Geometric Interpretation of Gene Expression by Sparse Reconstruction of Transcript Profiles

Yosef Prat, Menachem Fromer, Michal Linial*, Nathan Linial

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Large-scale data collection technologies have come to play a central role in biological and biomedical research in the last decade. Consequently, it has become a major goal of functional genomics to develop, based on such data, a comprehensive description of the functions and interactions of all genes and proteins in a genome. Most large-scale biological data, including gene expression profiles, are usually represented by a matrix, where n genes are examined in d experiments. Here, we view such data as a set of n points (vectors) in d-dimensional space, each of which represents the profile of a given gene over d different experimental conditions. Many known methods that have yielded meaningful biological insights seek geometric or algebraic features of these vectors.

Original languageEnglish
Title of host publicationResearch in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings
EditorsVineet Bafna, S. Cenk Sahinalp
PublisherSpringer Verlag
Pages355-357
Number of pages3
ISBN (Print)9783642200359
DOIs
StatePublished - 2011
Event15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011 - Vancouver, Canada
Duration: 28 Mar 201131 Mar 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6577 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011
Country/TerritoryCanada
CityVancouver
Period28/03/1131/03/11

Bibliographical note

Publisher Copyright:
© 2011, Springer-Verlag Berlin Heidelberg.

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