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http://www.dogmap.ch/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. An international collaboration between 46 labs from 20 different countries towards a low resolution canine marker map under the auspices of the International Society for Animal Genetics (ISAG). The map under development should achieve a resolution of about 20 cM and some of the markers should be mapped physically. The participants have agreed to use microsatellites as markers on a common panel of reference families which will provide the backbone of the marker map. It is foreseen to also include type I markers in the mapping effort and to produce cosmid derived microsatellites for physical mapping. For this purpose part of the effort focuses on the standardization of the canine karyotype. Special attention is payed to hereditary diseases where efforts are under way to establish resource families either by collecting families or by specific breeding. A point of emphasis of the DogMap project is the setting up of an internationally accessible database for handling the mapping data. The structure of the DogMap collaboration includes a managing committee and scientific advisers. The managing committee is responsible for the overall coordination of the activities within the collaboration, for the dissemination of relevant information to all of the participants and for the representation of DogMap outside the collaboration., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DogMap (RRID:SCR_002332) Copy   

•   Source: SciCrunch Registry
  

http://edas2.bioinf.fbb.msu.ru/

Databases of alternatively spliced genes with data on the alignment of proteins, mRNAs, and EST. It contains information on all exons and introns observed, as well as elementary alternatives formed from them. The database makes it possible to filter the output data by changing the cut-off threshold by the significance level. It contains splicing information on human, mouse, dog (not yet functional) and rat (not yet functional). For each database, users can search by keyword or by overall gene expression. They can also view genes based on chromosomal arrangement or other position in genome (exon, intron, acceptor site, donor site), functionality, position, conservation, and EST coverage. Also offered is an online Fisher test.

Proper citation: EDAS - EST-Derived Alternative Splicing Database (RRID:SCR_002449) Copy   

•   Source: SciCrunch Registry
  

http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

•   Source: SciCrunch Registry
  

http://www.nitrc.org/projects/saibn/

A 3D stereoscopic (anaglyph method) full brain functional connectivity atlas created using a parcellation atlas published by Craddock et al. (2012). Using 3D Slicer 3.6.3 and the two hundred Region of Interest (ROI) version of the Craddock atlas, 200 grayscale surface models were created using a z-stat threshold > 2.3, and each surface model was processed with a surface decimation algorithm, smoothed with the Taubin algorithm and without surface normals. For improved visualization of the functional connectivity networks and their relative anatomical position, the surface model of five subcortical anatomical structures (corpus callosum, bilateral caudate, pallidum, putamen, thalamus, amygdala and hippocampus) were included in SAIBN. These surfaces were created with 3D Slicer using the segmentation computed with Freesurfer v. 5.1. The viewer should use red-cyan glasses to see the 3D stereoscopic effect using 3D Slicer (version 3.6.3, http://www.slicer.org/pages/Special:SlicerDownloads).

Proper citation: Stereoscopic Atlas of Intrinsic Brain Networks (RRID:SCR_002568) Copy   

•   Source: SciCrunch Registry
  

http://www.earthchem.org/petdb

Accepts and provides access to geochemical and petrological data for ocean floor igneous and metamorphic rocks, (whole rock, volcanic, glass, mineral, and melt inclusion analyses), and mantle and lower-crustal xenolith samples. Data are compiled primarily from the published literature. Authors are encouraged to submit their datasets and databases to EarthChem.

Proper citation: PetDB (RRID:SCR_002209) Copy   

•   Source: SciCrunch Registry
  

https://interferome.org/interferome/search/showSearch.jspx

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 28,2022. InterPare is a database server for protein interaction interface information. It contains large-scale interface data of proteins whose 3D-structures are known. Protein interface information is derived from three different methods. InterPare introduces a large-scale protein domain interaction interface database called InterPare. InterPare uses three methods: 1) the Euclidean distance method for checking the distance among subunits in multidomain proteins, 2) Accessible Surface Area (ASA) for detecting the buried region of a protein that is detached from a solvent when forming multimers or complexes, 3) the Voronoi diagram, a computational geometry method, that uses a mathematical definition of interface regions. InterPare includes tools with different display modes for viewing protein interior, surface, and interaction interfaces.

Proper citation: The Protein Interfaceome Database (RRID:SCR_002126) Copy   

•   Source: SciCrunch Registry
  

http://neuronbank.org/wiki

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. Platform for Neuroscientists to describe neurons and neural circuitry. Registered users may edit. The ultimate goal is advance the field of Neuromics by creating an encyclopedia of neurons and neural circuitry. NOTE: The database is no longer being maintained due to lack of funding.

Proper citation: NeuronBank (RRID:SCR_002004) Copy   

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http://rulai.cshl.edu/LSPD/

LSPD provides liver specific gene. It lists ~300 promoter regions responsible for liver specific transcriptions, collect ~400 experimentally verified regulatory regions and elements, provide information on transcription regulation of liver genes, compare transcription regulation of functionally or evolutionarily related genes, and retrieve sequences of the promoter region. Its regulatory elements provides information on transcription regulatory elements, reports the methods for verification of the elements, records binding affinity and regulatory function, and summarizes the site distribution and sequence consensus.

