%0 Journal Article %1 Taylor:2006:Bioinformatics:16954144 %A Taylor, R C %A Shah, A %A Treatman, C %A Blevins, M %D 2006 %J Bioinformatics %K bio imported inference network pathway %N 21 %P 2706-2708 %R 10.1093/bioinformatics/btl444 %T SEBINI: Software Environment for BIological Network Inference %U http://www.ncbi.nlm.nih.gov/pubmed/16954144?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DiscoveryPanel.Pubmed_Discovery_RA&linkpos=4&log$=relatedarticles&logdbfrom=pubmed %V 22 %X The Software Environment for BIological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment and evaluation of algorithms used to reconstruct the structure of biological regulatory and interaction networks. SEBINI can be used to compare and train network inference methods on artificial networks and simulated gene expression perturbation data. It also allows the analysis within the same framework of experimental high-throughput expression data using the suite of (trained) inference methods; hence SEBINI should be useful to software developers wishing to evaluate, compare, refine or combine inference techniques, and to bioinformaticians analyzing experimental data. SEBINI provides a platform that aids in more accurate reconstruction of biological networks, with less effort, in less time. AVAILABILITY: A demonstration website is located at https://www.emsl.pnl.gov/NIT/NIT.html. The Java source code and PostgreSQL database schema are available freely for non-commercial use.

@article{Taylor:2006:Bioinformatics:16954144, abstract = {The Software Environment for BIological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment and evaluation of algorithms used to reconstruct the structure of biological regulatory and interaction networks. SEBINI can be used to compare and train network inference methods on artificial networks and simulated gene expression perturbation data. It also allows the analysis within the same framework of experimental high-throughput expression data using the suite of (trained) inference methods; hence SEBINI should be useful to software developers wishing to evaluate, compare, refine or combine inference techniques, and to bioinformaticians analyzing experimental data. SEBINI provides a platform that aids in more accurate reconstruction of biological networks, with less effort, in less time. AVAILABILITY: A demonstration website is located at https://www.emsl.pnl.gov/NIT/NIT.html. The Java source code and PostgreSQL database schema are available freely for non-commercial use.}, added-at = {2009-04-29T09:37:40.000+0200}, author = {Taylor, R C and Shah, A and Treatman, C and Blevins, M}, biburl = {https://www.bibsonomy.org/bibtex/2cdf468bda73fa1494b21f8eb56538b2d/wnpxrz}, description = {SEBINI: Software Environment for BIological Networ...[Bioinformatics. 2006] - PubMed Result}, doi = {10.1093/bioinformatics/btl444}, interhash = {834b90c2c9af4ba6b502bbd2582c6de2}, intrahash = {cdf468bda73fa1494b21f8eb56538b2d}, journal = {Bioinformatics}, keywords = {bio imported inference network pathway}, month = Nov, number = 21, pages = {2706-2708}, pmid = {16954144}, timestamp = {2009-04-29T09:37:40.000+0200}, title = {SEBINI: Software Environment for BIological Network Inference}, url = {http://www.ncbi.nlm.nih.gov/pubmed/16954144?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DiscoveryPanel.Pubmed_Discovery_RA&linkpos=4&log$=relatedarticles&logdbfrom=pubmed}, volume = 22, year = 2006 }