Bioinformatics, a convergence of biological and computational sciences, is a growing area of research interest in the Department of Computer and Information Sciences at the University of Delaware. The department, an active participant in the Delaware Biotechnology Institute, has five faculty members engaged in research in this area, applying their expertise in machine learning, distributed artificial intelligence, computer vision, and natural language processing to address a wide variety of biological problems.
In addition, the Department of Computer and Information Sciences is also the academic home of the Center for Bioinformatics & Computational Biology (CBCB). The CBCB is an interdisciplinary, cross-campus and inter-institutional initiative for the Delaware research and education community, and is built on the Bioinformatics core at the Delaware Biotechnology Institute (DBI) and the Bioinformatics infrastructure of the Protein Information Resource (PIR). Students who are interested in Bioinformatics can apply directly to the Graduate programs in Bioinformatics and Computational Biology. These programs are administered through the Department of Computer & Information Sciences, and are coordinated by the CBCB.
Current projects include identifying protein homologues such as immune system enhancers and transporter proteins, building automated annotation systems, inferring genetic networks and their evolution, analyzing images of microarrays, and protein docking, and text-mining information such as protein-protein and protein-drug interactions from biomedical literature. These projects are supported by grants from NSF, NIH, USDA, and the US Army.
- Keith Decker, Associate Professor: Automated information gathering and integration; Data mining/extraction; Gene networks and pathways.
- Chandra Kambhamettu, Professor: Protein docking; Image analysis; Visualization for bioinformatics applications.
- Li Liao, Associate Professor: Functional; Comparative genomics; Gene networks and pathways; Machine learning.
- Vijay Shanker, Professor: Text mining; Information extraction; Machine learning.
- Hagit Shatkay, Associate Professor (joint appointment with Center for Bioinformatics & Computational Biology and Biomedical Engineering): Computational biology; Medical informatics; Bioinformatics; Machine learning; Data and text mining, and their various combinations.
- Cathy Wu, Edward G. Jefferson Chair of Bioinformatics and Computational Biology: Biological Text Mining; Biological Ontology; Computational Systems Biology; Protein Structure-Function-Network Analysis; Bioinformatics Cyberinfrastructure
- CISC 636 Bioinformatics
- CISC 637 Database Systems
- CISC 681 Artificial Intelligence
- CISC 841 Bioinformatics
- CISC 849 Computational Biomedicine
- CISC 889 Advanced Topics: Bioinformatics
- CISC 889 Advanced Topics: Machine Learning
- CISC 889 Advanced Topics: Modeling and Simulation for Bioinformatic Systems
Bioinformatics Research Group Laboratory
421 Smith Hall, Professor Li Liao.
Dr. Liao’s laboratory is developing algorithms and models that offer computational solutions to important biological problems, which include: annotating biochemical functions for proteins, predicting structure of transmembrane proteins, identifying elements that regulate gene expression, and predicting protein-protein interactions. One of the projects in the laboratory, funded by an NSF grant, is to develop assembly algorithms for de novo genome sequencing using two next-generation sequencing technologies which have been said to revolutionize genomic research – decoding a human being’s genome at cost less than $1000.
Center for Bioinformatics & Computational Biology (CBCB)
147D Ammon-Pinizzotto Biopharmaceutical Innovation Building
Delaware Biotechnology Institute, Professor Cathy Wu and research team: Professors Cecilia Arighi, Chuming Chen, Hongzhan Huang, and Shawn Polson, and Manabu Torii.
Bioinformatics and Computational Biology is an emerging field where biological and computational disciplines converge.
Dr. Wu’s team conducts research encompassing protein structure-function-network analysis, biological text mining, biological ontology, computational systems biology, and bioinformatics cyberinfrastructure. The Protein Information Resource (PIR, http://ProteinInformationResource.org) directed by Dr. Wu provides integrated databases and bioinformatics tools to support genomics, proteomics and systems biology research. PIR is a member of the UniProt Consortium (https://www.uniprot.org) which offers a central international resource on protein sequences and function. The UniProt web site is accessible by researchers worldwide with over 100 million webhits (6.5 million pageviews) from more than 775,000 unique sites on a monthly average. and is accessible by researchers worldwide with 10 million+ web hits/month from 100,000+ unique sites. Funded by NSF, NIH and DOE grants, among others, her team is developing a research infrastructure for integrating, mining, analyzing, visualizing and modeling high-throughput omics data in systems biology context to help basic understanding of biology and facilitate drug discovery, disease diagnosis, and energy and environment studies.
Computational Biomedicine Laboratory
111 Elkton Rd., Professor Hagit Shatkay
We are interested in finding computational solutions to current biomedical problems. In the laboratory we develop and use algorithms and machine learning methods to explain and predict biological processes and medical outcomes. In particular we are interested in mining biomedical text, analyzing patient data as well as genomic and proteomic sequence data, predicting protein subcellular location, biomedical image analysis, and integrating biological and medical data from multiple sources and types to address problems presented to us by biologists and physicians.
Text Mining Laboratory
102 Smith Hall, Professor Vijay Shanker.
The Text Mining Laboratory, directed by Vijay Shanker, is concerned with the development of language technology algorithms to assist scientists to rapidly access relevant information from research literature. Projects include the extraction of targeted information, retrieval of relevant textual passages, and assistance in the knowledge discovery process. A related project involves rapid adaptation of language processing tools that were developed for a general domain to be used in a specific domain. A third project involves multi-disciplinary effort that integrates natural language cues found in large software programs and program analysis for multiple software development and maintenance tasks.
Multi Agent Systems Laboratory (MAS Lab)
447 Smith Hall, Professor Keith Decker.
An agent is a computer system capable of flexible, autonomous action in dynamic multi-agent environments. The success of the Internet has shown that computing is no longer only about fast numerical calculation, or isolated information processing. It is now also about interaction and coordination amongst machines, and between machines and people. The MAS laboratory focuses on the science of coordination in applications ranging from distributed energy management and emergency response support to scientific information gathering.
Computational Learning Laboratory
342 Smith Hall, Professor John Case.
The members of the Computational Learning Laboratory do theoretical, mathematical work regarding abstract machine models of, among other things, learning and self-modeling.
VIMS Vision Laboratory
212 Smith Hall, Professor Chandra Kambhametu.
VIMS (Video/Image Modeling and Synthesis) Lab encompasses research in areas related to computer vision and graphics. Our current research topics include camera systems, structure and motion recovery, stereo vision, facial image analysis, medical image analysis, object recognition and scene understanding, scientific visualization. Work done at VIMS explores solutions to challenging real-world problems such as Arctic ice motion and thickness studies, medical diagnosis and assistive robotics.