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http://app.cgu.edu.tw/circlnc/

Web application for mapping functional networks of long or circular forms of non-coding RNAs. It supports the uploading and processing of user-defined NGS-based gene expression matrix data.

Proper citation: circlncRNAnet (RRID:SCR_015794) Copy   

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http://schizconnect.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 6,2026. Platform for mediation and integration of schizophrenia neuroimaging-related databases. It provides access to federated databases, novel mediation software, and large-scale data-sharing features.

Proper citation: SchizConnect (RRID:SCR_015766) Copy   

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https://sparc.science

SPARC data repository as of 2023 is an open data repository developed as part of the NIH SPARC initiative and has been used by SPARC funded investigator groups to curate and publish high quality datasets related to the autonomic nervous system. We are thrilled that as of August 2022, SPARC is accepting datasets from investigators that are not funded through the NIH SPARC program. The NIH's Common Fund Stimulating Peripheral Activity to Relieve Conditions (SPARC) program aims to transform our understanding of these nerve-organ interactions and ultimately advance neuromodulation field toward precise treatment of diseases and conditions for which conventional therapies fall short.

Proper citation: SPARC Portal (RRID:SCR_017041) Copy   

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https://depmap.org/portal/

Portal for identifying genetic and pharmacologic dependencies and biomarkers that predicts them by providing access to datasets, visualizations, and analysis tools that are being used by Cancer Dependency Map Project at Broad Institute. Project to systematically identify genes and small molecule dependencies and to determine markers that predict sensitivity. All data generated by DepMap Project are available to public under CC BY 4.0 license on quarterly basis and pre-publication.

Proper citation: Cancer Dependency Map Portal (RRID:SCR_017655) Copy   

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http://www.functionalnet.org/humannet/about.html

Database of human protein-encoding genes that is constructed by a modified Bayesian integration of 'omics' data from multiple organisms. Each data type is weighted according to how well it links genes that are known to function together in humans, and each interaction has an associated log-likelihood score (LLS) that measures the probability of an interaction representing a true functional linkage between two genes.

Proper citation: HumanNet (RRID:SCR_016146) Copy   

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http://www.lincsproject.org/

Project to create network based understanding of biology by cataloging changes in gene expression and other cellular processes when cells are exposed to genetic and environmental stressors. Program to develop therapies that might restore pathways and networks to their normal states. Has LINCS Data Coordination and Integration Center and six Data and Signature Generation Centers: Drug Toxicity Signature Generation Center, HMS LINCS Center, LINCS Center for Transcriptomics, LINCS Proteomic Characterization Center for Signaling and Epigenetics, MEP LINCS Center, and NeuroLINCS Center.

Proper citation: LINCS Project (RRID:SCR_016486) Copy   

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http://www.cs.cmu.edu/~jernst/stem/

The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database supporting GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Short Time-series Expression Miner (STEM) (RRID:SCR_005016) Copy   

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http://mgc.nci.nih.gov/

NIH initiative project to provide full-length open reading frame (FL-ORF) clones for human, mouse, and rat genes, cow. MGC cDNA clones were obtained by screening of cDNA libraries, by transcript-specific RT-PCR cloning, and by DNA synthesis of cDNA inserts. All MGC sequences are deposited in GenBank and clones can be purchased from distributors of IMAGE consortium. With conclusion of MGC project in March 2009, GenBank records of MGC sequences will be frozen, without further updates. Since definition of what constitutes full-length coding region for some of genes and transcripts for which they have MGC clones will likely change in future, users planning to order MGC clones will need to monitor for these changes. Users can make use of genome browsers and gene-specific databases, such as the UCSC Genome browser, NCBI's Map Viewer, and Entrez Gene, to view relevant regions of genome (browsers) or gene-related information (Entrez Gene).

Proper citation: Mammalian Gene Collection (RRID:SCR_007024) Copy   

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http://www.bumc.bu.edu/cardiovascularproteomics/cpctools/strap/

Software program that automatically annotates a protein list with information that helps in the meaningful interpretation of data from mass spectrometry and other techniques. It takes protein lists as input, in the form of plain text files, protXML files (usually from the TPP), or Dat files from MASCOT search results. From this, it generates protein annotation tables, and a variety of GO charts to aid individual and differential analysis of proteomics data. It downloads information from mainly the Uniprot and EBI QuickGO databases. STRAP requires Windows XP or higher with at least version 3.5 of the Microsoft .NET Framework installed. Platform: Windows compatible

Proper citation: STRAP (RRID:SCR_005675) Copy   

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http://eol.org/

Database that gathers, generates, and shares taxa, images, videos, and sounds to freely provide knowledge about life on earth to increase awareness and understanding of living nature. Free EOL memberships are ranked so members have greater authority and editorial abilities based on their level of expertise.

