Bioinformatics and Life Sciences

Sequencing and protein docking are very compute-intensive tasks that see a large performance benefit by using a CUDA-enabled GPU. There is quite a bit of ongoing work on using GPUs for a range of Bioinformatics and life sciences codes.

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Accelerating HMMER using GPUs Scalable Informatics	MUMmerGPU: High-through DNA sequence alignment using GPUs Schatz, et al

Learn more about Bioinformatics codes by downloading the Life Science Apps Catalog

Other Relevant Software using CUDA

• MUMmerGPU: High-throughput DNA sequence alignment using CUDA
• Smith-Waterman Code on GPUs
• Online CUDA Smith-Waterman
• ClustalW on CUDA: Multiple Sequence Alignment using CUDA
• Folding @ home using CUDA-enabled GPUs
• LISSOM: model of human neocortex using CUDA
• CUDA-based AutoDock from Silicon Informatics

• Sequence alignment
• CUSHAW: a CUDA compatible short read aligner to large genomes
• MUMmerGPU: High-through DNA sequence alignment using GPUs
• CUDASW++: Smith-Waterman Sequence Database Searches
• Smith-Waterman sequence alignment using CUDA
• Papers on Bioinformatics using CUDA
• Infernal-GPU: CUDA-accelerated RNA Alignment , Infernal (INFERence of RNA Alignment)
• SWAMP Sequence alignment
• CMatch: Fast protein and gene sequence string matching

• Docking
• 3D Protein Docking
• Accelerating PIPER using CUDA
• Protein Docking work at University of Wisconsin and video interview of David Dynerman
• Jack Collins from National Cancer Institute talks about GPU computing
• High-performance computational pipeline for metagenomic data analysis
• MrBayes on GPU
• Stochastic simulation algorithm (SSA) for biological systems
• Self-organizing computation models of human visual cortex
• DNA Microarray tool for assaying gene expression by computing pairwise Euclidean distance on GPUs

GPU Technology Conference 2012:

• Acceleration of Complex Network Analysis – Newcastle University
• GHOSTM: A GPU-Accelerated Homology Search Tool for Metgenomics – Tokyo Institute of Technology
• Algorithms and Tools for Bioinformatics on GPUs – Nanyang Technological University
• SeqNFind: Application of CUDA GPU Technologies to Sequence Alignment Techniques – Accelerated Technology Labs
• Swift: A GPU-based Smith-Waterman Sequence Alignment Program – St. Jude Children’s Research Hospital
• CUMACH – A Fast GPU-based Genotype Imputation Tool – NVIDIA
• SOAP3: GPU-based Compressed Indexing and Ultra-fast Parallel Alignment of Short Reads – BGI
• Accurate Sequence Alignment Using Distributed Filtering on GPU Clusters – University of Illinois at Urbana-Champaign and UC Berkeley
• Towards Computing the Cure for Cancer – Virginia Tech
• High-Throughput Epistasis Screening Using GPUs – Insilicos LLC
• GPGPU Accelerated Protein Similarity Measures Identifying Biological Relevant Structure – Vanderbilt University
• Dynamic Programming on CUDA: Finding the Most Similar DNA Sequence – IBM Poland
• The Advantage of GPU Computation for Analyzing Complex Traits – Zhejiang University
• GPU Accelerated Bioinformatics Research at BGI - BGI

More presentations are available on GTC On-Demand.

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• Molecular Dynamics
• Computational Chemistry
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