Welcome to the Bioinformatics and Computational Biology Community!

Bioinformatics and Computational Biology have emerged as primary application areas for the use of GPU computing. This is mainly caused by the large amount of publicly available sequence, expression, and structure data. The amount of availabe data will grow even further in the near future due to advances in high-throughput technologies - leading to a data explosion. Since GPU performance grows faster than CPU performance, the use of GPUs for Bioinformatics is therefore a perfect match. Several examples of already availabe GPU-enabled Bioinformatics tools can be accessed through the Tesla Bio Workbench, such as  CUDA-BLASTP, CUDA-EC, CUDA-MEME, CUDA-SW++, GPUHMMer, and GPUMUMmer. Four of these tools have been developed by my research group at Nanyang Tech. 

This community discusses all aspects of using GPUs for Bioinformatics and Computational Biolgy algorithms and tools. Particular examples of research areas of interest include:

• Sequence Analysis and Alignment
• Database Searching and Indexing
• Next-generation Sequencing and its Applications
• Phylogeny Reconstruction
• Computational Genomcis and Proteomics
• Gene experssion, Microarrays and Gene Reglatory Networks
• Protein Structure Prediction
• Production-level GPU Parallelization of widely used algorithms and tools.

As community interests manifest themselves, new forum topics can be created to focus participation. The intention is to make our community a focal point for quality discussions on problems and solutions that can be used as a searchable knowledge base to benefit everyone interested in the use of GPUs for Bioinformatics and Computational Biology. 

Bertil Schmidt, Nanyang Technological University