Browse
Submit Data
Databases
API
Help

Dataset Information

13 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Uniclust databases of clustered and deeply annotated protein sequences and alignments.

ABSTRACT: We present three clustered protein sequence databases, Uniclust90, Uniclust50, Uniclust30 and three databases of multiple sequence alignments (MSAs), Uniboost10, Uniboost20 and Uniboost30, as a resource for protein sequence analysis, function prediction and sequence searches. The Uniclust databases cluster UniProtKB sequences at the level of 90%, 50% and 30% pairwise sequence identity. Uniclust90 and Uniclust50 clusters showed better consistency of functional annotation than those of UniRef90 and UniRef50, owing to an optimised clustering pipeline that runs with our MMseqs2 software for fast and sensitive protein sequence searching and clustering. Uniclust sequences are annotated with matches to Pfam, SCOP domains, and proteins in the PDB, using our HHblits homology detection tool. Due to its high sensitivity, Uniclust contains 17% more Pfam domain annotations than UniProt. Uniboost MSAs of three diversities are built by enriching the Uniclust30 MSAs with local sequence matches from MMseqs2 profile searches through Uniclust30. All databases can be downloaded from the Uniclust server at uniclust.mmseqs.com. Users can search clusters by keywords and explore their MSAs, taxonomic representation, and annotations. Uniclust is updated every two months with the new UniProt release.

SUBMITTER: Mirdita M

PROVIDER: S-EPMC5614098 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Searching databases of conserved sequence regions by aligning protein multiple-alignments.

Project description:A general searching method for comparing multiple sequence alignments was developed to detect sequence relationships between conserved protein regions. Multiple alignments are treated as sequences of amino acid distributions and aligned by comparing pairs of such distributions. Four different comparison measures were tested and the Pearson correlation coefficient chosen. The method is sensitive, detecting weak sequence relationships between protein families. Relationships are detected beyond the range of conventional sequence database searches, illustrating the potential usefulness of the method. The previously undetected relation between flavoprotein subunits of two oxidoreductase families points to the potential active site in one of the families. The similarity between the bacterial RecA, DnaA and Rad51 protein families reveals a region in DnaA and Rad51 proteins likely to bind and unstack single-stranded DNA. Helix--turn--helix DNA binding domains from diverse proteins are readily detected and shown to be similar to each other. Glycosylasparaginase and gamma-glutamyltransferase enzymes are found to be similar in their proteolytic cleavage sites. The method has been fully implemented on the World Wide Web at URL: http://blocks.fhcrc.org/blocks-bin/LAMAvsearch.

| S-EPMC146152 | biostudies-other

Clustal Omega for making accurate alignments of many protein sequences.

Project description:Clustal Omega is a widely used package for carrying out multiple sequence alignment. Here, we describe some recent additions to the package and benchmark some alternative ways of making alignments. These benchmarks are based on protein structure comparisons or predictions and include a recently described method based on secondary structure prediction. In general, Clustal Omega is fast enough to make very large alignments and the accuracy of protein alignments is high when compared to alternative packages. The package is freely available as executables or source code from www.clustal.org or can be run on-line from a variety of sites, especially the EBI www.ebi.ac.uk.

| S-EPMC5734385 | biostudies-literature

KinFin: Software for Taxon-Aware Analysis of Clustered Protein Sequences.

Project description:The field of comparative genomics is concerned with the study of similarities and differences between the information encoded in the genomes of organisms. A common approach is to define gene families by clustering protein sequences based on sequence similarity, and analyze protein cluster presence and absence in different species groups as a guide to biology. Due to the high dimensionality of these data, downstream analysis of protein clusters inferred from large numbers of species, or species with many genes, is nontrivial, and few solutions exist for transparent, reproducible, and customizable analyses. We present KinFin, a streamlined software solution capable of integrating data from common file formats and delivering aggregative annotation of protein clusters. KinFin delivers analyses based on systematic taxonomy of the species analyzed, or on user-defined, groupings of taxa, for example, sets based on attributes such as life history traits, organismal phenotypes, or competing phylogenetic hypotheses. Results are reported through graphical and detailed text output files. We illustrate the utility of the KinFin pipeline by addressing questions regarding the biology of filarial nematodes, which include parasites of veterinary and medical importance. We resolve the phylogenetic relationships between the species and explore functional annotation of proteins in clusters in key lineages and between custom taxon sets, identifying gene families of interest. KinFin can easily be integrated into existing comparative genomic workflows, and promotes transparent and reproducible analysis of clustered protein data.

| S-EPMC5633385 | biostudies-literature

MAGA: A Supervised Method to Detect Motifs From Annotated Groups in Alignments.

Project description:Multiple sequence alignments are usually phylogenetically driven. They are studied in the framework of evolution. But sometimes, it is interesting to study residue conservation at positions unconstrained by evolutionary rules. We present a supervised method to access a layer of information difficult to appreciate visually when many protein sequences are aligned. This new tool (MAGA; http://cbdm-01.zdv.uni-mainz.de/~munoz/maga/) locates positions in multiple sequence alignments differentially conserved in manually defined groups of sequences.

| S-EPMC7218316 | biostudies-literature

Vespucci: a system for building annotated databases of nascent transcripts.

