable to those observed for experimental ADS. The model also adequately reproduced post-action potential excitability changes (i.e., recovery cycles) observed in vivo. We performed a series of control experiments replicating blockade of particular ion channels as well as changing temperature and extracellular ion concentrations. In the absence of direct experimental approaches, the model allows specific hypotheses to be formulated regarding the mechanisms underlying activity-dependent changes in C-fiber conduction. Because ADS might functionally act as a negative feedback to limit trains of nociceptor activity, we envisage that identifying its mechanisms may also direct efforts aimed at alleviating neuronal hyperexcitability in pain patients.

  • 264.
    Toledo-Suarez, Carlos
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Duarte, Renato
    Morrison, Abigail
    Liquid computing on and off the edge of chaos with a striatal microcircuit2014Inngår i: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 8, artikkel-id 130Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In reinforcement learning theories of the basal ganglia, there is a need for the expected rewards corresponding to relevant environmental states to be maintained and modified during the learning process. However, the representation of these states that allows them to be associated with reward expectations remains unclear. Previous studies have tended to rely on pre-defined partitioning of states encoded by disjunct neuronal groups or sparse topological drives. A more likely scenario is that striatal neurons are involved in the encoding of multiple different states through their spike patterns, and that an appropriate partitioning of an environment is learned on the basis of task constraints, thus minimizing the number of states involved in solving a particular task. Here we show that striatal activity is sufficient to implement a liquid state, an important prerequisite for such a computation, whereby transient patterns of striatal activity are mapped onto the relevant states. We develop a simple small scale model of the striatum which can reproduce key features of the experimentally observed activity of the major cell types of the striatum. We then use the activity of this network as input for the supervised training of four simple linear readouts to learn three different functions on a plane, where the network is stimulated with the spike coded position of the agent. We discover that the network configuration that best reproduces striatal activity statistics lies on the edge of chaos and has good performance on all three tasks, but that in general, the edge of chaos is a poor predictor of network performance.

  • 265.
    Torbaghan, Solmaz Shariat
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Yazdi, Daniel
    Mirpour, Koorosh
    Bisley, James W.
    Inhibition of return in a visual foraging task in non-human subjects2012Inngår i: Vision Research, ISSN 0042-6989, E-ISSN 1878-5646, Vol. 74, s. 2-9Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Inhibition of return is thought to help guide visual search by inhibiting the orienting of attention to previously attended locations. We have previously shown that, in a foraging visual search task, the neural responses to objects in parietal cortex are reduced after they have been examined. Here we ask whether the animals' reaction times (RTs) in the same task show a psychophysical correlate of inhibition of return: a slowing of reaction time in response to a probe placed at a previously fixated location. We trained three animals to perform an RT version of the visual foraging task. In the foraging task, subjects visually searched through an array of five identical distractors and five identical potential targets; one of which had a reward linked to it. In the RT variant of the task, subjects had to rapidly respond to a probe if it appeared. We found that RTs were slower for probes presented at locations that contained previously fixated objects, faster to potential targets and between the two for behaviorally irrelevant distractors that had not been fixated. These data show behavioral inhibitory tagging of previously fixated objects and suggest that the suppression of activity seen previously in the same task in parietal cortex could be a neural correlate of this mechanism.

  • 266.
    Tully, Philip
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Karolinska Institutet, Sweden; University of Edinburgh, UK.
    Lindén, Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Karolinska Institutet, Sweden.
    Hennig, Matthias
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm University, Stockholm; Karolinska Institutet, Sweden.
    Probabilistic computation underlying sequence learning in a spiking attractor memory network2013Inngår i: BMC neuroscience (Online), ISSN 1471-2202, E-ISSN 1471-2202, nr 14 (Suppl 1)Artikkel i tidsskrift (Fagfellevurdert)
  • 267. Tyrcha, Joanna
    et al.
    Hertz, John
    KTH, Centra, Nordic Institute for Theoretical Physics NORDITA.
    Network Inference With Hidden Units2014Inngår i: Mathematical Biosciences and Engineering, ISSN 1547-1063, E-ISSN 1551-0018, Vol. 11, nr 1, s. 149-165Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We derive learning rules for finding the connections between units in stochastic dynamical networks from the recorded history of a "visible" subset of the units. We consider two models. In both of them, the visible units are binary and stochastic. In one model the "hidden" units are continuous-valued, with sigmoidal activation functions, and in the other they are binary and stochastic like the visible ones. We derive exact learning rules for both cases. For the stochastic case, performing the exact calculation requires, in general, repeated summations over an number of configurations that grows exponentially with the size of the system and the data length, which is not feasible for large systems. We derive a mean field theory, based on a factorized ansatz for the distribution of hidden-unit states, which offers an attractive alternative for large systems. We present the results of some numerical calculations that illustrate key features of the two models and, for the stochastic case, the exact and approximate calculations.

