hmmemit (genouest)

hmmemit (genouest) performs protein sequence similarity searches using profile hidden Markov models (profile HMMs) to detect homologous proteins and identify protein families and domains such as those in the Pfam database.

Key Features:

• Probabilistic profile HMMs: Uses profile hidden Markov models to model protein families and detect sequence similarity.
• HMMER3 performance: Implements HMMER3 algorithms reported to provide up to a 100-fold increase in speed over previous versions for rapid searching.
• Query types: Accepts single protein sequences, multiple sequence alignments, or profile HMMs as queries against target sequence databases.
• Pfam integration: Supports searches of protein sequences against the Pfam database for family and domain identification.
• Batch processing: Supports simultaneous processing of multiple queries for high-throughput analyses.
• Programmatic access: Exposes search methods as RESTful web services for integration into scripted workflows.

Scientific Applications:

• Homology detection: Identify homologous proteins in sequence databases using profile HMM-based similarity.
• Protein family and domain identification: Assign sequences to protein families and domains by matching to Pfam and other profile models.
• Evolutionary inference: Support analyses of evolutionary relationships among proteins via profile HMM comparisons.
• Genome annotation: Annotate newly sequenced genomes with putative protein functions by detecting matches to profile HMMs.

Methodology:

Applies probabilistic methods using profile hidden Markov models and HMMER3 algorithms to search queries (single sequences, multiple sequence alignments, or profile HMMs) against sequence databases including Pfam.