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http://geneatlas.roslin.ed.ac.uk

Database of associations between traits and variants using UK Biobank cohort. Searchable atlas of genetic associations. Assists researchers to query UK Biobank. Provides unbiased view of phenotype and genotype associations across of traits.

Proper citation: GeneATLAS (RRID:SCR_017577) Copy   

•   Source: SciCrunch Registry

https://github.com/tseemann/abricate

Software tool for mass screening of contigs for antimicrobial and virulence genes. Mass screening of contigs for antimicrobial resistance or virulence genes. It comes bundled with multiple databases: NCBI, CARD, ARG-ANNOT, Resfinder, MEGARES, EcOH, PlasmidFinder, Ecoli_VF and VFDB.

Proper citation: Abricate (RRID:SCR_021093) Copy   

•   Source: SciCrunch Registry

https://www.humancellatlas.org

Software tool as a catalog of comprehensive reference of human cells based on their stable properties, transient features, locations and abundances. Map to show the relationships among its elements. Open data international collaborative project involving diverse scientific communities to provide a framework for understanding cellular dysregulation in human disease.

Proper citation: Human Cell Atlas (RRID:SCR_016530) Copy   

•   Source: SciCrunch Registry

https://cm.jefferson.edu/rna22/

Software tool as a pattern based algorithm for detecting microRNA binding sites and their corresponding microRNA and mRNA complexes. Allows interactive exploration and visualization of miRNA target predictions. Permits link-out to external expression repositories and databases.

Proper citation: RNA22 (RRID:SCR_016507) Copy   

•   Source: SciCrunch Registry

https://pave.niaid.nih.gov

Collection of curated papillomavirus genomic sequences, accompanied by web-based sequence analysis tools. Database and web applications support the storage, annotation, analysis, and exchange of information.

Proper citation: PaVE (RRID:SCR_016599) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/cgi-bin/tess/tess

TESS is a web tool for predicting transcription factor binding sites in DNA sequences. It can identify binding sites using site or consensus strings and positional weight matrices from the TRANSFAC, JASPAR, IMD, and our CBIL-GibbsMat database. You can use TESS to search a few of your own sequences or for user-defined CRMs genome-wide near genes throughout genomes of interest. Search for CRMs Genome-wide: TESS now has the ability to search whole genomes for user defined CRMs. Try a search in the AnGEL CRM Searches section of the navigation bar.. You can search for combinations of consensus site sequences and/or PWMs from TRANSFAC or JASPAR. Search DNA for Binding Sites: TESS also lets you search through your own sequence for TFBS. You can include your own site or consensus strings and/or weight matrices in the search. Use the Combined Search under ''Site Searches'' in the menu or use the box for a quick search. TESS assigns a TESS job number to all sequence search jobs. The job results are stored on our server for a period of time specified in the search submit form. During this time you may recall the search results using the form on this page. TESS can also email results to you as a tab-delimited file suitable for loading into a spreadsheet program. Query for Transcription Factor Info: TESS also has data browsing and querying capabilities to help you learn about the factors that were predicted to bind to your sequence. Use the Query TRANSFAC or Query Matrices links above or use the search interface provided from the home page.

Proper citation: TESS: Transcription Element Search System (RRID:SCR_010739) Copy   

•   Source: SciCrunch Registry

https://genome.unc.edu/

Database for microarray data storage, retrieval, analysis, and visualization.

Proper citation: UNC Microarray Database (RRID:SCR_010979) Copy   

•   Source: SciCrunch Registry

http://www.ala.org.au/

Online repository of information about Australian plants, animals, and fungi. Development started in 2006. The Commonwealth Scientific and Industrial Research Organisation is organisation significantly involved in development of ALA.