Project description:Global run-on sequencing (GRO-seq) is a recent addition to the series of high-throughput sequencing methods that enables new insights into transcriptional dynamics within a cell. However, GRO-sequencing presents new algorithmic challenges, as existing analysis platforms for ChIP-seq and RNA-seq do not address the unique problem of identifying transcriptional units de novo from short reads located all across the genome. Here, we present a novel algorithm for de novo transcript identification from GRO-sequencing data, along with a system that determines transcript regions, stores them in a relational database and associates them with known reference annotations. We use this method to analyze GRO-sequencing data from primary mouse macrophages and derive novel quantitative insights into the extent and characteristics of non-coding transcription in mammalian cells. In doing so, we demonstrate that Vespucci expands existing annotations for mRNAs and lincRNAs by defining the primary transcript beyond the polyadenylation site. In addition, Vespucci generates assemblies for un-annotated non-coding RNAs such as those transcribed from enhancer-like elements. Vespucci thereby provides a robust system for defining, storing and analyzing diverse classes of primary RNA transcripts that are of increasing biological interest.

| S-EPMC3936758 | biostudies-literature

Collection of Annotated Acinetobacter Genome Sequences.

Project description:The genus Acinetobacter contains environmental species as well as opportunistic pathogens of humans. Several species are competent for natural transformation, an important mechanism of horizontal gene transfer. Here, we present the genome sequences of 19 Acinetobacter strains used in past and upcoming studies of natural transformation.

| S-EPMC10019184 | biostudies-literature

Annotating RNA motifs in sequences and alignments.

Project description:RNA performs a diverse array of important functions across all cellular life. These functions include important roles in translation, building translational machinery and maturing messenger RNA. More recent discoveries include the miRNAs and bacterial sRNAs that regulate gene expression, the thermosensors, riboswitches and other cis-regulatory elements that help prokaryotes sense their environment and eukaryotic piRNAs that suppress transposition. However, there can be a long period between the initial discovery of a RNA and determining its function. We present a bioinformatic approach to characterize RNA motifs, which are critical components of many RNA structure-function relationships. These motifs can, in some instances, provide researchers with functional hypotheses for uncharacterized RNAs. Moreover, we introduce a new profile-based database of RNA motifs--RMfam--and illustrate some applications for investigating the evolution and functional characterization of RNA. All the data and scripts associated with this work are available from: https://github.com/ppgardne/RMfam.

| S-EPMC4333381 | biostudies-literature

DbClustal: rapid and reliable global multiple alignments of protein sequences detected by database searches.

Project description:DbClustal addresses the important problem of the automatic multiple alignment of the top scoring full-length sequences detected by a database homology search. By combining the advantages of both local and global alignment algorithms into a single system, DbClustal is able to provide accurate global alignments of highly divergent, complex sequence sets. Local alignment information is incorporated into a ClustalW global alignment in the form of a list of anchor points between pairs of sequences. The method is demonstrated using anchors supplied by the Blast post-processing program, Ballast. The rapidity and reliability of DbClustal have been demonstrated using the recently annotated Pyrococcus abyssi proteome where the number of alignments with totally misaligned sequences was reduced from 20% to <2%. A web site has been implemented proposing BlastP database searches with automatic alignment of the top hits by DbClustal.

| S-EPMC102675 | biostudies-literature

Flavitrack: an annotated database of flavivirus sequences.

Project description:Properly annotated sequence data for flaviviruses, which cause diseases, such as tick-borne encephalitis (TBE), dengue fever (DF), West Nile (WN) and yellow fever (YF), can aid in the design of antiviral drugs and vaccines to prevent their spread. Flavitrack was designed to help identify conserved sequence motifs, interpret mutational and structural data and track evolution of phenotypic properties.Flavitrack contains over 590 complete flavivirus genome/protein sequences and information on known mutations and literature references. Each sequence has been manually annotated according to its date and place of isolation, phenotype and lethality. Internal tools are provided to rapidly determine relationships between viruses in Flavitrack and sequences provided by the user.

| S-EPMC2629353 | biostudies-literature

MisPred: a resource for identification of erroneous protein sequences in public databases.

Project description:Correct prediction of the structure of protein-coding genes of higher eukaryotes is still a difficult task; therefore, public databases are heavily contaminated with mispredicted sequences. The high rate of misprediction has serious consequences because it significantly affects the conclusions that may be drawn from genome-scale sequence analyses of eukaryotic genomes. Here we present the MisPred database and computational pipeline that provide efficient means for the identification of erroneous sequences in public databases. The MisPred database contains a collection of abnormal, incomplete and mispredicted protein sequences from 19 metazoan species identified as erroneous by MisPred quality control tools in the UniProtKB/Swiss-Prot, UniProtKB/TrEMBL, NCBI/RefSeq and EnsEMBL databases. Major releases of the database are automatically generated and updated regularly. The database (http://www.mispred.com) is easily accessible through a simple web interface coupled to a powerful query engine and a standard web service. The content is completely or partially downloadable in a variety of formats. DATABASE URL: http://www.mispred.com.

| S-EPMC3713709 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data