ArticleBMC bioinformatics2024
An FPGA-based hardware accelerator supporting sensitive sequence homology filtering with profile hidden Markov models.
Article in BMC bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- GPU-accelerated homology search with MMseqs2.Nature methods · 2025Article
- NEAR: neural embeddings for amino acid relationships.Bioinformatics (Oxford, England) · 2025Article
- NEAR: Neural Embeddings for Amino acid Relationships.bioRxiv : the preprint server for biology · 2025Article
- nail: software for high-speed, high-sensitivity protein sequence annotation.bioRxiv : the preprint server for biology · 2024Article
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2 authors.
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Abstract
backgroundSequence alignment lies at the heart of genome sequence annotation. While the BLAST suite of alignment tools has long held an important role in alignment-based sequence database search, greater sensitivity is achieved through the use of profile hidden Markov models (pHMMs). Here, we describe an FPGA hardware accelerator, called HAVAC, that targets a key bottleneck step (SSV) in the analysis pipeline of the popular pHMM alignment tool, HMMER.
resultsThe HAVAC kernel calculates the SSV matrix at 1739 GCUPS on a
conclusionsHAVAC demonstrates the potential offered by FPGA hardware accelerators to produce dramatic speed gains in sequence annotation and related bioinformatics applications. Because these computations are performed on a co-processor, the host CPU remains free to simultaneously compute other aspects of the analysis pipeline.
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