The Fifth International Conference on Bioinformatics of Genome Regulation and Structure (BGRS’2006) (BGRS’2006)
|Event Date/Time: Jul 16, 2006||End Date/Time: Jul 22, 2006|
|Registration Date: May 15, 2006|
|Early Registration Date: May 15, 2006|
|Abstract Submission Date: Mar 30, 2006|
We are pleased to invite scientists with an interest in bioinformatics, mathematical, theoretical, or computational biology to attend the meeting.
Its scope includes development and application of advanced methods of computational and theoretical analysis to structure–function genome organization, proteomics, and evolutionary and system biology. The event addresses the latest research in these fields, and will be a great opportunity for attendees to showcase their works.
BGRS’2006 provides a general forum for disseminating and facilitating the latest developments in bioinformatics in molecular biology, and we also invite scientists participating in experimental research and using theoretical and/or computational methods in their practice to come. We will be delighted to see industry representatives from biotechnology and pharmaceutical companies as BGRS’2006 conferees, too.
· COMPUTATIONAL STRUCTURAL AND FUNCTIONAL GENOMICS:
Large-scale genome analysis and comparison; genome functional annotation, gene finding and prediction; genome knowledge bases and ontologies; mobile genetic elements and repeated DNA sequences; DNA nucleosomal organization. Regulatory genomic sequences: databases and knowledge bases, computer analysis, modeling and simulation, comparative genomics of regulatory regions; gene expression (models of transcription, splicing, and translation control); gene structure prediction (transcription and translation start sites, splicing and polyadenylation signals); and prediction of protein-coding potential of eukaryotic genes and genomes.
· COMPUTATIONAL STRUCTURAL AND FUNCTIONAL PROTEOMICS:
RNA structure–function organization (analysis and prediction); antisense transcription and RNA-RNA interactions; protein structure and function analysis, modeling, and prediction; classification of folds and structural motifs in proteins; analysis of protein 3D structure; functional sites and active centers in 3D protein structure (recognition and modeling of function); large-scale analysis of proteomes and protein–protein interactions.
· COMPUTATIONAL SYSTEMS BIOLOGY:
Gene networks, regulatory networks, signal transduction pathways, metabolic pathways, gene expression pathways (databases and knowledge bases, computer analysis, modeling, and simulation); mathematical algorithms for control of the gene network and metabolic pathway functions; solution of inverse problems for gene networks and metabolic pathways; computer algorithms for metabolic engineering; in silico reconstruction of gene networks by computational analysis of microarray data; description and modeling of intracellular dynamics; intercellular communication modeling; virtual cell; networks and development; systems biology and biotechnology, epigenetics; computer models of genetic control of complex phenotypic traits based on analysis of complex genetic traits; modeling of morphogenesis.
· COMPUTATIONAL EVOLUTIONARY BIOLOGY:
Genetic variation (SNPs, haplotypes, etc.); large scale genome rearrangements; genome polymorphism; molecular evolution (genes, genomes, regulatory systems, and metabolic pathways); reconstruction of molecular-level evolutionary events, construction of evolutionary scripts (models, algorithms, and analysis of biological examples); evolution of genetic macromolecules and gene networks; comparative genomics: gene regulatory regions and gene coding regions; evolution of protein structure and function; phylogenetic trees reconstruction; horizontal transmission of genetic information; theoretical and computer approaches to analysis and evolution of complex systems (gene networks, metabolic pathways, signal transduction pathways, etc.).
· METHODS FOR ANALYSIS AND SIMULATION OF BIOMOLECULAR SYSTEMS AND PROCESSES:
Computer technologies knowledge production, accumulation warehousing, and analysis in genomics, transcriptomics, proteomics, and systems biology; natural language processing for biological texts; neuroinformatics; interactive links between bioinformatics and experimental research on functional and structural genomics, transcriptomics, and metabolomics (gene expression array analysis and other new technologies and methods); data warehousing, knowledge discovery, data mining, and machine learning in genomics and proteomics; superlarge computer systems in molecular biology and molecular genetics, high performance computing in functional and structural genomics and proteomics; data management methods and systems; integration of databases and data processing; data visualization; string and graph algorithms; stochastic modeling; modern methods for algorithmic and software-based solution of bioinformatics problems; methods for verification of mathematical models; analysis and simulation of biological processes at different time scales and different levels of organization; reading, analysis and visualization of genomic, proteomic, and microarray data; computational applications in biotechnology; methods and approaches in programming of bioinformatics algorithms and models involving parallel computational systems and grid technologies; analogs of bioinformatics models and their relations with pattern recognition methods, content–text models in linguistics, and modeling of color vision.
· BIOINFORMATICS AND EDUCATION