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 languageAmerican English
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.

Fingerprint

Dive into the research topics of 'Geometric Interpretation of Gene Expression by Sparse Reconstruction of Transcript Profiles'. Together they form a unique fingerprint.

Cite this