@article {46742, title = {HMMER web server: 2015 update.}, journal = {Nucleic Acids Research}, year = {2015}, month = {2015 May 5}, abstract = {

The HMMER website, available at http://www.ebi.ac.uk/Tools/hmmer/, provides access to the protein homology search algorithms found in the HMMER software suite. Since the first release of the website in 2011, the search repertoire has been expanded to include the iterative search algorithm, jackhmmer. The continued growth of the target sequence databases means that traditional tabular representations of significant sequence hits can be overwhelming to the user. Consequently, additional ways of presenting homology search results have been developed, allowing them to be summarised according to taxonomic distribution or domain architecture. The taxonomy and domain architecture representations can be used in combination to filter the results according to the needs of a user. Searches can also be restricted prior to submission using a new taxonomic filter, which not only ensures that the results are specific to the requested taxonomic group, but also improves search performance. The repertoire of profile hidden Markov model libraries, which are used for annotation of query sequences with protein families and domains, has been expanded to include the libraries from CATH-Gene3D, PIRSF, Superfamily and TIGRFAMs. Finally, we discuss the relocation of the HMMER webserver to the European Bioinformatics Institute and the potential impact that this will have.

}, issn = {1362-4962}, doi = {10.1093/nar/gkv397}, author = {Finn, Robert D and Clements, Jody and Arndt, William and Miller, Benjamin L and Wheeler, Travis J and Schreiber, Fabian and Bateman, Alex and Eddy, Sean R} } @article {46185, title = {Rfam 12.0: updates to the RNA families database.}, journal = {Nucleic Acids Research}, volume = {43}, year = {2015}, month = {2015 Jan 28}, pages = {D130-7}, abstract = {

The Rfam database (available at http://rfam.xfam.org) is a collection of non-coding RNA families represented by manually curated sequence alignments, consensus secondary structures and annotation gathered from corresponding Wikipedia, taxonomy and ontology resources. In this article, we detail updates and improvements to the Rfam data and website for the Rfam 12.0 release. We describe the upgrade of our search pipeline to use Infernal 1.1 and demonstrate its improved homology detection ability by comparison with the previous version. The new pipeline is easier for users to apply to their own data sets, and we illustrate its ability to annotate RNAs in genomic and metagenomic data sets of various sizes. Rfam has been expanded to include 260 new families, including the well-studied large subunit ribosomal RNA family, and for the first time includes information on short sequence- and structure-based RNA motifs present within families.

}, issn = {1362-4962}, doi = {10.1093/nar/gku1063}, author = {Nawrocki, Eric P and Burge, Sarah W and Bateman, Alex and Daub, Jennifer and Eberhardt, Ruth Y and Eddy, Sean R and Floden, Evan W and Gardner, Paul P and Jones, Thomas A and Tate, John and Finn, Robert D} } @article {6887, title = {iPfam: a database of protein family and domain interactions found in the Protein Data Bank.}, journal = {Nucleic acids research}, volume = {42}, year = {2014}, month = {2014 Jan}, pages = {D364-73}, abstract = {The database iPfam, available at http://ipfam.org, catalogues Pfam domain interactions based on known 3D structures that are found in the Protein Data Bank, providing interaction data at the molecular level. Previously, the iPfam domain-domain interaction data was integrated within the Pfam database and website, but it has now been migrated to a separate database. This allows for independent development, improving data access and giving clearer separation between the protein family and interactions datasets. In addition to domain-domain interactions, iPfam has been expanded to include interaction data for domain bound small molecule ligands. Functional annotations are provided from source databases, supplemented by the incorporation of Wikipedia articles where available. iPfam (version 1.0) contains >9500 domain-domain and 15 500 domain-ligand interactions. The new website provides access to this data in a variety of ways, including interactive visualizations of the interaction data.}, keywords = {Databases, Internet, Ligands, Protein, Protein Interaction Domains and Motifs, Protein Interaction Mapping, Protein Interaction Maps, Proteins, Software}, issn = {1362-4962}, doi = {10.1093/nar/gkt1210}, author = {Finn, Robert D and Miller, Benjamin L and Clements, Jody and Bateman, Alex} } @article {6886, title = {Pfam: the protein families database.}, journal = {Nucleic acids research}, volume = {42}, year = {2014}, month = {2014 Jan}, pages = {D222-30}, abstract = {Pfam, available via servers in the UK (http://pfam.sanger.ac.uk/) and the USA (http://pfam.janelia.org/), is a widely used database of protein families, containing 14 831 manually curated entries in the current release, version 27.0. Since the last update article 2 years ago, we have generated 1182 new families and maintained sequence coverage of the UniProt Knowledgebase (UniProtKB) at nearly 80\%, despite a 50\% increase in the size of the underlying sequence database. Since our 2012 article describing Pfam, we have also undertaken a comprehensive review of the features that are provided by Pfam over and above the basic family data. For each feature, we determined the relevance, computational burden, usage statistics and the functionality of the feature in a website context. As a consequence of this review, we have removed some features, enhanced others and developed new ones to meet the changing demands of computational biology. Here, we describe the changes to Pfam content. Notably, we now provide family alignments based on four different representative proteome sequence data sets and a new interactive DNA search interface. We also discuss the mapping between Pfam and known 3D structures.}, keywords = {Databases, DNA, Internet, Intrinsically Disordered Proteins, Protein, Protein Conformation, Proteins, Proteome, Sequence Alignment, Sequence Analysis}, issn = {1362-4962}, doi = {10.1093/nar/gkt1223}, author = {Finn, Robert D and Bateman, Alex and Clements, Jody and Coggill, Penelope and Eberhardt, Ruth Y and Sean R. Eddy and Heger, Andreas and Hetherington, Kirstie and Holm, Liisa and Mistry, Jaina and Sonnhammer, Erik L L and Tate, John and Punta, Marco} } @article {45865, title = {Structure and computational analysis of a novel protein with metallopeptidase-like and circularly permuted winged-helix-turn-helix domains reveals a possible role in modified polysaccharide biosynthesis.}, journal = {BMC Bioinformatics}, volume = {15}, year = {2014}, month = {2014 Mar 19}, pages = {75}, abstract = {

