Friday, September 6, at 327 Yost
Refreshments: 3:00 - 3:30 p.m, Talk: 3:30
- 4:30 p.m.
A major problem in studying biological traits and systems biology is
understanding how genes work together to provide organismal structures and
functions. Conventional paradigms usually involve a reductionist approaches
where specific functions are attributed to particular genes, motifs and
amino acids. The equally important but harder problem involves the
synthesis of information to understand functionality at higher levels. We
have developed a computational method, called Phenotype Segregation
Networks (PSNs), that uses assays of component traits to learn about higher
level systems. We used subtle, naturally-occurring, multigenic variation of
cardiovascular(CV) properties in the A/J and C57BL/6J strains and the AXB /
BXA RI strains to perturb CV functions in non-pathologic ways. In this
proof-of-concept study, computational analysis correctly identified the
known functional relations among CV properties and revealed key aspects of
heart functions. This PSN was then used to account for the functional
consequences of single gene mutantions and the effects of drug treatments.
PSNs account for functional dependencies in ways that genetic networks and
biochemical pathways do not and are therefore an important complementary
approach for defining and characterizing functional relations in complex
biological systems in health and disease.