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http://degradome.uniovi.es/diseases.html

This resource has cataloged a total of 80 human hereditary diseases caused by mutations in protease-coding genes, which implies that more than 10% of the human protease genes are involved in human pathologies. They are classified in three groups: loss of function, gain of function, and an heterogeneous group including non-protease homologs (np), putative proteases, and hedgehog proteins with only autoprocessing activity. Type of inheritance is indicated by R (recessive) or D (dominant).

Proper citation: Human Hereditary Diseases of Proteolysis (RRID:SCR_008344) Copy   

•   Source: SciCrunch Registry

http://portal.ncibi.org/gateway/gin.html

GIN-IE is a high precision system for extracting protein/gene interactions, interaction cue words, and directionality from the literature. Syntax-aware inferences about the roles of the entities are made by using the syntactic and dependency parse tree structures of the sentences. Negation and speculation are frequently occurring language phenomena that modify the factuality of the information contained in text. GIN-IE detects and distinguishes interactions that are extracted from negated or speculative sentences. GIN-IE has been integrated with the NCIBI PubMed daily update and processing pipeline. The extracted interactions are accessible through MimiWeb.

Proper citation: Gene Interaction Extraction from the Literature (RRID:SCR_008660) Copy   

•   Source: SciCrunch Registry

http://pslid.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.

Annotated database of fluorescence microscope images depicting subcellular location proteins with two interfaces: a text and image content search interface, and a graphical interface for exploring location patterns grouped into Subcellular Location Trees. The annotations in PSLID provide a description of sample preparation and fluorescence microscope imaging.

Proper citation: Protein Subcellular Location Image Database (RRID:SCR_008663) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://www.ingenuity.com/products/pathways_analysis.html

A web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.

Proper citation: Ingenuity Pathway Analysis (RRID:SCR_008653) Copy   

•   Source: SciCrunch Registry

http://www.quertle.info/v2/

Quertle is a biomedical search engine focused on delivering informative results to biomedical researchers using advanced linguistic technologies, along with an in-depth understanding of the biomedical field. Quertle''s friendly interface makes it simple to search and refine results. Using advanced semantics, Quertle finds quality results, not just long lists. And it hods: all of PubMed, a growing number of full-text documents, news, and more. Features: :- Find Relationships, not Just :- Focus on Core Concepts: Since Quertle searches for Relationships, all the terms in your query must be found together in a meaningful way. Thus, Quertle immediately gives you results with more relevance. :- Unleash the Strength of Power Terms: Use Power Terms to search for categories of objects. For instance, you can use Protein to search for any protein, rather than the occurrence of the term, protein. View all Power Terms. :- Search Full-text Documents: The Quertle search engine has been optimized to search full-text documents, including the Material and Methods section (but not the Bibliography). :- Use Real Biology & Chemistry Terms: Quertle recognizes capital TWIST as the transcription factor (not the verb), and capital NO as nitrous oxide(not a negative). So, use proper capitalization in your query, and you won''t be lost in a sea of irrelevant results. :- Look for the Quertle Difference on the Results Page : More relevant results : Easy filtering and breadcrumb tracking : Automatic identification of key concepts : Single-click access to PDFs of full-text documents :Keyword: Biomedical, Search engine, Database, Researcher, Linguistic, Technology, Semantic, Relationship, Protein, Biology, Chemistry, :

Proper citation: Quertle: Relationship-Driven Biomedical Search (RRID:SCR_008676) Copy   

•   Source: SciCrunch Registry

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

Service providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.