  • 268. Ullah, I.
    et al.
    Karthik, G. -M
    Alkodsi, A.
    Kjällquist, U.
    Stålhammar, G.
    Lövrot, J.
    Martinez, N. -F
    Lagergren, Jens
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Hautaniemi, S.
    Hartman, J.
    Bergh, J.
    Evolutionary history of metastatic breast cancer reveals minimal seeding from axillary lymph nodes2018Inngår i: Journal of Clinical Investigation, ISSN 0021-9738, E-ISSN 1558-8238, Vol. 128, nr 4, s. 1355-1370Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Metastatic breast cancers are still incurable. Characterizing the evolutionary landscape of these cancers, including the role of metastatic axillary lymph nodes (ALNs) in seeding distant organ metastasis, can provide a rational basis for effective treatments. Here, we have described the genomic analyses of the primary tumors and metastatic lesions from 99 samples obtained from 20 patients with breast cancer. Our evolutionary analyses revealed diverse spreading and seeding patterns that govern tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, in which multiple metastatic subclones originated from the primary tumor and/or other distant metastases. Synchronous ALN metastasis, a well-established prognosticator of breast cancer, was not involved in seeding the distant metastasis, suggesting a hematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably an increase in apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like-associated (APOBEC-associated) mutagenesis. Our data provide genomic evidence for a role of ALN metastasis in seeding distant organ metastasis and elucidate the evolving mutational landscape during cancer progression.

  • 269.
    Ullah, Ikram
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Probabilistic Models for Species Tree Inference and Orthology Analysis2015Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    A phylogenetic tree is used to model gene evolution and species evolution using molecular sequence data. For artifactual and biological reasons, a gene tree may differ from a species tree, a phenomenon known as gene tree-species tree incongruence. Assuming the presence of one or more evolutionary events, e.g., gene duplication, gene loss, and lateral gene transfer (LGT), the incongruence may be explained using a reconciliation of a gene tree inside a species tree. Such information has biological utilities, e.g., inference of orthologous relationship between genes.

    In this thesis, we present probabilistic models and methods for orthology analysis and species tree inference, while accounting for evolutionary factors such as gene duplication, gene loss, and sequence evolution. Furthermore, we use a probabilistic LGT-aware model for inferring gene trees having temporal information for duplication and LGT events.

    In the first project, we present a Bayesian method, called DLRSOrthology, for estimating orthology probabilities using the DLRS model: a probabilistic model integrating gene evolution, a relaxed molecular clock for substitution rates, and sequence evolution. We devise a dynamic programming algorithm for efficiently summing orthology probabilities over all reconciliations of a gene tree inside a species tree. Furthermore, we present heuristics based on receiver operating characteristics (ROC) curve to estimate suitable thresholds for deciding orthology events. Our method, as demonstrated by synthetic and biological results, outperforms existing probabilistic approaches in accuracy and is robust to incomplete taxon sampling artifacts.

    In the second project, we present a probabilistic method, based on a mixture model, for species tree inference. The method employs a two-phase approach, where in the first phase, a structural expectation maximization algorithm, based on a mixture model, is used to reconstruct a maximum likelihood set of candidate species trees. In the second phase, in order to select the best species tree, each of the candidate species tree is evaluated using PrIME-DLRS: a method based on the DLRS model. The method is accurate, efficient, and scalable when compared to a recent probabilistic species tree inference method called PHYLDOG. We observe that, in most cases, the analysis constituted only by the first phase may also be used for selecting the target species tree, yielding a fast and accurate method for larger datasets.

    Finally, we devise a probabilistic method based on the DLTRS model: an extension of the DLRS model to include LGT events, for sampling reconciliations of a gene tree inside a species tree. The method enables us to estimate gene trees having temporal information for duplication and LGT events. To the best of our knowledge, this is the first probabilistic method that takes gene sequence data directly into account for sampling reconciliations that contains information about LGT events. Based on the synthetic data analysis, we believe that the method has the potential to identify LGT highways.

  • 270.
    Ullah, Ikram
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Parviainen, Pekka
    Lagergren, Jens
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Centra, SeRC - Swedish e-Science Research Centre.
    Species tree inference using a mixture model2015Inngår i: Molecular biology and evolution, ISSN 0737-4038, E-ISSN 1537-1719Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Species tree reconstruction has been a subject of substantial research due to its central role across biology and medicine. A species tree is often reconstructed using a set of gene trees or by directly using sequence data. In either of these cases, one of the main confounding phenomena is the discordance between a species tree and a gene tree due to evolutionary events such as duplications and losses. Probabilistic methods can resolve the discordance by co-estimating gene trees and the species tree but this approach poses a scalability problem for larger data sets.

