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http://www.oasis-brains.org/

Project aimed at making neuroimaging data sets of brain freely available to scientific community. By compiling and freely distributing neuroimaging data sets, future discoveries in basic and clinical neuroscience are facilitated.

Proper citation: Open Access Series of Imaging Studies (RRID:SCR_007385) Copy   

•   Source: SciCrunch Registry

http://mousespinal.brain-map.org/about.html

Platform for exploring spinal cord at cellular and molecular levels. Map of gene expression for adult and juvenile mouse spinal cord. Provides map of normal mouse when used to compare gene expression in diseased or injury models. Interactive database of gene expression mapped across all anatomic segments of mouse spinal cord at postnatal days 4 and 56. Indexed set of images based on RNA in situ hybridization data, searchable and sortable by gene, age, expression, cervical, thoracic, lumbar, sacral, and coccygeal segments.

Proper citation: Allen Mouse Spinal Cord Atlas (RRID:SCR_007418) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/Web/Newsltr/Spring04/cancer.html

Cancer Chromosomes is an integration of three databases, the NCI/NCBI SKY/M-FISH & CGH Database, the NCI Mitelman Database of Chromosome Aberrations in Cancer, and the NCI Recurrent Aberrations in Cancer, which all focus on various aspects of cancer and cancer genes. The goal of the SKY/M-FISH and CGH database is to provide a public platform for investigators to share and compare their molecular cytogenetic data. The database is open to everyone and all users can view an individual investigator''s public data or compare public cases from different investigators. The information in the Mitelman Database of Chromosome Aberrations in Cancer relates chromosomal aberrations to tumor characteristics, based either on individual cases or associations. All the data have been manually culled from the literature. Complete karyotypes, patient characteristics, and references are found in the Mitelman Database of Chromosome Aberrations in Cancer. Users can search all three databases for cytogenetic, clinical, and/or reference information.

Proper citation: Cancer Chromosomes (RRID:SCR_007575) Copy   

•   Source: SciCrunch Registry

http://www.hubmed.org/

HubMed provides an interface to PubMed. Quick access to searches with a Firefox search plugin or a HubMed bookmarklet (drag to your browser''s bookmarks toolbar). Export citations in RIS, BibTeX, RDF and MODS formats, or directly to RefWorks. Unzip HubMed''s import filter into Endnote''s Filters folder for direct import into Endnote, or install the RIS Export plugin for direct import into ProCite, RefMan and older versions of Endnote. Use the Citation Finder to convert reference lists from PDFs into search results. Create lists of closely related papers using Rank Relations, then visualise and browse clusters of related papers using TouchGraph (requires Java). Graph occurrences of keywords in published papers over time. Tag and store annotated metadata for articles of interest.

Proper citation: HubMed (RRID:SCR_007296) Copy   

•   Source: SciCrunch Registry

http://haldanessieve.org/

Blog discussing preprints in population and evolutionary genetics.

Proper citation: Haldanes Sieve (RRID:SCR_007178) Copy   

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http://genome.mc.pref.osaka.jp/BGED/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 08, 2011. This database contains gene expression data for various physiological and pathological processes in mouse brain. All the data have been obtained by adaptor-tagged competitive PCR, an advanced version of quantitative PCR. Brain Gene Expression Database (BGED) contains gene expression data for various physiological and pathological processes in mouse brain. All the data have been obtained by adaptor-tagged competitive PCR, an advanced version of quantitative PCR. Manual Download 1. Data retrieval Gene expression data can be retrieved either by ID numbers or by keywords representing functional annotations from this page. The ID numbers include GenBank, RefSeq, SwissProt, Gene Ontology, and BED (our own ID). The keyword search is based either on definition in GenBank, SwissProt and RefSeq, functional annotation of SwissProt database, or Gene Ontology terms. 2. Gene expression pattern display * Display of multiple gene expression patterns. Expression patterns of multiple genes selected by the keyword search can be displayed from the result page of the keyword search. * Gene expression pattern similarity search This function is available on the information page of each gene accessed through BED ID (in-house ID).

Proper citation: Brain Gene Expression Database (RRID:SCR_007299) Copy   

•   Source: SciCrunch Registry

http://www.med.nihon-u.ac.jp/department/physiol1/

Series of MRI slices from 3 male Japanese snow monkeys (Macaca fuscata). Images are provided of 2 mm MRI slices of male monkey brain in the coronal (N = 5), horizontal (N =1) and sagittal (N =1) planes. Slices are presented according to distance from interaural line. The slices are low resolution and no annotations are provided. Would be suitable for low resolution 3D reconstruction of monkey brain, however. Also, there are datasets provided for 5 monkeys total, 3 m.fuscata and 2 m. mulatta.

