Time-Window Analysis of Developmental Gene Expression Data with Multiple Genetic Backgrounds | Zendy

Tamir Tuller | Zendy; Efrat Oron | Zendy; Erez Makavy | Zendy; Daniel Chamovitz | Zendy; Benny Chor | Zendy

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Time-Window Analysis of Developmental Gene Expression Data with Multiple Genetic Backgrounds

Author(s) -

Tamir Tuller,

Efrat Oron,

Erez Makavy,

Daniel Chamovitz,

Benny Chor

Publication year - 2005

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-29008-7

DOI - 10.1007/11557067_5

Subject(s) - heuristics , computer science , window (computing) , expression (computer science) , time complexity , genetic algorithm , biological data , artificial intelligence , bioinformatics , machine learning , algorithm , biology , programming language , operating system

We study gene expression data, derived from developing tissues, under multiple genetic backgrounds (mutations). Motivated by the perceived behavior under these background, our main goals are to explore time windows questions: Find a large set of genes that have a similar behavior in two different genetic backgrounds, under an appropriate time shift. Find a model that approximates the dynamics of a gene network in developing tissues at different continuous time windows. We first explain the biological significance of these problems, and then explore their computational complexity, which ranges from polynomial to NP-hard. We developed algorithms and heuristics for the different problems, and ran those on synthetic and biological data, with very encouraging results.

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