    We present MixTreEM-DLRS: a two-phase approach for reconstructing a species tree in the presence of gene duplications and losses. In the first phase, MixTreEM, a novel structural EM algorithm based on a mixture model is used to reconstruct a set of candidate species trees, given sequence data for monocopy gene families from the genomes under study. In the second phase, PrIME-DLRS, a method based on the DLRS model ( ̊Akerborg et al., 2009), is used for selecting the best species tree. PrIME-DLRS can handle multicopy gene families since DLRS, apart from modeling sequence evolution, models gene duplication and loss using a gene evolution model (Arvestad et al., 2009).

    We evaluate MixTreEM-DLRS using synthetic and biological data, and compare its performance to a recent genome-scale species tree reconstruction method PHYLDOG (Boussau et al., 2013) as well as to a fast parsimony-based algorithm Duptree (Wehe et al., 2008). Our method is competitive with PHYLDOG in terms of accuracy and runs significantly faster and our method outperforms Duptree in accuracy. The analysis constituted by MixTreEM without DLRS may also be used for selecting the target species tree, yielding a fast and yet accurate algorithm for larger data sets. MixTreEM is freely available at http://prime.scilifelab.se/mixtreem.

  • 271.
    Ullah, Ikram
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Sjöstrand, Joel
    Andersson, Peter
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Sennblad, Bengt
    Lagergren, Jens
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Centra, SeRC - Swedish e-Science Research Centre.
    Integrating Sequence Evolution into Probabilistic Orthology Analysis2015Inngår i: Systematic Biology, ISSN 1063-5157, E-ISSN 1076-836X, Vol. 64, nr 6, s. 969-982Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Orthology analysis, that is, finding out whether a pair of homologous genes are orthologs - stemming from a speciation - or paralogs - stemming from a gene duplication - is of central importance in computational biology, genome annotation, and phylogenetic inference. In particular, an orthologous relationship makes functional equivalence of the two genes highly likely. A major approach to orthology analysis is to reconcile a gene tree to the corresponding species tree, (most commonly performed using the most parsimonious reconciliation, MPR). However, most such phylogenetic orthology methods infer the gene tree without considering the constraints implied by the species tree and, perhaps even more importantly, only allow the gene sequences to influence the orthology analysis through the a priori reconstructed gene tree. We propose a sound, comprehensive Bayesian MCMC-based method, DLRSOrthology, to compute orthology probabilities. It efficiently sums over the possible gene trees and jointly takes into account the current gene tree, all possible reconciliations to the species tree, and the, typically strong, signal conveyed by the sequences. We compare our method with PrIME-GEM, a probabilistic orthology approach built on a probabilistic duplication-loss model, and MrBayesMPR, a probabilistic orthology approach that is based on conventional Bayesian inference coupled with MPR. We find that DLRSOrthology outperforms these competing approaches on synthetic data as well as on biological data sets and is robust to incomplete taxon sampling artifacts.

  • 272. Undeman, Carl
    et al.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Fully Automatic Segmentation of MRI Brain Images using Probabilistic Anisotropic Diffusion and Multi-Scale Watersheds2003Rapport (Annet vitenskapelig)
    Abstract [en]

    This article presents a fully automatic method for segmenting the brain from other tissue in a 3-D MR image of the human head. The method is a an extension and combination of previous techniques, and consists of the following processing steps: (i) After an initial intensity normalization, an affine alignment is performed to a standard anatomical space, where the unsegmented image can be compared to a segmented standard brain. (ii) Probabilistic diffusion, guided by probability measures between white matter, grey matter and cerebrospinal fluid, is performed in order to suppress the influence of extra-cerebral tissue. (iii) A multi-scale watershed segmentation step creates a slightly over-segmented image, where the brain contour constitutes a subset of the watershed boundaries.(iv) A segmentation of the over-segmented brain is then selected by using spatial information from the pre-segmented standard brain in combination with additional stages of probabilistic diffusion, morphological operations and thresholding.

    The composed algorithm has been evaluated on 50 T1-weighted MR volumes, by visual inspection and by computing quantitative measures of (i) the similarity between the segmented brain and a manual segmentation of the same brain, and (ii) the ratio of the volumetric difference between automatically and manually segmented brains relative to the volume of the manually segmented brain. The mean value of the similarity index was 0.9961 with standard deviation 0.0034 (worst value 0.9813, best 0.9998). The mean percentage volume error was 0.77 % with standard deviation 0.69 % (maximum percentage error 3.81 %, minimum percentage error 0.05 %).

