Automated Analysis and Reannotation of Subcellular Locations in Confocal Images from the Human Protein Atlas
2012 (English)In: PLoS ONE, ISSN 1932-6203, Vol. 7, no 11, e50514- p.Article in journal (Refereed) Published
The Human Protein Atlas contains immunofluorescence images showing subcellular locations for thousands of proteins. These are currently annotated by visual inspection. In this paper, we describe automated approaches to analyze the images and their use to improve annotation. We began by training classifiers to recognize the annotated patterns. By ranking proteins according to the confidence of the classifier, we generated a list of proteins that were strong candidates for reexamination. In parallel, we applied hierarchical clustering to group proteins and identified proteins whose annotations were inconsistent with the remainder of the proteins in their cluster. These proteins were reexamined by the original annotators, and a significant fraction had their annotations changed. The results demonstrate that automated approaches can provide an important complement to visual annotation.
Place, publisher, year, edition, pages
2012. Vol. 7, no 11, e50514- p.
algorithm, article, automation, cellular distribution, classifier, cluster analysis, image analysis, immunofluorescence, information processing, protein database, protein localization
Cell and Molecular Biology
IdentifiersURN: urn:nbn:se:kth:diva-110203DOI: 10.1371/journal.pone.0050514ISI: 000312376100111ScopusID: 2-s2.0-84870595917OAI: oai:DiVA.org:kth-110203DiVA: diva2:586137
FunderScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
QC 201301112013-01-112013-01-102013-02-01Bibliographically approved