Bioinformatics and Computational Biology
Our researchers work on core computational biology-related problems, including genomics, proteomics, metagenomics, and phylogenomics. We develop novel techniques that combine ideas from mathematics, computer science, probability, statistics, and physics, and we help identify and formalize computational challenges in the biological domain, while experimentally validating novel hypotheses generated by our analyses.
We are developing algorithms with improved accuracy for large-scale and complex estimation problems in phylogenomics (genome-scale phylogeny estimation), multiple sequence alignment, and metagenomics. We are exploring gene regulation—developing advanced techniques to predict the diverse function of noncoding parts of DNA and to relate interspecies and interpersonal differences in DNA to differences in the organism’s form and function. We work broadly in the development of machine learning techniques for computational biology, with research spanning the areas of molecular and structural biology; networks and systems biology; and molecular mechanisms of human disease.
CS Faculty and Their Research Interests
|Nancy M. Amato||Modeling Molecular Motions, Protein Folding, Protein/Ligand Binding|
|Mohammed El-Kebir||Bioinformatics, Cancer Genomics, Cancer Phylogenetics, Phylodynamics, Phylogeography, Information Visualization|
|Jiawei Han||Mining Biological Text, Biological Named Entity and Relation Extraction|
|Jian Peng||Bioinformatics, Protein Function and Structure, Systems Biology, Machine Learning and Optimization|
|Saurabh Sinha||Bioinformatics, Genomics, Modeling, Sequence Analysis, Machine Learning, Probabilistic Methods, Cancer, Behavior|
|Jimeng Sun (Joining Spring 2020)||Deep Learning for Drug Discovery, Molecule Property Prediction and Generation, Genomic & Phenotypic Modeling|
|Tandy Warnow||Graph Algorithms, Statistical Estimation, Heuristics for NP-Hard Optimization Problems, Phylogenomics, Metagenomics, Multiple Sequence Alignment, Historical Linguistics|
|ChengXiang Zhai||Intelligent Biomedical Decision Support Systems, Analysis of Electronic Medical Records, Biomedical Literature Retrieval and Mining|
Bioinformatics and Computational Biology Research Efforts and Groups
- Carl R. Woese Institute for Genomic Biology (IGB)
- Comp-Gen Initiative in the Carl R. Woese Institute for Genomic Biology
- KnowEnG, an NIH Center for Excellence for Big Data to Knowledge (BD2K) in the Carl R. Woese Institute for Genomic Biology
- Midwest Big Data Hub
- National Center for Supercomputing Applications (NCSA)
Bioinformatics and Computational Biology Research News
Chemistry World -- Professor Saurabh Sinha is a member of a team that has created a fully automated algorithm-driven platform that can not only design, build, and test biochemical pathways to make valuable compounds, it can learn from its mistakes and also optimize the process.