A Scalable and Integrative System for Pathway Bioinformatics and Systems Biology

  • Behnam Compani
  • Trent Su
  • Ivan Chang
  • Jianlin Cheng
  • Kandarp H. Shah
  • Thomas Whisenant
  • Yimeng Dou
  • Adriel Bergmann
  • Raymond Cheong
  • Barbara Wold
  • Lee Bardwell
  • Andre Levchenko
  • Pierre Baldi
  • Eric Mjolsness
Conference paper
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 680)


Motivation: Progress in systems biology depends on developing scalable informatics tools to predictively model, visualize, and flexibly store information about complex biological systems. Scalability of these tools, as well as their ability to integrate within larger frameworks of evolving tools, is critical to address the multi-scale and size complexity of biological systems.

Results: Using current software technology, such as self-generation of database and object code from UML schemas, facilitates rapid updating of a scalable expert assistance system for modeling biological pathways. Distribution of key components along with connectivity to external data sources and analysis tools is achieved via a web service interface.

Availability: All sigmoid modeling software components and supplementary information are available through:


Bioinformatics Biosynthetic Database Metabolic Modeling Signal transduction Simulation Systems biology 



This work has been supported by NSF grant EIA-0321390 and NIH grant T15 LM007443 to PB, a Laurel Wilkening faculty innovation award to PB, a UC Systemwide Biotechnology Research and Education Program 2002–2006 award to PB, NIH grant GM069013 to EM, and NCI Director’s Challenge support to Children’s Hospital Los Angeles for EM. B.C. was supported by NIH grant T15LM07443 from the National Library of Medicine; A.L. was supported by NIH grants: GM69013 and GM072024, KS and TW were supported by NIH P50 grant GM76516, NASA Intelligent Systems Program support of EM, and by the Institute for Genomics and Bioinformatics at UCI. We would like to thank students, programmers, and colleagues who have provided us with valuable feedback or have helped implement particular components of the infrastructure. They include Ben Bornstein, G. Wesley Hatfield, Peter Hebden, Elliot Meyerowitz, Kirill Petrov, Lucas Scharenbroich, Tarek Najdi, Li Zhang, Bruce Shapiro, Diane Trout, and Chin-ran Yang.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Behnam Compani
  • Trent Su
  • Ivan Chang
  • Jianlin Cheng
  • Kandarp H. Shah
  • Thomas Whisenant
  • Yimeng Dou
  • Adriel Bergmann
  • Raymond Cheong
  • Barbara Wold
  • Lee Bardwell
  • Andre Levchenko
  • Pierre Baldi
  • Eric Mjolsness
    • 1
    • 2
  1. 1.Institute for Genomics and BioinformaticsUniversity of CaliforniaIrvineUSA
  2. 2.School of Information and Computer SciencesUniversity of CaliforniaIrvineUSA

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