Onto-Tools

Onto-Tools, the toolkit of the modern biologist: Onto-Express, Onto-Compare, Onto-Design and Onto-Translate. Onto-Tools is a set of four seamlessly integrated databases: Onto-Express, Onto-Compare, Onto-Design and Onto-Translate. Onto-Express is able to automatically translate lists of genes found to be differentially regulated in a given condition into functional profiles characterizing the impact of the condition studied upon various biological processes and pathways. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function and chromosome location. Statistical significance values are calculated for each category. Once the initial exploratory analysis identified a number of relevant biological processes, specific mechanisms of interactions can be hypothesized for the conditions studied. Currently, many commercial arrays are available for the investigation of specific mechanisms. Each such array is characterized by a biological bias determined by the extent to which the genes present on the array represent specific pathways. Onto-Compare is a tool that allows efficient comparisons of any sets of commercial or custom arrays. Using Onto-Compare, a researcher can determine quickly which array, or set of arrays, covers best the hypotheses studied. In many situations, no commercial arrays are available for specific biological mechanisms. Onto-Design is a tool that allows the user to select genes that represent given functional categories. Onto-Translate allows the user to translate easily lists of accession numbers, UniGene clusters and Affymetrix probes into one another. All tools above are seamlessly integrated. The Onto-Tools are available online at http://vortex.cs.wayne.edu/Projects.html.


References in zbMATH (referenced in 10 articles )

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  1. Drăghici, Sorin: Statistics and data analysis for microarrays using R and Bioconductor. With CD-ROM. (2012)
  2. Guerra, Rudy (ed.); Goldstein, Darlene R. (ed.): Meta-analysis and combining information in genetics and genomics. (2010)
  3. Zhang, Zhong-Yuan; Li, Tao; Ding, Chris; Ren, Xian-Wen; Zhang, Xiang-Sun: Binary matrix factorization for analyzing gene expression data (2010) ioport
  4. Den Berg, Bart H. J. Van; Thanthiriwatte, Chamali; Manda, Prashanti; Bridges, Susan M.: Comparing gene annotation enrichment tools for functional modeling of agricultural microarray data (2009) ioport
  5. Wang, Lily; Chen, Xi; Wolfinger, Russell D.; Franklin, Jeffrey L.; Coffey, Robert J.; Zhang, Bing: A unified mixed effects model for gene set analysis of time course microarray experiments (2009)
  6. Antonov, Alexey V.; Mewes, Hans W.: Complex phylogenetic profiling reveals fundamental genotype-phenotype associations (2008)
  7. Hulshizer, Randall; Blalock, Eric M.: (Post hoc )pattern matching: Assigning significance to statistically defined expression patterns in single channel microarray data (2007) ioport
  8. Grossmann, Steffen; Bauer, Sebastian; Robinson, Peter N.; Vingron, Martin: An improved statistic for detecting over-represented gene ontology annotations in gene sets (2006)
  9. Khatri, Purvesh; Bhavsar, Pratik; Bawa, Gagandeep; Draghici, Sorin: Onto-tools: An ensemble of web-accessible, ontology-based tools for the functional design and interpretation of high-throughput gene expression experiments. (2004) ioport
  10. Draghici, Sorin; Khatri, Purvesh; Bhavsar, Pratik; Shah, Abhik; Krawetz, Stephen A.; Tainsky, Michael A.: Onto-tools, the toolkit of the modern biologist: Onto-express, onto-compare, onto-design and onto-translate. (2003) ioport