Proper citation: Stereotaxic MRI Brain Atlas of Monkey (RRID:SCR_007298) Copy   

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http://kulibin.mit.edu/coc/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 26, 2016. CoC Central is a searchable database of residue conservation data covering the universe of known protein structures. CoC is useful for identifying functionally, kinetically, and thermodynamically important residues. Knowledge of universally conserved positions in protein folds may aid in identifying positions of kinetic or thermodynamic importance in protein folding, as well as those with a functional role.

Proper citation: CoC Central (RRID:SCR_007602) Copy   

•   Source: SciCrunch Registry

https://bioinformatics.cs.vt.edu/cmgs/CMGSDB/

CMGSDB is a database whose objective is to investigate gene silencing from a computational perspective using tools of computational biology and bioinformatics. The database is C. elegans centric, although the schema is suitable for any organism and can be extended with minor changes to support multiple organisms. CMGSDB contains details of genome annotation data (chromosomes, genes, coding transcripts), protein structure data (secondary structure, physical properties), microarray expression data (genomewide gene expressions for over 500 microarray experiments), RNA interferance data (RNAi experiment details, phenotypes exhibited by genes in different experiments, phenotype hierarchy and associations between them), protein-protein interaction data, and gene-regulation data.

Proper citation: CMGSDB- Computational Models for Gene Silencing (RRID:SCR_007601) Copy   

•   Source: SciCrunch Registry

http://cogeme.ex.ac.uk/

COGEME is an ongoing BBSRC-funded study to construct a relational database of genomic information from phytopathogenic fungi. This site also hosts microarray data for Blumeria graminis. Expressed sequence tags (ESTs) obtained from eighteen species of plant pathogenic fungi, two species of phytopathogenic oomycete and three species of saprophytic fungi are included here. Hierarchical clustering software was used to classify together ESTs representing the same gene and produce a single contig, or consensus sequence. The unisequence set for each pathogen therefore represents a set of unique gene sequences, each one consisting of either a single EST or a contig sequence made from a group of ESTs. Unisequences were annotated based on top hits against the NCBI non-redundant protein database using blastx.

Proper citation: COGEME Phytopathogenic Fungi and Oomycete EST Database (RRID:SCR_007604) Copy   

•   Source: SciCrunch Registry

http://ppa.bcf.ku.edu/DB_PABP/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. DB-PABP is an attempt to document the publicly available experimentally determined polyanion binding proteins (PABPs). The purpose of the database is to provide life scientists who are interested in PA/PABP interactions with a comprehensive data repository, as well as computer scientists with a publicly available dataset to perform knowledge discovery and datamining studies. The database is manually curated. It uses protein annotations from NCBI protein database and literature information is retrieved from PubMed. Whenever applicable, links to NCBI protein database and PubMed are provided so users may access additional information available in these public databases.

Proper citation: DB-PABP: a database of polyanion binding proteins (RRID:SCR_007603) Copy   

•   Source: SciCrunch Registry

http://www.proteomicsresource.org/default.aspx

Biodefense Proteomics Resource Center presents information on Class A-C biodefense organisms. :This list includes Bacillus anthracis, Brucella abortus, Francisella tularensis, salmonella typhi, salmonella typhimurium, Virbio cholerae, Yersinia pestis, Cryptosporidium parvum, Toxoplasma gondii, Avian influenza, SARS, Monkeypox, Vaccinia, and Variola. For each organism, the page provides a general overview of the organism and the diseases it causes, protein (and protein interaction) data, reagents, and data from experiments performed with this organism. Users may also find links to the NCBI Taxonomy center.

Proper citation: Biodefense Proteomics Resource Center (RRID:SCR_007564) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/clustr/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented June 24, 2013 as per the Miriam database (http://www.ebi.ac.uk/miriam/main/collections/MIR:00000021). The CluSTr database offers an automatic classification of UniProt Knowledgebase and IPI proteins into groups of related proteins. The clustering is based on analysis of all pairwise comparisons between protein sequences. The database provides links to InterPro, which integrates information on protein families, domains and functional sites from PROSITE, PRINTS, Pfam, ProDom, SMART, TIGRFAMs, Gene3D, SUPERFAMILY, PIR Superfamily and PANTHER. To date (2011), CluSTr contains the following information: * 9,450,285 sequences from UniProt Knowledgebase release 15.6 * 308,281 sequences from IPI * 3,636,831,744 similarities, with pairwise alignments generated on-the-fly * 17,616,060 clusters * Clustering for 972 organisms with completely sequenced genomes. For the full list of the genomes see Integr8 * Putative homologues predictions for the above species. For more information see Homologue Selection at Integr8

