Intra-population heterogeneity is commonly observed in natural and cellular populations and has profound influence on their evolution. For example, intra-tumor heterogeneity is prevalent in most tumor types and can result in the failure of tumor therapy. However, the evolutionary process of heterogeneity remains poorly characterized at both genotypic and phenotypic level. Here we study the evol...

The diverse, specialized genes present in today's lifeforms evolved from a common core of ancient, elementary genes. However, these genes did not evolve individually: gene expression is controlled by a complex network of interactions, and alterations in one gene may drive reciprocal changes in its proteins' binding partners. Like many complex networks, these gene regulatory networks (GRNs) are ...

Abstract Background Seminal studies of vertebrate protein evolution speculated that gene regulatory changes can drive anatomical innovations. However, very little is known about network (GRN) associated with phenotypic effect across ecologically diverse species. Here we use a novel approach for comparative GRN analysis in species to study representative the most striking examples adaptive radia...

Modeling and simulation of gene-regulatory networks (GRNs) has become an important aspect of modern systems biology investigations into mechanisms underlying gene regulation. A key challenge in this area is the automated inference (reverse-engineering) of dynamic, mechanistic GRN models from gene expression time-course data. Common mathematical formalisms for representing such models capture tw...

Link prediction is an important data mining problem that has many applications in different domains such as social network analysis and computational biology. For example, biologists model gene regulatory networks (GRNs) as directed graphs where nodes are genes and links show regulatory relationships between the genes. By predicting links in GRNs, biologists can gain a better understanding of t...

Technological development led to an increased interest in systems biological approaches in plants to characterize developmental mechanism and candidate genes relevant to specific tissue or cell morphology. AUX-IAA proteins are important plant-specific putative transcription factors. There are several reports on physiological response of this family in Arabidopsis but in cotton fiber the transcr...

With the advent of various data assaying techniques, gene expression time series data have become a useful resource to investigate the complex interactions occurring amongst the transcription factors and genes. While a number of methodologies have been de (GRN), the presence of high noise in gene expression data have made the estimation of non interactions among the genes an ill been proposed t...

OUTLINE Introduction Formal representation of GRNs An example of a GRN: The Lac Operon Hierarchies of GRN models: From probabilistic graphs to mechanistic models A guide to databases and knowledgebases on the internet Pathway Databases & Platforms Ontologies for GRN modeling Current Gene, Interaction, and Pathway Ontologies Whole­cell modeling platforms Ontology for modeling multi­scale and inc...

This article presents some reflections on how the recently published Boolean gene regulatory network (GRN) model for sea urchin endomesoderm development affects the problem of what we can expect to know about a developmental process. The Boolean computation demonstrated that, on a system-wide level, a topological GRN model can contain sufficient regulatory information to predict in silico all t...

Elucidation of gene regulatory networks (GRNs) underlying aspects of leaf development in multiple model species has uncovered surprisingly plastic regulatory architecture. The meticulously mapped network interactions in one model species cannot now be assumed to map directly onto a different species. Despite these overall differences, however, many modules do appear to be almost universal. Extr...