Proper citation: EOL - Encyclopedia of Life (RRID:SCR_005905) Copy   

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http://neurosynth.org

Platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. It''s a website wrapped around a set of open-source Python and JavaScript packages. Neurosynth lets you run crude but useful analyses of fMRI data on a very large scale. You can: * Interactively visualize the results of over 3,000 term-based meta-analyses * Select specific locations in the human brain and view associated terms * Browse through the nearly 10,000 studies in the database Their ultimate goal is to enable dynamic real-time analysis, so that you''ll be able to select foci, tables, or entire studies for analysis and run a full-blown meta-analysis without leaving your browser. You''ll also be able to do things like upload entirely new images and obtain probabilistic estimates of the cognitive states most likely to be associated with the image.

Proper citation: NeuroSynth (RRID:SCR_006798) Copy   

•   Source: SciCrunch Registry

http://hollywood.mit.edu/burgelab/rescue-ese/

Specific short oligonucleotide sequences that enhance pre-mRNA splicing when present in exons, termed exonic splicing enhancers (ESEs), play important roles in constitutive and alternative splicing (ESE References). A hybrid computational/experimental method, RESCUE-ESE, was recently developed for identifying sequences with ESE activity. In this approach, specific hexanucleotide sequences are identified as candidate ESEs on the basis that they have both significantly higher frequency of occurrence in exons than in introns and also significantly higher frequency in exons with weak (non-consensus) splice sites than in exons with strong (consensus) splice sites. Representative hexamers from ten different classes of candidate ESEs, together with 6 or 7 bases of flanking sequence context on each side, were introduced into a weak (poorly spliced) exon in a splicing reporter construct. These reporter minigenes were then transfected into cultured cells, where they are transcribed and spliced, and the relative level of inclusion of the test exon was assayed by quantitative (radio-labeled) RT-PCR. Point mutants of these sequences were also analyzed to confirm the precise motifs responsible for ESE activity. The RESCUE-ESE approach identified 238 hexamers as candidate ESEs using a large database of human genes of known exon-intron structure containing over 30,000 nonredudant exons. In more recent analyses by Yeo et al., the RESCUE-ESE approach was utilized to predict hexamers as candidate ESEs in other vertebrate genes, namely, Fugu rubipes, Zebrafish and Mouse. This allows the identification of motifs that are conserved in vertebrates. This web server allows a sequence to be checked for presence of these candidate ESE hexamers.

Proper citation: RESCUE-ESE (RRID:SCR_008496) Copy   

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https://compumedicsneuroscan.com/products/by-name/curry/

Processing software for multimodal neuroimaging centered on combining functional data such as EEG and MEG with imaging data from MRI and CT to optimize source reconstruction. They are now combining Curry's strength with the acquisition and signal processing features of the SCAN software for a comprehensive EEG acquisition, data analysis, source localization and source imaging package.

Proper citation: CURRY (RRID:SCR_009546) Copy   

•   Source: SciCrunch Registry

http://www.yeastract.com

A curated repository of more than 206000 regulatory associations between transcription factors (TF) and target genes in Saccharomyces cerevisiae, based on more than 1300 bibliographic references. It also includes the description of 326 specific DNA binding sites shared among 113 characterized TFs. Further information about each Yeast gene has been extracted from the Saccharomyces Genome Database (SGD). For each gene the associated Gene Ontology (GO) terms and their hierarchy in GO was obtained from the GO consortium. Currently, YEASTRACT maintains a total of 7130 terms from GO. The nucleotide sequences of the promoter and coding regions for Yeast genes were obtained from Regulatory Sequence Analysis Tools (RSAT). All the information in YEASTRACT is updated regularly to match the latest data from SGD, GO consortium, RSA Tools and recent literature on yeast regulatory networks. YEASTRACT includes DISCOVERER, a set of tools that can be used to identify complex motifs found to be over-represented in the promoter regions of co-regulated genes. DISCOVERER is based on the MUSA algorithm. These algorithms take as input a list of genes and identify over-represented motifs, which can then be compared with transcription factor binding sites described in the YEASTRACT database.

Proper citation: Yeast Search for Transcriptional Regulators And Consensus Tracking (RRID:SCR_006076) Copy   

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http://operons.ibt.unam.mx/OperonPredictor/

The Prokaryotic Operon DataBase (ProOpDB) constitutes one of the most precise and complete repository of operon predictions in our days. Using our novel and highly accurate operon algorithm, we have predicted the operon structures of more than 1,200 prokaryotic genomes. ProOpDB offers diverse alternatives by which a set of operon predictions can be retrieved including: i) organism name, ii) metabolic pathways, as defined by the KEGG database, iii) gene orthology, as defined by the COG database, iv) conserved protein motifs, as defined by the Pfam database, v) reference gene, vi) reference operon, among others. In order to limit the operon output to non-redundant organisms, ProOpDB offers an efficient protocol to select the more representative organisms based on a precompiled phylogenetic distances matrix. In addition, the ProOpDB operon predictions are used directly as the input data of our Gene Context Tool (GeConT) to visualize their genomic context and retrieve the sequence of their corresponding 5�� regulatory regions, as well as the nucleotide or amino acid sequences of their genes. The prediction algorithm The algorithm is a multilayer perceptron neural network (MLP) classifier, that used as input the intergenic distances of contiguous genes and the functional relationship scores of the STRING database between the different groups of orthologous proteins, as defined in the COG database. Nevertheless, the operon prediction of our method is not restricted to only those genes with a COG assignation, since we successfully defined new groups of orthologous genes and obtained, by extrapolation, a set of equivalent STRING-like scores based on conserved gene pairs on different genomes. Since the STRING functional relationships scores are determined in an un-bias manner and efficiently integrates a large amount of information coming from different sources and kind of evidences, the prediction made by our MLP are considerably less influenced by the bias imposed in the training procedure using one specific organism.