  • 273. Undeman, Carl
    et al.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Fully Automatic Segmentation of MRI Brain Images using Probabilistic Anisotropic Diffusion and Multi-Scale Watersheds2003Inngår i: Scale Space'03 Proceedings of the 4th International Conference on Scale space methods in computer vision, Springer Berlin/Heidelberg, 2003, Vol. 2695, s. 641-656Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This article presents a fully automatic method for segmenting the brain from other tissue in a 3-D MR image of the human head. The method is a an extension and combination of previous techniques, and consists of the following processing steps: (i) After an initial intensity normalization, an affine alignment is performed to a standard anatomical space, where the unsegmented image can be compared to a segmented standard brain. (ii) Probabilistic diffusion, guided by probability measures between white matter, grey matter and cerebrospinal fluid, is performed in order to suppress the influence of extra-cerebral tissue. (iii) A multi-scale watershed segmentation step creates a slightly over-segmented image, where the brain contour constitutes a subset of the watershed boundaries. (iv) A segmentation of the over-segmented brain is then selected by using spatial information from the pre-segmented standard brain in combination with additional stages of probabilistic diffusion, morphological operations and thresholding. The composed algorithm has been evaluated on 50 T1-weighted MR volumes, by visual inspection and by computing quantitative measures of (i) the similarity between the segmented brain and a manual segmentation of the same brain, and (ii) the ratio of the volumetric difference between automatically and manually segmented brains relative to the volume of the manually segmented brain. The mean value of the similarity index was 0.9961 with standard deviation 0.0034 (worst value 0.9813, best 0.9998). The mean percentage volume error was 0.77 % with standard deviation 0.69 % (maximum percentage error 3.81 %, minimum percentage error 0.05 %).

  • 274. Valentin, A.
    et al.
    Humphrey, J. D.
    Holzapfel, Gerhard A.
    KTH, Skolan för teknikvetenskap (SCI), Hållfasthetslära (Inst.).
    A finite element-based constrained mixture implementation for arterial growth, remodeling, and adaptation: Theory and numerical verification2013Inngår i: International Journal for Numerical Methods in Biomedical Engineering, ISSN 2040-7939, Vol. 29, nr 8, s. 822-849Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We implemented a constrained mixture model of arterial growth and remodeling in a nonlinear finite element framework to facilitate numerical analyses of diverse cases of arterial adaptation and maladaptation, including disease progression, resulting in complex evolving geometries and compositions. This model enables hypothesis testing by predicting consequences of postulated characteristics of cell and matrix turnover, including evolving quantities and orientations of fibrillar constituents and nonhomogenous degradation of elastin or loss of smooth muscle function. The nonlinear finite element formulation is general within the context of arterial mechanics, but we restricted our present numerical verification to cylindrical geometries to allow comparisons with prior results for two special cases: uniform transmural changes in mass and differential growth and remodeling within a two-layered cylindrical model of the human aorta. The present finite element model recovers the results of these simplified semi-inverse analyses with good agreement.

  • 275. Visell, Y.
    et al.
    Fontana, F.
    Giordano, B. L.
    Nordahl, R.
    Serafin, S.
    Bresin, Roberto
    KTH, Skolan för datavetenskap och kommunikation (CSC), Tal, musik och hörsel, TMH, Musikakustik.
    Sound design and perception in walking interactions2009Inngår i: International journal of human-computer studies, ISSN 1071-5819, E-ISSN 1095-9300, Vol. 67, nr 11, s. 947-959Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper reviews the state of the art in the display and perception of walking generated sounds and tactile vibrations, and their current and potential future uses in interactive systems. As non-visual information sources that are closely linked to human activities in diverse environments, such signals are capable of communicating about the spaces we traverse and activities we encounter in familial and intuitive ways However, in order for them to be effectively employed in human-computer interfaces, significant knowledge is required in areas including the perception of acoustic signatures of walking, and the design, engineering, and evaluation of interfaces that utilize them. Much of this expertise has accumulated in recent years, although many questions remain to be explored We highlight past work and current research directions in this Multidisciplinary area of investigation, and point to potential future trends.

  • 276. Vitale, Renzo
    et al.
    Bresin, Roberto
    KTH, Skolan för datavetenskap och kommunikation (CSC), Tal, musik och hörsel, TMH, Musikakustik.
    Emotional cues in knocking sounds2008Inngår i: Proc. of the 10th International Conference on Music Perception and Cognition, 2008, s. 276-Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The object of this research is to describe how temporal and dynamic cues in knocking sounds can communicate emotions, just like in expressive musical performances. An experiment has been conducted where several emotions were supposed to be expressed by different performers. Participants were asked to knock on a wooden door according to instructions. Knocking sounds have been recorded both outside and inside the room, and afterwards they were rated in listening tests. Together with acoustic measurements, arm movements during the knocking action were detected through a motion capture system, so that the body behaviour (visual component) could be correlated to the sound evaluation (acoustical component). Based on previous research on arm movements and music performance, ten different emotions were selected for investigation. Results confirm the use of the same strategies in both expressive everyday body gestures and expressive music performance. Listeners were able to perceive emotions to a large extent. Strong similarities between the use of acoustical features in knocking and music performance were found. The intended emotions were generally perceived correctly. Among the relevant acoustical features extracted from the recordings, rhythm and IOI as well as loudness revealed to be strong cues.

