An Integrative Computational Framework for Hypotheses-Driven Systems Biology Research in Proteomics and Genomics
Systems biology research is sometimes categorized as either discovery science or hypothesis-driven science. However, we believe that hypotheses are always used regardless, and that explicit recognition that hypothesis testing underlies all high-throughput data analysis leads to better experimental designs, data analysis and interpretation of the data. We outline the current use of hypothesis testing for proteomics data analysis in systems biology research for several projects at the Pacific Northwest National Laboratory, and provide examples of where scientific principles can be used to formulate the hypotheses used to analyze the data. We additionally discuss the data infrastructure is required to (1) track the data from different projects and diverse assays, (2) pull the data together in a congruent manner, (3) analyze the data with respect to cellular networks, and (4) visualize the resulting networks and contrast those with information from bioinformatics databases.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 961674
- Report Number(s):
- PNNL-SA-57999; KJ0101030; TRN: US200923%%159
- Resource Relation:
- Related Information: Computational and Systems Biology: Methods and Applications, 63-85
- Country of Publication:
- United States
- Language:
- English
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