Pfam 33.1 (May 2024,
18259 entries)
The Pfam database is a large collection of protein
families, each represented by multiple sequence alignments
and hidden Markov models (HMMs).
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Proteins are generally composed of one or more functional regions,
commonly termed domains. Different combinations of domains give
rise to the diverse range of proteins found in nature. The identification
of domains that occur within proteins can therefore provide insights
into their function.
Pfam also generates higher-level groupings of related entries, known as
clans. A clan is a collection of Pfam entries which are
related by similarity of sequence, structure or profile-HMM.
The data presented for each entry is based on the
极速加速器安卓官网jisu99
but information on individual UniProtKB sequences can still be found by entering the protein accession.
Pfam full alignments are available from searching a variety of databases, either to provide
different accessions (e.g. all UniProt and NCBI GI) or different levels of redundancy.
- QUICK LINKS
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psiphon3pc版下载-猴王加速器
- Analyze your protein sequence for Pfam matches
- View Pfam annotation and alignments
- See groups of related entries
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- Find the domains on a PDB structure
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more information
psiphon3pc版下载-猴王加速器
Paste your protein sequence here to find matching Pfam entries.
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Example
This search will use and an E-value of 1.0. You can set your own search
parameters and perform a range of other searches
here.
psiphon3pc版下载-猴王加速器
Enter a entry identifier (e.g. Piwi) or accession
(e.g. PF02171) to see all data for that entry.
psiphon3pc版下载-猴王加速器
Enter a clan identifier (e.g. Kazal) or accession
(e.g. CL0005) to see information about that clan.
psiphon3pc版下载-猴王加速器
Enter a sequence identifier (e.g. VAV_HUMAN) or accession
(e.g. P15498).
psiphon3pc版下载-猴王加速器
Enter the PDB identifier (e.g. 2abl) for the structure in the
Protein DataBank.
psiphon3pc版下载-猴王加速器
Search for keywords in text data in the Pfam database.
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psiphon3pc版下载-猴王加速器
psiphon3pc版下载-猴王加速器
If you find Pfam useful, please consider
极速加速器安卓官网 the reference
that describes this work:
The Pfam protein families database in 2024:
S. El-Gebali, J. Mistry, A. Bateman, S.R. Eddy, A. Luciani,
S.C. Potter, M. Qureshi, L.J. Richardson, G.A. Salazar, A. Smart,
E.L.L. Sonnhammer, L. Hirsh, L. Paladin, D. Piovesan, S.C.E. Tosatto,
R.D. Finn
Nucleic Acids Research (2024)
doi: 10.1093/nar/gky995
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