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Hmmer
Jul 20, 2023
Profile hidden Markov models for biological sequence analysis
HMMER is an implementation of profile hidden Markov model methods for sensitive searches of biological sequence databases using multiple sequence alignments as queries.
Given a multiple sequence alignment as input, HMMER builds a statistical model called a “hidden Markov model” which can then be used as a query into a sequence database to find and/or align additional homologues of the sequence family.
Checkout these related ports:
- Wise - Intelligent algorithms for DNA searches
- Wfa2-lib - Exact gap-affine algorithm using homology to accelerate alignment
- Vt - Discovers short variants from Next Generation Sequencing data
- Vsearch - Versatile open-source tool for metagenomics
- Viennarna - Alignment tools for the structural analysis of RNA
- Velvet - Sequence assembler for very short reads
- Vcftools - Tools for working with VCF genomics files
- Vcflib - C++ library and CLI tools for parsing and manipulating VCF files
- Vcf2hap - Generate .hap file from VCF for haplohseq
- Vcf-split - Split a multi-sample VCF into single-sample VCFs
- Unikmer - Toolkit for nucleic acid k-mer analysis, set operations on k-mers
- Unanimity - Pacific Biosciences consensus library and applications
- Ugene - Integrated bioinformatics toolkit
- Ucsc-userapps - Command line tools from the UCSC Genome Browser project
- Trimmomatic - Flexible read trimming tool for Illumina NGS data