General Research Interest

I am interested in applying techniques from computer science and mathematics to biological problems. My current work focuses on investigating alternative splicing, developing methods for analyzing microarray and deep sequencing experiments, designing algorithms for finding common intervals, and developing animations for Bioinformatics Education.

Current Research Projects

Alternative Splicing

In higher eukaryotes, genes often contain intervening sequences called introns. During splicing the introns are removed and the remaining sequences, the exons, are concatenated. Often, a gene might be spliced in various ways, resulting in several splice variants and the corresponding protein isoforms. This process is known as alternative splicing. I am interested in investigating alternative splicing and its regulation in specific contexts, such as different cell and tissue types, different developmental stages, different environmental stresses, and in disease. Please visit the Alternative Splicing Gallery (ASG) to see some of my work.

Analyzing High-Throughput Gene Expression Data

DNA microarrays have been the tool of choice for measuring gene expression. Recently, deep sequencing has emerged as a powerful alternative. Both approaches produce vast amounts of data. How to store, retrieve and analyse the resulting data is, to date, a major research challenge. My lab is currently developing methods to support experimental design, automatic and semi-automatic preprocessing, and data analysis of high-throughput gene expresssion data.

Common Intervals

Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of the same set of elements, is called a common interval. Common intervals have applications in different fields. In Bioinformatics, common intervals are used to detect possible functional associations between genes. It is assumed that neighboring genes occurring together in different genomes tend to encode functionally interacting proteins. Other applications use common intervals to compute the reversal distance between genomes, and to define a similarity measure for gene order permutations. In the context of combinatorial optimization, genetic algorithms using subtour exchange crossover based on common intervals, have been proposed for sequencing problems such as the traveling salesman problem or the single machine scheduling problem.

Educational Animations

Due to the interdisciplinary nature and rapid pace, Bioinformatics is a challenging task for students and teachers. Despite many excellent text books and tutorials, there are few supplementary educational tools available. Animations can enhance student learning of complex Bioinformatics topics by providing additional visual representations. Most students are able to grasp information in animated graphical form better than in textual form. Often, in-class animations improve attention and increase students' enthusiasm for the subject. Using animation, concepts and algorithms will become less intimidating and more accessible. Students' attitude towards Bioinformatics classes will improve, resulting in better learning outcomes. We are currently developing a library of animations for teaching Bioinformatics, please visit the Bioinformatics in Motion project.

Software

Alternative Splicing Gallery (ASG)

Remote Analysis Computation for gene Expression data (RACE)

Bioinformatics in Motion

Research Funding

Current Students

Previous Students

  1. Pankaj Chopra, PhD Computer Science, Co-Chair with D.Bitzer, completed 4/9/2009
  2. Sihui Zhao, PhD Bioinformatics, Chair with Z.B.Zang, completed, 3/23/2009
  3. Wang, Tianyuan, PhD Bioinformatics, Chair with E.Hauser, completed 3/12/2009
  4. Benjamin Wheeler, MS Computer Science, Chair, thesis, completed 5/7/2008
  5. Li Li, PhD Bioinformatics, Chair, completed 9/20/2007
  6. Soma Saha, MS Computer Science, Chair, thesis, completed 2007
  7. Dhiral Phadke, MR Bioinformatics, Chair, completed 2005
  8. Hermonta Godwin, MS Bioinformatics, Chair, completed 2005