1 Jun 2002 - 'Knowledge Discovery meets Drug Discovery'

May 2002
First annual "Knowledge Discovery meets Drug Discovery" Leuven, Belgium, Oct 22-23 2002

Supported by: KDNet, PharmaDM and BNVKI

Genomics, proteomics, combinatorial chemistry and high throughput screening have provided a tremendous increase in the amount of data available for use in target and drug discovery. The pharmaceutical research community has, as yet, not been able to translate these data into valuable knowledge and directly harness this knowledge into the enhancement of the drug discovery process. This is essentially because the interface between computer scientists and life scientists is still sub-optimal and needs to be addressed.
Knowledge Discovery meets Drug Discovery aims
- to inform the Knowledge Discovery community of the specific problems faced while exploring Drug Discovery data.
- to identify and anticipate new emerging technologies and trends in Knowledge Discovery and to make those available to the drug discovery scientists.

Knowledge Discovery meets Drug Discovery, for the first time, will bring together both the Drug Discovery community (bio- and chemo-informaticians as well as in-silico drug discovery scientists) and the Knowledge Discovery community in a programme that will stimulate open interaction.

Knowledge Discovery meets Drug Discovery, Oct 23 2002 Venue: Leuven, Belgium Begijnhof, Huis van Chicvres

Keynote talks address specific challenges related to knowledge discovery respectively in bio- and chemo- data. Both talks also address the need for analysis of integrated bio/chemo/clinical data and integrated analysis of structured/unstructured data.
The subsequent talks will concentrate on new technologies and trends in knowledge discovery, aimed at addressing these challenges.

Pre conference tutorial: ABC of Knowledge Discovery (for life scientists)
Date: Oct 22, 14h-18h
Venue: Begijnhof, Faculty Club: Bisschopskamer
Who should attend: Any life scientist with an interest in analysing biological and/or chemical data. Prior knowledge of Artificicial Intelligence and/or Machine learning is not required.
Scope: Introduction to knowledge discovery with concrete examples from life sciences.

Related hyperlink