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http://202.38.126.151:8080/SDisease/

Curated database of experimentally supported data of RNA Splicing mutation and disease. The RNA Splicing mutations include cis-acting mutations that disrupt splicing and trans-acting mutations that affecting RNA-dependent functions that cause disease. Information such as EntrezGeneID, gene genomic sequence, mutation (nucleotide substitutions, deletions and insertions), mutation location within the gene, organism, detailed description of the splicing mutation and references are also given. Users are able to submit new entries to the database. This database integrating RNA splicing and disease associations would be helpful for understanding not only the RNA splicing but also its contribution to disease. In SpliceDisease database, they manually curated 2337 splicing mutation disease entries involving 303 genes and 370 diseases, which have been supported experimentally in 898 publications. The SpliceDisease database provides information including the change of the nucleotide in the sequence, the location of the mutation on the gene, the reference PubMed ID and detailed description for the relationship among gene mutations, splicing defects and diseases. They standardized the names of the diseases and genes and provided links for these genes to NCBI and UCSC genome browser for further annotation and genomic sequences. For the location of the mutation, they give direct links of the entry to the respective position/region in the genome browser.

Proper citation: SpliceDisease (RRID:SCR_006130) Copy   

•   Source: SciCrunch Registry

http://equilibrator.weizmann.ac.il/

Web interface designed for thermodynamic analysis of biochemical systems. eQuilibrator enables free-text search for biochemical compounds and reactions and provides thermodynamic estimates for both in a variety of conditions. It can provide estimates for compounds in the KEGG database, and individual compounds and enzymes can be searched for by their common names (water, glucosamine, hexokinase). Reactions can be entered in a free-text format that eQuilibrator parses automatically. eQuilibrator also allows manipulation of the conditions of a reaction - pH, ionic strength, and reactant and product concentrations.

Proper citation: eQuilibrator (RRID:SCR_006011) Copy   

•   Source: SciCrunch Registry

http://aias.biol.uoa.gr/OMPdb/

A database of Beta-barrel outer membrane proteins from Gram-negative bacteria. The web interface of OMPdb offers the user the ability not only to view the available data, but also to submit advanced queries for text search within the database''s protein entries or run BLAST searches against the database. The most up-to-date version of the database (as well as all past versions) can be downloaded in various formats (flat text, XML format or raw FASTA sequences). For constructing OMPdb, multiple freely accessible resources were combined and a detailed literature search was performed. The classification of OMPdb''s protein entries into families is based mainly on structural and functional criteria. Information included in the database consists of sequence data, as well as annotation for structural characteristics (such as the transmembrane segments), literature references and links to other public databases, features that are unique worldwide. Along with the database, a collection of profile Hidden Markov Models that were shown to be characteristic for Beta-barrel outer membrane proteins was also compiled. This set, when used in combination with our previously developed algorithms (PRED-TMBB, MCMBB and ConBBPRED) will serve as a powerful tool in matters of discrimination and classification of novel Beta-barrel proteins and whole-genome analyses., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: OMPdb (RRID:SCR_006221) Copy   

•   Source: SciCrunch Registry

http://evolution.genetics.washington.edu/phylip.html

A free package of software programs for inferring phylogenies (evolutionary trees). The source code is distributed (in C), and executables are also distributed. In particular, already-compiled executables are available for Windows (95/98/NT/2000/me/xp/Vista), Mac OS X, and Linux systems. Older executables are also available for Mac OS 8 or 9 systems.

Proper citation: PHYLIP (RRID:SCR_006244) Copy   

•   Source: SciCrunch Registry

http://www.chemspider.com/

Collection of chemical structures. Provides access to structures, properties and associated information from hundreds of data sources to find compounds of interest and provides services to improve this data by curation and annotation and to integrate it with users applications.

Proper citation: ChemSpider (RRID:SCR_006360) Copy   

•   Source: SciCrunch Registry

http://brainvis.wustl.edu/wiki/index.php/Caret:About

Software package to visualize and analyze structural and functional characteristics of cerebral and cerebellar cortex in humans, nonhuman primates, and rodents. Runs on Apple (Mac OSX), Linux, and Microsoft Windows operating systems.

Proper citation: Computerized Anatomical Reconstruction and Editing Toolkit (RRID:SCR_006260) Copy   

•   Source: SciCrunch Registry

http://www.geenivaramu.ee/en/tools/gwama

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software tool for meta analysis of whole genome association data.

