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Mission Statement
Bioinformatics is a research area at the intersection of
biology, medicine, computer science, mathematics and statistics. Bioethics and
linguistics are important supporting disciplines.
Bioinformatics aims at computational modeling of biological
phenomena and applies techniques from areas such as artificial intelligence,
databases, software engineering, theoretical computer science, discrete
mathematics, optimization theory, control theory and statistical modeling.
Bioinformatics makes up an integral part of much of
research in modern biology, medicine, veterinary and agricultural sciences.
|  | Goals and aims |
| | | To become a centre of excellence through cutting edge research.
To conduct joint research projects in cooperation with researchers in
biological sciences and leading centres of bioinformatics.
To go beyond traditional lines of research and cooperate with the
humanities in areas such as linguistics and ethics.
To attract talented students to bioinformatics.
To provide, in cooperation with the Swedish EMBnet node,
bioinformatics services and expertise, and in particular help develop a
bioinformatics infrastructure for the national Functional Genomic research
initiative.
To provide education in bioinformatics for Swedish science and industry.
To develop mutually beneficial relationships with industry.
To foster collaborations with computer scientists, mathematicians and
statisticians.
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Our strengths
A unique composition of computational and mathematical
competence coupled with a commitment to interdisciplinary work.
Enthusiasm of the founding members of the centre and an
outstanding environment provided by some of the largest biomedical
research centres in Europe.
An established track record in bioinformatics.
Geographical location in the Stockholm-Uppsala region with
the highest density of biotech companies in Europe.
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| | Tools |
| | | ROSETTA
is a toolkit for analyzing tabular data within the framework of rough
set theory. ROSETTA is designed to support the overall data mining and
knowledge discovery process: From initial browsing and preprocessing of
the data, via computation of minimal attribute sets and generation of
if-then rules or descriptive patterns, to validation and analysis of the
induced rules or patterns. .
more tools...
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