Bioinformatics Research

The bioinformatics group’s chief aim is to better understand life through an application of a mix of established disciplines: computer science, statistics, life sciences, molecular biology, genetics, chemistry, etc. We seek to model, discover, and manage biological data typically through computational means—either creating applications directly or employing existing tools for both us and the bioinformatics community at large.

Because bioinformatics is a shared endeavor, our closely-knit group actively collaborates not only with each other, but throughout the IU Bloomington campus, with other academic institutions, and with private industry.

Bioinformatics is fueled by Indiana University’s Life Science Initiative and INGEN (INdiana GENomics Initiative), made possible by the Indianapolis-based Lilly Endowment.

What we’ll provide here is not an exhaustive listing, but an excellent approximation to the kind of ongoing projects we’re actively pursuing. To get more information, we invite you to contact us to discuss the work or possible work in more detail. The list is not presented in any special order—like bioinformatics itself it’s a grand mix of perspectives, disciplines, and pursuits about life.


The projects listed by area below are just a few examples of all of our research. Please visit the project web pages and researcher’s homepage for more information about their research projects..

Evolution and comparative genomics

Evolution of gene families/gene regulation, population genomics, gene cluster analysis, mobile genetic elements

A Platform for Computational Comparative Genomics 
Computational analysis of (gene) family evolution 
Human disease

Disease ontology, molecular analysis of protein diseases

Integration and Discovery in Gene Networks
a web-based tool designed to detect novel gene-disease associations in humans 
Protein bioinformatics

Structural bioinformatics, automated functional annotation, protein-protein interactions, text mining

Curation and Alignment Tool for Protein Analysis

Computational glycomics and glycoproteomics, peptide/protein identification and quantification using mass spectrometry

Protein Inference solutions from Proteome ARTworks 
Peptide Detectability Predictor:
Proteome ARTworks
Peptide Tandem Mass Spectrum Predictor:
Sequence analysis

String pattern matching, motif discovery, fragment assembly, RNA editing, genome alignment and segmental duplications

Improved Gibbs Motif Sampler for Proteins by Sequence Clustering and Iterative Pattern Refinement 
Systems biology

Biochemical pathways, data integration, discovery in gene/protein networks, regulatory genomics, theoretical enzymology, embryology