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http://diprodb.fli-leibniz.de

The Dinucleotide Property Database is designed to collect and analyse thermodynamic, structural and other dinucleotide properties. The table presenting all the dinucleotide properties can be pruned and rearranged by different criteria. The database contains different export and analysis functions.

Proper citation: Dinucleotide Property Database (RRID:SCR_007128) Copy   

•   Source: SciCrunch Registry

http://globin.cse.psu.edu/globin/hbvar

HbVar is a relational database of information about hemoglobin variants and mutations that cause thalassemia. The initial data came from Syllabi authored by Prof. Titus H.J. Huisman, Mrs. Marianne F.H. Carver, Dr. Erol Baysal, and Prof. Georgi D. Efremov. This information was converted to a database, and now new entries are added and old entries are corrected by curators. HbVar results from a collaboration among several investigators at Penn State University (USA), INSERM Creteil (France), and Boston University Medical Center (USA). Visit our query page or summary page to see the types of information available.

Proper citation: Database of Human Hemoglobin Variants and Thalassemias (RRID:SCR_007084) Copy   

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http://dptf.cbi.pku.edu.cn/

Database of collected known and predicted transcription factors (TF) of the black cottonwood tree, Populus trichocarpa. They have made extensive annotations, including similarity searches against major databases (Uniprot, RefSeq, EMBL, TRANSFAC et al) and EST expression information extraction from UniGene clusters and microarray expression, to provide comprehensive information for the putative TFs. In addition, multiple alignment of the DNA-binding domain of each family, Neighbor-Joining phylogenetic tree of each family, the GO annotation, homolog with the Database of Arabidopsis Transcription Factors (DATF), the Database of Rice Transcription Factors (DRTF) are included.

Proper citation: Database of Poplar Transcription Factors (RRID:SCR_007080) Copy   

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http://gbrowse.org/

A database and interactive web site for manipulating and displaying annotations on genomes. Features include: detailed views of the genome; use of a variety of premade or personally made glyphs ; customizable order and appearance of tracks by administrators and end-users; search by annotation ID, name, or comment; support of third party annotation using GFF formats; DNA and GFF dumps; connectivity to different databases, including BioSQL and Chado; and a customizable plug-in architecture (e.g. run BLAST, find oligonucleotides, design primers, etc.). GBrowse is distributed as source code for Macintosh OS X, UNIX and Linux platforms, and as pre-packaged binaries for Windows machines. It can be installed using the standard Perl module build procedure, or automated using a network-based install script. In order to use the net installer, you will need to have Perl 5.8.6 or higher and the Apache web server installed. The wiki portion accepts data submissions.

Proper citation: GBrowse (RRID:SCR_006829) Copy   

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http://www.expasy.org/ch2d/

A database of proteins identified by various 2-D PAGE and SDS-PAGE reference maps. Each SWISS-2DPAGE entry contains textual data on one protein, including mapping procedures, physiological and pathological information, experimental data (isoelectric point, molecular weight, amino acid composition, peptide masses) and bibliographical references. In addition to this textual data, SWISS-2DPAGE provides several 2-D PAGE and SDS-PAGE images showing the experimentally determined location of the protein, as well as a theoretical region computed from the sequence protein, indicating where the protein might be found in the gel. Using the database, users can locate these proteins on the 2-D PAGE maps or display the region of a 2-D PAGE map where one might expect to find a protein from UniProtKB/Swiss-Prot.

Proper citation: SWISS-2DPAGE (RRID:SCR_006946) Copy   

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http://neuropathologyblog.blogspot.com/

Blog by Brian E. Moore, MD, discussing issues pertaining to the practice of neuropathology -- including nervous system tumors, neuroanatomy, neurodegenerative disease, muscle and nerve disorders, ophthalmologic pathology, neuro trivia, neuropathology gossip, job listings and anything else that might be of interest to a blue-collar neuropathologist. Brian E. Moore, MD: Neuropathologist, Memorial Medical Center in Springfield, Illinois. Co-Chair, Southern Illinois University School of Medicine Department of Pathology.

Proper citation: neuropathology blog (RRID:SCR_006825) Copy   

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http://wwwmgs.bionet.nsc.ru/mgs/gnw/aspd/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 04, 2014. Curated database on selected from randomized pools proteins and peptides designed for accumulation of experimental data on protein functionality obtained by in vitro directed evolution methods (phage display, ribosome display, SIP etc.) ASPD is integrated by means of hyperlinks with different databases (SWISS-PROT, PDB, PROSITE, etc). The database also contains modules for pairwise correlation analysis and BLAST search.

Proper citation: Artificial Selected Proteins/Peptides Database (RRID:SCR_007557) Copy   

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http://precedings.nature.com/

Nature Precedings is a free online service from NPG that enables researchers in the life sciences to openly share preliminary findings, disseminate emerging results, solicit community feedback, and claim priority over discoveries by posting preprint manuscripts, white papers, technical reports, posters, and presentations. It is a permanent, citable archive for pre-publication research and preliminary findings.

