Journal Article

PathCase: pathways database system

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

in Bioinformatics

Volume 24, issue 21, pages 2526-2533
Published in print November 2008 | ISSN: 1367-4803
Published online August 2008 | e-ISSN: 1460-2059 | DOI:
PathCase: pathways database system

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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.

Availability: Available online at


Journal Article.  5443 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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