BACKGROUND: CA_C2195 from Clostridium acetobutylicum is a protein of unknown function. Sequence analysis predicted that part of the protein contained a metallopeptidase-related domain. There are over 200 homologs of similar size in large sequence databases such as UniProt, with pairwise sequence identities in the range of ~40-60\%. CA_C2195 was chosen for crystal structure determination for structure-based function annotation of novel protein sequence space.

RESULTS: The structure confirmed that CA_C2195 contained an N-terminal metallopeptidase-like domain. The structure revealed two extra domains: an α+β domain inserted in the metallopeptidase-like domain and a C-terminal circularly permuted winged-helix-turn-helix domain.

CONCLUSIONS: Based on our sequence and structural analyses using the crystal structure of CA_C2195 we provide a view into the possible functions of the protein. From contextual information from gene-neighborhood analysis, we propose that rather than being a peptidase, CA_C2195 and its homologs might play a role in biosynthesis of a modified cell-surface carbohydrate in conjunction with several sugar-modification enzymes. These results provide the groundwork for the experimental verification of the function.

}, keywords = {Bacterial Proteins, Clostridium acetobutylicum, Crystallography, X-Ray, Metalloproteases, Models, Molecular, Protein Structure, Tertiary}, issn = {1471-2105}, doi = {10.1186/1471-2105-15-75}, author = {Das, Debanu and Murzin, Alexey G and Rawlings, Neil D and Finn, Robert D and Coggill, Penelope and Bateman, Alex and Godzik, Adam and Aravind, L} } @article {6272, title = {Challenges in homology search: HMMER3 and convergent evolution of coiled-coil regions.}, journal = {Nucleic Acids Research}, volume = {41}, year = {2013}, month = {2013 Jul}, pages = {e121}, abstract = {

Detection of protein homology via sequence similarity has important applications in biology, from protein structure and function prediction to reconstruction of phylogenies. Although current methods for aligning protein sequences are powerful, challenges remain, including problems with homologous overextension of alignments and with regions under convergent evolution. Here, we test the ability of the profile hidden Markov model method HMMER3 to correctly assign homologous sequences to \>13,000 manually curated families from the Pfam database. We identify problem families using protein regions that match two or more Pfam families not currently annotated as related in Pfam. We find that HMMER3 E-value estimates seem to be less accurate for families that feature periodic patterns of compositional bias, such as the ones typically observed in coiled-coils. These results support the continued use of manually curated inclusion thresholds in the Pfam database, especially on the subset of families that have been identified as problematic in experiments such as these. They also highlight the need for developing new methods that can correct for this particular type of compositional bias.

