Asa Ben-Hur, Assistant Professor
Department of Computer Science, Colorado State University

Beh-Hur's CV (pdf)

Title: A Kernel Method for Predicting Protein-Protein Interactions

Abstract: Most proteins perform their function by interacting with other proteins.
Therefore, information about the network of interactions that occur in a cell can greatly increase our understanding of protein function. We present a kernel method for predicting protein-protein interactions using a combination of data sources, including protein sequences, annotations of protein function, local properties of the network, and interactions in different species. We propose a pairwise kernel that provides a similarity between pairs of proteins, and illustrate its effectiveness in conjunction with a support vector machine classifier. We obtain improved performance by combining several sequence-based kernels and by further augmenting the pairwise sequence kernel with features that are based on additional sources of data.

Larry Hunter,
University of Colorado School of Medicine

Dr. Kirk E. Jordan (Bio)
Emerging Solutions Executive IBM Strategic Growth Business/Deep Computing

Title: Blue Gene/L Impacting Computational Biology - One Year Later

Authors: Kirk E. Jordan, IBM Deep Computing

Last year at Rocky ’04, I asked the question is Blue Gene a System for Computational Biology? One year has passed and Blue Gene has been placed at several sites, many of which have a computational biology component. In this talk, I will review some of the results obtained at some of these sites. I will elaborate on work underway with collaborators and colleagues in the area of computational biology. For those unfamiliar with the Blue Gene System, I will very briefly describe the hardware and software environment. I will describe how Blue Gene might be used to tackle multi-scale problems, many existing in computational biology. While progress is being made, there remain many challenges for the computational biology community to apply the Blue Gene resource to “Big” science problems with impact on society that until now or in current implementations have fallen short of the mark. Finally, I will elaborate on opportunities that exist for the community to get access to Blue Gene.

Dr. Katherina J. Kechris
Postdoctoral Fellow
University of California, San Francisco
Department of Biochemistry and Biophysics

Kechris's CV (pdf)

Title: Sequence Analysis of Human Alternative Splices Predicted from Exon Junction Arrays

Abstract: Alternative splicing of exons in a pre-mRNA transcript is an important mechanism that contributes to the protein complexity found in humans. Alternative splicing is thought to be regulated by various protein-protein and protein-RNA interactions, including those that involve specific sequence elements that act as enhancers or suppressors. The recent adaptation of DNA microarray technology to measure splice variants is providing new directions for the high-throughput study of alternative splicing. In this talk, methods will be presented for predicting alternatively spliced exons from splicing arrays that consist of exon-junction probes. I will then illustrate how contrast word counts and regression-based methods can be used to identify candidate enhancers and silencers that may regulate splice site choice.


Steve Lincoln, Vice President of Informatics, Affymetrix, Inc.

Title: Emerging Technology and Applications of Affymetrix GeneChips: Implications for Data Management and Analysis

Abstract: Over the last few years, microarray technology has made significant contributions to biomedical research and development by allowing high-quality gene expression and genotyping data to be generated in volume cost-effectively. Of the technology components needed to successfully generate and exploit such data, arguably computational analysis remains both critical today as well as a vital ongoing area of research. With current evolution of microarray technology, we believe this situation is soon to be amplified.

Using new manufacturing and instrumentation technologies which scale down to 5 micron features, Affymetrix GeneChip cartridges with over 6 million different probes, as well as 96-well plates with 150 million probes, can be reliably manufactured, hybridized and scanned. In this very brief overview we will describe various new GeneChips which have be designed using these methods and we will illustrate biological data from these chips in a variety of applications: gene expression, splice variant analysis, transcriptome analysis, genetic variation and copy number analysis. We will also provide a brief introduction to changes being implemented in instrumentation and software to better accommodate the size and complexity of these data. We will discuss data sets and other materials available to the research community who may wish to pursue any one of a number of open problems in the field.

Eugene Myers, Ph.D.
Group Leader
Howard Hughes Medical Institute, Janelia Farms Research Campus (HHMI JFRC)

Title: Computer-Assisted Forensic Analysis of Mass Disasters

Abstract: We examine the problem of identifying remains in mass disasters such as the World Trade Center, Waco, and airplane crashes. Typically, the problem is closed or nearly so, in that the individuals that could be involved are known. Depending on the state of the remains, nuclear DNA profiles, typically the 13 CODIS loci used by the FBI, are produced for each sample, and in cases where the remains are significantly degraded, as in the case of severe heat or fire, one may also sequence mitochondrial DNA from the hyper-variable control region. The problem is to determine the individual from whom each sample came from, given the genetic profiles of near relatives and possibly direct evidence from personal effects of the victim.

The talk will elaborate on the nature of the data, develop the necessary background on computing the probability of a pedigree, and formulate the overall goal as a series of algorithmic problems with a preliminary progress report on each.

Christoph W. Sensen, Professor
University of Calgary, Department of Biochemistry and Molecular Biology,
Sun Center of Excellence for Visual Genomics, Faculty of Medicine

Title: Visualizing Bioinformatics Results

Abstract: My laboratory has long been involved in the creation of tools for the integration and visualization of Bioinformatics results. Early efforts focused on the characterization of Genomes, building tools such as MAGPIE and Bluejay in the process. While we are still working on tools for 2D Bioinformatics, we have embarked on the visualization of data with a spatial and temporal aspect, such as the results of Gene Expression or Protein modification studies. Our approach is to build the computational infrastructure for 4D Bioinformatics "top down". This includes the use of Virtual Reality environments, the creation of a middleware layer, which allows scientists to explore their data space without scripting or programming, and the creation of "top down" models of the organisms that we work with (mainly humans, mice and rats). We are now beginning to conduct case studies using the new environment, which are focused on the characterization of genetic diseases and developmental patterns.