Proper citation: GWAMA (RRID:SCR_006624) Copy   

•   Source: SciCrunch Registry

https://www.iedb.org/

Repository contains antibody/B cell and T cell epitope information and epitope prediction and analysis tools. Immune epitopes are defined as molecular structures recognized by specific antigen receptors of the immune system, namely antibodies, B cell receptors, and T cell receptors. Immune epitopes from infectious diseases, excluding HIV, and immune-mediated diseases and the accompanying biological information are included.

Proper citation: Immune Epitope Database and Analysis Resource (IEDB) (RRID:SCR_006604) Copy   

•   Source: SciCrunch Registry

http://dictybase.org/

Model organism database for the social amoeba Dictyostelium discoideum that provides the biomedical research community with integrated, high quality data and tools for Dictyostelium discoideum and related species. dictyBase houses the complete genome sequence, ESTs, and the entire body of literature relevant to Dictyostelium. This information is curated to provide accurate gene models and functional annotations, with the goal of fully annotating the genome to provide a ''''reference genome'''' in the Amoebozoa clade. They highlight several new features in the present update: (i) new annotations; (ii) improved interface with web 2.0 functionality; (iii) the initial steps towards a genome portal for the Amoebozoa; (iv) ortholog display; and (v) the complete integration of the Dicty Stock Center with dictyBase. The Dicty Stock Center currently holds over 1500 strains targeting over 930 different genes. There are over 100 different distinct amoebozoan species. In addition, the collection contains nearly 600 plasmids and other materials such as antibodies and cDNA libraries. The strain collection includes: * strain catalog * natural isolates * MNNG chemical mutants * tester strains for parasexual genetics * auxotroph strains * null mutants * GFP-labeled strains for cell biology * plasmid catalog The Dicty Stock Center can accept Dictyostelium strains, plasmids, and other materials relevant for research using Dictyostelium such as antibodies and cDNA or genomic libraries.

Proper citation: Dictyostelium discoideum genome database (RRID:SCR_006643) Copy   

•   Source: SciCrunch Registry

http://www.phytozome.net/

A comparative platform for green plant genomics. Families of orthologous and paralogous genes that represent the modern descendents of ancestral gene sets are constructed at key phylogenetic nodes. These families allow easy access to clade specific orthology / paralogy relationships as well as clade specific genes and gene expansions. As of release v9.1, Phytozome provides access to forty-one sequenced and annotated green plant genomes which have been clustered into gene families at 20 evolutionarily significant nodes. Where possible, each gene has been annotated with PFAM, KOG, KEGG, and PANTHER assignments, and publicly available annotations from RefSeq, UniProt, TAIR, JGI are hyper-linked and searchable., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Phytozome (RRID:SCR_006507) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/expression.shtml

Community database that collects and integrates the gene expression information in MGI with a primary emphasis on endogenous gene expression during mouse development. The data in GXD are obtained from the literature, from individual laboratories, and from large-scale data providers. All data are annotated and reviewed by GXD curators. GXD stores and integrates different types of expression data (RNA in situ hybridization; Immunohistochemistry; in situ reporter (knock in); RT-PCR; Northern and Western blots; and RNase and Nuclease s1 protection assays) and makes these data freely available in formats appropriate for comprehensive analysis. There is particular emphasis on endogenous gene expression during mouse development. GXD also maintains an index of the literature examining gene expression in the embryonic mouse. It is comprehensive and up-to-date, containing all pertinent journal articles from 1993 to the present and articles from major developmental journals from 1990 to the present. GXD stores primary data from different types of expression assays and by integrating these data, as data accumulate, GXD provides increasingly complete information about the expression profiles of transcripts and proteins in different mouse strains and mutants. GXD describes expression patterns using an extensive, hierarchically-structured dictionary of anatomical terms. In this way, expression results from assays with differing spatial resolution are recorded in a standardized and integrated manner and expression patterns can be queried at different levels of detail. The records are complemented with digitized images of the original expression data. The Anatomical Dictionary for Mouse Development has been developed by our Edinburgh colleagues, as part of the joint Mouse Gene Expression Information Resource project. GXD places the gene expression data in the larger biological context by establishing and maintaining interconnections with many other resources. Integration with MGD enables a combined analysis of genotype, sequence, expression, and phenotype data. Links to PubMed, Online Mendelian Inheritance in Man (OMIM), sequence databases, and databases from other species further enhance the utility of GXD. GXD accepts both published and unpublished data.