  • 277. Weidel, Philipp
    et al.
    Djurfeldt, Mikael
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Parallelldatorcentrum, PDC.
    Duarte, Renato C.
    Morrison, Abigail
    Closed Loop Interactions between Spiking Neural Network and Robotic Simulators Based on MUSIC and ROS2016Inngår i: Frontiers in Neuroinformatics, ISSN 1662-5196, E-ISSN 1662-5196, Vol. 10, artikkel-id 31Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In order to properly assess the function and computational properties of simulated neural systems, it is necessary to account for the nature of the stimuli that drive the system. However, providing stimuli that are rich and yet both reproducible and amenable to experimental manipulations is technically challenging, and even more so if a closed-loop scenario is required. In this work, we present a novel approach to solve this problem, connecting robotics and neural network simulators. We implement a middleware solution that bridges the Robotic Operating System (ROS) to the Multi-Simulator Coordinator (MUSIC). This enables any robotic and neural simulators that implement the corresponding interfaces to be efficiently coupled, allowing real-time performance for a wide range of configurations. This work extends the toolset available for researchers in both neurorobotics and computational neuroscience, and creates the opportunity to perform closed-loop experiments of arbitrary complexity to address questions in multiple areas, including embodiment, agency, and reinforcement learning.

  • 278.
    Westerlund, Annie M.
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Delemotte, Lucie
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Effect of Ca2+on the promiscuous target-protein binding of calmodulin2018Inngår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 14, nr 4, artikkel-id e1006072Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Calmodulin (CaM) is a calcium sensing protein that regulates the function of a large number of proteins, thus playing a crucial part in many cell signaling pathways. CaM has the ability to bind more than 300 different target peptides in a Ca2+-dependent manner, mainly through the exposure of hydrophobic residues. How CaM can bind a large number of targets while retaining some selectivity is a fascinating open question. Here, we explore the mechanism of CaM selective promiscuity for selected target proteins. Analyzing enhanced sampling molecular dynamics simulations of Ca2+-bound and Ca2+-free CaM via spectral clustering has allowed us to identify distinct conformational states, characterized by interhelical angles, secondary structure determinants and the solvent exposure of specific residues. We searched for indicators of conformational selection by mapping solvent exposure of residues in these conformational states to contacts in structures of CaM/target peptide complexes. We thereby identified CaM states involved in various binding classes arranged along a depth binding gradient. Binding Ca2+modifies the accessible hydrophobic surface of the two lobes and allows for deeper binding. Apo CaM indeed shows shallow binding involving predominantly polar and charged residues. Furthermore, binding to the C-terminal lobe of CaM appears selective and involves specific conformational states that can facilitate deep binding to target proteins, while binding to the N-terminal lobe appears to happen through a more flexible mechanism. Thus the long-ranged electrostatic interactions of the charged residues of the N-terminal lobe of CaM may initiate binding, while the short-ranged interactions of hydrophobic residues in the C-terminal lobe of CaM may account for selectivity. This work furthers our understanding of the mechanism of CaM binding and selectivity to different target proteins and paves the way towards a comprehensive model of CaM selectivity.

  • 279. Williams, A. J.
    et al.
    Ekins, S.
    Spjuth, Ola
    KTH, Centra, SeRC - Swedish e-Science Research Centre.
    Willighagen, Egon L.
    Accessing, using, and creating chemical property databases for computational toxicology modeling2012Inngår i: Computational Toxicology: Volume I, Springer , 2012, s. 221-241Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    Toxicity data is expensive to generate, is increasingly seen as precompetitive, and is frequently used for the generation of computational models in a discipline known as computational toxicology. Repositories of chemical property data are valuable for supporting computational toxicologists by providing access to data regarding potential toxicity issues with compounds as well as for the purpose of building structure-toxicity relationships and associated prediction models. These relationships use mathematical, statistical, and modeling computational approaches and can be used to understand the mechanisms by which chemicals cause harm and, ultimately, enable prediction of adverse effects of these chemicals to human health and/or the environment. Such approaches are of value as they offer an opportunity to prioritize chemicals for testing. An increasing amount of data used by computational toxicologists is being published into the public domain and, in parallel, there is a greater availability of Open Source software for the generation of computational models. This chapter provides an overview of the types of data and software available and how these may be used to produce predictive toxicology models for the community.

