PathCase: Pathways database system

Brendan Elliott*, Mustafa Kirac, Ali Cakmak, Gokhan Yavas, Stephen Mayes, En Cheng, Yuan Wang, Chirag Gupta, Gultekin Ozsoyoglu, Zehra Meral Ozsoyoglu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

Abstract

Motivation: As the blueprints of cellular actions, biological pathways characterize the roles of genomic entities in various cellular mechanisms, and as such, their availability, manipulation and queriability over the web is important to facilitate ongoing biological research. Results: In this article, we present the new features of PathCase, a system to store, query, visualize and analyze metabolic pathways at different levels of genetic, molecular, biochemical and organismal detail. The new features include: (i) a web-based system with a new architecture, containing a server-side and a client-side, and promoting scalability, and flexible and easy adaptation of different pathway databases, (ii) an interactive client-side visualization tool for metabolic pathways, with powerful visualization capabilities, and with integrated gene and organism viewers, (iii) two distinct querying capabilities: an advanced querying interface for computer savvy users, and built-in queries for ease of use, that can be issued directly from pathway visualizations and (iv) a pathway functionality analysis tool. PathCase is now available for three different datasets, namely, KEGG pathways data, sample pathways from the literature and BioCyc pathways for humans.

Original languageEnglish
Pages (from-to)2526-2533
Number of pages8
JournalBioinformatics
Volume24
Issue number21
DOIs
Publication statusPublished - Nov 2008
Externally publishedYes

Funding

Funding: National Science Foundation (DBI 0218061and CNS-0551603); Charles B. Wang Foundation to the Center for Computational Genomics, CWRU.

FundersFunder number
Charles B. Wang Foundation
National Science FoundationDBI 0218061and CNS-0551603
Case Western Reserve University
Center for Computational, Evolutionary and Human Genomics, Stanford University

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