Biological network analyses: computational genomics and systems approaches

Abstract

The complex responses of cells to stimuli are the aggregate of alterations at the genetic, protein, metabolic and cellular levels. The immense quantities of data now available from high-throughput genomic, proteomic and metabolomic sources require specialized analytical approaches. The integration of such data for the computational elucidation and analysis of cellular pathways and networks is an area of considerable current interest. As the quantity of available data continues to increase, strategies to extract the useful information from the data will continue to provide answers to important biological questions. Chemical engineers are actively involved in this field that has taken on the global title of “Systems Biology”. These research groups have made considerable impact from both the computational and experimental standpoints. This commentary describes some of the recent contributions of chemical engineering researchers to the computational analysis of high-throughput, multi-source data as described in recent publications and presentations from the 2005 AIChE Annual Meeting.

Keywords:

• Systems biology
• Network inference
• Multi-source data
• Signaling networks
• Integrated networks

Acknowledgements

The authors gratefully acknowledge support from the National Science Foundation (BES 0222747, BES 0331297, and BES 0425821), the Environmental Protection Agency, the Whitaker Foundation, and Michigan State University. Z. L. is supported in part by a deVlieg fellowship for Computational Engineering at Michigan State University.

Notes

^†Tel.: [phone]. Fax: [phone].

^‡Email: [email protected].

^¶Email: [email protected].

Additional information

Notes on contributors

S.P. Walton

† †Tel.: [phone]. Fax: [phone].

Z. Li

‡ ‡Email: [email protected].

C. Chan

¶ ¶Email: [email protected].