Data from: Machine learning-based differential network analysis: a study of stress-responsive transcriptomes in Arabidopsis thaliana

Ma C, Xin M, Feldmann KA, Wang X

Date Published: February 11, 2014

DOI: http://dx.doi.org/10.5061/dryad.41b9g

 

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Title Supplemental Dataset 1
Downloaded 95 times
Description Known Stress-related Genes Collected from the TAIR and DRASTIC Databases, their Expression Changes in the Stress Microarray Datasets, and the Statistical Results of their Gene Ontology (GO) Annotations
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Title Supplemental Dataset 2
Downloaded 103 times
Description “Informative” Genes Obtained from PSOL-based ML Analysis for Gene Co-expression Network Construction under Six Studied Stresses in Two Tissues
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Title Supplemental Dataset 3
Downloaded 107 times
Description Candidate Stress-related Genes Predicted by mlDNA
Download Supplemental Dataset 3.xls (21.27 Mb)
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Title Supplemental Dataset 4
Downloaded 72 times
Description List of the Candidate Stress-related Genes Evidenced by a High-throughput Phenotypic Screening Experiment
Download Supplemental Dataset 4.xls (111.6 Kb)
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Title Supplemental Dataset 5
Downloaded 61 times
Description Detailed Information for Gene Ontology (GO) Modules Enriched with Salt Stress-related Genes
Download Supplemental Dataset 5.xls (239.1 Kb)
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Title Supplemental Dataset 6
Downloaded 75 times
Description List of Stress Shared Genes
Download Supplemental Dataset 6.xls (104.4 Kb)
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Title Supplemental Dataset 7
Downloaded 265 times
Description List of Stress-Specific Genes
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When using this data, please cite the original publication:

Ma C, Xin M, Feldmann KA, Wang X (2014) Machine learning-based differential network analysis: a study of stress-responsive transcriptomes in Arabidopsis thaliana. The Plant Cell 26(2): 520-537. http://dx.doi.org/10.1105/tpc.113.121913

Additionally, please cite the Dryad data package:

Ma C, Xin M, Feldmann KA, Wang X (2014) Data from: Machine learning-based differential network analysis: a study of stress-responsive transcriptomes in Arabidopsis thaliana. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.41b9g
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