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https://mendel.imp.ac.at/gpi/gpi_server.html

Prediction tool locating potential GPI-modification sites in precursor sequences applied for large-scale protein sequence database searches. The composite prediction function (with separate parametrization for metazoan and protozoan proteins) consists of terms evaluating both amino acid type preferences at sequence positions near a supposed omega-site as well as the concordance with general physical properties encoded in multi-residue correlation within the motif sequence. The latter terms are especially successful in rejecting non-appropriate sequences from consideration. The algorithm has been validated with a self-consistency and two jack-knife tests for the learning set of fully annotated sequences from the SWISS-PROT database as well as with a newly created database big-Pi (more than 300 GPI-motif mutations extracted from original literature sources). The accuracy of predicting the effect of mutations in the GPI sequence motif was above 83 %.

Proper citation: big-PI Predictor (RRID:SCR_001599) Copy   

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http://babelomics.bioinfo.cipf.es

An integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling. Version 4 of Babelomics integrates primary (normalization, calls, etc.) and secondary (signatures, predictors, associations, TDTs, clustering, etc.) analysis tools within an environment that allows relating genomic data and/or interpreting them by means of different functional enrichment or gene set methods. Such interpretation is made not only using functional definitions (GO, KEGG, Biocarta, etc.) but also regulatory information (from Transfac, Jaspar, etc.) and other levels of regulation such as miRNA-mediated interference, protein-protein interactions, text-mining module definitions and the possibility of producing de novo annotations through the Blast2GO system . Babelomics has been extensively re-engineered and now it includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. In this release GEPAS and Babelomics have integrated into a unique web application with many new features and improvements: * Data input: import and quality control for the most common microarray formats * Normalization and base calling: for the most common expression, tiling and SNP microarrays (Affymetrix and Agilent). * Transcriptomics: diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and time-series analysis. * Genotyping: stratification analysis, association, TDT. * Functional profiling: functional enrichment and gene set enrichment analysis with functional terms (GO, KEGG, Biocarta, etc.), regulatory (Transfac, Jaspar, miRNAs, etc.), text-mining, derived bioentities, protein-protein interaction analysis. * Integrative analysis: Different variables can be related to each other (e.g. gene expression to gnomic copy number) and the results subjected to functional analysis. Platform: Online tool

Proper citation: Babelomics (RRID:SCR_002969) Copy   

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http://diyhpl.us/~bryan/irc/protocol-online/protocol-cache/TFSEARCH.html

The TFSEARCH searches highly correlated sequence fragments against TFMATRIX transcription factor binding site profile database in the "TRANSFAC" databases developed at GBF-Braunschweig, Germany. The TFSEARCH program was written by Yutaka Akiyama (Kyoto University, currently at RWCP) in 1995.

Proper citation: TFSEARCH: Searching Transcription Factor Binding Sites (RRID:SCR_004262) Copy   

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http://spot.cgsmd.isi.edu

A web-based tool for using biological databases to prioritize single nucleotide polymorphisms (SNPs) after a genome-wide association study (GWAS). The site allows users to upload a list of SNPs and GWAS P-values and returns a prioritized list of SNPs using the GIN method. Users can specify candidate genes or genomic regions with custom levels of prioritization. The results can be downloaded or viewed in the browser where users can interactively explore the details of each SNP, including graphical representations of the genomic information network (GIN) method. For investigators interested in incorporating biological databases into a post-GWAS SNP selection strategy, the SPOT web tool is an easily implemented and flexible solution.

Proper citation: SPOT - Biological prioritization after a SNP association study (RRID:SCR_005193) Copy   

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https://www.schrodinger.com/Phase/

Pharmacophore modeling software to create 3D structure activity relationships, screen databases, and generate hits through establishing a chemical space occupied by active ligands. Used in drug design.

Proper citation: Phase (RRID:SCR_014884) Copy   

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http://funspec.med.utoronto.ca/

FunSpec is a web-based tool for statistical evaluation of groups of genes and proteins (e.g. co-regulated genes, protein complexes, genetic interactors) with respect to existing annotations, including GO terms. FunSpec (an acronym for Functional Specification) inputs a list of yeast gene names, and outputs a summary of functional classes, cellular localizations, protein complexes, etc. that are enriched in the list. The classes and categories evaluated were downloaded from the MIPS Database and the GO Database . In addition, many published datasets have been compiled to evaluate enrichment against. Hypertext links to the publications are given. The p-values, calculated using the hypergeometric distribution, represent the probability that the intersection of given list with any given functional category occurs by chance. The Bonferroni-correction divides the p-value threshold, that would be deemed significant for an individual test, by the number of tests conducted and thus accounts for spurious significance due to multiple testing over the categories of a database. After the Bonferroni correction, only those categories are displayed for which the chance probability of enrichment is lower than: p-value/#CD where #CD is the number of categories in the selected database. Without the Bonferroni Correction, all categories are displayed for which the same probability of enrichment is lower than: p-value threshold in an individual test Note that many genes are contained in many categories, especially in the MIPS database (which are hierarchical) and that this can create biases for which FunSpec currently makes no compensation. Also the databases are treated as independent from one another, which is really not the case, and each is searched seperately, which may not be optimal for statistical calculations. Nonetheless, we find it useful for sifting through the results of clustering analysis, TAP pulldowns, etc. Platform: Online tool

