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https://bioinfo3d.cs.tau.ac.il/PatchDock/

Web server for molecular docking. Performs structure prediction of protein–protein and protein–small molecule complexes. Molecular docking algorithm based on shape complementarity principles.

Proper citation: PatchDock (RRID:SCR_017589) Copy   

•   Source: SciCrunch Registry

http://apps.cytoscape.org/apps/cytohubba

Software tool for identifying hub objects and sub-networks from complex interactome. Predicts and explore nodes and subnetworks in given network by several topological algorithms. Provides interface to analyze topology of protein-protein interaction networks, such as human, yeast, rat, mouse, fly etc. Plugin works with Cytoscape 2.6 or above, which requires Java 1.5 or above.

Proper citation: cytoHubba (RRID:SCR_017677) Copy   

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https://github.com/santeripuranen/SuperDCA

Software tool for global direct coupling analysis of input genome alignments. Implements variant of pseudolikelihood maximization direct coupling analysis, with emphasis on optimizations that enable its use on genome scale. May be used to discover co evolving pairs of loci.Used for genome wide epistasis analysis.

Proper citation: SuperDCA (RRID:SCR_018175) Copy   

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http://interactome.org/index.php/Main_Page

This Wiki page provides information about Interactome of various species. An interactome of a species provides an important clues on how to interpret metabolic pathways of constituent enzymes and global protein network, which facilitates in turn to understand the mechanism responsible for the cellular functions.

Proper citation: Interactome Wiki (RRID:SCR_000750) Copy   

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http://statalign.github.io/

Software package for Bayesian analysis of protein, DNA and RNA sequences. It utilizes multiple alignments, phylogenetic trees and evolutionary parameters to quantify uncertainty in these analyses. It is written in Java.

Proper citation: StatAlign (RRID:SCR_001892) Copy   

•   Source: SciCrunch Registry

http://www.nactem.ac.uk/facta/

Text mining tool to discover associations between biomedical concepts from MEDLINE articles. Use the service from your browser or via a Web Service. The whole MEDLINE corpus containing more than 20 million articles is indexed with an efficient text search engine, and it allows you to navigate such associations and their textual evidence in a highly interactive manner - the system accepts arbitrary query terms and displays relevant concepts immediately. A broad range of important biomedical concepts are covered by the combination of a machine learning-based term recognizer and large-scale dictionaries for genes, proteins, diseases, and chemical compounds. There is also a FACTA+ visualization service that can be found here: http://www.nactem.ac.uk/facta-visualizer/

Proper citation: FACTA+. (RRID:SCR_001767) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/geo/

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

Proper citation: Gene Expression Omnibus (GEO) (RRID:SCR_005012) Copy   

•   Source: SciCrunch Registry

http://www.proteomexchange.org

A data repository for proteomic data sets. The ProteomeExchange consortium, as a whole, aims to provide a coordinated submission of MS proteomics data to the main existing proteomics repositories, as well as to encourage optimal data dissemination. ProteomeXchange provides access to a number of public databases, and users can access and submit data sets to the consortium's PRIDE database and PASSEL/PeptideAtlas.

Proper citation: ProteomeXchange (RRID:SCR_004055) Copy   

•   Source: SciCrunch Registry

http://abi.inf.uni-tuebingen.de/Services/YLoc/webloc.cgi

An interpretable web server for predicting subcellular localization. In addition to the predicted location, YLoc gives a reasoning why this prediction was made and which biological properties of the protein sequence lead to this prediction. Moreover, a confidence estimate helps users to rate predictions as trustworthy. YLoc+ is able to predict the location of multiple-targeted proteins with high accuracy. The YLoc webserver is also accessible via SOAP.

Proper citation: YLoc (RRID:SCR_002464) Copy   

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http://genome.unmc.edu/ngLOC/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.An n-gram-based Bayesian classifier that predicts subcellular localization of proteins both in prokaryotes and eukaryotes. The downloadable version of this software with source code is freely available for academic use under the GNU General Public License.

Proper citation: ngLOC (RRID:SCR_003150) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/hPATM/

A web tool, based on a heuristic transformation of the original global pairwise and local pairwise alignment algorithms, offers objective alignments for transmembrane protein sequences. hPATM takes advantage of the information offered by the knowledge of the position of transmembrane segmets, by experiment or prediction. The heuristic approach may reveal similarities between diverge sequences with low percentages of identity and similarity. The produced alignments, based on common structural scaffolds derived by the transmembrane segments of the sequence, can be used to spot conserved non-transmembrane segments or as a basis for the production of 3-D models via homology modelling. The hPAFAG algorithm is based on the heuristic transformation of the Needleman & Wunsch and Smith & Waterman algorithms, featuring affine gap penalties. The heuristic transformation is based on two extra features: * a heuristic bonus, added to the score when two amino acids that belong to transmembrane segmens are aligned. * a heuristic gap penalty, substracted from the score when a gap is opened in a transmembrane segment. This way transmembrane segments are anchored (not by force, but by more strict alignment) together, allowing the pairwise alignment to focus on non-transmembrane segments. This web server offers a friendly interface for the hPATM command line version. The algorithm was implemented in PERL and the source code of the command line version is available on request by the authors.

