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New Software for Analyzing Biologic Pathways

By Biotechdaily staff writers
Posted on 08 Nov 2002
Software that helps scientists analyze their computational data now comes with enhancements in data modeling and data acquisition.

PathDB version 2.0 of the pathway analysis tool of the National Center for Genome Resources (NCGR, Santa Fe, NM, USA) is now available. PathDB is both a data respository and a system for building and visualizing cellular networks targeted for researchers engaged in gene expression, proteomics, and metabolic profiling. Uses include finding all pathways and phenotypes associated with genes in a cluster or validating computational predicted associations with known biological data.

The data model has changed from a concrete model of metabolism, primarily supporting curation from literature, to an abstract model for all kinds of cellular function, e.g. signal cascade, gene regulatory, protein-protein interaction, and protein-small molecule binding data, as well as metabolism.

"Leveraging off the new data model, our concentration shifted to importing large data-sets which drove the development of our Import Framework and an elegant solution to ‘publish and subscribe' for data warehousing,” said Faye Schilkey, program leader for software development at NCGR. "Researchers can now more easily focus and combine data of interest with our flexible data model and Import Framework innovations and file upload capabilities.”

NCGR's current public pathways database houses curated Arabidopsis literature, gene ontology data, and data from recently published large-scale experiments in yeast with transcriptional binding factors from Richard Young's lab at MIT staged for addition. The company says it welcomes directed-research engagements to create focused and private data-sets.

The client download is available from NCGR's website. PathDB(TM) 2.0 is free for non-commercial users. Commercial users can evaluate the client download model free for 60 days. The National Center for Genome Resources is a nonprofit institute for discovery-driven research in computational biology, medicine and bioinformatics. Its scientists have research interest in both systems biology and the development of novel methods for integrating software applications and data.




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