Tag: Hidden Markov Models (HMM)

Now Available! NCBI Hidden Markov Models (HMM) Release 17.0

Now Available! NCBI Hidden Markov Models (HMM) Release 17.0

Download release 17.0 of the NCBI protein profile Hidden Markov models (HMMs) used by the Prokaryotic Genome Annotation Pipeline (PGAP). Search this collection against your favorite prokaryotic proteins to identify their function using the HMMER sequence analysis package.

What’s New?

Release 17.0 contains:

  • 17,433 HMMs maintained by NCBI
  • 386 new HMMs since release 16.0

Continue reading “Now Available! NCBI Hidden Markov Models (HMM) Release 17.0”

NCBI Hidden Markov Models (HMM) Release 16.0 Now Available!

NCBI Hidden Markov Models (HMM) Release 16.0 Now Available!

Download release 16.0 of the NCBI protein profile Hidden Markov models (HMMs) used by the Prokaryotic Genome Annotation Pipeline (PGAP)! Search this collection against your favorite prokaryotic proteins to identify their function using the HMMER sequence analysis package.

What’s New?

Release 16.0 contains:

  • 17,078 HMMs maintained by NCBI
  • 406 new HMMs since release 15.0
  • The GO terms between NCBI HMMs and the corresponding Interpro entries were compared and evaluated over a substantial number of HMMs and updated (added: 307; deleted: 39; updated: 1,482). 

Continue reading “NCBI Hidden Markov Models (HMM) Release 16.0 Now Available!”

NCBI Hidden Markov Models (HMM) Release 15.0 Now Available!

NCBI Hidden Markov Models (HMM) Release 15.0 Now Available!

Download release 15.0 of the NCBI protein profile Hidden Markov models (HMMs) used by the Prokaryotic Genome Annotation Pipeline (PGAP)! Search this collection against your favorite prokaryotic proteins to identify their function using the HMMER sequence analysis package.

What’s New?

Release 15.0 contains:

  • 16,667 HMMs maintained by NCBI
  • 279 new HMMs since release 14.0
  • Several hundreds HMMs with better names, EC numbers, Gene Ontology (GO) terms, gene symbols, or publications. 

Continue reading “NCBI Hidden Markov Models (HMM) Release 15.0 Now Available!”

Now Available: NCBI Hidden Markov Models (HMM) Release 14.0!

Now Available: NCBI Hidden Markov Models (HMM) Release 14.0!

Download release 14.0 of the NCBI protein profile Hidden Markov models (HMMs) used by the Prokaryotic Genome Annotation Pipeline (PGAP)! Search this collection against your favorite prokaryotic proteins to identify their function using the HMMER sequence analysis package. Continue reading “Now Available: NCBI Hidden Markov Models (HMM) Release 14.0!”

NCBI Hidden Markov Models (HMM) Release 13.0 Now Available!

NCBI Hidden Markov Models (HMM) Release 13.0 Now Available!

Release 13.0 of the NCBI protein profile Hidden Markov models (HMMs) used by the Prokaryotic Genome Annotation Pipeline (PGAP) is now available for download. You can search this collection against your favorite prokaryotic proteins to identify their function using the HMMER sequence analysis package.

What’s new?

The 13.0 release contains:

  • 16,143 HMMs maintained by NCBI
  • 315 new HMMs since release 12.0
  • 286 HMMs with better names, EC numbers, Gene Ontology (GO) terms, gene symbols or publications

Continue reading “NCBI Hidden Markov Models (HMM) Release 13.0 Now Available!”

New! May 2023 Release of Stand-Alone PGAP

New! May 2023 Release of Stand-Alone PGAP

We are happy to announce the release of a new version of the stand-alone Prokaryotic Genome Annotation Pipeline (PGAP) with many exciting new features.

Improved user interface

This version has an improved user interface that takes the genome FASTA file and associated organism name directly on the command line. For example, to annotate a Vibrio cholerae genome sequence in the file Vchol.fasta:

pgap.py -r -g Vchol.fasta -s 'Vibrio cholerae' -o Vchol.annot

For more details visit our Quick Start page. Continue reading “New! May 2023 Release of Stand-Alone PGAP”

NCBI Hidden Markov Models (HMM) Release 12.0 Now Available!

NCBI Hidden Markov Models (HMM) Release 12.0 Now Available!

Release 12.0 of the NCBI protein profile Hidden Markov models (HMMs) used by the Prokaryotic Genome Annotation Pipeline (PGAP) is now available for download. You can search this collection against your favorite prokaryotic proteins to identify their function using the HMMER sequence analysis package.

What’s new?

The 12.0 release contains:

  • 15,849 HMMs maintained by NCBI
  • 271 new HMMs since release 11.0
  • 1,248 HMMs with better names, EC numbers, Gene Ontology (GO) terms, gene symbols or publications

Continue reading “NCBI Hidden Markov Models (HMM) Release 12.0 Now Available!”

NCBI hidden Markov models (HMM) release 11.0 now available!

NCBI hidden Markov models (HMM) release 11.0 now available!

Release 11.0 of the NCBI protein profile Hidden Markov models (HMMs) used by the Prokaryotic Genome Annotation Pipeline (PGAP) is now available for download. You can search this collection against your favorite prokaryotic proteins to identify their function using the HMMER sequence analysis package. Continue reading “NCBI hidden Markov models (HMM) release 11.0 now available!”

NCBI hidden Markov models (HMM) release 10.0 now available!

NCBI hidden Markov models (HMM) release 10.0 now available!

Release 10.0 of the NCBI Hidden Markov models (HMM) used by the Prokaryotic Genome Annotation Pipeline (PGAP) is now available for download. You can search this collection against your favorite prokaryotic proteins to identify their function using the HMMER sequence analysis package.

The 10.0 release contains 15,360 models maintained by NCBI, including 228 that are new since 9.0, 99 that were modified significantly, and 205 that were assigned better names, EC numbers, Gene Ontology (GO) terms, gene symbols or publications. You can search and view the details for these in the Protein Family Model collection, which also includes conserved domain architectures and BlastRules, and find all RefSeq proteins they name.

GO terms associated with HMMs are now propagated to CDSs and proteins annotated with PGAP. In case you missed it, see our previous blog post on this topic.