Proper citation: Gene Expression Database (RRID:SCR_006539) Copy   

•   Source: SciCrunch Registry

http://www.dpvweb.net/

DPVweb provides a central source of information about viruses, viroids and satellites of plants, fungi and protozoa. Comprehensive taxonomic information, including brief descriptions of each family and genus, and classified lists of virus sequences are provided. The database also holds detailed, curated, information for all sequences of viruses, viroids and satellites of plants, fungi and protozoa that are complete or that contain at least one complete gene. For comparative purposes, it also contains a single representative sequence of all other fully sequenced virus species with an RNA or single-stranded DNA genome. The start and end positions of each feature (gene, non-translated region and the like) have been recorded and checked for accuracy. As far as possible, nomenclature for genes and proteins are standardized within genera and families. Sequences of features (either as DNA or amino acid sequences) can be directly downloaded from the website in FASTA format. The sequence information can also be accessed via client software for PC computers (freely downloadable from the website) that enable users to make an easy selection of sequences and features of a chosen virus for further analyses. The public sequence databases contain vast amounts of data on virus genomes but accessing and comparing the data, except for relatively small sets of related viruses can be very time consuming. The procedure is made difficult because some of the sequences on these databases are incorrectly named, poorly annotated or redundant. The NCBI Reference Sequence project (1) provides a comprehensive, integrated, non-redundant set of sequences, including genomic DNA, transcript (RNA) and protein products, for major research organisms. This now includes curated information for a single sequence of each fully sequenced virus species. While this is a welcome development, it can only deal with complete sequences. An important feature of DPV is the opportunity to access genes (and other features) of multiple sequences quickly and accurately. Thus, for example, it is easy to obtain the nucleotide or amino acid sequences of all the available accessions of the coat protein gene of a given virus species or for a group of viruses. To increase its usefulness further, DPVweb also contains a single representative sequence of all other fully sequenced virus species with an RNA or single-stranded DNA (ssDNA) genome. Sponsors: This site is supported by the Association of Applied Biologists and the Zhejiang Academy of Agricultural Sciences, Hangzhou, People''s Republic of China.

Proper citation: Descriptions of Plant Viruses (RRID:SCR_006656) Copy   

•   Source: SciCrunch Registry

http://griffin.cbrc.jp/

Griffin (G-protein-receptor interacting feature finding instrument) is a high-throughput system to predict GPCR - G-protein coupling selectively with the input of GPCR sequence and ligand molecular weight. This system consists of two parts: 1) HMM section using family specific multiple alignment of GPCRs, 2) SVM section using physico-chemical feature vectors in GPCR sequence. G-protein coupled receptors (GPCR), which is composed of seven transmembrane helices, play a role as interface of signal transduction. The external stimulation for GPCR, induce the coupling with G-protein (Gi/o, Gq/11, Gs, G12/13) followed by different kinds of signal transduction to inner cell. About half of distributed drugs are intending to control this GPCR - G-protein binding system, and therefore this system is important research target for the development of effective drug. For this purpose, it is necessary to monitor, effectively and comprehensively, of the activation of G-protein by identifying ligand combined with GPCR. Since, at present, it is difficult to construct such biochemical experiment system, if the answers for experimental results can be prepared beforehand by using bioinformatics techniques, large progress is brought to G-protein related drug design. Previous works for predicting GPCR-G protein coupling selectivity are using sequence pattern search, statistical models, and HMM representations showed high sensitivity of predictions. However, there are still no works that can predict with both high sensitivity and specificity. In this work we extracted comprehensively the physico-chemical parameters of each part of ligand, GPCR and G-protein, and choose the parameters which have strong correlation with the coupling selectivity of G-protein. These parameters were put as a feature vector, used for GPCR classification based on SVM.

Proper citation: G protein receptor interaction feature finding instrument (RRID:SCR_008343) Copy   

•   Source: SciCrunch Registry

http://tree.bio.ed.ac.uk/software/figtree

A graphical viewer of phylogenetic trees and a program for producing publication-ready figures. It is designed to display summarized and annotated trees produced by BEAST.

Proper citation: FigTree (RRID:SCR_008515) Copy   

•   Source: SciCrunch Registry

https://CRAN.R-project.org/package=gma

Software package to perform Granger mediation analysis for time series. Includes single level GMA model and two-level GMA model, for time series with hierarchically nested structure.