Proper citation: InterPro (RRID:SCR_006695) Copy   

•   Source: SciCrunch Registry

http://aps.unmc.edu/AP/main.php

Database and data analysis system dedicated to glossary, nomenclature, classification, information search, prediction, design, and statistics of Antimicrobial peptides and beyond. The peptide data stored in the APD were gleaned from the literature (PubMed, PDB, Google, and Swiss-Prot) manually in the past several years. Peptides will be registered into this database if: # they are from natural sources (bacteria, protozoa, fungi, plants, and animals); # their antimicrobial activities are demonstrated (MIC

Proper citation: APD (RRID:SCR_006606) Copy   

•   Source: SciCrunch Registry

http://cellfinder.de/

Database of mapped validated gene and protein expression, phenotype and images related to cell types. The data allow characterization and comparison of cell types and can be browsed by using the body browser and by searching for cells or genes. All cells are related to more complex systems such as tissues, organs and organisms and arranged according to their position in development. CellFinder provides long-term data storage for validated and curated primary research data and provides additional expert-validation through relevant information extracted from text. Operated under the Open Source/Access model, community and scientific networking applications will allow users to store and retrieve their data and to explore cells and their interactions on singular and complex resolution levels. The involvement of stem cell registries and banks will allow direct access to selected cells. The set up the stem cell data repository will involve three lines of action: * the acquisition of scientific data and contents * the standardized description of this data, its organization with the help of ontologies and technical implementation * the integration of existing sources/logistics and to ensure sustainable long-term operation

Proper citation: CellFinder (RRID:SCR_006598) Copy   

•   Source: SciCrunch Registry

http://www.peptideresource.com/

A guide to peptide-related research and products including custom peptide suppliers, peptide synthesis reagent suppliers that provide resins, coupling reagents, and protected amino acids as well as biologically active peptides and substrates, peptide synthesizers for solution or solid phase peptide synthesis, peptide sequence analysis services, software to calculate the chemical or biochemical properties of peptides, including the prediction of antigenicity or difficult-to-synthesize sequences. There is an additional section on Proteomics Tools for the identification of proteins from peptide sequences determined by mass spectrometry. The site also contains a set of links to educational materials about peptide related research topics.

Proper citation: Peptide Resource Page: Your Complete Guide to Peptide Research and Suppliers (RRID:SCR_006676) Copy   

•   Source: SciCrunch Registry

http://www.mechanobio.info/

Portal that deals with the process of mechanotransduction, providing in-depth, regularly updated reviews on the mechanics of cellular and molecular function. Each review is written by scientists and subsequently peer reviewed by experts in the field to ensure the content is accurate, reliable and up to date. Each review emphasizes the functional and mechanical aspects of a process, rather than the genetic aspects, with the aim of making this resource accessible to a wider audience. MBInfo is an ideal resource for scientists working in alternative fields, individuals working in industries where products are based on biological principles or students seeking a reliable introduction to a given cellular process. Each topic is written in a pyramid structure. The top of the pyramid is represented by an overview page, providing a basic description of a given function or process. These pages target a broad spectrum of readers and assume only a basic understanding of biology. Further down the pyramid, the reader will encounter the steps involved in the process described and functional modules that address specific mechanical aspects. These pages outline the protein complexes involved and the mechanisms by which they achieve the given process or function. These pages assume the readers have a more in-depth knowledge of scientific terms and principles. For every topic, a series of graphics and/or animations are available. These supplement the reviews, clarify information and guide the reader through complex processes pictorially. This makes MBInfo an ideal teaching resource, whether in the classroom or for clients trying to understand your product. All images and text are copyright protected and are for personal use only. Current Topics include: * Cellular Structures in Mechanosensing and Cell Motility * Methods in the Study of Mechanobiology * Nuclear Mechanotransduction Almost 100 stand alone Glossary Terms are now available. These include short definitions or summaries of proteins and processes that relate to broader topics discussed within the site. Browse an extensive range of figures, tables and videos in our resources section. New quizzes and other interactive content can also be found.

Proper citation: MBInfo (RRID:SCR_006768) Copy   

•   Source: SciCrunch Registry

http://bar.utoronto.ca/welcome.htm

Web-based tools for working with functional genomics and other data, including Gene Expression and Protein Tools, Molecular Markers and Mapping Tools, and Other Genomic Tools. Most are designed with the plant (mainly Arabidopsis) researcher in mind, but a couple of them can be useful to the wider research community, e.g. Mouse eFP Browser or BlastDigester. The associated paper for most tools is available.

