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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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PolySearch Resource Report Resource Website 10+ mentions |
PolySearch (RRID:SCR_005291) | PolySearch | data analysis service, analysis service resource, production service resource, service resource | A web-based tool that supports more than 50 different classes of queries against nearly a dozen different types of text, scientific abstract or bioinformatic databases. The typical query supported by PolySearch is Given X, find all Y''s where X or Y can be diseases, tissues, cell compartments, gene/protein names, SNPs, mutations, drugs and metabolites. PolySearch also exploits a variety of techniques in text mining and information retrieval to identify, highlight and rank informative abstracts, paragraphs or sentences. | text mining, disease, gene, protein, drug, metabolite, snp, gene sequence, pathway, tissue, gene family, subcellular localization, organ |
is listed by: OMICtools has parent organization: University of Alberta; Alberta; Canada |
OMICS_01194 | SCR_005291 | 2026-08-04 09:41:19 | 20 | |||||||||
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Structure Superposition Database Resource Report Resource Website 1+ mentions |
Structure Superposition Database (RRID:SCR_005236) | database, data or information resource | The SSD has been developed to address the need for resources and tools for understanding large sets of superpositions in order to understand evolutionary relationships and to make predictions of function. We have therefore created the Structure Superposition Database (SSD) for accessing, viewing and understanding large sets of structure superposition data. It contains the results of pairwise, all-by-all superpositions of a representative set of 115 (beta/alpha) barrel structures (TIM barrels). The initial implementation of the SSD contains the results of pairwise, all-by-all superpositions of a representative set of 115 (/alpha)8 barrel structures (TIM barrels). Future plans call for extending the database to include representative structure superpositions for many additional folds. The SSD can be browsed with a user interface module developed as an extension to Chimera, an extensible molecular modeling program. Features of the user interface module facilitate viewing multiple superpositions together. | alpha barrel structure, barrel structure, beta barrel structure, protein, quaternary structure, structure superposition | nif-0000-03504 | SCR_005236 | SSD | 2026-08-04 09:41:19 | 2 | ||||||||||
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BiGG Database Resource Report Resource Website 100+ mentions |
BiGG Database (RRID:SCR_005809) | BiGG | database, data or information resource | A knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest. | biochemical, genetics, genomics, genome, metabolic network, reconstruction, model, metabolic pathway, gene, protein, reaction, metabolite, metabolic reconstruction, compound, pathway, FASEB list |
uses: SBML is used by: BiGGR is listed by: 3DVC has parent organization: University of California at San Diego; California; USA |
NIH ; Ruth L. Kirschstein National Research Service Award - NIH Bioinformatics Training ; University of California at San Diego; California; USA ; Calit2 summer research scholarship ; NIGMS GM00806-06 |
PMID:20426874 | nlx_149299, r3d100011567 | https://doi.org/10.17616/R3MG9M | SCR_005809 | BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions, BiGG - a Biochemical Genetic and Genomic knowledgebase | 2026-08-04 09:41:26 | 124 | |||||
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UniPROBE Resource Report Resource Website 100+ mentions |
UniPROBE (RRID:SCR_005803) | UniPROBE | database, data or information resource | Database that hosts experimental data from universal protein binding microarray (PBM) experiments (Berger et al., 2006) and their accompanying statistical analyses from prokaryotic and eukaryotic organisms, malarial parasites, yeast, worms, mouse, and human. It provides a centralized resource for accessing comprehensive data on the preferences of proteins for all possible sequence variants ("words") of length k ("k-mers"), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. The database's web tools include a text-based search, a function for assessing motif similarity between user-entered data and database PWMs, and a function for locating putative binding sites along user-entered nucleotide sequences. | protein, in vitro, dna binding, protein binding, genetics, dna, nucleotide sequence, sequence variant, k-mer, position weight matrix, graphical sequence logo, motif, motif similarity, binding site, microarray, protein-dna interaction, protein binding microarray probe sequence, probe, FASEB list |
is listed by: re3data.org is listed by: OMICtools |
PMID:21037262 PMID:18842628 |
Acknowledgement requested, Academic research use license | nif-0000-03611, OMICS_00546, r3d100010557 | http://thebrain.bwh.harvard.edu/pbms/webworks_pub/, https://doi.org/10.17616/R35C9J | SCR_005803 | UniPROBE Database, Universal Protein Binding Microarray Resource for Oligonucleotide Binding Evaluation, Universal PBM Resource for Oligonucleotide Binding Evaluation | 2026-08-04 09:41:26 | 149 | |||||
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MutationAssessor Resource Report Resource Website 500+ mentions |
MutationAssessor (RRID:SCR_005762) | mutationassessor.org | data analysis service, analysis service resource, production service resource, service resource | A web server that predicts the functional impact of amino-acid substitutions in proteins, such as mutations discovered in cancer or nonsynonymous polymorphisms. The functional impact is assessed based on evolutionary conservation of the affected amino acid in protein homologs. The method has been validated on a large set (51k) of disease associated (OMIM) and polymorphic variants., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. | cancer, protein, mutation, function, amino-acid, substitution |
is listed by: OMICtools is listed by: SoftCite |
PMID:21727090 | THIS RESOURCE IS NO LONGER IN SERVICE | OMICS_00134, nlx_149228 | SCR_005762 | MutationAssessor - functional impact of protein mutations, MutationAssessor - functional impact of mutations, mutationassessor.org - functional impact of protein mutations | 2026-08-04 09:41:26 | 669 | ||||||
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Computational Biology at ORNL Resource Report Resource Website |
Computational Biology at ORNL (RRID:SCR_005710) | Computational Biology at ORNL | data analysis service, analysis service resource, production service resource, service resource | We are the Computational Biology and Bioinformatics Group of the Biosciences Division of Oak Ridge National Laboratory. We conduct genetics research and system development in genomic sequencing, computational genome analysis, and computational protein structure analysis. We provide bioinformatics and analytic services and resources to collaborators, predict prospective gene and protein models for analysis, provide user services for the general community, including computer-annotated genomes in Genome Channel. Our collaborators include the Joint Genome Institute, ORNL''s Computer Science and Mathematics Division, the Tennessee Mouse Genome Consortium, the Joint Institute for Biological Sciences, and ORNL''s Genome Science and Technology Graduate Program. | genetics, research, system development, genomic sequencing, computation, genome analysis, protein structure, analysis, gene, protein, gene annotation, annotation, genome | has parent organization: Oak Ridge National Laboratory | nlx_149161 | SCR_005710 | Computational Biology at Oak Ridge National Laboratory, Computational Biology and Bioinformatics Group at ORNL, Computational Biology Bioinformatics Group at ORNL | 2026-08-04 09:41:25 | 0 | ||||||||
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GOtcha Resource Report Resource Website 1+ mentions |
GOtcha (RRID:SCR_005790) | GOtcha | data analysis service, analysis service resource, production service resource, service resource | GOtcha provides a prediction of a set of GO terms that can be associated with a given query sequence. Each term is scored independently and the scores calibrated against reference searches to give an accurate percentage likelihood of correctness. These results can be displayed graphically. Why is GOtcha different to what is already out there and why should you be using it? * GOtcha uses a method where it combines information from many search hits, up to and including E-values that are normally discarded. This gives much better sensitivity than other methods. * GOtcha provides a score for each individual term, not just the leaf term or branch. This allows the discrimination between confident assignments that one would find at a more general level and the more specific terms that one would have lower confidence in. * The scores GOtcha provides are calibrated to give a real estimate of correctness. This is expressed as a percentage, giving a result that non-experts are comfortable in interpreting. * GOtcha provides graphical output that gives an overview of the confidence in, or potential alternatives for, particular GO term assignments. The tool is currently web-based; contact David Martin for details of the standalone version. Platform: Online tool | function, protein, prediction, genome, annotation, gene, statistical analysis |
is listed by: Gene Ontology Tools is related to: Gene Ontology has parent organization: University of Dundee; Scotland; United Kingdom |
Wellcome Trust 060269; European Union fifth framework QLRI-CT-2000-00127 |
PMID:15550167 | Free for academic use | nlx_149269 | http://www.compbio.dundee.ac.uk/Software/GOtcha/gotcha.html | SCR_005790 | 2026-08-04 09:41:26 | 1 | |||||
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GoAnnotator Resource Report Resource Website 1+ mentions |
GoAnnotator (RRID:SCR_005792) | GOAnnotator | data analysis service, analysis service resource, production service resource, service resource | A tool for assisting the GO annotation of UniProt entries by linking the GO terms present in the uncurated annotations with evidence text automatically extracted from the documents linked to UniProt entries. Platform: Online tool | text mining, protein, gene ontology, annotation |
is listed by: Gene Ontology Tools is related to: Gene Ontology is related to: UniProt has parent organization: University of Lisbon; Lisbon; Portugal |
European Union contract QLRI-1999-50595 | PMID:17181854 | Free for academic use | nlx_149303 | SCR_005792 | 2026-08-04 09:41:27 | 1 | ||||||
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GOanna Resource Report Resource Website 10+ mentions |
GOanna (RRID:SCR_005684) | GOanna | data analysis service, analysis service resource, production service resource, service resource | GOanna is used to find annotations for proteins using a similarity search. The input can be a list of IDs or it can be a list of sequences in FASTA format. GOanna will retrieve the sequences if necessary and conduct the specified BLAST search against a user-specified database of GO annotated proteins. The resulting file contains GO annotations of the top BLAST hits. The sequence alignments are also provided so the user can use these to access the quality of the match. Platform: Online tool | agriculture, annotation, protein, ontology or annotation search engine, ontology or annotation editor |
is listed by: Gene Ontology Tools is related to: Gene Ontology has parent organization: AgBase |
USDA ; Mississippi State University; Mississippi; USA ; MSU Office of Research ; MSU Bagley College of Engineering ; MSU College of College of Veterinary Medicine ; MSU Life Science and Biotechnology Institute |
PMID:17135208 PMID:16961921 |
Free for academic use | nlx_149139 | SCR_005684 | AgBase GOanna | 2026-08-04 09:41:25 | 17 | |||||
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TranspoGene Resource Report Resource Website 1+ mentions |
TranspoGene (RRID:SCR_005634) | database, data or information resource | A publicly available database of Transposed elements (TEs) which are located within protein-coding genes of 7 organisms: human, mouse, chicken, zebrafish, fruilt fly, nematode and sea squirt. Using TranspoGene the user can learn about the many aspects of the effect these TEs have on their hosting genes, such as: exonization events (including alternative splicing-related data), insertion of TEs into introns, exons, and promoters, specific location of the TE over the gene, evolutionary divergence of the TE from its consensus sequence and involvement in diseases. TranspoGene database is quickly searchable through its website, enables many kinds of searches and is available for download. TranspoGene contains information regarding specific type and family of the TEs, genomic and mRNA location, sequence, supporting transcript accession and alignment to the TE consensus sequence. The database also contains host gene specific data: gene name, genomic location, Swiss-Prot and RefSeq accessions, diseases associated with the gene and splicing pattern. The TranspoGene and microTranspoGene databases can be used by researchers interested in the effect of TE insertion on the eukaryotic transcriptome. | element, eukaryotic, evolutionary, exon, exonization, family, fruit fly, gene, genome, alternative, chicken, coding, disease, divergence, genomic, hosting, human, human genome databases, intron, location, map, maps, mouse, mrna, nematode, organism, pattern, promoter, protein, sea squirt, sequence, splicing, transcript, transcriptome, transposed, viewers, worm, zebrafish | has parent organization: Tel Aviv University; Ramat Aviv; Israel | nif-0000-03579 | SCR_005634 | TranspoGene | 2026-08-04 09:41:24 | 9 | |||||||||
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FuSSiMeG: Functional Semantic Similarity Measure between Gene-Products Resource Report Resource Website |
FuSSiMeG: Functional Semantic Similarity Measure between Gene-Products (RRID:SCR_005738) | FuSSiMeG | data analysis service, analysis service resource, production service resource, service resource | FuSSiMeG is being discontinued, may not be working properly. Please use our new tool ProteinOn. Functional Semantic Similarity Measure between Gene Products (FuSSiMeG) provides a functional similarity measure between two proteins using the semantic similarity between the GO terms annotated with the proteins. Platform: Online tool | protein, similarity, gene ontology, gene, ontology, statistical analysis, term enrichment, semantic similarity, analysis, other analysis |
is listed by: Gene Ontology Tools is related to: Gene Ontology is related to: ProteInOn has parent organization: University of Lisbon; Lisbon; Portugal |
Free for academic use | nlx_149198 | SCR_005738 | Functional Semantic Similarity Measure between Gene-Products, Functional Semantic Similarity Measure between Gene Products (FuSSiMeG) | 2026-08-04 09:41:26 | 0 | |||||||
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SCAR Resource Report Resource Website 50+ mentions |
SCAR (RRID:SCR_006227) | SCAR | data analysis service, analysis service resource, production service resource, service resource | A web tool to create, display and manipulate structures of small molecules, proteins and DNA. | structure, small molecule, protein, dna, visualize, manipulate, display, create |
is related to: DAM-Bio has parent organization: University of Athens Biophysics and Bioinformatics Laboratory |
nlx_151782 | SCR_006227 | Structure Creation and Representation, SCAR - Structure Creation and Representation, S.C.A.R., S.C.A.R | 2026-08-04 09:41:32 | 82 | ||||||||
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SecStr Resource Report Resource Website 1+ mentions |
SecStr (RRID:SCR_006220) | SecStr | data analysis service, analysis service resource, production service resource, service resource | A tool to Predict the Secondary Structure of a protein from its amino acid sequence alone. The SecStr package uses six different secondary structure prediction methods (Nagano, Garnier et al., Burges et al., Chou and Fasman , Lim and Dufton and Hider). The results of those methods are combined into a Joint Prediction Histogram (JPH) as described by Hamodrakas, 1988 and Hamodrakas et al., 1982. As previously mentioned, the SecStr package contains computer programs making use of the secondary structure prediction methods of Nagano, Garnier et al., Burges et al., Chou and Fasman, Lim and Dufton and Hider. These programs were written in Fortran. The results of individual prediction methods are combined as described by Hamodrakas (1988), using a Perl program, to produce joint prediction histograms (JPH), for three types of secondary structure, which may be presented separately on a Java Applet. The output may be given either in text or graphics mode. For the latter a Java capable browser is required. | secondary structure, prediction, protein, algorithm, text, graphics |
is related to: DAM-Bio has parent organization: University of Athens Biophysics and Bioinformatics Laboratory |
All rights are reserved for the whole or part of the program. Permission to use, Copy, And modify this software and its documentation is granted for academic use provided that:1. this copyright notice appears in all copies of the software and related documentation; 2. bugs will be reported to the authors. | nlx_151767 | SCR_006220 | SecStr - Secondary Structure Prediction, Secondary Structure Prediction, Secondary Structure Prediction of Proteins | 2026-08-04 09:41:33 | 7 | |||||||
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CW-PRED Resource Report Resource Website 10+ mentions |
CW-PRED (RRID:SCR_006188) | CW-PRED | data analysis service, analysis service resource, production service resource, service resource | A web tool for the prediction of Cell Wall-Anchored Proteins in Gram+ Bacteria. Gram-positive bacteria have surface proteins that are often implicated in virulence. A group of extracellular proteins attached to the cell wall contains an LPXTG-like motif that is target for cleavage and covalent coupling to peptidoglycan by sortase enzymes. A new Hidden Markov Model (HMM), an extension to the HMM model from Litou et al., http://www.ncbi.nlm.nih.gov/pubmed/18464329, was developed for predicting the LPXTG and LPXTG-like cell-wall proteins of Gram-positive bacteria. An analysis of 177 completely sequenced genomes has been performed as well. We identified in total 1456 cell-wall proteins, from which 1283 have the LPXTG motif, 39 the NPXTG motif, 53 have the LPXTA and 81 the LAXTG motif. | hidden markov model, gram-positive bacteria, protein, classification, cell-wall protein | has parent organization: University of Athens Biophysics and Bioinformatics Laboratory | Free for academic use, Acknowledgement requested | nlx_151733 | SCR_006188 | CW-PRED: A HMM-based method for the classification of cell wall-anchored proteins of Gram-positive bacteria | 2026-08-04 09:41:31 | 16 | |||||||
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orienTM Resource Report Resource Website |
orienTM (RRID:SCR_006218) | orienTM | data analysis service, analysis service resource, production service resource, service resource | A computer software that utilizes an initial definition of transmembrane segments to predict the topology of transmembrane proteins from their sequence. It uses position-specific statistical information for amino acid residues which belong to putative non-transmembrane segments derived from a statistical analysis of non-transmembrane regions of membrane proteins stored in the SwissProt database. Its accuracy compares well with that of other popular existing methods. | topology, prediction, transmembrane, protein, segment, algorithm, transmembrane protein |
is related to: waveTM is related to: DAM-Bio has parent organization: University of Athens Biophysics and Bioinformatics Laboratory |
European Union ERBFMRXCT960019 | PMID:11477216 | nlx_151764 | SCR_006218 | orienTM - Orientation of TransMembrane proteins | 2026-08-04 09:41:32 | 0 | ||||||
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IndelFR - Indel Flanking Region Database Resource Report Resource Website 1+ mentions |
IndelFR - Indel Flanking Region Database (RRID:SCR_006050) | IndelFR | database, data or information resource | THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Indel Flanking Region Database is an online resource for indels and the flanking regions of proteins in SCOP superfamilies, including amino acid sequences, lengths, locations, secondary structure constitutions, hydrophilicity / hydrophobicity, domain information, 3D structures and so on. It aims at providing a comprehensive dataset for analyzing the qualities of amino acid insertion/deletions(indels), substitutions and the relationship between them. The indels were obtained through the pairwise alignment of homologous structures in SCOP superfamilies. The IndelFR database contains 2,925,017 indels with flanking regions extracted from 373,402 structural alignment pairs of 12,573 non-redundant domains from 1053 superfamilies. IndelFR has already been used for molecular evolution studies and may help to promote future functional studies of indels and their flanking regions. | indel, flanking region, protein, structural domain, domain, protein superfamily, protein structure, insertion/deletion, insertion, deletion, protein sequence, sequence, structure, protein domain, bio.tools |
is listed by: Debian is listed by: bio.tools is related to: SCOP: Structural Classification of Proteins is related to: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) has parent organization: Shandong University; Shandong; China |
Independent Innovation Foundation of Shandong University 2009JC006; National Natural Science Foundation of China 30970092; National Natural Science Foundation of China 61070017; Scientific Research Reward Fund for excellent Young and Middle-Aged scientists in Shandong Province 20090451326 |
PMID:22127860 | THIS RESOURCE IS NO LONGER IN SERVICE | biotools:indelfr, nlx_151448 | https://bio.tools/indelfr | SCR_006050 | IndelFR: Indel Flanking Region Database, Indel Flanking Region Database | 2026-08-04 09:41:29 | 2 | ||||
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ProPortal Resource Report Resource Website 1+ mentions |
ProPortal (RRID:SCR_006112) | ProPortal | database, data or information resource | ProPortal is a database containing genomic, metagenomic, transcriptomic and field data for the marine cyanobacterium Prochlorococcus. Our goal is to provide a source of cross-referenced data across multiple scales of biological organization--from the genome to the ecosystem--embracing the full diversity of ecotypic variation within this microbial taxon, its sister group, Synechococcus and phage that infect them. The site currently contains the genomes of 13 Prochlorococcus strains, 11 Synechococcus strains and 28 cyanophage strains that infect one or both groups. Cyanobacterial and cyanophage genes are clustered into orthologous groups that can be accessed by keyword search or through a genome browser. Users can also identify orthologous gene clusters shared by cyanobacterial and cyanophage genomes. Gene expression data for Prochlorococcus ecotypes MED4 and MIT9313 allow users to identify genes that are up or downregulated in response to environmental stressors. In addition, the transcriptome in synchronized cells grown on a 24-h light-dark cycle reveals the choreography of gene expression in cells in a ''natural'' state. Metagenomic sequences from the Global Ocean Survey from Prochlorococcus, Synechococcus and phage genomes are archived so users can examine the differences between populations from diverse habitats. Finally, an example of cyanobacterial population data from the field is included. | genomic, metagenomic, transcriptomic, field data, marine cyanobacterium, genome, ecosystem, ecotypic variation, microbial taxon, phage, genome, gene, orthologous gene cluster, cyanobacteria, cyanophage genome, population dynamics, microarray, metagenome, protein, cyanophage, bio.tools |
is listed by: Debian is listed by: bio.tools has parent organization: Massachusetts Institute of Technology; Massachusetts; USA; |
NSF OCE-0425602; NSF EF0424599; DOE DE-FG02-02ER63445; DOE DE-FG02-08ER64516; DOE DE-FG02-07ER64506; Gordon and Betty Moore Foundation award letter 495.01 |
PMID:22102570 | Public | nlx_151586, biotools:proportal | https://bio.tools/proportal | SCR_006112 | Prochlorococcus Portal | 2026-08-04 09:41:30 | 9 | ||||
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MCMBB Resource Report Resource Website 1+ mentions |
