Research
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 tumor evolution and inferring tumor phylogenies.
- Understanding and modeling evolution at the subgene/domain level.
- Reconstructing highly accurate gene trees for evolutionary and functional genomic studies.
- Inferring infectious disease transmission networks.
- Building whole-genome and multi-locus species phylogenies.
Videos describing some of our work are publicly available on YouTube at the following URLs:
ISMB 2012 talk: https://youtu.be/Z30z9xAh8_U
ISMB 2014 talk: https://youtu.be/GoMcy7jhp6s
ISCBacademy Webinar 2021: https://youtu.be/P8P_yDeInN4
Evolution meeting 2023 virtual talk: https://youtu.be/2cRbRJSA5Qw?list=PLnl_pi1g6UveUBQ63SaajGgRfEHsHkz7c&t=1724
Open Positions
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.
Spotlight
November 2024: Samson's paper on improved reconstruction of tumor phylogenies from copy number data to appear in the journal Life Science Alliance. The corresponding software, DICE, is freely available from https://github.com/samsonweiner/DICE.
September 2024: Our new software for improved duplication-loss phylogenomics, DupLoss-2, is now available. A preprint describing DupLoss-2 is available here.
August 2024: New PhD student Naeem Ahmed joins the lab. Welcome!
August 2024: Lina's paper on automated classification of additive and replacing HGTs to appear in Genome Biology and Evolution.
March 2024: Samson's paper on microbial phylogenomics using gene tree parsimony to appear in the proceedings of RECOMB-CG 2024.
August 2023: Sumaira's paper on improving gene family sequence alignments in the presence of domain rearrangement to appear in the proceedings of ISBRA 2023.
July 2023: Samson's paper on improved simulation of single-cell copy number profiles from tumors to appear in the journal Bioinformatics.
July 2023: Abhijit's paper on generalized domain-gene-species reconciliation to appear in IEEE/ACM Transactions on Computational Biology and Bioinformatics.
April 2023: Lab member Sumaira Zaman has successfully defended her PhD dissertation. Congratulations!
April 2023: After almost two years with the lab, undergraduate researcher Rachel Parsons is graduating and will be starting her PhD in computer science at the University of Maryland in Fall 2023. We wish Rachel all the best!
February 2023: Abhijit's paper on phylogenetic dating using relative time constraints to appear in the journal Bioinformatics.
November 2022: Lab member Abhijit Mondal has successfully defended his PhD dissertation! Congratulations!
July 2022: Paper describing virDTL, a new computational protocol for viral recombination analysis, to appear in the Journal of Computational Biology.
March 2022: Sumaira's paper on the impact of partial gene transfer on gene tree reconstruction to appear in the proceedings of RECOMB-CG 2022.
March 2022: Book chapter describing the use of phylogenetic reconciliation to understand microbial evolution to appear in Methods in Molecular Biology book series.
August 2021: Samson's paper on duplication-transfer-loss reconciliation with extinct and unsampled lineages to appear in Algorithms.
July 2021: Saurav's paper on disease transmission network inference at the level of individuals and geographical regions to appear in IEEE/ACM Transactions on Computational Biology and Bioinformatics.
July 2021: Keegan's paper on optimal completion and comparison of incomplete phylogenetic trees wins best student paper award at CPM 2021.
About
The computational biology laboratory resides within the Department of Computer Science and Engineering at the University of Connecticut and is led by Mukul Bansal.
Software Quick Links
Phylogenetic reconciliation; Gene family evolution
Phylogenomics; Whole-genome species tree construction
Tumor evolution and tumor phylogenetics
Protein domain and subgene level evolution
Phylogenetic simulation of gene and subgene evolution
Horizontal gene transfer inference
Gene tree reconstruction and error-correction; Domain-aware sequence alignment
Viral transmission network inference
Phylogenetic dating
Viral recombination analysis
Tree comparison; Optimal tree completion
Supertree construction
Contact
Mukul Bansal
371 Fairfield Way, ITEB 359
Storrs, CT 06269
mukul.bansal@uconn.edu
860-486-2572