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NSC Seminars on High Performance Computing

Please click here for information on forthcoming seminars.

List of old seminars

Time Place Speaker Title (click to see abstract)
Tue., Nov. 28, 2000, at 13.15 Room Schrödinger Prof. Göran Wahnström, Chalmers University of Technology and Göteborgs University Atomic-Scale Computational Materials Science
Tue., Dec. 12, 2000, at 16.15 Room Schrödinger Prof. Jan Komorowski, Norwegian University of Science and Technology & Linköping University Mining Microarray Data: Predicting Gene Function from Gene Expressions and Background Knowledge


Detailed Programme


Title:        Atomic-Scale Computational Materials Science

Speaker:    Prof. Göran Wahnström, Chalmers University of Technology and Göteborgs University

Time:        Tuesday, Nov. 28, 2000, at 13.15-14.00

Abstract

With the rapid development of advanced technologies materials science is confronted with many challenging problems. Atomic-scale computational materials science has become one important tool in improving our understanding and in facilitating the design of new materials. Quantum mechanical calculations provide a means to describe materials on a truly microscopic level. In principle the laws governing the behaviour of the microscopic constituents of a material, the electrons and atomic nuclei, are well known: it is sufficient to solve the Schrödinger equation. However, besides in some trivial cases this is a formidable numerical task.

I would like to present common approximations and numerical techniques used in solving the Schrödinger equation in the field of real materials. I will use vacancies in aluminium as an illustrative example. Aluminium has often been used as a test case for developing the computational methodology and, to some extent, it can be viewed as the "hydrogen atom" of computational materials science.


Title:        Mining Microarray Data: Predicting Gene Function from Gene Expressions and Background Knowledge -- State-of-the-art and Opportunities for High Performance Computing

Speaker:    Prof. Jan Komorowski

Time:        Tuesday, Dec. 12, 2000, at 16.15-17.00

Abstract

The majority of states in health or disease is most likely controlled by hundreds of genes.  Until recently, molecular biomedicine could study one or very few genes in parallel.  With the advent of the so-called high throughput micro-array technology it is now possible to observe the levels of activity in literally thousands of genes. At the same time, genome mapping projects such as, for instance, the Human Genome Initiative, which is an international research program for the creation of detailed genetic and physical maps of the human genome, generate enormous quantities of data.  For the human genome, there are approximately 100K genes out of which ca 5K genes are known.  The major goal of Functional Genomics is an assignment of function to genes.  State-of-the-art in Functional Genomics is the use of unsupervised learning methods.  Our multidisciplinary team has developed a supervised learning method for inducing predictive rule models for functional classification of gene expressions from microarray hybridization experiments.

In this talk I show how we have resolved some of the thorny issues in the functional classification of gene expressions.  Then, I identify potential research and application areas for High Performance Computing.

Nota bene. The talk is self-contained with respect to the knowledge of molecular biology.



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info@nsc.liu.se     Last modified: Jan 8, 2001        fager@nsc.liu.se