Proper citation: FunSpec (RRID:SCR_006952) Copy   

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http://vcell.org/

V-Cell is a remote user modeling and simulation environment utilizing Java''s Remote Method Invocation (RMI). The biologically oriented user interface allows experimentalists to create models, define cellular geometry, specify simulations and analyze the simulation results. The results are run and stored on a remote server and can be reviewed in the software and/or exported in a variety of popular formats. The design of the biological to mathematical mapping allows for separate use of biological and math components, and includes automatic mathematical simplification using pseudo-steady approximations and mass conservation relationships. This allows for direct specification of mathematical problems, performing simulations and analysis on those systems. The stand alone mathematics user interface is also a powerful tool for modeling reaction-diffusion systems. A transparent general purpose solver is used to translate the initial biological description into a set of concise mathematical problems. The solver is transparent to the average user, but is accessible to the theorist as the Math Editor component. The software is composed of three main components: 1. The modeling framework represents the physiological models of the Virtual Cell and allows for persistence and database support. 2. The mathematics framework transparently solves an important class of mathematical problems encountered in the cellular modeling. 3. The WWW accessible graphical user interface provides access to the technology mentioned above. The user interface has been developed using Java 2 Applets.

Proper citation: Virtual Cell at the National Resource for Cell Analysis and Modeling (RRID:SCR_007421) Copy   

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http://fmri.wfubmc.edu/software/PickAtlas

A software toolbox that provides a method for generating Region of Interest (ROI) masks based on the Talairach Daemon database. The atlases include Brodmann area, Lobar, Hemisphere, Anatomic Label (gyral anatomy), and Tissue type. The atlases have been extended to the vertex in MNI space, and corrected for the precentral gyrus anomaly. Additional atlases (including non-human atlases) can be added without difficulty., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: WFU PickAtlas (RRID:SCR_007378) Copy   

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http://carta.anthropogeny.org/moca/about

The Museum of Comparative Anthropogeny (MOCA) is a collection of comparative information regarding humans and our closest evolutionary cousins (chimpanzees, bonobos, gorillas and orangutans i.e, great apes), with an emphasis on uniquely human features. MOCA is organized by Domains, each grouping Topics by areas of interest and scientific discipline. Each topic entry will eventually cover existing information about a particular difference (alleged or documented) between humans and non-human hominids. Comparisons of these non-human hominids with humans are difficult, as so little is known about their phenotypic features (phenomes), in contrast to humans. Ethical, fiscal and practical issues also limit collection of further information about great apes. MOCA attempts to collect existing information about human-specific differences from great apes, currently scattered in the literature. Having such information in one location could lead to new insights and multi-disciplinary interactions, and to ethically-sound studies to explain differences, and uniquely human specializations. MOCA is not targeted at experts in specific disciplines, but rather aims to communicate basic information to a broad audience of scientists from many backgrounds, and to the interested lay public. MOCA includes not only aspects wherein there are known or apparent differences between humans and great apes, but additionally, topics for which popular wisdom about claimed or assumed differences is not entirely correct. It is for all these reasons that MOCA is called a Museum, and not an Encyclopedia or Database.

Proper citation: MOCA (RRID:SCR_010638) Copy   

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http://www.census.gov/did/www/nlms/

