Different definitions of the Bioinformatics are used. One example: “The merger of biotechnology and information technology with the goal of revealing new insights and principles in biology” [1]. Another example: «Bioinformatics derives knowledge from computer analysis of biological data. These can consist of the information stored in the genetic code, but also experimental results from various sources, patient statistics, and scientific literature. Research in bioinformatics includes method development for storage, retrieval, and analysis of the data. Bioinformatics is a rapidly developing branch of biology and is highly interdisciplinary, using techniques and concepts from informatics, statistics, mathematics, chemistry, biochemistry, physics, and linguistics. It has many practical applications in different areas of biology and medicine» [2]. We define the Bioinformatics as a multidisciplinary field of science, integrating informational-computational technologies with the achievements of biology and medicine. Bioinformatics’ subject is the development and application of mathematical methods, computer programs and databases for storage and retrieval of information, generation of new knowledge on the basis of vast amounts of experimental data, which are obtained by highthroughput biomedical studies. Solution of the following problems requires the application of Bioinformatics’ methods: 1. Comparative genomics and proteomics. Analysis of nucleotide and amino acid sequences of deciphered genomes. Study of molecular evolution of the organisms. 2. Functional genomics and proteomics. Determination of gene structure and regulatory signals, antigenic determinants, active sites and other functionally-essential regions in nucleic acids and proteins. Study of gene expression regulatory systems. Analysis of structure and function of non-coding regions in nucleic acids. 3. Structural genomics and proteomics. Modeling of 3D structure of proteins and nucleic acids. Determination of posttranscriptional and posttranslational modifications. 4. Analysis of proteomes of various biological samples for determination of similarity and diversity. Identification of protein-protein interactions. 5. Systems biology. Analysis of biological processes at supramolecular level using genomic, transcriptomic, proteomic and metabolomic information. Modeling of metabolic and signal regulatory pathways in a cell. 6. Analysis of SNPs and SAPs, abundance of repeats and other changes at the molecular level, in view of disease-disposing, features of their developing, and individuality of pharmacotherapeutic responses. 7. Revelation of potential markers for detection of diseases. 8. Identification of prospective molecular targets for new drugs. 9. Analysis of interaction of natural and synthetic bioregulators with molecular targets, design and optimization of lead compounds with the required properties as new pharmaceutical agents. 10. Design of immunogenic constructions for creation of new vaccines. 11. Bioengineering (design) of microorganisms and plants as producents of physiologically active substances with required properties. 12. Textomics as a method for determination of associations between the scientific results obtained in different fields of biomedical science. 13. Revelation of signals in noisy postgenomics data (mass-spectrometry, atomic force microscopy, microarrays, etc.). 14. Integration and development of means for the analysis of heterogeneous types of data in large-scale databases on biomedical information. Since the mission of Bioinformatics is “Filling Gaps in the Existing Knowledge”, it could be considered as a “Critical Technology” for Life Sciences. 1. http://www.ncbi.nlm.nih.gov/Education/BLASTinfo/glossary2.html 2. http://www.pasteur.fr/recherche/unites/Binfs/definition/bioinformatics_definition.html
Abstr. Fourth Moscow Conference on Computational Molecular Biology (MCCMB'09), Moscow, Russia, Jule 20-23, 2009, p. 296–297.