}, issn = {1362-4962}, doi = {10.1093/nar/gkt263}, author = {Mistry, Jaina and Finn, Robert D and Eddy, Sean R. and Bateman, Alex and Punta, Marco} } @article {6298, title = {Rfam 11.0: 10 years of RNA families.}, journal = {Nucleic Acids Research}, volume = {41}, year = {2013}, month = {2013 Jan}, pages = {D226-32}, abstract = {

The Rfam database (available via the website at http://rfam.sanger.ac.uk and through our mirror at http://rfam.janelia.org) is a collection of non-coding RNA families, primarily RNAs with a conserved RNA secondary structure, including both RNA genes and mRNA cis-regulatory elements. Each family is represented by a multiple sequence alignment, predicted secondary structure and covariance model. Here we discuss updates to the database in the latest release, Rfam 11.0, including the introduction of genome-based alignments for large families, the introduction of the Rfam Biomart as well as other user interface improvements. Rfam is available under the Creative Commons Zero license.

}, keywords = {Base Sequence, Databases, Genomics, Internet, Molecular Sequence Annotation, Nucleic Acid, Nucleic Acid Conformation, RNA, Sequence Alignment, Untranslated, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gks1005}, author = {Burge, Sarah W and Daub, Jennifer and Eberhardt, Ruth and Tate, John and Barquist, Lars and Nawrocki, Eric P and Eddy, Sean R. and Gardner, Paul P and Bateman, Alex} } @article {6537, title = {Two Pfam protein families characterized by a crystal structure of protein lpg2210 from Legionella pneumophila.}, journal = {BMC Bioinformatics}, volume = {14}, year = {2013}, month = {2013 Sep 3}, pages = {265}, abstract = {

BACKGROUND: Every genome contains a large number of uncharacterized proteins that may encode entirely novel biological systems. Many of these uncharacterized proteins fall into related sequence families. By applying sequence and structural analysis we hope to provide insight into novel biology. RESULTS: We analyze a previously uncharacterized Pfam protein family called DUF4424 [Pfam:PF14415]. The recently solved three-dimensional structure of the protein lpg2210 from Legionella pneumophila provides the first structural information pertaining to this family. This protein additionally includes the first representative structure of another Pfam family called the YARHG domain [Pfam:PF13308]. The Pfam family DUF4424 adopts a 19-stranded beta-sandwich fold that shows similarity to the N-terminal domain of leukotriene A-4 hydrolase. The YARHG domain forms an all-helical domain at the C-terminus. Structure analysis allows us to recognize distant similarities between the DUF4424 domain and individual domains of M1 aminopeptidases and tricorn proteases, which form massive proteasome-like capsids in both archaea and bacteria. CONCLUSIONS: Based on our analyses we hypothesize that the DUF4424 domain may have a role in forming large, multi-component enzyme complexes. We suggest that the YARGH domain may play a role in binding a moiety in proximity with peptidoglycan, such as a hydrophobic outer membrane lipid or lipopolysaccharide.

}, issn = {1471-2105}, doi = {10.1186/1471-2105-14-265}, author = {Coggill, Penelope and Eberhardt, Ruth Y and Finn, Robert D and Chang, Yuanyuan and Jaroszewski, Lukasz and Godzik, Adam and Das, Debanu and Xu, Qingping and Axelrod, Herbert L and Aravind, L and Murzin, Alexey G and Bateman, Alex} } @article {4974, title = {Bioimage informatics: a new category in Bioinformatics.}, journal = {Bioinformatics}, volume = {28}, year = {2012}, month = {2012 Apr 15}, pages = {1057}, issn = {1367-4811}, doi = {10.1093/bioinformatics/bts111}, author = {Peng, Hanchuan and Bateman, Alex and Valencia, Alfonso and Wren, Jonathan D} } @article {6503, title = {Making your database available through Wikipedia: the pros and cons.}, journal = {Nucleic Acids Research}, volume = {40}, year = {2012}, month = {2012 Jan}, pages = {D9-12}, abstract = {

Wikipedia, the online encyclopedia, is the most famous wiki in use today. It contains over 3.7 million pages of content; with many pages written on scientific subject matters that include peer-reviewed citations, yet are written in an accessible manner and generally reflect the consensus opinion of the community. In this, the 19th Annual Database Issue of Nucleic Acids Research, there are 11 articles that describe the use of a wiki in relation to a biological database. In this commentary, we discuss how biological databases can be integrated with Wikipedia, thereby utilising the pre-existing infrastructure, tools and above all, large community of authors (or Wikipedians). The limitations to the content that can be included in Wikipedia are highlighted, with examples drawn from articles found in this issue and other wiki-based resources, indicating why other wiki solutions are necessary. We discuss the merits of using open wikis, like Wikipedia, versus other models, with particular reference to potential vandalism. Finally, we raise the question about the future role of dedicated database biocurators in context of the thousands of crowdsourced, community annotations that are now being stored in wikis.