Proper citation: CluSTr (RRID:SCR_007600) Copy   

•   Source: SciCrunch Registry

http://www.nia.nih.gov/research/nonhuman-primate-tissue-bank-handbook

A repository of tissue collected from nonhuman primate (NHP) species under contractual arrangement with Wisconsin National Primate Research Center (WI NPRC). NIA''''s Nonhuman Primate Tissue Bank collects and archives tissue from necropsies performed at primate centers nationwide. The goal is to collect various tissues from aged monkeys with smaller amounts of the same tissues from young and middle-aged monkeys. Tissue will be provided as: (1) fresh frozen, stored at ����?��������??80 degrees Celsius; (2) formalin fixed; or (3) fresh frozen tissue in OCT medium.Most frozen tissues are provided in approximately 1 gram of tissue per vial. Fixed tissue is available as slides (sections) from paraffin-embedded blocks. Slides can be stained if requested. Tissue from NIA''''s Nonhuman Primate Tissue Bank is available to investigators at academic and nonprofit research institutions who are engaged in funded research on aging. The project name and funding source must accompany all orders. The NIA will not be able to ship non-human primate tissue outside of the United States or US territories. Investigators at for-profit entities are not eligible to purchase tissue from NIA''''s Nonhuman Primate Tissue Bank unless it is for a Small Business Innovation Research grant from NIA. NIA provides the health information as given by the donor site and cannot guarantee other aspects of the health status not explicitly stated in the Vital Statistics Information Sheet. Concerns about the specific health status of donor animals should be indicated on the order form.

Proper citation: NIA Nonhuman Primate Tissue Bank (RRID:SCR_007324) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu/odordb

OdorDb is a database of odorant molecules, which can be searched in a few different ways. One can see odorant molecules in the OdorDB, and the olfactory receptors in ORDB that they experimentally shown to bind. You can search for odorant molecules based on their attributes or identities: Molecular Formula, Chemical Abstracts Service (CAS) Number and Chemical Class. Functional studies of olfactory receptors involve their interactions with odor molecules. OdorDB contains a list of odors that have been identified as binding to olfactory receptors.

Proper citation: Odor Molecules DataBase (RRID:SCR_007286) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/genre/proj/ustilago/

The MIPS Ustilago maydis Genome Database aims to present information on the molecular structure and functional network of the entirely sequenced, filamentous fungus Ustilago maydis. The underlying sequence is the initial release of the high quality draft sequence of the Broad Institute. The goal of the MIPS database is to provide a comprehensive genome database in the Genome Research Environment in parallel with other fungal genomes to enable in depth fungal comparative analysis. The specific aims are to: 1. Generate and assemble Whole Genome Shotgun sequence reads yielding 10X coverage of the U. maydis genome 2. Integrate the genomic sequence assembly with physical maps generated by Bayer CropScience 3. Perform automated annotation of the sequence assembly 4. Align the strain 521 assembly with the FB1 assembly provided by Exelixis 5. Release the sequence assembly and results of our annotation and analysis to public Ustilago maydis is a basidiomycete fungal pathogen of maize and teosinte. The genome size is approximately 20 Mb. The fungus induces tumors on host plants and forms masses of diploid teliospores. These spores germinate and form haploid meiotic products that can be propagated in culture as yeast-like cells. Haploid strains of opposite mating type fuse and form a filamentous, dikaryotic cell type that invades plant tissue to reinitiate infection. Ustilago maydis is an important model system for studying pathogen-host interactions and has been studied for more than 100 years by plant pathologists. Molecular genetic research with U. maydis focuses on recombination, the role of mating in pathogenesis, and signaling pathways that influence virulence. Recently, the fungus has emerged as an excellent experimental model for the molecular genetic analysis of phytopathogenesis, particularly in the characterization of infection-specific morphogenesis in response to signals from host plants. Ustilago maydis also serves as an important model for other basidiomycete plant pathogens that are more difficult to work with in the laboratory, such as the rust and bunt fungi. Genomic sequence of U. maydis will also be valuable for comparative analysis of other fungal genomes, especially with respect to understanding the host range of fungal phytopathogens. The analysis of U. maydis would provide a framework for studying the hundreds of other Ustilago species that attack important crops, such as barley, wheat, sorghum, and sugarcane. Comparisons would also be possible with other basidiomycete fungi, such as the important human pathogen C. neoformans. Commercially, U. maydis is an excellent model for the discovery of antifungal drugs. In addition, maize tumors caused by U. maydis are prized in Hispanic cuisine and there is interest in improving commercial production. The complete putative gene set of the Broad Institute''s second release is loaded into the database and in addition all deviating putative genes from a putative gene set produced by MIPS with different gene prediction parameters are also loaded. The complete dataset will then be analysed, gene predictions will be manually corrected due to combined information derived from different gene prediction algorithms and, more important, protein and EST comparisons. Gene prediction will be restricted to ORFs larger than 50 codons; smaller ORFs will be included only if similarities to other proteins or EST matches confirm their existence or if a coding region was postulated by all prediction programs used. The resulting proteins will be annotated. They will be classified according to the MIPS classification catalogue receiving appropriate descriptions. All proteins with a known, characterized homolog will be automatically assigned to functional categories using the MIPS functional catalog. All extracted proteins are in addition automatically analysed and annotated by the PEDANT suite.

