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Date(s) - 26/02/2013
2:00 pm - 3:00 pm

SGDP seminar room


Grace Lu –¬†Insights into Structure Properties of Protein Complexes and Gene Variants

The project uses Protein-Protein Interaction Networks (PPINs) as a tool to extract complexes of human proteins and study their binding interfaces. Numerous studies have indicated the correlation between protein complex structure and functions. In particular, the three-dimensional (3D) properties of protein binding interfaces are thought to embed the key role in mediating biological activities and in regulating cellular functions. However, structure-based studies are limited by the low number of solved 3D structures, due to the complexity associated with their determination. Thus, the work proposed here uses the sequence information from large-scale studies to generate structure-integrated PPINs at the domain level, with the structure space enriched by the 3D modeling of homologue protein complexes and the analysis of the relative interfaces. While PPIN became an important tool to study biological systems, the biomedical field is flooded with additional information coming from the success of sequencing projects. In the last years, the completion of the 1000 Genome project has opened a new era in comparative biology and paved the way to more accurate insights in the relationship between genotype and phenotype. It is therefore very timely to combine these insights with 3D structural knowledge by studying the occurrences of Single Nucleotide Polymorphism (SNPs) on protein structures, in particular, protein interfaces and 3D-modeled interfaces. Non-synonymous SNPs (nsSNPs) could cause conformational changes or failures in forming protein complexes. A large-scale study on nsSNPs may lead us to novel insights into the relation between cellular mechanism and human diseases.


Jennifer Mollon –¬†Searching for Epistasis in Genome-Wide Association Studies: Methods and Applications

In this seminar I will outline two pieces of work I carried out during my PhD studies. First I will present a comparison of three promising methods for identifying statistical interactions associated with binary traits in genome-wide association studies, using real data as a test case. Next I will present a method and software package I developed to search for an overall enrichment in low p-values from potential statistical interactions derived from published protein-protein interactions. I will present the results of applying this method to data from the WTCCC GWAS in Crohn’s disease.

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