LegumeGRN: a gene regulatory network prediction server for functional and comparative studies

Building accurate gene regulatory networks (GRNs) from high-throughput gene expression data is a long-standing challenge. However, with the emergence of new algorithms combined with the increase of transcriptomic data availability, it is now reachable. To help biologists to investigate gene regulato...

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Detalhes bibliográficos
Autor principal: Wang, Mingyi (author)
Outros Autores: Verdier, Jerome (author), Benedito, Vagner A (author), Tang, Yuhong (author), Murray, Jeremy D (author), Ge, Yinbing (author), Becker, Jörg D (author), Carvalho, Helena (author), Rogers, Christian (author), Udvardi, Michael (author), He, Ji (author)
Formato: article
Idioma:eng
Publicado em: 2015
Assuntos:
Machine learning algorithms
Gene expression
Legumes
Gene regulatory networks
Medicago
Transcriptome analysis
Regulons
Gene regulation
Texto completo:http://hdl.handle.net/10400.7/487
País:Portugal
Oai:oai:arca.igc.gulbenkian.pt:10400.7/487

Texto Completo

http://hdl.handle.net/10400.7/487

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