Proper citation: MIPS Ustilago maydis Database (RRID:SCR_007563) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu/odormapdb

OdorMapDB is designed to be a database to support the experimental analysis of the molecular and functional organization of the olfactory bulb and its basis for the perception of smell. It is primarily concerned with archiving, searching and analyzing maps of the olfactory bulb generated by different methods. The first aim is to facilitate comparison of activity patterns elicited by odor stimulation in the glomerular layer obtained by different methods in different species. It is further aimed at facilitating comparison of these maps with molecular maps of the projections of olfactory receptor neuron subsets to different glomeruli, especially for gene targeted animals and for antibody staining. The main maps archived here are based on original studies using 2-deoxyglucose and on current studies using high resolution fMRI in mouse and rat. Links are also provided to sites containing maps by other laboratories. OdorMapDB thus serves as a nodal point in a multilaboratory effort to construct consensus maps integrating data from different methodological approaches. OdorMapDB is integrated with two other databases in SenseLab: ORDB, a database of olfactory receptor genes and proteins, and OdorDB, a database of odor molecules that serve as ligands for the olfactory receptor proteins. The combined use of the three integrated databases allows the user to identify odor ligands that activate olfactory receptors that project to specific glomeruli that are involved in generating the odor activity maps.

Proper citation: Olfactory Bulb Odor Map DataBase (OdorMapDB) (RRID:SCR_007287) Copy   

•   Source: SciCrunch Registry

http://www.homepages.ed.ac.uk/pmckeigu/pooling/poolscore.htm

Software program for analysis of case-control genetic association studies using allele frequency measurements on DNA pools (entry from Genetic Analysis Software)

Proper citation: POOLSCORE (RRID:SCR_007514) Copy   

•   Source: SciCrunch Registry

http://www.chromdb.org

ChromDB is a chromatin database. Three types of sequences are included in the database: genomic-based (predominantly plant sequences); transcript-based (EST contigs or cDNAs for plants lacking a sequenced genome); and NCBI RefSeq sequences for a variety of model animal organisms. The Gene Record Page for any sequence indicates the type of sequence. The broad mission of ChromDB is display, annotate, and curate sequences of two broad functional classes of biologically important proteins: chromatin-associated proteins (CAPs) and RNA interference-associated proteins. Plant proteins are the major focus of the work support by The Plant Genome Research Program (PGRP) of the National Science Foundation. Our intent is to produce intensively curated sequence information and make it available to the research and teaching community in support of comparative analyses toward understanding the chromatin proteome in plants, especially in important crop species. In order to do a comparative analysis, it is necessary to include non-plant proteins in the database. Non-plant genes are not curated to the degree carried out for plants and to automate the process of data import, our non-plant genes are from the RefSeq database of NCBI. We reason that the inclusion of non-plant, model organisms will broaden the relevance and usefulness of ChromDB to the entire chromatin community and will provide a more complete data set for phylogenetic analyses in support of the evolution of the plant chromatin proteome. ChromDB is funded by a grant from the National Science Foundation Plant Genome Research Project(#DBI-0421679).

Proper citation: ChromDB- the chromatin database (RRID:SCR_007597) Copy   

•   Source: SciCrunch Registry

http://oxytricha.princeton.edu/dimorphism/database.htm

IES-MDS DB is a database of macronuclear and micronuclear genes in spirotrichous ciliates. The database contains information on 440 MDS pairs (each pair composed of the MIC and the MAC version of a given MDS), 392 IES and 361 pointer triples (each pointer has two active copies in the MIC and one copy in the MAC) (7). Out of the 440 MDSs, 235 are scrambled, and 65 are in the opposite strand in the MIC. A total of 320 IESs and 202 pointers are scrambled. For each pair of genes in the database the user can see the micronuclear and macronuclear organization and has the option to see all the MDS, IES and pointer sequences. Another option is to download the MIC sequence with the MDSs and pointers in uppercase and the IESs in lowercase. It is also possible to graphically compare the organization of several genes.

Proper citation: Ciliate IES-MDS database (RRID:SCR_007599) Copy   

•   Source: SciCrunch Registry