A database based on a random sample of the noninstitutionalized population of the United States, developed for the purpose of studying the effects of demographic and socio-economic characteristics on differentials in mortality rates. It consists of data from 26 U.S. Current Population Surveys (CPS) cohorts, annual Social and Economic Supplements, and the 1980 Census cohort, combined with death certificate information to identify mortality status and cause of death covering the time interval, 1979 to 1998. The Current Population Surveys are March Supplements selected from the time period from March 1973 to March 1998. The NLMS routinely links geographical and demographic information from Census Bureau surveys and censuses to the NLMS database, and other available sources upon request. The Census Bureau and CMS have approved the linkage protocol and data acquisition is currently underway. The plan for the NLMS is to link information on mortality to the NLMS every two years from 1998 through 2006 with research on the resulting database to continue, at least, through 2009. The NLMS will continue to incorporate data from the yearly Annual Social and Economic Supplement into the study as the data become available. Based on the expected size of the Annual Social and Economic Supplements to be conducted, the expected number of deaths to be added to the NLMS through the updating process will increase the mortality content of the study to nearly 500,000 cases out of a total number of approximately 3.3 million records. This effort would also include expanding the NLMS population base by incorporating new March Supplement Current Population Survey data into the study as they become available. Linkages to the SEER and CMS datasets are also available. Data Availability: Due to the confidential nature of the data used in the NLMS, the public use dataset consists of a reduced number of CPS cohorts with a fixed follow-up period of five years. NIA does not make the data available directly. Research access to the entire NLMS database can be obtained through the NIA program contact listed. Interested investigators should email the NIA contact and send in a one page prospectus of the proposed project. NIA will approve projects based on their relevance to NIA/BSR''s areas of emphasis. Approved projects are then assigned to NLMS statisticians at the Census Bureau who work directly with the researcher to interface with the database. A modified version of the public use data files is available also through the Census restricted Data Centers. However, since the database is quite complex, many investigators have found that the most efficient way to access it is through the Census programmers. * Dates of Study: 1973-2009 * Study Features: Longitudinal * Sample Size: ~3.3 Million Link: *ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00134

Proper citation: National Longitudinal Mortality Study (RRID:SCR_008946) Copy   

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http://www.biochem.ucl.ac.uk/bsm/virus_database/VIDA3/VIDA.html

VIDA contains a collection of homologous protein families derived from open reading frames from complete and partial virus genomes. For each family, users can get an alignment of the conserved regions, functional and taxonomy information, and links to DNA sequences and structures. * Search homologous protein families from particular virus families * Links to complete genome sequence: Arteriviridae, Coronaviridae, Herpesviridae, Poxviridae The Virus Database at University College London has been developed as a system to organize animal virus open reading frame sequences. All known and predicted protein sequences from complete and partial genomes of particular virus families are extracted from GenBank and filtered to remove 100% redundancy. On the basis of sequence similarity the sequences are then clustered into homologous protein families (HPFs). The families are enriched with annotations including function and functional classification, related protein structures, taxonomy, length of the proteins, boundaries of the conserved region/s, virus-specific gene name and links to EMBL entries and SWISSPROT., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: VIDA (RRID:SCR_007111) Copy   

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http://blanco.biomol.uci.edu/membrane_proteins_xtal.html

Table providing information about integral membrane proteins whose crystallographic, or sometimes NMR, structures have been determined to a resolution sufficient to identify TM helices of helix-bundle membrane proteins (typically 4 - 4.5 angstroms). It is based upon Preusch et al. (1998) as revised by White & Wimley (1999). Reference is made to all of the protein types whose structures have been determined. They have attempted to make the database as inclusive as possible.

Proper citation: Mpstruct (RRID:SCR_013284) Copy   

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http://paleobiodb.org/

A non-governmental, non-profit public database for paleontological data providing researchers and the public with information about the entire fossil record. It has been organized and operated by a multi-disciplinary, multi-institutional, international group of paleobiological researchers. Its purpose is to provide global, collection-based occurrence and taxonomic data for organisms of all geological ages, as well data services to allow easy access to data for independent development of analytical tools, visualization software, and applications of all types. The Database's broader goal is to encourage and enable data-driven collaborative efforts that address large-scale paleobiological questions. Paleontological data files are accepted for upload. However, PaleoBioDB needs some basic data types to be included in order to perform an upload. The Application Programming Interface (API) gives scientists, students, and developers programmatic access to taxonomic, spatial, and temporal data contained within the database.

Proper citation: Paleobiology Database (RRID:SCR_003798) Copy   

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http://www.innomed-addneuromed.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9,2023. Project portal for a cross European study designed to find biomarkers, or tests, for Alzheimer's disease. Its objectives are to produce and improve experimental models of Alzheimer's for biomarker discovery and to identify a biomarker for Alzheimer's disease suitable for diagnosis, prediction, and monitoring disease progression for use in clinical trials and in clinical practice. The baseline dataset database was scheduled to be completed and locked in 2008 and become available to researchers by 2009. Requests to access the data will be reviewed by the scientific projects committee.