  • 280. Wistrand, Markus
    et al.
    Käll, Lukas
    Sonnhammer, Erik L. L.
    A general model of G protein-coupled receptor sequences and its application to detect remote homologs2006Inngår i: Protein Science, ISSN 0961-8368, E-ISSN 1469-896X, Vol. 15, nr 3, s. 509-521Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    G protein-coupled receptors (GPCRs) constitute a large superfamily involved in various types of signal transduction pathways triggered by hormones, odorants, peptides, proteins, and other types of ligands. The superfamily is so diverse that many members lack sequence similarity, although they all span the cell membrane seven times with an extracellular N and a cytosolic C terminus. We analyzed a divergent set of GPCRs and found distinct loop length patterns and differences in amino acid composition between cytosolic loops, extracellular loops, and membrane regions. We configured GPCRHMM, a hidden Markov model, to fit those features and trained it on a large dataset representing the entire superfamily. GPCRHMM was benchmarked to profile HMMs and generic transmembrane detectors on sets of known GPCRs and non-GPCRs. In a cross-validation procedure, profile HMMs produced an error rate nearly twice as high as GPCRHMM. In a sensitivity-selectivity test, GPCRHMM's sensitivity was about 15% higher than that of the best transmembrane predictors, at comparable false positive rates. We used GPCRHMM to search for novel members of the GPCR superfamily in five proteomes. All in all we detected 120 sequences that lacked annotation and are potentially novel GPCRs. Out of those 102 were found in Caenorhabditis elegans, four in human, and seven in mouse. Many predictions (65) belonged to Pfam domains of unknown function. GPCRHMM strongly rejected a family of arthropod-specific odorant receptors believed to be GPCRs. A detailed analysis showed that these sequences are indeed very different from other GPCRs. GPCRHMM is available at http://gpcrhmm.cgb.ki.se.

  • 281.
    Wärnberg, Emil
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Modelling Low Dimensional Neural Activity2016Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    A number of recent studies have shown that the dimensionality of the neural activity in the cortex is low. However, what network structures are capable of producing such activity is not theoretically well understood. In this thesis, I discuss a few possible solutions to this problem, and demonstrate that a network with a multidimensional attractor can give rise to such low dimensional activity. The network is created using the Neural Engineering Framework, and exhibits several biologically plausible features, including a log-normal distribution of the synaptic weights.

  • 282. Yazdi, Samira
    et al.
    Stein, Matthias
    Elinder, Fredrik
    Andersson, Magnus
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för teknikvetenskap (SCI), Teoretisk fysik, Beräkningsbiofysik.
    Lindahl, Erik
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för teknikvetenskap (SCI), Teoretisk fysik, Beräkningsbiofysik. Stockholms universitet, Sweden.
    The Molecular Basis of Polyunsaturated Fatty Acid Interactions with the Shaker Voltage-Gated Potassium Channel2016Inngår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 12, nr 1, artikkel-id e1004704Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Voltage-gated potassium (K-V) channels are membrane proteins that respond to changes in membrane potential by enabling K+ ion flux across the membrane. Polyunsaturated fatty acids (PUFAs) induce channel opening by modulating the voltage-sensitivity, which can provide effective treatment against refractory epilepsy by means of a ketogenic diet. While PUFAs have been reported to influence the gating mechanism by electrostatic interactions to the voltage-sensor domain (VSD), the exact PUFA-protein interactions are still elusive. In this study, we report on the interactions between the Shaker K-V channel in open and closed states and a PUFA-enriched lipid bilayer using microsecond molecular dynamics simulations. We determined a putative PUFA binding site in the open state of the channel located at the protein-lipid interface in the vicinity of the extracellular halves of the S3 and S4 helices of the VSD. In particular, the lipophilic PUFA tail covered a wide range of non-specific hydrophobic interactions in the hydrophobic central core of the protein-lipid interface, while the carboxylic head group displayed more specific interactions to polar/charged residues at the extracellular regions of the S3 and S4 helices, encompassing the S3-S4 linker. Moreover, by studying the interactions between saturated fatty acids (SFA) and the Shaker K-V channel, our study confirmed an increased conformational flexibility in the polyunsaturated carbon tails compared to saturated carbon chains, which may explain the specificity of PUFA action on channel proteins.

  • 283.
    Yim, Man Yi
    et al.
    University of Hong Kong, Hong Kong.
    Kumar, Arvind
    Bernstein Center Freiburg, University of Freiburg, Germany .
    Aertsen, Ad
    Rotter, Stefan
    Impact of correlated inputs to neurons: modeling observations from in vivo intracellular recordings2014Inngår i: Journal of Computational Neuroscience, ISSN 0929-5313, E-ISSN 1573-6873, Vol. 37, nr 2, s. 293-304Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In vivo recordings in rat somatosensory cortex suggest that excitatory and inhibitory inputs are often correlated during spontaneous and sensory-evoked activity. Using a computational approach, we study how the interplay of input correlations and timing observed in experiments controls the spiking probability of single neurons. Several correlation-based mechanisms are identified, which can effectively switch a neuron on and off. In addition, we investigate the transfer of input correlation to output correlation in pairs of neurons, at the spike train and the membrane potential levels, by considering spike-driving and non-spike-driving inputs separately. In particular, we propose a plausible explanation for the in vivo finding that membrane potentials in neighboring neurons are correlated, but the spike-triggered averages of membrane potentials preceding a spike are not: Neighboring neurons possibly receive an ongoing bombardment of correlated subthreshold background inputs, and occasionally uncorrelated spike-driving inputs.

  • 284. Yosef, Nir
    et al.
    Käll, Lukas
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    From sequence to structure to networks2008Inngår i: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 9, nr 11Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A report on the 7th European Conference on Computational Biology (ECCB), Cagliari, Italy, 22-26 September 2008.