Proper citation: BAR (RRID:SCR_006748) Copy   

•   Source: SciCrunch Registry

http://genome.ucsc.edu/ENCODE

Encyclopedia of DNA elements consisting of list of functional elements in human genome, including elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Enables scientific and medical communities to interpret role of human genome in biology and disease. Provides identification of common cell types to facilitate integrative analysis and new experimental technologies based on high-throughput sequencing. Genome Browser containing ENCODE and Epigenomics Roadmap data. Data are available for entire human genome.

Proper citation: ENCODE (RRID:SCR_006793) Copy   

•   Source: SciCrunch Registry

http://weizhong-lab.ucsd.edu/cd-hit-otu/

Data analysis service and software program that perform Operantional Taxonomic Units (OTUs) finding. It uses a three-step clustering for identifying OTUs. The first-step clustering is raw read filtering and trimming. The second step is error-free reads picking.. At the last step, OTU clustering is done at different distanct cutoffs (0.01, 0.02, 0.03... 0.12).

Proper citation: CD-HIT-OTU (RRID:SCR_006983) Copy   

•   Source: SciCrunch Registry

http://ailun.stanford.edu/

Re-annotated gene expression / proteomics data from GEO by relating all probe IDs to Entrez Gene IDs once every three months, enabling you to find data from GEO, and compare them from different platforms and species. Platform Annotations adds the latest annotations to any uploaded probe / gene ID list file. Platform Comparison compares any two platforms to find corresponding probes mapping to the same gene. Cross-species mapping maps platform annotations to other species. Gene Search finds deposited platforms and samples in GEO that contain a list of genes. GPL ID Search finds the GPL ID (GEO platform ID) for your array. You can also download the latest annotations files for all arrays and their comprehensive universal gene identifier table, which relates all types of gene / protein / clone identifiers to Entrez Gene IDs for all species. Note: The database was last updated on 4/30/2011. They have successfully mapped 54932732 individual probes from 385099 GEO samples measuring 3519 GEO platforms across 217 species.

Proper citation: Array Information Library Universal Navigator (RRID:SCR_006967) Copy   

•   Source: SciCrunch Registry

http://goblet.molgen.mpg.de/cgi-bin/goblet2008/goblet.cgi

Tool that performs annotation based on GO and pathway terms for anonymous cDNA or protein sequences. It uses the species independent GO structure and vocabulary together with a series of protein databases collected from various sites, to perform a detailed GO annotation by sequence similarity searches. The sensitivity and the reference protein sets can be selected by the user. GOblet runs automatically and is available as a public service on our web server. GOblet expects query sequences to be in FASTA-Format (with header-lines). Protein and nucleotide sequences are accepted. Total size of all sequences submitted per request should not be larger than 50kb currently. For security reasons: Larger post's will be rejected. Due to limited capacities the queries may be processed in batches depending on the server load. The output of the BLAST job is filtered automatically and the relevant hits are displayed. In addition, the respective GO-terms are shown together with the complete GO-hierarchy of parent terms., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GOblet (RRID:SCR_006998) Copy   

•   Source: SciCrunch Registry

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

Open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions. Direct user submissions of molecular interaction data are encouraged, which may be deposited prior to publication in a peer-reviewed journal. The IntAct Database contains (Jun. 2014): * 447368 Interactions * 33021 experiments * 12698 publications * 82745 Interactors IntAct provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows "zooming in" on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available.

Proper citation: IntAct (RRID:SCR_006944) Copy   

•   Source: SciCrunch Registry

http://pga.mgh.harvard.edu/primerbank/

Database of human and mouse primer pairs for gene expression analysis by polymerase chain reaction (PCR) and quantitative PCR (qPCR). A total of 306,800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as T(m), location on the transcript and amplicon size. For each gene, at least one primer pair has been designed and in many cases alternative primer pairs exist. Primers have been designed to work under the same PCR conditions, thus facilitating high-throughput QPCR. All primers in PrimerBank were carefully designed to ensure gene specificity. All experimental validation data for mouse primers are available from PrimerBank. You can submit your primers. They will be added to the database once they are properly QCd.

