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GOModeler specifications

Information


Unique identifier OMICS_22587
Name GOModeler
Interface Web user interface
Restrictions to use None
Input data A Gene Expression File containing identifiers and gene expression values; and (a Hypothesis File containing the hypothesis terms of interest OR a Hypothesis GO Term File containing the hypothesis terms AND associated GO Terms.
Input format TXT
Output data The results, a job identifier, and a link to the edit interface.
Programming languages Perl
Computer skills Basic
Stability No
Maintained No

Maintainer


This tool is not available anymore.

Additional information


http://agbase.msstate.edu/help/gomodelerhelp.htm http://www.agbase.msstate.edu/Education/NABDAWorkshop/tutorial_6/GOModeler_Tutorial.htm

Publication for GOModeler

GOModeler citations

 (2)
library_books

Ultrasonic Incisions Produce Less Inflammatory Mediator Response during Early Healing than Electrosurgical Incisions

2013
PLoS One
PMCID: 3776814
PMID: 24058457
DOI: 10.1371/journal.pone.0073032

[…] but does not incorporate the quantitative aspects of de (up-and down-regulated genes) to evaluate the net effect of these changes on any of these functional categories. we used agbase tool gomodeler to determine the net effect of de of genes on these go terms. gomodeler navigates the go to determine whether genes annotated to specific function are known to be positive (‘pro’) […]

library_books

Genotype Dependent Tumor Regression in Marek’s Disease Mediated at the Level of Tumor Immunity

2009
PMCID: 2787926
PMID: 19308678
DOI: 10.1007/s12307-008-0018-z

[…] variance. table 1f: forward; r: reverse., f: forward; r: reverse., we tested our hypotheses using go-based modeling of our qpcr data exactly as described []. briefly, we used the computational tool gomodeler [], which scores the effects of each gene product on a process as either “pro” (+1), “anti” (−1), “no effect” (0) or “no data” (blank cell), then multiplies these score by the qpcr data […]


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GOModeler institution(s)
Department of Computer Science and Engineering, Mississippi State University, MS, USA; Institute of Digital Biology, Mississippi State University, MS, USA; Life Sciences and Biotechnology Institute, Mississippi State University, MS, USA; College of Veterinary Medicine, Mississippi State University, MS, USA
GOModeler funding source(s)
Supported by National Research Initiative of the USDA Cooperative State Research, Education and Extension Service under grant number 2007-35205-17941 and by the National Science Foundation under grant number EPS 0903787.

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