  • 285. Yoshida, Motoharu
    et al.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Hasselmo, Michael E.
    mGluR-dependent persistent firing in entorhinal cortex layer III neurons2008Inngår i: European Journal of Neuroscience, ISSN 0953-816X, E-ISSN 1460-9568, Vol. 28, nr 6, s. 1116-1126Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Persistent firing is believed to be a crucial mechanism for memory function including working memory. Recent in vivo and in vitro findings suggest an involvement of metabotropic glutamate receptors (mGluRs) in persistent firing. Using whole-cell patch-recording techniques in a rat entorhinal cortex (EC) slice preparation, we tested whether EC layer III neurons display persistent firing due to mGluR activation, independently of cholinergic activation. Stimulation of the angular bundle drove persistent firing in 90% of the cells in the absence of a cholinergic agonist. The persistent firing was typically stable for > 4.5 min at which point persistent firing was terminated by the experimenter. The average frequency of the persistent firing was 2.1 Hz, ranging from 0.4 to 5.5 Hz. This persistent firing was observed even in the presence of atropine (2 mu M), suggesting that the persistent firing can occur independent of cholinergic activation. Furthermore, ionotropic glutamate and GABAergic synaptic blockers (2 mm kynurenic acid, 100 mu M picrotoxin and 1 mu M CGP55845) did not block the persistent firing. On the other hand, blockers of group I mGluRs (100 mu M LY367385 and 20 mu M MPEP) completely blocked or suppressed the persistent firing. An agonist of group I mGluRs (20 mu M DHPG) greatly enhanced the persistent firing induced by current injection. These results indicate that persistent firing can be driven through group I mGluRs in entorhinal layer III neurons, suggesting that glutamatergic synaptic input alone could enable postsynaptic neurons to hold input signals in the form of persistent firing.

  • 286.
    Zagal, Juan Cristobal
    et al.
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Björkman, Eva
    Lindeberg, Tony
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Roland, P.
    Signficance determination for the scale-space primal sketch by comparison of statistics of scale-space blob volumes computed from PET signals vs. residual noise2000Inngår i: : HBM'00 published in Neuroimage, volume 11, number 5, 2000, 2000, Vol. 11, s. 493-493Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A dominant approach to brain mapping is to define functional regions in the brain by analyzing brain activation images obtained by PET or fMRI. In [1], it has been shown that the scale-space primal sketch provides a useful tool for such analysis. Some attractive properties of this method are that it only makes few assumptions about the data and the process for extracting activations is fully automatic.

    In the present version of the scale-space primal sketch, however, there is no method for determining p-values. The purpose here is to present a new methodology for addressing this question, by introducing a descriptor referred to as the -curve, which serves as a first step towards determining the probability of false positives, i.e. alpha.

  • 287. Zhang, Bo
    et al.
    Pirmoradian, Mohammad
    Zubarev, Roman
    Käll, Lukas
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, SeRC - Swedish e-Science Research Centre. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences2017Inngår i: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 16, nr 5, s. 936-948Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Most implementations of mass spectrometry-based proteomics involve enzymatic digestion of proteins, expanding the analysis to multiple proteolytic peptides for each protein. Currently, there is no consensus of how to summarize peptides' abundances to protein concentrations, and such efforts are complicated by the fact that error control normally is applied to the identification process, and do not directly control errors linking peptide abundance measures to protein concentration. Peptides resulting from suboptimal digestion or being partially modified are not representative of the protein concentration. Without a mechanism to remove such unrepresentative peptides, their abundance adversely impacts the estimation of their protein's concentration. Here, we present a relative quantification approach, Diffacto, that applies factor analysis to extract the covariation of peptides' abundances. The method enables a weighted geometrical average summarization and automatic elimination of incoherent peptides. We demonstrate, based on a set of controlled label-free experiments using standard mixtures of proteins, that the covariation structure extracted by the factor analysis accurately reflects protein concentrations. In the 1% peptide-spectrum match-level FDR data set, as many as 11% of the peptides have abundance differences incoherent with the other peptides attributed to the same protein. If not controlled, such contradicting peptide abundance have a severe impact on protein quantifications. When adding the quantities of each protein's three most abundant peptides, we note as many as 14% of the proteins being estimated as having a negative correlation with their actual concentration differences between samples. Diffacto reduced the amount of such obviously incorrectly quantified proteins to 1.6%. Furthermore, by analyzing clinical data sets from two breast cancer studies, our method revealed the persistent proteomic signatures linked to three subtypes of breast cancer. We conclude that Diffacto can facilitate the interpretation and enhance the utility of most types of proteomics data.

