Projects / Programmes
Podatkovno rudarjenje za integrativno analizo podatkov v sistemski biologiji (Slovene)
| Code |
Science |
Field |
Subfield |
| 2.07.07 |
Engineering sciences and technologies |
Computer science and informatics |
Intelligent systems - software |
| Code |
Science |
Field |
| 1.02 |
Natural Sciences |
Computer and information sciences |
Researchers (7)
| no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
| 1. |
15660 |
PhD Marko Debeljak |
Biology |
Researcher |
2009 - 2012 |
313 |
| 2. |
11130 |
PhD Sašo Džeroski |
Computer science and informatics |
Head |
2009 - 2012 |
1,204 |
| 3. |
26475 |
PhD Valentin Gjorgjioski |
Computer science and informatics |
Junior researcher |
2010 - 2011 |
15 |
| 4. |
32284 |
PhD Elena Ikonomovska |
Computer science and informatics |
Junior researcher |
2010 - 2012 |
17 |
| 5. |
31050 |
PhD Dragi Kocev |
Computer science and informatics |
Researcher |
2009 - 2012 |
204 |
| 6. |
27759 |
PhD Panče Panov |
Computer science and informatics |
Researcher |
2009 - 2012 |
155 |
| 7. |
22279 |
PhD Bernard Ženko |
Computer science and informatics |
Researcher |
2009 - 2012 |
172 |
Organisations (1)
| no. |
Code |
Research organisation |
City |
Registration number |
No. of publicationsNo. of publications |
| 1. |
0106 |
Jožef Stefan Institute |
Ljubljana |
5051606000 |
90,682 |
Significance for science
The research carried out within this project is relevant for the
development of several scientific disciplines. First, it contributes to
the field of computer science (information technologies) broadly
speaking, and the discipline of machine learning and data mining more
specifically. The project has moved well beyond the state of the art in
this area, by developing methods for the analysis of complex structured data, as well as developing an ontology of data mining for supporting complex knowledge discovery processes.
Our research is also relevant for the scientific field within which we
are applying the developed methods, namely systems biology. Even though
the problem of complex structured data analysis is highly relevant, few
effective approaches exist for mining such data. By addressing the
pressing needs of systems biology, our research greatly facilitates its
development.
The problem of analyzing complex structured data (from heterogeneous
sources in the presence of domain knowledge) is not only present in
systems biology, but also in many other scientific disciplines.
Environmental data, for example, can easily reach complexity of the
levels encountered in systems biology. We have demonstrated the
usefulness of the developed approaches on a number of environmental data
analysis problems as well. The methods developed in this project are
also relevant to other scientific disciplines that encounter complex
data analysis problems.
Significance for the country
We believe the results of our research have a direct impact on Slovenian
economy and society in the areas of information and biotechnologies, as
well as indirect impact in the areas of health and sustainable
development. More specifically, in the area of information technologies
it is conceivable that the developed methods for complex data analysis
that use background knowledge written in the form of ontologies would
give rise to a software product, which could be marketed to a
potentially broad customer base in many disciplines (incl. various types
of engineering). Slovenian industry has a strong IT sector that would be
capable of turning the achieved research results into a commercial product.
The developed methods are also used in the area of systems biology,
i.e., for integrative analysis of a variety of data about various
processes at the cell level. The knowledge discovered in this fashion
can be of use in the development of new therapies for the studied
diseases, which would be relevant for the pharmaceutical industry in
general and the Slovenian pharmaceutical industry in particular.
Diseases that we studied include embryonal tumors, Salmonella
infections, and tuberculosis.
The project promoted the visibility of Slovenian researchers and
Slovenia in the specific research areas considered (machine learning,
bioinformatics, and systems biology) and the corresponding wider
scientific areas (information technology and biology). It also increased
the international cooperation of Slovenian researchers, since our research
was (and still is) performed in cooperation with the Katholieke Universiteit Leuven, Belgium, University of Porto, Portugal, the Center for Integrative Systems
Biology at Imperial College, London, the Leiden University Medical
Center, and the Max Planck Institute for Cell Biology and Genetics, Dresden. This
facilitates the creation of consortia and formulation of international
and European project proposals in the areas addressed by the project.
The project also facilitated the transfer of knowledge in the area of
systems biology to Slovenia. Systems biology is an emerging research
area that will receive increased attention over the coming years. A
concrete example of knowledge transfer was the organization of the MLSB
2009 and 2010 workshops (Third and Fourth Workshop on Machine Learning
in Systems Biology) in Ljubljana and Edinburgh. This is a highly reputed
workshop with high quality invited speakers and reviewed contributions
that attracted more than 60 participants in each edition.
Finally, the project contributes to the development of researchers in
its areas of interest, both at the PhD student and at the PostDoc level.
The scientific content of the project is related to topics taught within
several courses at the Jozef Stefan International Postgraduate School in
Ljubljana, and the University of Nova Gorica. Its findings thus
contribute to the further development and improvement of these courses.
Most important scientific results
Annual report
2009,
2010,
2011,
final report,
complete report on dLib.si
Most important socioeconomically and culturally relevant results
Annual report
2009,
2010,
2011,
final report,
complete report on dLib.si