Proper citation: GMA (RRID:SCR_009212) Copy   

•   Source: SciCrunch Registry

http://clipserve.clip.ubc.ca/topfind

An integrated knowledgebase focused on protein termini, their formation by proteases and functional implications. It contains information about the processing and the processing state of proteins and functional implications thereof derived from research literature, contributions by the scientific community and biological databases. It lists more than 120,000 N- and C-termini and almost 10,000 cleavages. TopFIND is a resource for comprehensive coverage of protein N- and C-termini discovered by all available in silico, in vitro as well as in vivo methodologies. It makes use of existing knowledge by seamless integration of data from UniProt and MEROPS and provides access to new data from community submission and manual literature curating. It renders modifications of protein termini, such as acetylation and citrulination, easily accessible and searchable and provides the means to identify and analyse extend and distribution of terminal modifications across a protein. The data is presented to the user with a strong emphasis on the relation to curated background information and underlying evidence that led to the observation of a terminus, its modification or proteolytic cleavage. In brief the protein information, its domain structure, protein termini, terminus modifications and proteolytic processing of and by other proteins is listed. All information is accompanied by metadata like its original source, method of identification, confidence measurement or related publication. A positional cross correlation evaluation matches termini and cleavage sites with protein features (such as amino acid variants) and domains to highlight potential effects and dependencies in a unique way. Also, a network view of all proteins showing their functional dependency as protease, substrate or protease inhibitor tied in with protein interactions is provided for the easy evaluation of network wide effects. A powerful yet user friendly filtering mechanism allows the presented data to be filtered based on parameters like methodology used, in vivo relevance, confidence or data source (e.g. limited to a single laboratory or publication). This provides means to assess physiological relevant data and to deduce functional information and hypotheses relevant to the bench scientist. TopFIND PROVIDES: * Integration of protein termini with proteolytic processing and protein features * Displays proteases and substrates within their protease web including detailed evidence information * Fully supports the Human Proteome Project through search by chromosome location CONTRIBUTE * Submit your N- or C-termini datasets * Contribute information on protein cleavages * Provide detailed experimental description, sample information and raw data

Proper citation: TopFIND (RRID:SCR_008918) Copy   

•   Source: SciCrunch Registry

http://go.princeton.edu/cgi-bin/GOTermFinder

The Generic GO Term Finder finds the significant GO terms shared among a list of genes from an organism, displaying the results in a table and as a graph (showing the terms and their ancestry). The user may optionally provide background information or a custom gene association file or filter evidence codes. This tool is capable of batch processing multiple queries at once. GO::TermFinder comprises a set of object-oriented Perl modules GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. This implementation, developed at the Lewis-Sigler Institute at Princeton, depends on the GO-TermFinder software written by Gavin Sherlock and Shuai Weng at Stanford University and the GO:View module written by Shuai Weng. It is made publicly available through the GMOD project. The full source code and documentation for GO:TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Generic GO Term Finder (RRID:SCR_008870) Copy   

•   Source: SciCrunch Registry

http://plantgrn.noble.org/LegumeIP/

LegumeIP is an integrative database and bioinformatics platform for comparative genomics and transcriptomics to facilitate the study of gene function and genome evolution in legumes, and ultimately to generate molecular based breeding tools to improve quality of crop legumes. LegumeIP currently hosts large-scale genomics and transcriptomics data, including: * Genomic sequences of three model legumes, i.e. Medicago truncatula, Glycine max (soybean) and Lotus japonicus, including two reference plant species, Arabidopsis thaliana and Poplar trichocarpa, with the annotation based on UniProt TrEMBL, InterProScan, Gene Ontology and KEGG databases. LegumeIP covers a total 222,217 protein-coding gene sequences. * Large-scale gene expression data compiled from 104 array hybridizations from L. japonicas, 156 array hybridizations from M. truncatula gene atlas database, and 14 RNA-Seq-based gene expression profiles from G. max on different tissues including four common tissues: Nodule, Flower, Root and Leaf. * Systematic synteny analysis among M. truncatula, G. max, L. japonicus and A. thaliana. * Reconstruction of gene family and gene family-wide phylogenetic analysis across the five hosted species. LegumeIP features comprehensive search and visualization tools to enable the flexible query on gene annotation, gene family, synteny, relative abundance of gene expression.

Proper citation: LegumeIP (RRID:SCR_008906) Copy   

•   Source: SciCrunch Registry

http://hymenopteragenome.org/beebase/

Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.

Proper citation: BeeBase (RRID:SCR_008966) Copy   

•   Source: SciCrunch Registry

http://pages.stat.wisc.edu/~yandell/qtl/software/qtlbim/

Software library for QTL Bayesian Interval Mapping that provides a Bayesian model selection approach to map multiple interacting QTL. It works on experimentally inbred lines and performs a genome-wide search to locate multiple potential QTL. The package can handle continuous, binary and ordinal traits. (entry from Genetic Analysis Software)

Proper citation: R/QTLBIM (RRID:SCR_009375) Copy   

•   Source: SciCrunch Registry