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.
|Title of host publication
|Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings
|Vineet Bafna, S. Cenk Sahinalp
|Number of pages
|Published - 2011
|15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011 - Vancouver, Canada
Duration: 28 Mar 2011 → 31 Mar 2011
|Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
|15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011
|28/03/11 → 31/03/11
Bibliographical notePublisher Copyright:
© 2011, Springer-Verlag Berlin Heidelberg.