Proper citation: LSPD (RRID:SCR_002125) Copy   

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http://tpdb.medchem.ku.edu:8080/protein_database/index.jsp

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on July 29,2022. This database is an attempt to catalog in a convenient, searchable fashion the publicly available information about the identities of mammalian proteins that become covalently adducted by chemically-reactive metabolites of xenobiotic agents. At present all entries pertain to well-identified proteins that become adducted following defined exposures to known chemical agents in vivo or in cell culture experiments. Results from studies using enzymatic or chemical model systems have not been included but may be in the future. The search functions are relatively simple and intuitive, so most users can go straight to the Search page and begin searching. Additional explanations, examples and information about possible future expansions may be found.

Proper citation: Target Protein Database (RRID:SCR_002124) Copy   

•   Source: SciCrunch Registry
  

http://genome.jouy.inra.fr/spid/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. An online database of two-hybrid protein interactions in B. Subtilis. Interactions stored in SPID are either characterized by experimental evidence or by bibliographic references. A graphical user interface is provided to explore interaction networks as well as to view the details of each piece of evidence. The database contains 112 interactions between 79 proteins.

Proper citation: Subtilis Protein interaction Database (RRID:SCR_002123) Copy   

•   Source: SciCrunch Registry
  

http://hazmap.nlm.nih.gov/

Occupational health database designed for health and safety professionals and for consumers seeking information about the adverse effects of workplace exposures to chemical and biological agents. The main links in Haz-Map are between chemicals and occupational diseases. These links have been established using current scientific evidence. Haz-Map shows the diseases linked to each agent and the agents linked to each disease. Agents are chemical such as formaldehyde, or biological such as grain dust. Haz-Map links jobs and hazardous job tasks with occupational diseases and their symptoms. In Haz-Map, chronic occupational diseases are linked to both jobs and industries, while acute diseases and infectious diseases are linked only to jobs. Cancers are not linked to jobs, industries or findings. The information in Haz-Map comes from textbooks, journal articles, the Documentation of the Threshold Limit Values (published by ACGIH), and electronic databases such as NLM's Hazardous Substances Data Bank (HSDB). Haz-Map staff classifies, summarizes, and regularly updates the information found in the database.

Proper citation: Haz-Map: Occupational Exposure to Hazardous Agents (RRID:SCR_002365) Copy   

•   Source: SciCrunch Registry
  

http://www.pubgene.org/

It helps users retrieve information on genes and proteins. The underlying structure of PubGene can be viewed as a gene-centric database. Gene and protein names are cross-referenced to each other and to terms that are relevant to understanding their biological function, importance in disease and relationship to chemical substances. The result is a literature network organizing information in a form that is easy to navigate.

Proper citation: PubGene (RRID:SCR_002119) Copy   

•   Source: SciCrunch Registry
  

http://cpdb.molgen.mpg.de

An integrative interaction database that integrates different types of functional interactions from heterogeneous interaction data resources. Physical protein interactions, metabolic and signaling reactions and gene regulatory interactions are integrated in a seamless functional association network that simultaneously describes multiple functional aspects of genes, proteins, complexes, metabolites, etc. With human, yeast and mouse complex functional interactions, it currently constitutes the most comprehensive publicly available interaction repository for these species. Different ways of utilizing these integrated interaction data, in particular with tools for visualization, analysis and interpretation of high-throughput expression data in the light of functional interactions and biological pathways is offered.

Proper citation: ConsensusPathDB (RRID:SCR_002231) Copy   

•   Source: SciCrunch Registry
  

http://www.genscript.com/psort/wolf_psort.html

Data analysis service for protein subcellular localization prediction.

Proper citation: WoLF PSORT (RRID:SCR_002472) Copy   

•   Source: SciCrunch Registry
  

https://pfam.xfam.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. iPfam is a resource that describes physical interactions between those Pfam domains that have a representative structure in the Protein DataBank (PDB). When two or more domains occur within a single structure, the domains are analysed to see if they form an interaction. If the domains are close enough to form an interaction, the bonds that play a role in that interaction are determined. The goal has been to re-calculate iPfam interaction data for each new Pfam release, so that, as Pfam changes, the information within iPfam remains up to date.

