University of Delaware - College of Engineering


Laboratories - Bioinformatics

Learn about Bioinformatics Research

Bioinformatics and Computational Biology Laboratory

421 Smith Hall, Professor Li Liao.

205 Delaware Biotechnology Institute, Professor Cathy Wu and research team: Professors Cecilia Arighi, Chuming Chen, Hongzhan Huang, Shawn Polson, and Manabu Torii.

Bioinformatics and Computational Biology is an emerging field where biological and computational disciplines converge.

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.

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, directed by Dr. Wu provides integrated databases and bioinformatics tools to support genomics, proteomics and systems biology research and is accessible by researchers worldwide with 10 million+ web hits/month from 100,000+ unique sites. Funded by NSF, NIH and DOE grants, 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.

Global Computing Laboratory (GCLab)

203 Smith Hall, Professor Michela Taufer.

The Global Computing Laboratory focuses on various aspects of high performance computing (HPC) and its application to the sciences. We are engaged in the design and testing of efficient computational algorithms and adaptive scheduling policies for scientific computing on GPUs, cloud computing, and volunteer computing. Interdisciplinary research with scientists and engineers in fields such as chemistry and chemical engineering, pharmaceutical sciences, seismology, and mathematics is at the core of our activities and philosophy.

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.

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