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  • 1.
    Benfeitas, Rui
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Royal Institute of Technology, KTH.
    Bidkhori, Gholamreza
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mukhopadhyay, Bani
    Klevstig, Martina
    Arif, Muhammad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Zhang, Cheng
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lee, Sunjae
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Cinar, Resat
    Nielsen, Jens
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Boren, Jan
    Kunos, George
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis2019In: EBioMedicine, E-ISSN 2352-3964Article in journal (Refereed)
  • 2.
    Lee, Sunjae
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Liu, Zhengtao
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Benfeitas, Rui
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bidkhori, Gholamreza
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Deshmukh, Sumit
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Shobky, Mohamed AI
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lovric, Alen
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Boren, Jan
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    TCSBN: a database of tissue and cancer specific biological networks2017In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962Article in journal (Refereed)
  • 3.
    Liu, Zhengtao
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lee, Sunjae
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kim, Woonghee
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Klevstig, Martina
    Harzandi, Azadeh M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sikanic, Natasa
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Arif, Muhammad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Ståhlman, Marcus
    Nielsen, Jens
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Boren, Jan
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pyruvate kinase L/R is a regulator of lipid metabolism and mitochondrial function2019In: Metabolic engineering, ISSN 1096-7176, E-ISSN 1096-7184Article in journal (Refereed)
  • 4.
    Mahdessian, Diana
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Sullivan, D. P.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Danielsson, Frida
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Åkesson, Lovisa
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Gnann, Christian
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Shutten, Rutger
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Thul, Peter
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Carja, Oana
    Department of Genetics, Stanford University, Stanford, CA 94305, USA. ; Chan Zuckerberg Biohub, San Francisco, San Francisco, CA 94158, USA..
    Ayoglu, Burcu
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Centre for Host–Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, SE1 9RT, United Kingdom.
    Pontén, Fredrik
    Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, SE-751 85 Uppsala, Sweden.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Lindskog, Cecilia
    Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, SE-751 85 Uppsala, Sweden..
    Lundberg, Emma
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Department of Genetics, Stanford University, Stanford, CA 94305, USA. ; Chan Zuckerberg Biohub, San Francisco, San Francisco, CA 94158, USA..
    Spatiotemporal dissection of the cell cycle regulated human proteomeManuscript (preprint) (Other academic)
    Abstract [en]

    Here we present a spatiotemporal dissection of proteome single cell heterogeneity in human cells, performed with subcellular resolution over the course of a cell cycle. We identify 17% of the human proteome to display cell-to-cell variability, of which we could attribute 25% as correlated to cell cycle progression, and present the first evidence of cell cycle association for 258 proteins. A key finding is that the variance, of many of the cell cycle associated proteins, is only partially explained by the cell cycle, which hints at cross-talk between the cell cycle and other signaling pathways. We also demonstrate that several of the identified cell cycle regulated proteins may be clinically significant in proliferative disorders. This spatially resolved proteome map of the cell cycle, integrated into the Human Protein Atlas, serves as a valuable resource to accelerate the molecular knowledge of the cell cycle and opens up novel avenues for the understanding of cell proliferation.

  • 5.
    Zhang, Cheng
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Aldrees, Mohammed
    Arif, Muhammad
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Li, Xiangyu
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Aziz, Mohammad Azhar
    Elucidating the Reprograming of Colorectal Cancer Metabolism Using Genome-Scale Metabolic Modeling2019In: Frontiers in Oncology, ISSN 2234-943X, E-ISSN 2234-943X, Vol. 9, article id 681Article in journal (Refereed)
    Abstract [en]

    Colorectal cancer is the third most incidental cancer worldwide, and the response rate of current treatment for colorectal cancer is very low. Genome-scale metabolic models (GEMs) are systems biology platforms, and they had been used to assist researchers in understanding the metabolic alterations in different types of cancer. Here, we reconstructed a generic colorectal cancer GEM by merging 374 personalized GEMs from the Human Pathology Atlas and used it as a platform for systematic investigation of the difference between tumor and normal samples. The reconstructed model revealed the metabolic reprogramming in glutathione as well as the arginine and proline metabolism in response to tumor occurrence. In addition, six genes including ODC1, SMS, SRM, RRM2, SMOX, and SAT1 associated with arginine and proline metabolism were found to be key players in this metabolic alteration. We also investigated these genes in independent colorectal cancer patients and cell lines and found that many of these genes showed elevated level in colorectal cancer and exhibited adverse effect in patients. Therefore, these genes could be promising therapeutic targets for treatment of a specific colon cancer patient group.

  • 6.
    Zhang, Cheng
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bidkhori, Gholamreza
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Benfeitas, Rui
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lee, Sunjae
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Uhlen, Mathias
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    ESS: A Tool for Genome-Scale Quantification of Essentiality Score for Reaction/Genes in Constraint-Based Modeling2018In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, article id 1355Article in journal (Refereed)
    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.

1 - 6 of 6
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  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • en-GB
  • en-US
  • fi-FI
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  • nn-NB
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  • Other locale
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