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SoyNet: a database of co-functional networks for soybeanGlycine max
- Source :
- NUCLEIC ACIDS RESEARCH(45): D1, Nucleic Acids Research
- Publication Year :
- 2016
- Publisher :
- Oxford University Press (OUP), 2016.
-
Abstract
- Soybean (Glycine max) is a legume crop with substantial economic value, providing a source of oil and protein for humans and livestock. More than 50% of edible oils consumed globally are derived from this crop. Soybean plants are also important for soil fertility, as they fix atmospheric nitrogen by symbiosis with microorganisms. The latest soybean genome annotation (version 2.0) lists 56 044 coding genes, yet their functional contributions to crop traits remain mostly unknown. Co-functional networks have proven useful for identifying genes that are involved in a particular pathway or phenotype with various network algorithms. Here, we present SoyNet (available at www.inetbio.org/soynet), a database of co-functional networks for G. max and a companion web server for network-based functional predictions. SoyNet maps 1 940 284 co-functional links between 40 812 soybean genes (72.8% of the coding genome), which were inferred from 21 distinct types of genomics data including 734 microarrays and 290 RNA-seq samples from soybean. SoyNet provides a new route to functional investigation of the soybean genome, elucidating genes and pathways of agricultural importance.
- Subjects :
- 0301 basic medicine
Gene regulatory network
Genomics
Biology
computer.software_genre
Genome
Evolution, Molecular
Crop
03 medical and health sciences
Symbiosis
Gene Expression Regulation, Plant
Databases, Genetic
Genetics
Database Issue
Gene Regulatory Networks
Gene
Database
fungi
food and beverages
Genome project
Phenotype
030104 developmental biology
Soybeans
DNA microarray
computer
Metabolic Networks and Pathways
Signal Transduction
Subjects
Details
- ISSN :
- 13624962 and 03051048
- Volume :
- 45
- Database :
- OpenAIRE
- Journal :
- Nucleic Acids Research
- Accession number :
- edsair.doi.dedup.....50bd87a5b11513dd06e4ecc431fe8b9b
- Full Text :
- https://doi.org/10.1093/nar/gkw704