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GeneNetwork is a combined database and open-source bioinformatics data analysis software resource for systems genetics. [1] This resource is used to study gene regulatory networks that link DNA sequence differences to corresponding differences in gene and protein expression and to variation in traits such as health and disease risk.
Structure of a gene regulatory network Control process of a gene regulatory network. A gene (or genetic) regulatory network (GRN) is a collection of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression levels of mRNA and proteins which, in turn, determine the function of the cell.
Gene Disease Database; Gene Expression Omnibus (GEO [9]): a public functional genomics data repository from the U.S. National Cancer Institute (NCI), which supports array- and sequence-based data. Tools for querying and downloading gene expression profiles are provided.
A gene regulatory network [20] is a set of molecular regulators that interact with each other and with other substances in the cell. The regulator can be DNA, RNA, protein and complexes of these. Gene regulatory networks can be modeled in numerous ways including; Coupled ordinary differential equations, Boolean networks, Continuous networks ...
BIND was the first database of its kind to contain info on biomolecular interactions, reactions and pathways in one schema. It is also the first to base its ontology on chemistry which allows 3D representation of molecular interactions. The underlying chemistry allows molecular interactions to be described down to the atomic level of resolution ...
KEGG (Kyoto Encyclopedia of Genes and Genomes) is a collection of databases dealing with genomes, biological pathways, diseases, drugs, and chemical substances.KEGG is utilized for bioinformatics research and education, including data analysis in genomics, metagenomics, metabolomics and other omics studies, modeling and simulation in systems biology, and translational research in drug development.
Weighted correlation network analysis, also known as weighted gene co-expression network analysis (WGCNA), is a widely used data mining method especially for studying biological networks based on pairwise correlations between variables. While it can be applied to most high-dimensional data sets, it has been most widely used in genomic ...
A biological network is a method of representing systems as complex sets of binary interactions or relations between various biological entities. [1] In general, networks or graphs are used to capture relationships between entities or objects. [1]