Computational Biology & Bioinformatics

The Computational Biology and Bioinformatics Program (CBBP) conducts research and offers services and training in the management and analysis of biological and biomedical data.

The CBBP faculty and staff are a diverse group of interdisciplinary specialists, with research interests that span the life sciences. We have expertise in building infrastructure, developing algorithms, and designing and implementing analytical approaches. The data we handle ranges from species ecology through to genomic medicine; particular focus areas are illustrated in our Research page.

The CBBP brings computer scientists and engineers together with clinicians and medical research scientists to develop the methods and tools needed for the analysis of complex high-dimensional data sets. Please visit the Research page to learn more about CBBP’s collaborative projects.


Research Highlights

  • Comorbidity: a multidimensional approach, presented by E. Capobianco and published in a Cell Journal, provides a novel view of comorbidity. Abstract:   http://www.ncbi.nlm.nih.gov/pubmed/23948386
  • Human Genome Clinical Annotation Tool, (h-GCAT). h-GCAT is an online tool designed for the analysis of whole exome/genome sequencing data obtained from families affected by genetic disorder(s). Integrated with several important clinical and biological databases, h-GCAT provides the user with a relatively simple and intuitive interface to come down to a manageable gene list from the huge dataset.
  • SNP evaluation tool. The Genomic Oligoarray and SNP array evaluation tool was developed by Zhijie Jiang and Nick Tsinoremas in the collaboration with Klaas Wierenga at University of Oklahoma. The tool can spot disease causative genes on runs of homozygosity detected by SNP arrays. Currently the tool has 1000 registered users across the world.: