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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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Toolbox at the European Bioinformatics Institute Resource Report Resource Website 50+ mentions |
Toolbox at the European Bioinformatics Institute (RRID:SCR_002872) | software resource, software toolkit | The European Bioinformatics Institute (EBI) toolbox area provides a comprehensive range of tools for the field of bioinformatics. These are subdivided into categories in the left menu for convenience. EBI has developed a large number of very useful bioinformatics tools. A few examples include: - Similarity & Homology - the BLAST or FASTA programs can be used to look for sequence similarity and infer homology. - Protein Functional Analysis - InterProScan can be used to search for motifs in your protein sequence. - Proteomic Services NEW - UniProt DAS server allows researchers to show their research results in the context of UniProtKB/Swiss-Prot annotation. - Sequence Analysis - ClustalW2 a sequence alignment tool. - Structural Analysis - MSDfold can be used to query your protein structure and compare it to those in the Protein Data Bank (PDB). - Web Services - provide programmatic access to the various databases and retrieval/analysis services EBI provides. - Tools Miscellaneous - Expression Profiler a set of tools for clustering, analysis and visualization of gene expression and other genomic data. Sponsors: This resource is sponsored by EBI. | expression, functional, gene, bioinformatics, database, genomic, homology, protein, proteomic, sequence, structural, toolbox | has parent organization: European Bioinformatics Institute | Free | nif-0000-25553 | SCR_002872 | EBI Bioinformatics Tools | 2026-02-16 09:45:51 | 85 | ||||||||
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Protein Prospector Resource Report Resource Website 500+ mentions |
Protein Prospector (RRID:SCR_014558) | software resource, software toolkit | A package of over twenty mass spectrometry-based tools primarily geared toward proteomic data analysis and database mining. It can be run from the command line, but is primarily used through a web browser, and there is a public website that allows anyone to use the software without local installation. Tandem mass spectrometry analysis tools are used for database searching and identification of peptides, including post-translationally modified peptides and cross-linked peptides. Support for isotope and label-free quantification from this type of data is provided. MS-Viewer software allows sharing and displaying of annotated spectra from many different tandem mass spectrometry data analysis packages. Other tools include software for analyzing peptide mass fingerprinting data (MS-Fit); prediction of theoretical fragmentation of peptides (MS-Product); theoretical chemical or enzymatic digestion of proteins (MS-Digest); and theoretical modeling of the isotope distribution of any chemical, including peptides (MS-Isotope). Searches using amino acid sequence can be used to identify homologous peptides in a database (MS-Pattern); the use of the combination of amino acid sequence and masses can be used for homologous peptide and protein identification using MS-Homology. Tandem mass spectrometry peak list files can be filtered for the presence of certain peaks or neutral losses using MS-Filter. Given a list of proteins, MS-Bridge can report all potential cross-linked peptide combinations of a specified mass. Given a precursor peptide mass and information about known amino acid presence, absence, or modifications, MS-Comp can report all amino acid combinations that could lead to the observed mass. | database search program, database search, database management, peptide, protein, mass spectrometry, ms, utility program, batch msms, bio.tools, FASEB list |
is listed by: bio.tools is listed by: Debian has parent organization: University of California at San Francisco; California; USA |
Open source, Freely available to academic researchers | biotools:proteinprospector | https://bio.tools/proteinprospector | SCR_014558 | ProteinProspector | 2026-02-16 09:48:38 | 569 | |||||||
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SIGNOR Resource Report Resource Website 10+ mentions |
SIGNOR (RRID:SCR_018485) | data repository, database, storage service resource, service resource, data or information resource | Software application to organize and store in structured format signaling information published in scientific literature. Information is stored as binary causative relationships between biological entities and can be represented graphically as activity flow. Each relationship is linked to literature reporting experimental evidence. Each node is annotated with chemical inhibitors that modulate its activity. Signaling information is mapped to human proteome. SIGNOR 2.0 stores manually annotated causal relationships between proteins and other biologically relevant entities including chemicals, phenotypes, complexes, etc with compliance to FAIR data principles. | Signal transduction data, signaling information, published data collection, activity flow, chemical inhibitor, human proteome, manually annotated data, protein, protein relationship, FAIR data, bio.tools |
is listed by: Debian is listed by: bio.tools is related to: REDIportal |
Italian Association for Cancer Research ; ELIXIR-IIB ; Italian Node of the European ELIXIR infrastructure ; EMBL-EBI |
PMID:31665520 | Free, Available for download, Freely available | biotools:signor | https://bio.tools/signor | SCR_018485 | SIGnaling Network Open Resource, SIGNOR 2.0 | 2026-02-16 09:49:28 | 40 | |||||
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SCAR Resource Report Resource Website 50+ mentions |
SCAR (RRID:SCR_006227) | SCAR | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:39 | 82 | ||||||||
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SecStr Resource Report Resource Website 1+ mentions |
SecStr (RRID:SCR_006220) | SecStr | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:39 | 7 | |||||||
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CW-PRED Resource Report Resource Website 10+ mentions |
CW-PRED (RRID:SCR_006188) | CW-PRED | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:38 | 16 | |||||||
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orienTM Resource Report Resource Website |
orienTM (RRID:SCR_006218) | orienTM | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:39 | 0 | ||||||
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MutationAssessor Resource Report Resource Website 500+ mentions |
MutationAssessor (RRID:SCR_005762) | mutationassessor.org | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:32 | 669 | ||||||
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Computational Biology at ORNL Resource Report Resource Website |
Computational Biology at ORNL (RRID:SCR_005710) | Computational Biology at ORNL | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:31 | 0 | ||||||||
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GOtcha Resource Report Resource Website 1+ mentions |
GOtcha (RRID:SCR_005790) | GOtcha | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:33 | 1 | |||||
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GoAnnotator Resource Report Resource Website 1+ mentions |
GoAnnotator (RRID:SCR_005792) | GOAnnotator | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:33 | 1 | ||||||
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MCMBB Resource Report Resource Website 1+ mentions |
MCMBB (RRID:SCR_006198) | MCMBB | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:43 | 1 | |||||||
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waveTM Resource Report Resource Website 1+ mentions |
waveTM (RRID:SCR_006199) | waveTM | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:39 | 3 | |||||
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PRED-TMBB Resource Report Resource Website 50+ mentions |
PRED-TMBB (RRID:SCR_006190) | PRED-TMBB | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:38 | 54 | ||||
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GOanna Resource Report Resource Website 10+ mentions |
GOanna (RRID:SCR_005684) | GOanna | production service resource, service resource, data analysis service, analysis 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 | 2026-02-16 09:46:31 | 17 | |||||
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PRED-TMR2 Resource Report Resource Website 1+ mentions |
PRED-TMR2 (RRID:SCR_006205) | PRED-TMR2 | production service resource, service resource, data analysis service, analysis service resource | A web server that classifies proteins into two classes from their sequences alone: the membrane protein class and the non-membrane protein class. This may be important in the functional assignment and analysis of open reading frames (ORF''s) identified in complete genomes and, especially, those ORF''s that correspond to proteins with unknown function. The network has a simple hierarchical feed-forward topology and a limited number of neurons which makes it very fast. By using only information contained in 11 protein sequences, the method was able to identify, with 100% accuracy, all membrane proteins with reliable topologies collected from several papers in the literature. Applied to a test set of 995 globular, water-soluble proteins, the neural network classified falsely 23 of them in the membrane protein class (97.7% of correct assignment). The method was also applied to the complete SWISS-PROT database with considerable success and on ORF''s of several complete genomes. The neural network developed was associated with the PRED-TMR algorithm (Pasquier,C., Promponas,V.J., Palaios,G.A., Hamodrakas,J.S. and Hamodrakas,S.J., 1999) in a new application package called PRED-TMR2. | prediction, transmembrane, protein, algorithm, neural network, classification, transmembrane protein, protein classification, membrane protein, protein structure |
is related to: DAM-Bio has parent organization: PRED-TMR |
European Union ERBFMRXCT960019 | PMID:10469822 | nlx_151766 | SCR_006205 | PRED-TMR2: Prediction of Transmembrane regions in proteins | 2026-02-16 09:46:39 | 1 | ||||||
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Lists2Networks Resource Report Resource Website 1+ mentions |
Lists2Networks (RRID:SCR_006323) | L2N | production service resource, service resource, data analysis service, analysis service resource | A web-based software system that allows users to upload lists of mammalian genes/proteins onto a server-based program for integrated analysis. The system includes web-based tools to manipulate lists with different set operations, to expand lists using existing mammalian networks of protein-protein interactions, co-expression correlation, or background knowledge co-annotation correlation, as well as to apply gene-list enrichment analyses against many gene-list libraries of prior biological knowledge such as pathways, gene ontology terms, kinase-substrate, microRNA-mRAN, and protein-protein interactions, metabolites, and protein domains. Such analyses can be applied to several lists at once against many prior knowledge libraries of gene-lists associated with specific annotations. The system also contains features that allow users to export networks and share lists with other users of the system. | high-throughput sequencing, analysis, gene, protein |
is listed by: OMICtools has parent organization: Icahn School of Medicine at Mount Sinai; New York; USA |
PMID:20152038 | Free, Public, Account required | OMICS_02231 | http://www.lists2networks.org | SCR_006323 | Lists2Networks: Integrated analysis of gene/protein lists | 2026-02-16 09:46:41 | 3 | |||||
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PRED-TMR Resource Report Resource Website 1+ mentions |
PRED-TMR (RRID:SCR_006203) | PRED-TMR | production service resource, service resource, data analysis service, analysis service resource | A web server that predicts transmembrane domains in proteins using solely information contained in the sequence itself. The algorithm refines a standard hydrophobicity analysis with a detection of potential termini (edges, starts and ends) of transmembrane regions. This allows both to discard highly hydrophobic regions not delimited by clear start and end configurations and to confirm putative transmembrane segments not distinguishable by their hydrophobic composition. The accuracy obtained on a test set of 101 non homologous transmembranes proteins with reliable topologies compares well with that of other popular existing methods. Only a slight decrease in prediction accuracy was observed when the algorithm was applied to all transmembrane proteins of the SwissProt database (release 35). | predict, transmembrane segment, protein, algorithm, sequence, membrane protein, protein structure, transmembrane region, hydrophobicity analysis |
is related to: waveTM is related to: DAM-Bio has parent organization: University of Athens Biophysics and Bioinformatics Laboratory is parent organization of: PRED-TMR2 |
European Union ERBFMRXCT960019 | PMID:10360978 | nlx_151765 | SCR_006203 | PRED-TMR: A novel method for predicting transmembrane segment in proteins based on a statistical analysis of the SwissProt database | 2026-02-16 09:46:39 | 7 | ||||||
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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 | production service resource, service resource, data analysis service, analysis 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) | 2026-02-16 09:46:32 | 0 | |||||||
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Aggrescan: The Hot Spot Finder Resource Report Resource Website 50+ mentions |
Aggrescan: The Hot Spot Finder (RRID:SCR_008403) | Aggrescan | production service resource, service resource, data analysis service, analysis service resource | Web-based tool for identifying hot spots of aggregation in polypeptides. Aggrescan uses an aggregation-propensity scale for natural amino acids derived from in vivo experiments and on the assumption that short and specific sequence stretches modulate protein aggregation. The algorithm is shown to identify a series of protein fragments involved in the aggregation of disease-related proteins and to predict the effect of genetic mutations on their deposition propensities. It also provides new insights into the differential aggregation properties displayed by globular proteins, natively unfolded polypeptides, amyloidogenic proteins and proteins found in bacterial inclusion bodies. | aggregation, amino acid, protein, mutation, polypeptide, amyloid, bacterial protein, protein aggregation, neurodegeneration |
is listed by: 3DVC has parent organization: Autonomous University of Barcelona; Barcelona; Spain |
Ministerio de Educacion y Ciencia BIO2004-05879; Ministerio de Educacion y Ciencia BIO2003-02848; Spain Generalitat de Catalunya SGR2005-00037; Spain Generalitat de Catalunya SGR2005-01037 |
PMID:17324296 | Free, Acknowledgement requested | nif-0000-30073 | SCR_008403 | 2026-02-16 09:47:10 | 52 |
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