Proper citation: AddNeuroMed (RRID:SCR_003819) Copy   

•   Source: SciCrunch Registry

http://www.etoxproject.eu/

Project to develop a drug safety database from the pharmaceutical industry legacy toxicology reports and public toxicology data; innovative in silico strategies and novel software tools to better predict the toxicological profiles of small molecules in early stages of the drug development pipeline. The project is creating this pharmaco-toxicological database with an aim to: * Reduce the number of animal tests * Decrease the attrition rates of new drug candidates * Increase the success rate of new molecular entities becoming drugs * Improve the safety of drugs on the market The project consists of three different systems, * eTOX VITIC Database a unified database containing all confidential and non-confidential data collected in eTOX (historical data from the pharmaceutical industry) * ChOX Database a unified database containing public data (literature and public database) * eTOXsys Query and Prediction System an interface providing a uniform access to the two databases (VITIC and ChOX) and to all developed prediction models and systems

Proper citation: eTOX (RRID:SCR_003712) Copy   

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http://www.genome.jp/

GenomeNet is a Japanese network of database and computational services for genome research and related research areas in biomedical sciences, operated by the Kyoto University Bioinformatics Center. GenomeNet was established in September 1991 under the Human Genome Program of the then Ministry of Education, Science and Culture (Monbusho). The GenomeNet service has been developed by the Kanehisa Laboratory in Kyoto University as part of the research projects. GenomeNet is operated using the Supercomputer System of the Institute for Chemical Research, Kyoto University. LinkDB is supported by the National Bioscience Database Center of the Japan Science and Technology Agency.

Proper citation: GenomeNet (RRID:SCR_004165) Copy   

•   Source: SciCrunch Registry

http://biorxiv.org/

A free archive and distribution service for unpublished preprints in the life sciences allowing authors to make their findings immediately available to the scientific community and receive feedback on draft manuscripts before they are submitted to journals. An article may be posted prior to, or concurrently with, submission to a journal but should not be posted if it has already been published. Once an article is published in a journal, bioRxiv will update the preprint with a link to the published version.

Proper citation: bioRxiv (RRID:SCR_003933) Copy   

•   Source: SciCrunch Registry

https://nda.nih.gov/

The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. Research data repository for data sharing and collaboration among investigators. Used to accelerate scientific discovery through data sharing across all of mental health and other research communities, data harmonization and reporting of research results. Infrastructure created by National Database for Autism Research (NDAR), Research Domain Criteria Database (RDoCdb), National Database for Clinical Trials related to Mental Illness (NDCT), and NIH Pediatric MRI Repository (PedsMRI).

Proper citation: NIMH Data Archive (RRID:SCR_004434) Copy   

•   Source: SciCrunch Registry

http://discovery.hsci.harvard.edu/

An online database of curated cancer stem cell (CSC) experiments coupled to the Galaxy analytical framework. Driven by a need to improve our understanding of molecular processes that are common and unique across cancer stem cells (CSCs), the SCDE allows users to consistently describe, share and compare CSC data at the gene and pathway level. The initial focus has been on carefully curating tissue and cancer stem cell-related experiments from blood, intestine and brain to create a high quality resource containing 53 public studies and 1098 assays. The experimental information is captured and stored in the multi-omics Investigation/Study/Assay (ISA-Tab) format and can be queried in the data repository. A linked Galaxy framework provides a comprehensive, flexible environment populated with novel tools for gene list comparisons against molecular signatures in GeneSigDB and MSigDB, curated experiments in the SCDE and pathways in WikiPathways. Investigation/Study/Assay (ISA) infrastructure is the first general-purpose format and freely available desktop software suite targeted to experimentalists, curators and developers and that: * assists in the reporting and local management of experimental metadata (i.e. sample characteristics, technology and measurement types, sample-to-data relationships) from studies employing one or a combination of technologies; * empowers users to uptake community-defined minimum information checklists and ontologies, where required; * formats studies for submission to a growing number of international public repositories endorsing the tools, currently ENA (genomics), PRIDE (proteomics) and ArrayExpress (transcriptomics). Galaxy allows you to do analyses you cannot do anywhere else without the need to install or download anything. You can analyze multiple alignments, compare genomic annotations, profile metagenomic samples and much much more. Best of all, Galaxy''''s history system provides a complete analyses record that can be shared. Every history is an analysis workflow, which can be used to reproduce the entire experiment. The code for this Galaxy instance is available for download from BitBucket.

Proper citation: Stem Cell Discovery Engine (RRID:SCR_004453) Copy   

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http://figshare.com/

Repository for all data, figures, theses, publications, posters, presentations, filesets, videos, datasets, negative data in a citable, shareable and discoverable manner with Digital Object Identifiers. Allows to upload any file format to be made visualisable in the browser so that figures, datasets, media, papers, posters, presentations and filesets can be disseminated in a way that the current scholarly publishing model does not allow. Features integration with ORCID, Symplectic Elements, can import items from Github and is a source tracked by Altmetric.com. Figshare gives users unlimited public space and 1GB of private storage space for free. Data are digitally preserved by CLOCKSS. Supported by Digital Science, a division of Macmillan Publishers Limited, as a community-based, open science project that retains its autonomy.

Proper citation: FigShare (RRID:SCR_004328) Copy   

•   Source: SciCrunch Registry