Proper citation: PrimerBank (RRID:SCR_006898) Copy   

•   Source: SciCrunch Registry

http://yetfasco.ccbr.utoronto.ca/

Collection of all available transcription factor (TF) specificities for the yeast Saccharomyces cerevisiae in Position Frequency Matrix (PFM) or Position Weight Matrix (PWM) formats. The specificities are evaluated for quality using several metrics. With this website, you can scan sequences with the motifs to find where potential binding sites lie, inspect precomputed genome-wide binding sites, find which TFs have similar motifs to one you have found, and download the collection of motifs. Submissions are welcome.

Proper citation: YeTFaSCo (RRID:SCR_006893) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.albany.edu/~dmaps

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016. DMAPS database contains pre-computed multiple structure alignments for protein chains in the Protein Data Bank (PDB). Automated structure alignments have been generated for classified protein families using CE-MC algorithm. Alignments have been built only for those families with at least three members. Currently, multiple structure alignments are available for 3050 SCOP-, 3087 CATH-, 664 ENZYME- and 1707 CE-based families. Users will be able to retrieve multiple alignments for a given PDB chain classified by one of these criteria.

Proper citation: DMAPS - A Database of Multiple Alignments for Protein Structures (RRID:SCR_007140) Copy   

•   Source: SciCrunch Registry

http://www.biomanta.org/

This project encompasses development of novel biological network analysis methods and infrastructure for querying biological data in a semantically-enabled format, and aims to create a semantic interactome model. Research within the BioMANTA project will focus on computational modelling and analysis, primarily using Semantic Web technologies and Machine Learning methods, of large-scale protein-protein interaction and compound activity networks across a wide variety of species. A range of information such as kinetic activity, tissue expression, and subcellular localization and disease state attributes will be included in the resulting data model. Protein interactions are a fundamental component of biological processes. Many proteins are functional only in multimeric complexes, or require interaction partners to achieve their correct localisation or function. For this reason, the study of protein-protein interaction (PPI) networks has become an area of growing interest in computational biology. Through the use of Semantic Web technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL), interaction data is modelled to create a knowledge representation in which meaning is vested in the ontology rather than instances of data. Stochastic and computational intelligence methods are applied to this data to infer high coverage networks. Semantic inferencing is used to infer previously unknown and meaningful pathways. Major project components: - The BioMANTA Ontology:- An OWL DL ontology incorporating the PSI-MI Ontology, the NCBI Taxonomy, and elements of BioPax ontology and Gene Ontology (describing subcellular localisation). This allows us to re-use existing ontologies, thereby reducing overheads associated with knowledge acquisition in the ontology development process. We are able to integrate existing public data that contain annotation in these formats. - Data conversion & semantic protein integration:- A set of software components that convert protein-protein databases (DIP, MPact, IntAct, etc.) from PSI-MI XML to RDF compliant with the BioMANTA ontology. These software allow us to make these protein-protein interaction datasets (and more generally, any PSI-MI XML data) semantically available for querying and inference within BioMANTA. - A RDF triple store based on RDF Molecules and the MapReduce architecture:- A proof-of-concept RDF triple store using RDF molecules and Hadoop scale-out architectures. Regular RDF graphs are deconstructed into RDF molecules, which are distributed over distributed compute nodes in the MapReduce architecture, and are subsequently combined to form equivalent RDF graphs. Such an approach makes the distributed SPARQL querying and reasoning on RDF triple stores possible. - A quantitative framework to integrate networks extracted from independent data sources (gene expression, subcellular localization, and ortholog mapping):- The model is multi-layer, with a first layer based on Decision Trees where each Decision tree is built on each dataset independently. The tree nodes are cut using Shannon''s entropy (mutual information); the decision of these independent trees is integrated using logistic regression, and the parameters are optimised using maximum likelihood. Sponsors: This resource is supported by the Pfizer Global Research and Development, the Institute for Molecular Bioscience (IMB), and the University of Queensland, Australia.

Proper citation: BioMANTA (RRID:SCR_007177) Copy   

•   Source: SciCrunch Registry