Gene networks from expression data

LUIS ANIBAL DIAMBRA

Bahia Blanca

Conferencia; VI Argentinian Conference on Bioinformatics and Computational Biology; 2015

A2B2C

One of the key issue in modern biology is the elucidation of the structure and function of gene regulatory circuits. To address this challenge many efforts have been devoted to develop computational methods able to infer gene regulatory networks. The structure of a network is defined as a graph whose nodes are associated with genes, and whose edges represent the interactions between the nodes. The task of uncovering the GRN architecture from gene-expression profiles, associated with cell states, represents a very complex inverse problem that has become central in functional genomics.In this talk I will review some emerging tools to embed steady states, and phenotypic transitions between these steady states in response to environmental cues, into the dynamics of a gene network model. Furthermore, applications for modeling parasite's life cycle, and cell differentiation will be also discussed.