New computational techniques and methods involving machine learning, data mining, pattern recognition, knowledge representation, databases, data modeling, stochastic modeling, string and graph algorithms, constraint optimization, data analysis, data visualization, parallel computation, data integration, modeling and simulation and their application in biological science domains.
Relevant topics should include but are not limited to following series of theme
Track-1: Genomics (Structure, Function and Evolution)
Genomic evolution
Phylogeny
Comparative Genomics
Functional Genomics
Gene Regulation
Alternative Splicing
Genetic Network Analysis
DNA & RNA Sequence Analysis
Gene Expression Analysis
Track-2: Proteomics (Structure, Function and Dynamics)
Protein Structure modeling
Protein Network
Protein Structural Dynamics study
Annotation of Hypothetical protein
Functional and Structural Annotation
Docking
Molecular Dynamics
Active Site Prediction
Protein Folding
Protein Sequence Analysis
Track-3: Computational Systems Biology
Transcriptomics
Microarray Data Analysis
Network/Pathway Analysis
Protein-Protein Interaction
Metabolomics, Epigenomics
ncRNA Prediction and Analysis
DNA Methylation Analysis
Pathway Simulation and Modeling
Track- 4: Biological Data Mining and Analytics
Biological Data Mining
Ontology
Machine Leaning and Prediction
Biological Data Visualization
Computational Modeling and Data Integration of Bio-system
High Performance Computing
Big Data Analytics
Pipelines and Tools
io-inspired Computing
03月04日
2016
03月06日
2016
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