Research
Interdisciplinary Nature Enables Expanded Research Potential
WPI’s Bioinformatics & Computational Biology (BCB) program comprises multiple disciplines, and the research focus areas of our program are similarly varied and diverse. Working in state-of-the-art facilities like WPI’s Life Sciences and Bioengineering Center at Gateway Park, our faculty and student researchers make groundbreaking discoveries at the intersection of Biology, Mathematics, and Computer Science.
Research Area Focus
- Clinical and health informatics
- Combinatorics of sequences
- Comparative genomics
- Computational epidemiology
- Data mining and machine learning of biological data
- Data visualization
- Genome-wide association studies
- Mathematical biology
- Simulation of biological systems
- Structural bioinformatics
- Systems and network biology
WPI Researcher Shares 3D Roadmap of Coronavirus with Scientists Worldwide
Researchers use Mixed Reality to Visualize Complex Biological Networks
Learn more about our fascinating research efforts and world-class faculty members involved in them:
Faculty Member | Research Focus Areas |
---|---|
Computer graphics, mobile computing, wireless networks, smartphones as healthcare delivery platform | |
Tanja Dominko | Regenerative cell biology, stem cells, nuclear reprogramming, epigenetics, reproductive/developmental biology |
Joseph B. Duffy | Cancer biology/signal transduction, cancer therapeutics, cell adhesion mechanisms, neurodegenerative disorders |
Database management systems, information management | |
Information visualization, visual analytics, human-computer interactions | |
Data mining, social networks, machine learning, big data analytics, connectome | |
Dmitry Korkin | Bioinformatics of disease, big data in biomedicine, computational genomics, systems biology, data mining, machine learning |
Amity Manning | Cancer cell biology, cell cycle regulation, mitotic progression and chromosome segregation, chromatin regulation, genome stability |
Algebraic combinatorics, applied combinatorics | |
Mathematical biology, chemical signaling, mechanics, hydrodynamics | |
Large scale data analytics, statistical machine learning, compressed sensing, network analysis. | |
Samuel M. Politz | Genetic control of surface glycoprotein expression in C. elegans, chemosensory control of nematode behavior and development, host immune responses to parasitic nematode infections |
Genomic studies and high throughput screening to understand and manage fungal diseases in humans | |
Data mining, machine learning, artificial intelligence, biomedical data mining | |
Data and information management, big data analytics, visual data discovery, stream and pattern mining, large scale data infrastructures | |
Elizabeth F. Ryder | Computational biology, simulation of biological systems, neurobiology |
Combinatorics, matroid and graph theory, structural topology, geometry, history and philosophy of mathematics | |
Scarlet Shell | Bacterial pathogenesis, bacterial stress response, prokaryotic gene regulation, prokaryotic genomics and transcriptomics |
Bacterial pathogenesis, bacterial stress response, prokaryotic gene regulation, prokaryotic genomics and transcriptomics | |
Biofluids, biosolids, blood flow, mathematical modeling, numerical methods, scientific computing, nonlinear analysis, computational fluid dynamics | |
Erkan Tuzel | Statistical mechanics and polymer physics applied to biology and materials science |
Plant cell biology and molecular genetics, live cell microscopy, molecular motors/cytoskeleton | |
Biostatistics, high-dimensional model selection, linear and generalized linear modeling, statistical genetics, bioinformatics | |
Financial time series, spatial statistics, biosurveillance, high dimensional statistical inference, Bayesian statistics |
State-of-the-Art Facilities Enhance Research and Learning
BCB faculty and students benefit from access to diverse resources available through participating academic departments, the campus computation center, and the research laboratories at Gateway Park, as well as University of Massachusetts Medical School.
Grid and cloud computing, along with high-speed networking, provide substantial computational infrastructure. Students and researchers can tap into most major biological databases, and a wide range of bioinformatics software packages are installed and maintained. Wet labs at the Life Sciences and Bioengineering Center at Gateway Park and University of Massachusetts Medical School are also available for use.