Research

1. Elicitiation Knowledge from Complex Biological Data Sources

The research has aimed at integrating knowledge extracted from different repositories and resources and used them to formulate clues on the interpretation of biologically relevant events. The research activities have been developed along with a number of inter-related projects. The most relevant ones are:

  • Novel informatics infrastructure for phylogentetic analysis: this project is aimed at developing informatics solutions that enable a wider applicability of phylogeneticanaylsis methods in genomics and other ares of biomedical research. The project has already led to the development of the first ontology for comparative data analysis and work is in progress to create a minimal reporting standard for phylogenetic analysis [Lead: Pontelli].
  • Information modeling and management system for emerging pathogens: the goal of this project is to establish community-wide repositories unifying data collections relevant to emerging pathogens (e.g., Hantavirus), and to create informatics solutions to model pathogens' development and spreading [Lead: Milligan].
  • Modeling of gene regulatory networks: novel statistical techniques are investigated to enhance system-level understanding of gene regulation [Lead: Song].

2. Structure Determination of Complex Membrane Proteins

Novel approaches are investigated to enhance the determination of protein native conformations using integration of information drawn from different sources. The current line of work includes integration of data from prediction methods and from low-resolution protein density maps, with the goal of recognizing secondary structure components [Lead: He].

3. Determination of Cis-Elements and Regulatory Elements from and Expression Data

The project is aimed at developing bioinformatic tools to identify promoter regions and cis-elements within the promote regions of genes, apply them in the study of a number ofimportant molecular biology studies, especially on non-model organism, and create databses containing the discovered knowledge [Lead: Ranjan].