Shu-Yun Le

Staff Scientist working at the
Center for Cancer Research Nanobiology Program (CCRNP), CCR, NCI, NIH

Formerly the Laboratory of Experimental and Computational Biology, CCR, NCI, NIH

Formerly the Laboratory of Mathematical Biology (LMMB), NCI, NIH

Job: Computational Biology

• DNA and Protein Sequence Analysis
• RNA Structural Computation and Analysis
• Discovering Functional and Structural Features in RNAs by Computational Methods
• RNA Structure Modeling
• Interaction of RNA and RNA-binding protein
• Nanoparticle of RNA Building Block

Research Interests:

Rapid advances in computational biology and bioinformatics are providing new approaches to complex biological systems. Advances in systems biology and molecular medicine require combined efforts of bioinformaticists and molecular biologists in order to characterize mathematical models of underlying biological processes and the knowledgeable discovery of highly complex data sets. Such integrative approaches hold promise for elucidating gene function and RNA-based regulation of gene expressions, as well as for identifying potential therapeutic targets. During recent years my investigations have begun to focus on the novel challenges posed by the ongoing genomics and its generation of massive genome datasets. My research has emphasized in developing novel sophisticated algorithms by integrating statistical and computational tools of RNA folding, pattern search, sequence and structure comparison for finding ncRNAs, functional RNA elements and analysis of the complete genome sequence.

Currently, I am especially working on the following projects:

• To improve the algorithms for predicting common RNA structure and for data mining to discover RNA/DNA elements with structure-dependent functions
• Discovering viral and cellular IRES and the determination of their common structures
• Searching for functional RNA elements involving in the regulation of post-transcriptional gene control in mRNAs
• Finding ncRNAs and RNA structural motifs in genomic sequences
• 3-D modeling of small RNA structures