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Mission

The mission of the center is to foster “systems biology” approaches to addressing translational biomedical problems by breaking the existing boundaries of IUPUI academic units, facilities cores, and research centers. CSBPM will develop streamlined informatics tools and “Omics” experimental platforms built upon our in-house expertise on molecular networks and pathways. With these new capabilities, the center will promote novel research collaborations aiming to devise tailored genomics, proteomics, and metabolomics molecular strategies for future personalized medicine. The center will inspire other IUPUI researchers, through demonstration of exemplar research conducted by its founding members, how translational systems biology research could be initiated and sustained to yield significant external funding and rewarding new discovery opportunities.

What is Systems Biology? Personalized Medicine?

Systems Biology is one of the core technologies that can be developed to bridge the gap between information acquired in the post-genome era and new products for tailored clinical care—Personalized medicine. For Systems Biology, we refer to the simultaneous experimental measurement of global changes in perturbed biological systems at multiple scales, particularly at the molecular interaction network level, to understand and predict how biological systems behave. For Personalized Medicine, we refer to the application of cost-effective and individualized strategies for diagnosing, monitoring, and treating diseases.

Background

In post-genome medical research, functional genomics and proteomics analyses have led to many early successes in the molecular level classification of diseases, patients, or treatments. The new knowledge and their positive or adverse clinical implications can now be weighed quantitatively by informatics researchers and medical scientists. The excitement lies in the possibility of translating results from these analyses into disease biology knowledge and eventually generating individualized treatment options that are based on the likelihood of both the adverse outcome and therapeutic benefit of a given regimen—a field known as genome-based personalized medicine.

On of the major conceptual breakthrough is to perform patient stratification based on molecular systems biology knowledge discovery outcomes. The post-genome personalized medicine outlook represents a paradigm shift for traditional therapeutics, which was required to assume that all patients with a given disease have equal chances of developing complications. However, the unprecedented amount of data generated by new “Omics” high throughput instruments pose a significant practical challenge to their adoption by any translational medical research community. First, being able to interpret clinical data in the emerging context of bioinformatics at sub-cellular and molecular levels is the trend for addressing complex disease treatment and diagnostics problems in future clinics. Second, there are apparent limitations of current technology, including genome sequencing (for genotyping), RNA microarrays (for functional genomics), and mass spectrometers (for functional proteomics), for correlating observations at different scales and therefore requiring “networks and systems” level interpretation of molecular profiles of disease. Third, the science that explores cooperative complex relationships between genes, proteins, metabolites, cells, signaling molecules, environmental factors, and other complication factors suggests only an interdisciplinary team with holistic approaches would have the highest chance of success in research.

Scope of Research

The followings are examples of research topics related to Systems Biology and Personalized Medicine. These only serves as a guide to inspire additional thinking:

• Integrative Proteomics, Transcriptomics, and Metabolomic Analysis
• Disease Molecular Classifications
• Computational methods in stratifying patients based on genomics, proteomics, metabolic, environmental, and dieting factors
• Gene Regulatory Network Construction and Analysis
• Modeling and Simulation of biological networks and pathways
• Network Biology and Disease
• Statistical learning methods in disease-oriented systems biology
• Clinical applications of Genomics, Proteomics, and Glycomics
• Computational biomarker discoveries
• Computational drug discoveries using structural methods
• Semantic webs and ontology-driven biological data integration methods

Planned Scholarly Activities at CSBPM

The center will hold monthly brainstorming meetings for monitoring the progress of funded pilot projects, formulating grant proposal ideas, mocking review for proposals to be submitted, and proposing/advancing new pilot projects if budgets allow. Moreover, we will co-sponsor weekly seminar series to stimulate scientific discussions and seek potential collaborations. In addition, we will co-sponsor the annual meeting of Bioinformatics for the Midwest in Indianapolis with the Center for Computational Biology and Bioinformatics. Further, we will implement a plan for annual one-day on-site reviews by several external experts (former NIH panel members) who will offer their advices to the strength, weakness, and future development of the center. At the meantime, this exercise will promote our center to the scientific community.