  • 288.
    Zhang, Cheng
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Bidkhori, Gholamreza
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Benfeitas, Rui
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Lee, Sunjae
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Uhlen, Mathias
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    ESS: A Tool for Genome-Scale Quantification of Essentiality Score for Reaction/Genes in Constraint-Based Modeling2018Inngår i: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, artikkel-id 1355Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Genome-scale metabolic models (GEMs) are comprehensive descriptions of cell metabolism and have been extensively used to understand biological responses in health and disease. One such application is in determining metabolic adaptation to the absence of a gene or reaction, i.e., essentiality analysis. However, current methods do not permit efficiently and accurately quantifying reaction/gene essentiality. Here, we present Essentiality Score Simulator (ESS), a tool for quantification of gene/reaction essentialities in GEMs. ESS quantifies and scores essentiality of each reaction/gene and their combinations based on the stoichiometric balance using synthetic lethal analysis. This method provides an option to weight metabolic models which currently rely mostly on topologic parameters, and is potentially useful to investigate the metabolic pathway differences between different organisms, cells, tissues, and/or diseases. We benchmarked the proposed method against multiple network topology parameters, and observed that our method displayed higher accuracy based on experimental evidence. In addition, we demonstrated its application in the wild-type and ldh knock-out E. coli core model, as well as two human cell lines, and revealed the changes of essentiality in metabolic pathways based on the reactions essentiality score. ESS is available without any limitation at https://sourceforge.net/projects/essentiality-score-simulator.

  • 289.
    Åkerborg, Örjan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Taking advantage of phylogenetic trees in comparative genomics2008Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Phylogenomics can be regarded as evolution and genomics in co-operation. Various kinds of evolutionary studies, gene family analysis among them, demand access to genome-scale datasets. But it is also clear that many genomics studies, such as assignment of gene function, are much improved by evolutionary analysis. The work leading to this thesis is a contribution to the phylogenomics field. We have used phylogenetic relationships between species in genome-scale searches for two intriguing genomic features, namely and A-to-I RNA editing. In the first case we used pairwise species comparisons, specifically human-mouse and human-chimpanzee, to infer existence of functional mammalian pseudogenes. In the second case we profited upon later years' rapid growth of the number of sequenced genomes, and used 17-species multiple sequence alignments. In both these studies we have used non-genomic data, gene expression data and synteny relations among these, to verify predictions. In the A-to-I editing project we used 454 sequencing for experimental verification.

    We have further contributed a maximum a posteriori (MAP) method for fast and accurate dating analysis of speciations and other evolutionary events. This work follows recent years' trend of leaving the strict molecular clock when performing phylogenetic inference. We discretised the time interval from the leaves to the root in the tree, and used a dynamic programming (DP) algorithm to optimally factorise branch lengths into substitution rates and divergence times. We analysed two biological datasets and compared our results with recent MCMC-based methodologies. The dating point estimates that our method delivers were found to be of high quality while the gain in speed was dramatic.

    Finally we applied the DP strategy in a new setting. This time we used a grid laid out on a species tree instead of on an interval. The discretisation gives together with speciation times a common timeframe for a gene tree and the corresponding species tree. This is the key to integration of the sequence evolution process and the gene evolution process. Out of several potential application areas we chose gene tree reconstruction. We performed genome-wide analysis of yeast gene families and found that our methodology performs very well.

  • 290. Åkerman, S.
    et al.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Roland, P.
    Surface Model Generation and Segmentation of the Human Celebral Cortex for the Construction of Unfolded Cortical Maps1996Inngår i: Proc. 2nd International Conference on Functional Mapping of the Human Brain: HBM'96, published in Neuroimage, volume 3, number 3, 1996, s. S126-S126Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Representing the shape of the human cerebral cortex arises as a basic subproblem in several areas of brain science, such as when describing the anatomy of the cortex and when relating functional measurements to cortical regions. 

    Most current methods for building such representions of the cortical surface are either based on contours from two-dimensional cross sections or landmarks that have been obtained manually.

    In this article, we outline a methodology for semi-automatic contruction of a solely surface based representation of the human cerebral cortex in vivo for subsequent generation of  (unfolded) two-dimensional brain maps.

    The method is based on input data in the form of three-dimensional NMR images, and comprises the following main steps:

    • suppression of disturbing fine-scale structures by linear and non-linear scale-space techniques,
    • generation of a triangulated surface representation based on either iso-surfaces or three-dimensional edge detection,
    • division of the surface model into smaller segments based on differential invariants computed from the image data.

    When constructing an unfolded (flattened) surface representation, the instrinsic curvature of the cortex means that such a unfolding cannot be done without introducing distortions. To reduce this problem, we propose to cut the surface into smaller parts, where a ridge detector acts as guideline, and then unfold each patch individually, so as to obtain low distortions.

    Having a solely surface based representation of the cortex and expressing the image operations using multi-scale differential invariants in terms of scale-space derivatives as done in this work is a natural choice both in terms of conceptual and algorithmic simplicity. Moreover, explicitly handling the multi-scale nature of the data is necessary to obtain robust results.

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