Proper citation: ProOpDB (RRID:SCR_006111) Copy   

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http://malacards.org

An integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. The database contains 17,705 diseases, consolidated from 28 sources.

Proper citation: MalaCards (RRID:SCR_005817) Copy   

•   Source: SciCrunch Registry

http://wfleabase.org/

wFleaBase provides gene and genomic information for species of the genus Daphnia - commonly known as the water flea. It contains the genome of Daphnia pulex and other species, including bulk data files, and all gene pages, plus genomics tools including microsatellites, cDNA, Cosmid and BAC libraries, GSS and ESTs, and microarrays. It also contains maps of the Daphnia genome, and genome annotation tools. The freshwater crustacean Daphnia is a model system for ecology, evolution and the environmental sciences. The rapidly growing genomic data for this organism is stimulating interdisciplinary research to understand the complex interplay between genome structure, gene expression, individual fitness, and population-level responses to chemical contaminants and environmental change.wFleaBase includes data from all species of the genus, yet the primary species are D. pulex and D. magna, because of the broad set of genomic tools that have already been developed for these animals. A complete sequence for Daphnia pulex is now available at this site. Please observe this Data release policy. The data is a first characterization of the crustacean genome, which was made possible by the U.S. Department of Energy (DOE) Joint Genome Institute (JGI) in collaboration with the Daphnia Genomics Consortium (DGC) whose members were funded by the National Science Foundation. Category: Genomics Databases (non-vertebrate) Subcategory: Invertebrate genome databases

Proper citation: wFleaBase (RRID:SCR_006018) Copy   

•   Source: SciCrunch Registry

http://tbdb.org

Database providing integrated access to genome sequence, expression data and literature curation for Tuberculosis (TB) that houses genome assemblies for numerous strains of Mycobacterium tuberculosis (MTB) as well assemblies for over 20 strains related to MTB and useful for comparative analysis. TBDB stores pre- and post-publication gene-expression data from M. tuberculosis and its close relatives, including over 3000 MTB microarrays, 95 RT-PCR datasets, 2700 microarrays for human and mouse TB related experiments, and 260 arrays for Streptomyces coelicolor. (July 2010) To enable wide use of these data, TBDB provides a suite of tools for searching, browsing, analyzing, and downloading the data.

Proper citation: Tuberculosis Database (RRID:SCR_006619) Copy   

•   Source: SciCrunch Registry

http://iae.fafu.edu.cn/DBM/

Database storing and integrating genomic data of diamondback moth (DBM), Plutella xylostella (L.). It provides comprehensive search tools and downloadable datasets for scientists to study comparative genomics, biological interpretation and gene annotation of this insect pest. DBM-DB contains assembled transcriptome datasets from multiple DBM strains and developmental stages, and the annotated genome of P. xylostella (version 2). They have also integrated publically available ESTs from NCBI and a putative gene set from a second DBM genome (KONAGbase) to enable users to compare different gene models. DBM-DB was developed with the capacity to incorporate future data resources, and will serve as a long-term and open-access database that can be conveniently used for research on the biology, distribution and evolution of DBM. This resource aims to help reduce the impact DBM has on agriculture using genomic and molecular tools.

Proper citation: DBM-DB (RRID:SCR_006258) Copy   

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http://bard.nih.gov/

Database that allows scientists without specialized training to effectively utilize Molecular Libraries Program (MLP) data. It allows the research community to utilize and develop new chemical probes to explore biological functions by building a central, permanently accessible link to all aspects of chemical biology data and analyses. The project is split into two basic segments, the first segment delivering functionality for a data dictionary, as well as assay protocol and data entry tools. The second builds a data warehouse for analysis and visualization, accessible through a public RESTful API. They will initially deploy two clients that will use this API - a web-based interface and a desktop application. Advanced access to data and the platforms will also be available to support plug-in development and the repackaging of data by others. Initially the project will focus on small molecule assays. Features: * allow scientists to annotate assay data using a common, shared language * provide facile access to data, integrating existing chemical biology and computational resources * enable meaningful analysis and interpretation of discovery data by the research community * support hypothesis generation for iterative probe- and drug-discovery projects * inform the entire small molecule discovery and development process, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BARD (RRID:SCR_006283) Copy   

•   Source: SciCrunch Registry