Proper citation: hPATM (RRID:SCR_006224) Copy   

•   Source: SciCrunch Registry

http://jilab.biostat.jhsph.edu/database/cgi-bin/hmChIP.pl

A database of genome-wide chromatin immunoprecipitation (ChIP) data in human and mouse. Currently, the database contains >2000 samples from >500 ChIP-seq and ChIP-chip experiments, representing a total of >170 proteins and >10,000,000 protein-DNA interactions (March 2014). A web server provides an interface for database query. Protein-DNA binding intensities can be retrieved from individual samples for user-provided genomic regions. The retrieved intensities can be used to cluster samples and genomic regions to facilitate exploration of combinatorial patterns, cell type dependencies, and cross-sample variability of protein-DNA interactions.

Proper citation: hmChIP (RRID:SCR_005407) Copy   

•   Source: SciCrunch Registry

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

Database of all of the publicly available, complete prokaryotic genomes. In addition to having all of the organisms on a single website, common data types across all genomes in the CMR make searches more meaningful, and cross genome analysis highlight differences and similarities between the genomes. CMR offers a wide variety of tools and resources, all of which are available off of our menu bar at the top of each page. Below is an explanation and link for each of these menu options. * Genome Tools: Find organism lists as well as summary information and analyses for selected genomes. * Searches: Search CMR for genes, genomes, sequence regions, and evidence. * Comparative Tools: Compare multiple genomes based on a variety of criteria, including sequence homology and gene attributes. SNP data is also found under this menu. * Lists: Select and download gene, evidence, and genomic element lists. * Downloads: Download gene sequences or attributes for CMR organisms, or go to our FTP site. * Carts: Select genome preferences from our Genome Cart or download your Gene Cart genes. The Omniome is the relational database underlying the CMR and it holds all of the annotation for each of the CMR genomes, including DNA sequences, proteins, RNA genes and many other types of features. Associated with each of these DNA features in the Omniome are the feature coordinates, nucleotide and protein sequences (where appropriate), and the DNA molecule and organism with which the feature is associated. Also available are evidence types associated with annotation such as HMMs, BLAST, InterPro, COG, and Prosite, as well as individual gene attributes. In addition, the database stores identifiers from other centers such as GenBank and SwissProt, as well as manually curated information on each genome or each DNA molecule including website links. Also stored in the Omniome are precomputed homology data, called All vs All searches, used throughout the CMR for comparative analysis.

Proper citation: JCVI CMR (RRID:SCR_005398) Copy   

•   Source: SciCrunch Registry

http://harvester.fzk.de/harvester/

Harvester is a Web-based tool that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. It is a meta search engine for gene and protein information. It searches 16 major databases and prediction servers and combines the results on pregenerated HTML pages. In this way Harvester can provide comprehensive gene-protein information from different servers in a convenient and fast manner. As full text meta search engine, similar to Google trade mark, Harvester allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. Sponsors: This work has been supported by the BMBF with grants 01GR0101 and 01KW0013.

Proper citation: Bioinformatic Harvester IV (beta) at Karlsruhe Institute of Technology (RRID:SCR_008017) Copy   

•   Source: SciCrunch Registry

http://www.ideal.force.cs.is.nagoya-u.ac.jp/IDEAL/

IDEAL, Intrinsically Disordered proteins with Extensive Annotations and Literature, is a collection of knowledge on experimentally verified intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). IDEAL contains manually curated annotations on IDPs in locations, structures, and functional sites such as protein binding regions and posttranslational modification sites together with references and structural domain assignments. Protean segment One of the unique phenomena seen in IDPs is so-called the coupled folding and binding, where a short flexible segment can bind to its binding partner with forming a specific structure to act as a molecular recognition element. IDEAL explicitly annotates these regions as protean segment (ProS) when unstructured and structured information are both available in the region. Access to the data All the entries are tabulated in the list and individual entries can be retrieved by using the search tool at the upper-right corner in this page. IDEAL also provides the BLAST search, which can find homologs in IDEAL. All the information in IDEAL can be downloaded in the XML file.