Proper citation: Protein families database of alignments and HMMs (RRID:SCR_002115) Copy   

•   Source: SciCrunch Registry
  

http://compbio.cs.toronto.edu/psmdb

Database of non-redundant sets of protein - small-molecule complexes that are especially suitable for structure-based drug design and protein - small-molecule interaction research. PSMB supports: * Support frequent updates - The number of new structures in the PDB is growing rapidly. In order to utilize these structures, frequent updates are required. In contrast to manual procedures which require significant time and effort per update, generation of the PSMDB database is fully automatic thereby facilitating frequent database updates. * Consider both protein and ligand structural redundancy - In the database, two complexes are considered redundant if they share a similar protein and ligand (the protein - small-molecule non-redundant set). This allows the database to contain structural information for the same protein bound to several different ligands (and vice-versa). Additionally, for completeness, the database contains a set of non-redundant complexes when only protein structural redundancy is considered (our protein non-redundant set). The following images demonstrate the structural redundancy of the protein complexes in the PDB compared to the PSMDB. * Efficient handling of covalent bonds -Many protein complexes contain covalently bound ligands. Typically, protein-ligand databases discard these complexes; however, the PSMDB simply removes the covalently bound ligand from the complex, retaining any non-covalently bound ligands. This increases the number of usable complexes in the database. * Separate complexes into protein and ligand files -The PSMDB contains individual structure files for both the protein and all non-covalently bound ligands. The unbound proteins are in PDB format while the individual ligands are in SDF format (in their native coordinate frame).

Proper citation: Protein-Small Molecule Database (RRID:SCR_002112) Copy   

•   Source: SciCrunch Registry
  

http://www.dbass.soton.ac.uk/

A database of new exon boundaries induced by pathogenic mutations in human disease genes.

Proper citation: DBASS (RRID:SCR_002107) Copy   

•   Source: SciCrunch Registry
  

http://fullmal.hgc.jp/index_ajax.html

FULL-malaria is a database for a full-length-enriched cDNA library from the human malaria parasite Plasmodium falciparum. Because of its medical importance, this organism is the first target for genome sequencing of a eukaryotic pathogen; the sequences of two of its 14 chromosomes have already been determined. However, for the full exploitation of this rapidly accumulating information, correct identification of the genes and study of their expression are essential. Using the oligo-capping method, this database has produced a full-length-enriched cDNA library from erythrocytic stage parasites and performed one-pass reading. The database consists of nucleotide sequences of 2490 random clones that include 390 (16%) known malaria genes according to BLASTN analysis of the nr-nt database in GenBank; these represent 98 genes, and the clones for 48 of these genes contain the complete protein-coding sequence (49%). On the other hand, comparisons with the complete chromosome 2 sequence revealed that 35 of 210 predicted genes are expressed, and in addition led to detection of three new gene candidates that were not previously known. In total, 19 of these 38 clones (50%) were full-length. From these observations, it is expected that the database contains approximately 1000 genes, including 500 full-length clones. It should be an invaluable resource for the development of vaccines and novel drugs. Full-malaria has been updated in at least three points. (i) 8934 sequences generated from the addition of new libraries added so that the database collection of 11,424 full-length cDNAs covers 1375 (25%) of the estimated number of the entire 5409 parasite genes. (ii) All of its full-length cDNAs and GenBank EST sequences were mapped to genomic sequences together with publicly available annotated genes and other predictions. This precisely determined the gene structures and positions of the transcriptional start sites, which are indispensable for the identification of the promoter regions. (iii) A total of 4257 cDNA sequences were newly generated from murine malaria parasites, Plasmodium yoelii yoelii. The genome/cDNA sequences were compared at both nucleotide and amino acid levels, with those of P.falciparum, and the sequence alignment for each gene is presented graphically. This part of the database serves as a versatile platform to elucidate the function(s) of malaria genes by a comparative genomic approach. It should also be noted that all of the cDNAs represented in this database are supported by physical cDNA clones, which are publicly and freely available, and should serve as indispensable resources to explore functional analyses of malaria genomes. Sponsors: This database has been constructed and maintained by a Grant-in-Aid for Publication of Scientific Research Results from the Japan Society for the Promotion of Science (JSPS). This work was also supported by a Special Coordination Funds for Promoting Science and Technology from the Science and Technology Agency of Japan (STA) and a Grant-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Science, Sports and Culture of Japan.

Proper citation: Full-Malaria: Malaria Full-Length cDNA Database (RRID:SCR_002348) Copy   

•   Source: SciCrunch Registry
  

http://statpages.org/javasta2.html

A software registry which offers links to various free statistical software programs for stand-alone computing. The software programs are split into different categories: General Packages, Subset Packages, Curve Fitting and Modeling, Biostatistics and Epidemiology, Surveys, Testing and Measurement, Excel Spreadsheets and Add-ins, Programming Languages and Subroutine Libraries, Scripts and Macros, Miscellaneous, and Other Collections.

Proper citation: Free Statistical Software (RRID:SCR_013834) Copy   

•   Source: SciCrunch Registry
  

http://www.nitrc.org/projects/iterdrwsp/

Software which aims to better estimate the neuronal activation of an individual using the results of an independent component analysis (ICA) method applied to a temporally concatenated group of functional magnetic resonance imaging (fMRI) data (i.e., Tc-GICA method). This approach employs iterative LS solutions to refine both the individual SPs and TCs with an additional a priori assumption of sparseness in the SPs (i.e., minimally overlapping SPs) based on L(1)-norm minimization.

Proper citation: Iterative dual-regression with sparse prior (RRID:SCR_014128) Copy   

•   Source: SciCrunch Registry