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Projects / Programmes source: ARIS

Knowledge technology approaches in drug discovery: analysis and experiment planning in high-throughput genetics

Research activity

Code Science Field Subfield
2.07.00  Engineering sciences and technologies  Computer science and informatics   

Code Science Field
B110  Biomedical sciences  Bioinformatics, medical informatics, biomathematics biometrics 
Keywords
artificial intelligence bioinformatics data mining,experiment planning, chemical genomics drug development
Evaluation (rules)
source: COBISS
Researchers (14)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  02275  PhD Ivan Bratko  Computer science and informatics  Researcher  2008 - 2011  743 
2.  23399  PhD Tomaž Curk  Computer science and informatics  Researcher  2008 - 2011  253 
3.  23940  PhD Boštjan Japelj  Physics  Researcher  2008  38 
4.  29992  Petra Kaferle  Biochemistry and molecular biology  Researcher  2008 - 2011  21 
5.  00412  PhD Igor Križaj  Biochemistry and molecular biology  Researcher  2008 - 2011  727 
6.  18355  PhD Drago Kuzman  Physics  Researcher  2008  64 
7.  26460  PhD Mojca Mattiazzi Ušaj  Biochemistry and molecular biology  Researcher  2008 - 2011  62 
8.  25792  PhD Minca Mramor  Human reproduction  Researcher  2008 - 2011  61 
9.  24465  PhD Luka Peternel  Cardiovascular system  Researcher  2008  49 
10.  20653  PhD Uroš Petrovič  Biochemistry and molecular biology  Researcher  2008 - 2011  292 
11.  30142  PhD Marko Toplak  Computer science and informatics  Researcher  2008 - 2011  27 
12.  28519  PhD Lan Umek  Administrative and organisational sciences  Junior researcher  2008 - 2011  206 
13.  01878  PhD Uroš Urleb  Pharmacy  Researcher  2008  381 
14.  12536  PhD Blaž Zupan  Computer science and informatics  Head  2008 - 2011  532 
Organisations (3)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  90,976 
2.  0258  Lek Pharmaceutical Company d.d.  Ljubljana  1732811  8,210 
3.  1539  University of Ljubljana, Faculty of Computer and Information Science  Ljubljana  1627023  16,285 
Abstract
With recently developed high-throughput technologies that allow us to gather biomedical data on genome-wide scale under a wide range of experimental conditions, scientific discovery has shifted from labour-intensive to computationally intensive task. The project will develop and apply a set of computational tools for inference of the mechanism of action of pharmacologically active substances in a model organism S. cerevisiae. In the application we will use a set of chemical-genomics profiles, that is, currently the most informative source on the interactions between drugs and genes. Data mining will be used to uncover the mechanism of drugs’ action. We will combine data analysis with in silico experiment planning techniques, and carry the proposals out on a robotic platform to increase the reliability of proposed hypotheses. The expected principal results of this projects are A) bioinformatics toolbox (data analysis through clustering and classification of complex, genome-wide profiles, experiment planning through active learning), B) identification of a set of marker genes/mutants with high information content to predict the mechanism of drugs’ action, and C) a prototype of a high-throughput experimental platform combining state-of-the-art technologies from genetics, laboratory robotics and computational analysis for rapid classification of molecules based on their chemical-genetic interactions. Chemical-genomics is a very young and promising field of functional genomics, requiring dedicated computational tools for their application. With current practical demonstrations in this field being presently at best rare, development and application of proposed knowledge technology tools for analysis and proposal of experiments in drug discovery should be regarded as highly original.
Significance for science
In the project we developed the most accurate method to date for measuring growth rate of yeast cells in colonies in a small area, which enables determination of fitness phenotype of individual strains. This development is important from the perspective of increase in the accuracy of some of the techniques used in high-throughput genetics, as well as in the design of live cells-based biosensors.
Significance for the country
In the project we introduced new high-throughput genetics method not previously known in Slovenia, and through that enabled know-how important for competitiveness of pharmaceutical industry. The project is important also because of the training of postgraduate and undergraduate students in the fast-evolving area of functional genomics.
Most important scientific results Annual report 2008, 2009, final report, complete report on dLib.si
Most important socioeconomically and culturally relevant results Annual report 2008, 2009, final report, complete report on dLib.si
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