}, keywords = {Databases, Encyclopedias as Topic, Factual, Internet, Systems Integration}, issn = {1362-4962}, doi = {10.1093/nar/gkr1195}, author = {Finn, Robert D and Gardner, Paul P and Bateman, Alex} } @article {6296, title = {The Pfam protein families database.}, journal = {Nucleic acids research}, volume = {40}, year = {2012}, month = {2012 Jan}, pages = {D290-301}, abstract = {

Pfam is a widely used database of protein families, currently containing more than 13,000 manually curated protein families as of release 26.0. Pfam is available via servers in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/). Here, we report on changes that have occurred since our 2010 NAR paper (release 24.0). Over the last 2 years, we have generated 1840 new families and increased coverage of the UniProt Knowledgebase (UniProtKB) to nearly 80\%. Notably, we have taken the step of opening up the annotation of our families to the Wikipedia community, by linking Pfam families to relevant Wikipedia pages and encouraging the Pfam and Wikipedia communities to improve and expand those pages. We continue to improve the Pfam website and add new visualizations, such as the {\textquoteright}sunburst{\textquoteright} representation of taxonomic distribution of families. In this work we additionally address two topics that will be of particular interest to the Pfam community. First, we explain the definition and use of family-specific, manually curated gathering thresholds. Second, we discuss some of the features of domains of unknown function (also known as DUFs), which constitute a rapidly growing class of families within Pfam.

}, keywords = {Amino Acid, Databases, Encyclopedias as Topic, Internet, Protein, Protein Structure, Proteins, Sequence Homology, Tertiary}, issn = {1362-4962}, doi = {10.1093/nar/gkr1065}, author = {Punta, Marco and Coggill, Penny C and Eberhardt, Ruth Y and Mistry, Jaina and Tate, John and Boursnell, Chris and Pang, Ningze and Forslund, Kristoffer and Ceric, Goran and Clements, Jody and Heger, Andreas and Holm, Liisa and Sonnhammer, Erik L L and Sean R. Eddy and Bateman, Alex and Finn, Robert D} } @article {1927, title = {Rfam: Wikipedia, clans and the "decimal" release.}, journal = {Nucleic Acids Research}, volume = {39}, year = {2011}, month = {2011 Jan}, pages = {D141-5}, abstract = {

The Rfam database aims to catalogue non-coding RNAs through the use of sequence alignments and statistical profile models known as covariance models. In this contribution, we discuss the pros and cons of using the online encyclopedia, Wikipedia, as a source of community-derived annotation. We discuss the addition of groupings of related RNA families into clans and new developments to the website. Rfam is available on the Web at http://rfam.sanger.ac.uk.

}, issn = {1362-4962}, doi = {10.1093/nar/gkq1129}, author = {Gardner, Paul P and Daub, Jennifer and Tate, John and Moore, Benjamin L and Osuch, Isabelle H and Griffiths-Jones, Sam and Finn, Robert D and Nawrocki, Eric P and Kolbe, Diana L and Eddy, Sean R. and Bateman, Alex} } @article {4485, title = {RNIE: genome-wide prediction of bacterial intrinsic terminators.}, journal = {Nucleic Acids Research}, volume = {39}, year = {2011}, month = {2011 Aug}, pages = {5845-52}, abstract = {

Bacterial Rho-independent terminators (RITs) are important genomic landmarks involved in gene regulation and terminating gene expression. In this investigation we present RNIE, a probabilistic approach for predicting RITs. The method is based upon covariance models which have been known for many years to be the most accurate computational tools for predicting homology in structural non-coding RNAs. We show that RNIE has superior performance in model species from a spectrum of bacterial phyla. Further analysis of species where a low number of RITs were predicted revealed a highly conserved structural sequence motif enriched near the genic termini of the pathogenic Actinobacteria, Mycobacterium tuberculosis. This motif, together with classical RITs, account for up to 90\% of all the significantly structured regions from the termini of M. tuberculosis genic elements. The software, predictions and alignments described below are available from http://github.com/ppgardne/RNIE.

