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SHORT DESCRIPTION
INFORMATICS METHODS FOR THE ANALYSIS AND INTERPRETATION OF LARGE GENOMIC DATASETS
The extensive
activities at sequencing the genomes of
whole organisms revolutionize molecular
biology and biotechnology. Already more
than 10 microorganisms have completely
been sequenced (Status of March 1997).
Seven genomes are openly accessible
including the eucaryote yeast with about
12 million base pairs. The sequencing of
the human genome is planned to be
completed at the latest until the year
2005. The result of the sequencings is a
wealth of data, which cannot be dealt
with any more by conventional methods of
data analysis and modelling. Yeast,
whose sequencing has just been
completed, has about 6000 genes. Already
the task of getting an overview over
this amount of data requires new methods
of data analysis. It is not sufficient
any more to concentrate on the
examination of sequence patterns,
structures and functions of single
genes, RNA-molecules or proteins.
Rather, new procedures are needed in
order to search through and assess
selectively large genomic data records.
We call such procedures "screening
methods". Here, the analysis of
evolutionary, structural and functional
similarities play an important role. The
methods for this analysis originate from
computer science and mathematics. For
this reason, in its recommendations on
progress in biotechnology, the
Technology Council of the Chancellor of
the Federal Republic of Germany
attributes a high significance to
Computational Biology and recommends, to
push it forward with much emphasis. We
react to this recommendation with the
present suggestion for a priority
program of the DFG.
The priority program addresses the
interdisciplinary expert community of
computer scientists and mathematicians
on the one side and molecular biologists
and biochemists on the other side, which
has developed in Germany and
internationally established itself.
Thanks to the sequenced genomes we have
data records at our disposal containing
all the relevant information of a
growing number of species. However, a
detailed classification of the functions
of the genetic elements can only be done
partially up to now. Well over half of
all genes of the sequenced organisms
have not yet or only insufficiently been
characterized. Therefore, the main task
of the program is explore large genomic
data sets using the methods from
computer science. These systematic
comparisons of sequence patterns as well
a models of molecular structures and
interactions make it possible to uncover
relationships between structure and
function and thus categorize cellular
building blocks into metabolic or
regulatory networks. Through the
identification of orthologous proteins
in model genomes, human hereditary
diseases can be functionally classified,
pathogenicity of microorganisms studied
or approaches for drug development
found. These methods have fundamental
significance for biological basic
research. Due to the rapidly growing
number of available genomes,
computational biology is increasingly
challenged when dealing with the
definite identification of genes which
are to be chosen as candidates for the
costly experimental function analysis.
These difficulties must be seen, in
particular, in the context of the
sequencing of unicellular organisms in a
range of 20-40 megabases considered up
by DFG.
On the methodical side appropriate
modeling of complex biological
interactions as well as the development
of efficient algorithms plays a role for
the required data throughput, but also
data handling- and accessing-problems as
well as questions concerning visual
presentation of complex data are
important. After all, screening systems
consist of many software components,
whose consistency and usability must be
assured.
The following problem areas pertain to this overall goal:
- Analysis of molecular sequence data, especially sequence alignments and analysis of sequence variability, structuring of the genome as well as polymorphisms
- Systematic genome comparison (e.g. analysis of the genomic topology of related pathogen/non-pathogen organisms)
- Molecular structure determination with methods of computer science (proteins, RNA, complexes)
- Determination of molecular function based on sequence and/or structure comparison
- Molecular biology data bases (organization, access, data validation, pattern recognition, classification)
- Computer modelling of regulatory and metabolic networks
- Visualization of molecular biology data
In all these fields the focus of the priority program is on methods that afford a sufficiently high data throughput for subjecting large genomic datasets to complex analysis, as well.
Projects to be funded in the Priority Program have to have both significant Computer Science and/or mathematics content and direct relevance to important molecular biological questions. To this end, it is important to secure the methodical side through qualified computer science and/or mathematics and simultaneously secure that the goals of the project are relevant for genome research. Scientists from the fields of computational biology, Computer science and mathematics can apply. Interdisciplinary cooperation is especially desirable.
The evaluation should be carried out by specialists that have interdisciplinary competence in both biology and computer science/mathematics. The results of the priority program should be made accessible directly to the biological research community. Therefore, the validation of tools on biological data is mandatory and the software should be usable and accessible. Routine colloquiums shall present the work of the priority program and foster the direct exchange with the bio-sciences. An internet website of the priority program is an integral part of the program.