BIOSPECTRUM-2013

The International Symposium Computational Biology & Drug Design aims to promote the interaction among the scientific community, researchers, students and other stakeholders and to discuss the issues with an inquisitive approach, exploring the disciplines of Bioinformatics, Genomics and Systems Biology. The event will provide a premier forum for interdisciplinary research encompassing disciplines of computer science, mathematics, statistics, biology, bioinformatics, and biomedicine. The conference seeks original and high quality papers in the fields of bioinformatics, computational biology, systems biology, medical informatics and other related disciplines for oral or poster presentations. Technical sessions are arranged in the following specific areas.

• Gene Networks & Systems Biology
• Structural Biology
• Gene Expression Analysis
• Biological Databases & Management
• Computational Genomics  & Proteomics
• Genomics and Evolution
• Molecular Modeling and Simulation
• Computational Drug Design
• Data Mining and Visualization
• Software Tools and Applications
• Pharmacogenomics

About the symposium:

Biology is rapidly turning into an information science. The success of Bioinformatics in recent years has been prompted by research in Molecular Biology and allied disciplines in several initiatives. These initiatives gave rise to an exponential increase in the volume and diversification of data, including nucleotide and protein sequences and annotations, high-throughput experimental data, biomedical literature, and many others. This wealth of data allows us to model molecular systems at an unprecedented level of detail and to start to understand the underlying biological mechanisms. Systems Biology is a related research area that has been replacing the reductionist view that dominated biological research in the last decades, requiring the coordinated efforts of biological researchers with those related to data analysis, mathematical modeling, computer simulation and optimization. In fact, these methods have been helping in tasks related to knowledge discovery, modeling and optimization of biological information, aiming at the development of computational models so that the response of biological complex systems to any extent can be predicted. In this context, many widely successful approaches used by biologists for clustering and classification methods for gene expression data needs a reassessment. The accumulation and exploitation of large-scale databases prompts for new computational approaches and for multidisciplinary research into these issues.

Computer-aided drug design is a major component in the study and solution of problems in biotechnology which could enable scientists to rapidly and efficiently propose chemical structures that may achieve significant biological effects, thereby saving many years and millions of dollars in drug development.  Methodologies have been developed, however, that are showing great promise in the quest for intelligent or rational approaches to drug design.  Consequently, the area of computer-aided drug design has experienced a tremendous growth over the last few years as modern methods of theoretical calculations have improved notably and have been successfully combined with sophisticated graphics techniques and fast computer hardware.  The field is also starting to see dramatic results as artificial intelligence techniques have moved from theoretical research laboratories into practical problem-solving in the real world, especially in the field of biomedicine.