The Computational Biology Research Group develops new computational methods, efficient algorithms, and powerful software tools to help answer fundamental biological questions. We are especially interested in problems related to understanding the evolution of genes, genomes, and species. Some of our specific projects include:
- Inferring gene family and genome evolution through gene duplication, horizontal transfer, and loss.
- Understanding evolution at the sub-gene/domain level.
- Reconstructing highly accurate gene trees in both eukaryotes and prokaryotes for evolutionary and functional genomic studies.
- Building whole-genome and multi-locus species phylogenies.
The computer science and engineering department at UConn is one of the best places in the world for doing research in computational biology and bioinformatics (for example, see this metrics-based ranking). The following research positions are available:
PhD positions: Positions are available in the computational biology group for bright and motivated PhD students. Please click here for further details.
Research opportunities for UConn undergraduate students: Positions are also available for qualified UConn undergraduate students who wish to gain research experience by working on exciting research problems. Please click here for further details.
May 2020: Undergraduate researchers Emily Maciejewski, Taylor Wade, and Samson Weiner will all be graduating this spring. Emily will be starting her PhD in computer science at UCLA in Fall. Taylor Wade will be joining a PostBaccalaureate research program at The Jackson Laboratory. Samson will be continuing in the lab as a PhD student starting Fall. Congratulations Emily, Taylor, and Samson!
April 2020: Paper evaluating performance of gene tree rooting methods to appear in PLOS One.
April 2020: Paper on phylogenetic tree comparison and optimal tree completion appears in Algorithms for Molecular Biology.
March 2020: Undergraduate researcher Keegan Yao wins UConn SURF award to support his summer research in the lab.
March 2020: Saurav's paper on Phylogeny-Based Inference of Disease Transmission Networks accepted to ISBRA 2020.
January 2020: Misagh's paper on TreeSolve, a new method for rapid error-correction of microbial gene trees, accepted to AlCoB 2020.
December 2019: Our software for rapid error-correction of large microbial gene trees, TreeSolve, is now available.
October 2019: Our software for accurate inference of disease transmission networks based on intra-host strain diversity, TNet, is now available.
June 2019: Our software for computing RF(+) distances between phylogenetic trees with partially overlapping leaf sets, RF+, is now available.
May 2019: Undergraduate researcher Samuel Sledzieski will be graduating and starting his PhD in computer science at MIT. We wish Sam all the best!
March 2019: Misagh Kordi successfully defended his PhD and will soon be starting a postdoc with Eran Halperin at UCLA. We wish Misagh all the best!
Software Quick Links
Phylogenetic reconciliation; Gene family evolution
Protein domain and subgene level evolution
Phylogenetic simulation of gene and subgene evolution
Horizontal gene transfer inference
Phylogenomics; Whole-genome species tree construction
Gene tree reconstruction and error-correction
Transmission network inference
Tree comparison; Optimal tree completion