Proper citation: Atlas of Living Australia (RRID:SCR_006467) Copy   

•   Source: SciCrunch Registry

http://arxiv.org/

Electronic archive and distribution server for research articles providing open access to more than 850,000 e-prints in Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance and Statistics. Users can retrieve papers via the web interface. Registered authors may use the web interface to submit their articles to arXiv. Authors can also update their submissions if they choose, though previous versions remain available. Listings of newly submitted articles in areas of interest are available via the web interface, via RSS feeds, and by subscription to automatic email alerts.

Proper citation: arXiv (RRID:SCR_006500) Copy   

•   Source: SciCrunch Registry

http://www.disgenet.org

Database and discovery platform containing publicly available collections of genes and variants associated to human diseases. Integrates data from curated repositories, GWAS catalogues, animal models and scientific literature.

Proper citation: DisGeNET (RRID:SCR_006178) Copy   

•   Source: SciCrunch Registry

http://www.snpedia.com/index.php/SNPedia

Wiki investigating human genetics including information about the effects of variations in DNA, citing peer-reviewed scientific publications. It is used by Promethease to analyze and help explain your DNA. It is based on a wiki model in order to foster communication about genetic variation and to allow interested community members to help it evolve to become ever more relevant. As the cost of genotyping (and especially of fully determining your own genomic sequence) continues to drop, we''''ll all want to know more - a lot more - about the meaning of these DNA variations and SNPedia will be here to help. SNPedia has been launched to help realize the potential of the Human Genome Project to connect to our daily lives and well-being. For more information see the Wikipedia page, http://en.wikipedia.org/wiki/SNPedia * Download URL: http://www.SNPedia.com/index.php/Bulk * Web Service URL: http://bots.SNPedia.com/api.php

Proper citation: SNPedia (RRID:SCR_006125) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/PRED-TMBB/

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.

Proper citation: PRED-TMBB (RRID:SCR_006190) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.intec.ugent.be/magic/

Web based interface for exploring and analyzing a comprehensive maize-specific cross-platform expression compendium. This compendium was constructed by collecting, homogenizing and formally annotating publicly available microarrays from Gene Expression Omnibus (GEO), and ArrayExpress.

Proper citation: Magic (RRID:SCR_006406) Copy   

•   Source: SciCrunch Registry

http://omia.angis.org.au/

Describes phenotype relationships with between breeds and genes. Catalogue/compendium of inherited disorders, other (single-locus) traits, and genes in 245 animal species. Database of genes, inherited disorders and traits in animal species other than human, mouse, and rats. Database contains textual information and references, as well as links to relevant records from OMIM, PubMed and Gene.

Proper citation: OMIA - Online Mendelian Inheritance in Animals (RRID:SCR_006436) Copy   

•   Source: SciCrunch Registry

http://scop.mrc-lmb.cam.ac.uk/scop/

The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. Protein domains in SCOP are hierarchically classified into families, superfamilies, folds and classes. The continual accumulation of sequence and structural data allows more rigorous analysis and provides important information for understanding the protein world and its evolutionary repertoire. SCOP participates in a project that aims to rationalize and integrate the data on proteins held in several sequence and structure databases. As part of this project, starting with release 1.63, we have initiated a refinement of the SCOP classification, which introduces a number of changes mostly at the levels below superfamily. The pending SCOP reclassification will be carried out gradually through a number of future releases. In addition to the expanded set of static links to external resources, available at the level of domain entries, we have started modernization of the interface capabilities of SCOP allowing more dynamic links with other databases.

Proper citation: SCOP: Structural Classification of Proteins (RRID:SCR_007039) Copy   

•   Source: SciCrunch Registry

https://myhits.sib.swiss/

Database devoted to protein domains. It is also a collection of tools for the investigation of the relationships between protein sequences and motifs described on them.

