The research focus of Digital Biology Laboratory (DBL) is Bioinformatics and Computational Biology in the following areas: Poster1 Poster2
Protein Structure Prediction and Modeling: DBL develops effective computational methods for protein structure prediction and modeling. The research in this area includes protein secondary structure prediction, protein tertiary structure prediction, protein structure comparison, and structure-based function prediction.
High-throughput Biological Data Analyses
: DBL develops novel computational techniques for analyzing large-scale biological data, including genomic sequence, gene expression, protein-protein interaction, epigenomic data, proteomic data, and phenotypic data. A number of software tools have been developed for experimental design (e.g. high-throughput primer/probe design) and predictions of gene functions, protein phosphorylation, and biological pathways.
Application of Bioinformatics Methods in Biological Systems
DBL applies various computational methods/tools and available experimental data in studying the evolution, protein structure, gene function, gene regulation, and biological pathway through collaboration with experimentalists. The main target systems are plants, microbes, and human cancers.
Research has been supported by DOE, NSF, USDA, NIH, US Army, United Soybean Board, Missouri Soybean Merchandising Council, Missouri Life Science Trust Fund MU start-up fund, Monsanto Research Fund and National Center for Soybean Biotechnology.