• Genomic data is huge and searching for pattern over long DNA sequence is time consuming. To resolve the issue of huge amount of data and efficient pattern search, we aim to create indexing data-structure that is compressed. To this end, we have developed algorithms for next generation sequencing analysis.
  • Phylogenetic tree is used to study the evaluation relationship among a set of taxa and has been widely used in many biological areas. We have developed novel methods to construct and compare phylogenetic trees and networks.
  • The most direct mechanism to control the expression of genes is through controlling the initiation of the transcription process. One crucial point in this process is the binding of transcription factors to DNA. We have collaborated with biologists to analyze the next generation sequencing data to identify bidning sites of different TFs, predict the interaction of genomic regions, as well as predict the 3D chromatin structure of our genome.
  • Novel approaches to analyze proteomic profiles in the context of biological networks.
  • Plant metabolites are compounds synthesized by plants for essential functions, such as growth and development, and specific functions, such as pollinator attraction and defense against herbivores.
  • There is a critical need to address the emergence of drug resistant varieties of pathogens for several infectious diseases. We propose a system-based approach to analyze and counter drug resistance in pathogens, with M. tuberculosis as a test case.
  • Interaction data obtained by high-throughput assays may contain as much as 50\% false positives and false negatives. Further progress is needed to distinguish between permanent and trainsient interactions, to distinguish proten complexes from functional modules.
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