Proper citation: IDEAL - Intrinsically Disordered proteins with Extensive Annotations and Literature (RRID:SCR_006027) Copy   

•   Source: SciCrunch Registry

http://hdbase.org/cgi-bin/welcome.cgi

A community website for Huntington''s Disease (HD) research that currently contains Y2H and Mass spectrometry protein-protein interaction data centered around the HD protein (huntingtin) and information on therapeutic studies in mouse. Also available are raw Human and Mouse Affymetrix Microarray data. The protein interaction data is from several sources, including interactions curated from the literature by ISB staff, experimentally determined interactions produced by Bob Hughes and colleagues at Prolexys (currently password protected), and interactions reported in a recent publication by Goehler et al from Eric Wanker''s lab. Content areas that may be covered by the site include the following: * Therapeutic studies in mouse, primarily drug screens. * HD mouse models with a focus on timelines of disease progression. * Antibodies used in HD research. * Microarray gene expression studies. * Genes and proteins relevant to HD research. This includes HD itself, the growing list of proteins thought to interact directly or indirectly with huntingtin (Htt), and other genes and proteins implicated in the disease process. * Molecular pathways thought to be involved in the disease process. * Timelines of disease for Mouse models

Proper citation: HDBase (RRID:SCR_007132) Copy   

•   Source: SciCrunch Registry

http://specimencentral.com/

World's open biospecimen research database where biobanks and biomedical researchers meet to exchange human biospecimen needs and supply: whole blood, serum, plasma, solid tissue samples and more. The connection is accelerated so researchers save valuable time and money and tissue banks utilize inventory. The pace of specimen procurement remains unacceptably slow to the biomedical research community. Specimen Central is the foremost global resource to aid biomedical researchers in expediting their search for high quality human biospecimens, tissues, samples and specimens. They facilitate your search for blood, whole blood, buccal swab, DNA, RNA, protein, cell lines, plasma, serum, RBC, white cells, buffy coat, fluid, marrow, urine, stem cells, and solid tissue such as tumor, tumor and biopsy materials spanning all manner of common and rare pathologies and indications including Alzheimer's, basal cell carcinoma, bladder cancer, bone cancer, brain cancer, breast cancer, cerebrospinal fluid, amniotic fluid, colorectal cancer, colon cancer, hodgkins and non-hodgkins lymphoma, kidney/renal cancer, leukemia, liver cancer, lung cancer, melanoma, multiple sclerosis, myeloma neuroblastoma, neurodegenerative diseases, ovarian cancer, pancreatic cancer, prostate cancer, urinary cancer. This includes adult and pediatric indications. Specimen Central users specify a number of variables in their Specimen Requests, including preparation, preservation and handling requirements such as cryo-preserved, FFPE (Formalin-fixed paraffin-embedded), formalin, frozen, refrigerated, OCT, snap frozen, paraffin block, fresh, prospective, autopsy or cadaveric, etc. Many users require clinically annotated date associated with their specimens, as well as documentation of IRB or ethics committee approval and informed consents. For Researchers Most specimen databases require researchers to waste time and effort entering lengthy registrations and search queries that yield poor results, if anything. Specimen Central solves this problem by having tissue banks search for you. From years to months, months to weeks, and weeks to days, Specimen Central seeks to reduce delays and costs in the research & development life cycle by expediting connections between demand and supply. For Biobanks The capital costs of maintaining a biobank infrastructure are substantial and growing. Biobanks use Specimen Central as a marketing tool to augment their business development efforts. By routinely checking Specimen Central's Specimen Requests, biobanks can uncover market demand for their inventories and develop new connections and revenue streams to defray costs. Specimen Central supplements - not displaces - the efforts of your sales representatives, agents, brokers and commercial partners.

Proper citation: SpecimenCentral.com (RRID:SCR_003536) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Tools/

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.

Proper citation: Toolbox at the European Bioinformatics Institute (RRID:SCR_002872) Copy   

•   Source: SciCrunch Registry

https://web.uri.edu/riinbre/mic/

Core provides sequencing and bioinformatics support for INBRE and non-INBRE researchers. Provides data science services adjacent to traditional bioinformatics; access to computational and software resources for INBRE network institutions, particularly primarily undergraduate institutions; training for students and faculty in data science methods. Maintains professional network with other core and user facilities in Rhode Island and beyond to maximize resources available to our users.Utilizes novel technologies such as virtual/augmented reality for use in teaching and research.

Proper citation: Rhode Island INBRE Molecular Informatics Core Facility (RRID:SCR_017685) Copy   

•   Source: SciCrunch Registry

https://www.albany.edu/repr/

Resource offers range of mass spectrometry instrumentation, expertise in analysis of RNA, RNA modifications, and proteins involved in RNA metabolism/regulation, supports projects involving analysis of biomolecules, metabolites, and small synthetic molecules, provides consulting on experimental design, sample preparation and data interpretation, whole project development and grant writing contributions.

Proper citation: Albany University RNA Epitranscriptomics and Proteomics Resource Core Facility (RRID:SCR_017695) Copy   

•   Source: SciCrunch Registry