MCMBB (RRID:SCR_006198) | MCMBB | data analysis service, analysis service resource, production service resource, service resource | A web tool used in the discrimination of beta-barrel outer membrane proteins with a Markov chain model. MCMBB is a fast algorithm, which discriminates beta-barrel outer membrane proteins from globular proteins and from alpha-helical membrane proteins. The algorithm is based on a 1st order Markov Chain model, which captures the alternating pattern of hydrophilic-hydrophobic residues occurring in the membrane-spanning beta-strands of beta-barrel outer membrane proteins. The model achieves high accuracy in discriminating outer membrane proteins, since it can discriminate beta-barrel outer membrane with a correct classification rate of 90.08% and the globular proteins with a correct classification rate of 92.67%. When submitting alpha-helical membrane proteins, the method shows an accuracy of 100%. A score greater than zero, indicates that the protein is more likely to be a beta-barrel outer membrane protein, whereas a result lower than zero, indicates that the protein is probable not a beta-barrel. You may enter up to 1000 sequences in Fasta format. | algorithm, beta-barrel outer membrane protein, globular protein, alpha-helical membrane protein, markov chain model, beta-barrel, protein, outer membrane protein, classification, fasta, model |
is listed by: 3DVC has parent organization: University of Athens Biophysics and Bioinformatics Laboratory |
Acknowledgement requested | nlx_151742 | SCR_006198 | MCMBB: Markov Chain Model for Beta Barrels | 2026-08-04 09:41:32 | 1 | |||||||
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waveTM Resource Report Resource Website 1+ mentions |
waveTM (RRID:SCR_006199) | waveTM | data analysis service, analysis service resource, production service resource, service resource | A web tool for the prediction of transmembrane segments in alpha-helical membrane proteins. A sliding window of 20 residues is used in order to calculate an average residue hydrophobicity profile, using a hydrophobicity scale. Discrete Wavelet Transform is applied on the average residue hydrophobicity signal and the different frequency coefficients produced are adaptively thresholded so that a denoised signal is reconstructed. A dynamic programming algorithm processes the denoised signal to provide the optimal model for the number, the length and the location of membrane-spanning segments. The end points of the predicted segments are extended to include flanking hydrophobic residues. Topology prediction can also be obtained in conjunction with OrienTM (Liakopoulos et al, 2001). Analysis of a non-redundant test set, provides a ~95% per segment accuracy and ~90% per residue accuracy. Now, you can: * Run waveTM on a sequence * Browse the results obtained with the algorithm * View additional material concerning the hydrophobicity scale | wavelet, predict, transmembrane segment, alpha-helical membrane protein, protein, protein sequence, discrete wavelet transform, sequence, hydrophobicity scale, hydrophobicity, transmembrane protein, topology, transmembrane |
is related to: orienTM is related to: PRED-TMR has parent organization: University of Athens Biophysics and Bioinformatics Laboratory |
University of Athens; Athens; Greece | PMID:15107018 | Freely available | nlx_151743 | SCR_006199 | waveTM: Wavelet-based transmembrane segment prediction | 2026-08-04 09:41:32 | 3 | |||||
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PRED-TMBB Resource Report Resource Website 50+ mentions |
PRED-TMBB (RRID:SCR_006190) | PRED-TMBB | data analysis service, analysis service resource, production service resource, service resource | A web tool, based on a Hidden Markov Model, capable of predicting the transmembrane beta-strands of the gram-negative bacteria outer membrane proteins, and of discriminating such proteins from water-soluble ones when screening large datasets. The model is trained in a discriminative manner, aiming at maximizing the probability of the correct prediction rather than the likelihood of the sequences. The training is performed on a non-redundant database consisting of 16 outer membrane proteins (OMP''s) with their structures known at atomic resolution. We show that we can achieve predictions at least as good comparing with other existing methods, using as input only the amino-acid sequence, without the need of evolutionary information included in multiple alignments. The method is also powerful when used for discrimination purposes, as it can discriminate with a high accuracy the outer membrane proteins from water soluble in large datasets, making it a quite reliable solution for screening entire genomes. This web-server can help you run a discriminating process on any amino-acid sequence and thereafter localize the transmembrane strands and find the topology of the loops. | protein, hidden markov model, prediction, membrane protein, beta-barrel outer membrane protein, gram-negative bacteria, topology, outer membrane protein, beta-barrel protein, probability, transmembrane strand, bio.tools, FASEB list |
is listed by: bio.tools is listed by: Debian has parent organization: University of Athens Biophysics and Bioinformatics Laboratory |
Greek Ministry of National Education and Religious Affairs | PMID:15215419 PMID:15070403 |
Acknowledgement requested | biotools:pred-tmbb, nlx_151734 | https://bio.tools/pred-tmbb | SCR_006190 | PRED-TMBB: A Hidden Markov Model method capable of predicting and discriminating beta-barrel outer membrane proteins | 2026-08-04 09:41:32 | 54 |
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