Proper citation: MyHits (RRID:SCR_006757) Copy   

•   Source: SciCrunch Registry

http://www.genome.ad.jp/aaindex/

AAindex is a database of numerical indices representing various physicochemical and biochemical properties of amino acids and pairs of amino acids. AAindex consists of three sections now: AAindex1 for the amino acid index of 20 numerical values, AAindex2 for the amino acid mutation matrix and AAindex3 for the statistical protein contact potentials. All data are derived from published literature. An amino acid index is a set of 20 numerical values representing any of the different physicochemical and biological properties of amino acids. The AAindex1 section of the Amino Acid Index Database is a collection of published indices together with the result of cluster analysis using the correlation coefficient as the distance between two indices. This section currently contains 544 indices. Another important feature of amino acids that can be represented numerically is the similarity between amino acids. Thus, a similarity matrix, also called a mutation matrix, is a set of 210 numerical values, 20 diagonal and 20x19/2 off-diagonal elements, used for sequence alignments and similarity searches. The AAindex2 section of the Amino Acid Index Database is a collection of published amino acid mutation matrices together with the result of cluster analysis. This section currently contains 94 matrices. In the release 9.0, we added a collection of published protein pairwise contact potentials to AAindex as AAindex3. This section currently contains 47 contact potential matrices. Sponsors: This work was supported by grants and resources from the Ministry of Education, Culture, Sports, Science and Technology, and the Japan Science and Technology Agency, and the Bioinformatics Center, Institute for Chemical Research, Kyoto University and the Super Computer System, Human Genome Center, Institute of Medical Science, University of Tokyo.

Proper citation: Amino Acid Index Database (RRID:SCR_007044) Copy   

•   Source: SciCrunch Registry

http://www.re3data.org/

Global registry of research data repositories from all academic disciplines that allows the easy identification of appropriate research data repositories, both for data producers and users. Information icons display principal attributes of a repository that can be used for multi-faceted searches. Repository operators can suggest their infrastructures to be listed via a simple application form. A repository is indexed when the minimum requirements are met, i.e. mode of access to the data and repository, as well as the terms of use.

Proper citation: re3data.org (RRID:SCR_006782) Copy   

•   Source: SciCrunch Registry

http://prodoric.tu-bs.de/

Database about gene regulation and gene expression in prokaryotes. It includes a manually curated and unique collection of transcription factor binding sites. A variety of bioinformatics tools for the prediction, analysis and visualization of regulons and gene reglulatory networks is included. The integrated approach provides information about molecular networks in prokaryotes with focus on pathogenic organisms. In detail this concerns: * transcriptional regulation (transcription factors and their DNA binding sites * signal transduction (two-component systems, phosphylation cascades) * protein interactions (complex formation, oligomerization) * biochemical pathways (chemical reactions) * other regulation events (e.g. codon usage, etc. ...) It aims to be a resource to model protein-host interactions and to be a suitable platform to analyze high-throughput data from proteomis and transcriptomics experiments (systems biology). Currently it mainly contains detailed information about operon and promoter structures including huge collections of transcription factor binding sites. If an appropriate number of regulatory binding sites is available, a position weight matrix (PWM) and a sequence logo is provided, which can be used to predict new binding sites. This data is collected manually by screening the original scientific literature. PRODORIC also handles protein-protein interactions and signal-transduction cascades that commonly occur in form of two-component systems in prokaryotes. Furthermore it contains metabolic network data imported from the KEGG database., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRODORIC (RRID:SCR_007074) Copy   

•   Source: SciCrunch Registry

http://arabidopsis.med.ohio-state.edu

An information resource of Arabidopsis promoter sequences, transcription factors and their target genes that contains three databases. *AtcisDB consists of approximately 33,000 upstream regions of annotated Arabidopsis genes (TAIR9 release) with a description of experimentally validated and predicted cis-regulatory elements. *AtTFDB contains information on approximately 1,770 transcription factors (TFs). These TFs are grouped into 50 families, based on the presence of conserved domains. *AtRegNet contains 11,355 direct interactions between TFs and target genes. They provide free download of Arabidopsis thaliana cis-regulatory database (AtcisDB) and transcription factor database (AtTFDB).

Proper citation: Arabidopsis Gene Regulatory Information Server (RRID:SCR_006928) Copy   

•   Source: SciCrunch Registry