}, keywords = {Bacterial, Base Sequence, Conserved Sequence, Genetic, Genome, Genomics, Models, Molecular Sequence Annotation, Mycobacterium tuberculosis, Software, Statistical, Terminator Regions}, issn = {1362-4962}, doi = {10.1093/nar/gkr168}, author = {Gardner, Paul P and Barquist, Lars and Bateman, Alex and Nawrocki, Eric P and Weinberg, Zasha} } @article {4253, title = {The Pfam protein families database.}, journal = {Nucleic Acids Research}, volume = {38}, year = {2010}, month = {2010 Jan}, pages = {D211-22}, abstract = {

Pfam is a widely used database of protein families and domains. This article describes a set of major updates that we have implemented in the latest release (version 24.0). The most important change is that we now use HMMER3, the latest version of the popular profile hidden Markov model package. This software is approximately 100 times faster than HMMER2 and is more sensitive due to the routine use of the forward algorithm. The move to HMMER3 has necessitated numerous changes to Pfam that are described in detail. Pfam release 24.0 contains 11,912 families, of which a large number have been significantly updated during the past two years. Pfam is available via servers in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/).

}, keywords = {Amino Acid, Amino Acid Sequence, Animals, Archaeal, Computational Biology, Databases, Fungal, Genome, Humans, Information Storage and Retrieval, Internet, Molecular Sequence Data, Nucleic Acid, Protein, Protein Structure, Sequence Alignment, Sequence Homology, Software, Tertiary}, issn = {1362-4962}, doi = {10.1093/nar/gkp985}, author = {Finn, Robert D and Mistry, Jaina and Tate, John and Coggill, Penny and Heger, Andreas and Pollington, Joanne E and Gavin, O Luke and Gunasekaran, Prasad and Ceric, Goran and Forslund, Kristoffer and Holm, Liisa and Sonnhammer, Erik L L and Eddy, Sean R. and Bateman, Alex} } @article {4266, title = {Rfam: updates to the RNA families database.}, journal = {Nucleic Acids Research}, volume = {37}, year = {2009}, month = {2009 Jan}, pages = {D136-40}, abstract = {

Rfam is a collection of RNA sequence families, represented by multiple sequence alignments and covariance models (CMs). The primary aim of Rfam is to annotate new members of known RNA families on nucleotide sequences, particularly complete genomes, using sensitive BLAST filters in combination with CMs. A minority of families with a very broad taxonomic range (e.g. tRNA and rRNA) provide the majority of the sequence annotations, whilst the majority of Rfam families (e.g. snoRNAs and miRNAs) have a limited taxonomic range and provide a limited number of annotations. Recent improvements to the website, methodologies and data used by Rfam are discussed. Rfam is freely available on the Web at http://rfam.sanger.ac.uk/and http://rfam.janelia.org/.

}, keywords = {Computer Graphics, Databases, Internet, Nucleic Acid, RNA, Sequence Alignment, Sequence Analysis}, issn = {1362-4962}, doi = {10.1093/nar/gkn766}, author = {Gardner, Paul P and Daub, Jennifer and Tate, John G and Nawrocki, Eric P and Kolbe, Diana L and Lindgreen, Stinus and Wilkinson, Adam C and Finn, Robert D and Griffiths-Jones, Sam and Eddy, Sean R. and Bateman, Alex} } @article {45849, title = {The Pfam protein families database.}, journal = {Nucleic Acids Research}, volume = {36}, year = {2008}, month = {2008 Jan}, pages = {D281-8}, abstract = {

Pfam is a comprehensive collection of protein domains and families, represented as multiple sequence alignments and as profile hidden Markov models. The current release of Pfam (22.0) contains 9318 protein families. Pfam is now based not only on the UniProtKB sequence database, but also on NCBI GenPept and on sequences from selected metagenomics projects. Pfam is available on the web from the consortium members using a new, consistent and improved website design in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/), as well as from mirror sites in France (http://pfam.jouy.inra.fr/) and South Korea (http://pfam.ccbb.re.kr/).

}, keywords = {Animals, Databases, Protein, Genomics, Internet, Protein Structure, Tertiary, Proteins, Sequence Alignment, Sequence Analysis, Protein, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkm960}, author = {Finn, Robert D and Tate, John and Mistry, Jaina and Coggill, Penny C and Sammut, Stephen John and Hotz, Hans-Rudolf and Ceric, Goran and Forslund, Kristoffer and Eddy, Sean R and Sonnhammer, Erik L L and Bateman, Alex} }