POSet Ontology Categorizer (POSOC) V1.0 The POSet Ontology Categorizer (POSOC) software package provides tools for creating and mining of poset-structured ontologies, such as the Gene Ontology (GO). Given a list of weighted query items (ex.genes,proteins, and/or phrases) and one or more focus nodes, POSOC determines the ordered set of GO nodes that summarize the query, based on selections of a scoring function, pseudo-distance measure, specificity level, and cluster determination. Pseudo-distance measures provided are minimum chain length, maximum chain length, average of extreme chain lengths, and average of all chain lengths. A low specificity level, such as -1 or 0, results in a general set of clusters. Increasing the specificity results in more specific results in more specific and lighter clusters. POSOC cluster results can be compared agaist known results by calculations of precision, recall, and f-score for graph neighborhood relationships. This tool has been used in understanding the function of a set of genes, finding similar genes, and annotating new proteins. The POSOC software consists of a set of Java interfaces, classes, and programs that run on Linux or Windows platforms. It incorporates graph classes from OpenJGraph (openjgraph.sourceforge.net).
To order this software or receive further information, please fill out the following request: Request Software
@misc{osti_1230863,
title = {POSet Ontology Categorizer, Version 00},
author = {Miniszewski, Sue M.},
abstractNote = {POSet Ontology Categorizer (POSOC) V1.0 The POSet Ontology Categorizer (POSOC) software package provides tools for creating and mining of poset-structured ontologies, such as the Gene Ontology (GO). Given a list of weighted query items (ex.genes,proteins, and/or phrases) and one or more focus nodes, POSOC determines the ordered set of GO nodes that summarize the query, based on selections of a scoring function, pseudo-distance measure, specificity level, and cluster determination. Pseudo-distance measures provided are minimum chain length, maximum chain length, average of extreme chain lengths, and average of all chain lengths. A low specificity level, such as -1 or 0, results in a general set of clusters. Increasing the specificity results in more specific results in more specific and lighter clusters. POSOC cluster results can be compared agaist known results by calculations of precision, recall, and f-score for graph neighborhood relationships. This tool has been used in understanding the function of a set of genes, finding similar genes, and annotating new proteins. The POSOC software consists of a set of Java interfaces, classes, and programs that run on Linux or Windows platforms. It incorporates graph classes from OpenJGraph (openjgraph.sourceforge.net).},
doi = {},
url = {https://www.osti.gov/biblio/1230863},
year = {Tue Mar 01 00:00:00 EST 2005},
month = {Tue Mar 01 00:00:00 EST 2005},
note =
}
