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Projects / Programmes source: ARIS

Computational Phenomics

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Research activity

Code Science Field Subfield
2.07.07  Engineering sciences and technologies  Computer science and informatics  Intelligent systems - software 

Code Science Field
B110  Biomedical sciences  Bioinformatics, medical informatics, biomathematics biometrics 
Keywords
phenomics, drug discovery, functional genomics, gene sequence analyisis, data mining, bioinformatics, artificial intelligence
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (12)
no. Code Name and surname Research area Role Period No. of publications
1.  23399  PhD Tomaž Curk  Computer science and informatics  Researcher  2007 - 2009  253 
2.  16324  PhD Janez Demšar  Computer science and informatics  Researcher  2007 - 2009  340 
3.  29992  Petra Kaferle  Biochemistry and molecular biology  Technical associate  2009  21 
4.  23398  PhD Gregor Leban  Computer science and informatics  Researcher  2007 - 2009  65 
5.  26460  PhD Mojca Mattiazzi Ušaj  Biochemistry and molecular biology  Junior researcher  2007 - 2009  62 
6.  25792  PhD Minca Mramor  Human reproduction  Junior researcher  2007 - 2009  61 
7.  20653  PhD Uroš Petrovič  Biochemistry and molecular biology  Researcher  2007 - 2009  292 
8.  31175  Gregor Rot  Computer science and informatics  Researcher  2009  45 
9.  20389  PhD Aleksander Sadikov  Computer science and informatics  Researcher  2007 - 2009  190 
10.  30142  PhD Marko Toplak  Computer science and informatics  Researcher  2008 - 2009  27 
11.  28519  PhD Lan Umek  Administrative and organisational sciences  Junior researcher  2007 - 2009  206 
12.  12536  PhD Blaž Zupan  Computer science and informatics  Head  2007 - 2009  531 
Organisations (2)
no. Code Research organisation City Registration number No. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  90,664 
2.  1539  University of Ljubljana, Faculty of Computer and Information Science  Ljubljana  1627023  16,235 
Abstract
With the advent of systems biology, research in genomic medicine and recent advances in biotechnology, biomedicine as a scientific discipline has become dependent on the computational tools to infer new knowledge from the experimental data. The research paradigms have shifted from single-gene research to genome-wide studies. One of the recent key approaches that replaced classical techniques are data-rich, large-scale phenotypes. Standard, morphological phenotypes that were most often observed in biomedical studies are no longer sufficient for system-based approaches. In the past few years, techniques in experimental biology have advanced to the point where the state of the organism can be represented with genome-wide measurements, and where such phenotypes can be measured in parallel across thousands of experimental conditions. The principal benefit of such phenotypes is in the amount of potential information they hold: instead of studying limited effects of medical treatments or observing the progress of diseases by some limited indicator, large-scale phenotypes could provide us with much richer, systemic information. As such phenotypes and technology to obtain them are only emerging, an obvious next step is to construct appropriate computational tools to address them. This is exactly the mission of the proposed project, within which we plan to develop a collection of computational approaches that use complex phenotypes in analysis of active components of chemical compounds, functional genomics (gene function prediction) and discovery of mechanisms of transcription regulation. While primarily addressing the data from model organisms, the project’s principal target is to develop enabling technology for research in drug design, drug target identification and utility of large-scale phenotypes in diagnostic and prognostic procedures. The outcome of the project will consist of new computational methods, their software implementation in open-source data mining framework, and a set of utility studies in structure-activity analysis of drugs, functional genomics and inference of genetic pathways and gene sequence analysis.
Significance for science
The project has developed a set of new generation data mining methods for data from high-throughput experiments. The main goal of the project was to develop useful implementation of these methods to assist researchers in the fields of systems biology, chemical and functional genomics. We were especially concerned with methods that can replace classical, morphological phenotypes, with description-rich phenotypes stemming from characterization of transcriptome. In functional genomics, rich phenotypes may provide increased resolution and generality, leading to more accurate predictions of gene function. In chemical genomics, they allow us to identify side effects of drugs, or to more reliably identify main effects and targets. We have been developing our methods together with several prominent research partners from abroad (Houston, Toronto, Pavia, Gratz). Several tools developed within this project are today used word-wide. For instance, dictyExpress, on of the main products of this project, is today the only application for web-based data analytics for D. discoideum transcriptomics. A manifestation of the success of this projects are many letters of thanks for the project we have developed, and emerging applications and subsequent publications with our collaborators in high-rated journals, such as Current Biology, Genome Biology, and Nature Structural and Molecular Biology.
Significance for the country
Project has develop new computational tools for transcriptome analytics, whihc serve the needs of the members of Slovene Consortium of Biochips. We (Faculty of Computer and Information Science) have formally joined this consortium in 2009. Results of the project have been presented to the consurtium at several occasions, and we have also organized a short course in February 2009. Researchers involved in this project have collaborated in a number of courses held at University of Ljubljana from the areas of functional genomics, bioinformatics and systems biology. These courses are carried out at the III. level of Bologna programs of Biomedicine and Life Sciences. We are also collaborating in preparation of a coursework for the program of Systems biology. Furthermore, we were engaged in preparation of the course Bioinformatics, that will be carried out as a part of II. level of Bologna program in Computer and Information Science at the University of Ljubljana.
Most important scientific results Annual report 2008, final report, complete report on dLib.si
Most important socioeconomically and culturally relevant results Annual report 2008, final report, complete report on dLib.si
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