Proper citation: Nature Precedings (RRID:SCR_007438) Copy   

•   Source: SciCrunch Registry

http://bond.unleashedinformatics.com/

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 on August 19,2019.BOND, which requires registration of a free account, is a resource used to perform cross-database searches of available sequence, interaction, complex and pathway information. BOND integrates a range of component databases including GenBank and BIND, the Biomolecular Interaction Network Database. BOND contains 70+ million biological sequences, 33,000 structures, 38,000 GO terms, and over 200,000 human curated interactions contained in BIND, and is open access. BOND serves the interests of the developing global interactome effort encompassing the genomic, proteomic and metabolomic research communities. BOND is the first open access search resource to integrate sequence and interaction information. BOND integrates BLAST functionality, and contains a well-documented API. BOND also stores annotation links for sequences, including links to Genome Ontology descriptions, MedLine abstracts, taxon identifiers, associated structures, redundant sequences, sequence neighbors, conserved domains, data base cross-references, Online Mendalian Inheritance in Man identifiers, LocusLink identifiers and complete genomes. BIND on BOND The Biomolecular Interaction Network Database (BIND), a component database of BOND, is a collection of records documenting molecular interactions. The contents of BIND include high-throughput data submissions and hand-curated information gathered from the scientific literature. BIND is an interaction database with three classifications for molecular associations: molecules that associate with each other to form interactions, molecular complexes that are formed from one or more interaction(s) and pathways that are defined by a specific sequence of two or more interactions.Interactions A BIND record represents an interaction between two or more objects that is believed to occur in a living organism. A biological object can be a protein, DNA, RNA, ligand, molecular complex, gene, photon or an unclassified biological entity. BIND records are created for interactions which have been shown experimentally and published in at least one peer-reviewed journal. A record also references any papers with experimental evidence that support or dispute the associated interaction. Interactions are the basic units of BIND and can be linked together to form molecular complexes or pathways. The BIND interaction viewer is a tool to visualize and analyze molecular interactions, complexes and pathways. The BIND interaction viewer uses Ontoglyphs to display information about a protein via attributes such as molecular function, biological process and sub-cellular localization. Ontoglyphs allow to graphically and interactively explore interaction networks, by visualizing interactions in the context of 34 functional, 25 binding specificity and 24 sub-cellular localization Ontoglyphs categories. We will continue to provide an open access version of BOND, providing its subscribers with free, unlimited access to a core content set. But we are confident you will soon want to upgrade to BONDplus.

Proper citation: Biomolecular Object Network Databank (RRID:SCR_007433) Copy   

•   Source: SciCrunch Registry

http://ncrad.iu.edu/

Cell repository for Alzheimer's disease that collects and maintains biological specimens and associated data. Its data is derived from large numbers of genetically informative, phenotypically well-characterized families with multiple individuals affected with Alzheimer's disease, as well as individuals for case-control studies.

Proper citation: National Cell Repository for Alzheimer's Disease (RRID:SCR_007313) Copy   

•   Source: SciCrunch Registry

http://cocomac.g-node.org/main/index.php?

Online access (html or xml) to structural connectivity ("wiring") data on the Macaque brain. The database has become by far the largest of its kind, with data extracted from more than four hundred published tracing studies. The main database, contains data from tracing studies on anatomical connectivity in the macaque cerebral cortex. Also available are a variety of tools including a graphical simulation workbench, map displays and the CoCoMac-Paxinos-3D viewer. Submissions are welcome. To overcome the problem of divergent brain maps ORT (Objective Relational Transformation) was developed, an algorithmic method to convert data in a coordinate- independent way based on logical relations between areas in different brain maps. CoCoMac data is used to analyze the organization of the cerebral cortex, and to establish its structure- function relationships. This includes multi-variate statistics and computer simulation of models that take into account the real anatomy of the primate cerebral cortex. This site * Provides full, scriptable open access to the data in CoCoMac (you must adhere to the citation policy) * Powers the graphical interface to CoCoMac provided by the Scalable Brain Atlas * Sports an extensive search/browse wizard, which automatically constructs complex search queries and lets you further explore the database from the results page. * Allows you to get your hands dirty, by using the custom SQL query service. * Displays connectivity data in tabular form, through the axonal projections service. CoCoMac 2 was initiated at the Donders Institute for Brain, Cognition and Behaviour, and is currently supported by the German neuroinformatics node and the Computational and Systems Neuroscience group at the Juelich research institute.

Proper citation: CoCoMac (RRID:SCR_007277) Copy   

•   Source: SciCrunch Registry

http://www.agbase.msstate.edu/

A curated, open-source, web-accessible resource for functional analysis of agricultural plant and animal gene products. Our long-term goal is to serve the needs of the agricultural research communities by facilitating post-genome biology for agriculture researchers and for those researchers primarily using agricultural species as biomedical models. AgBase provides tools designed to assist with the analysis of proteomics data and tools to evaluate experimental datasets using the GO. Additional tools for sequence analysis are also provided. We use controlled vocabularies developed by the Gene Ontology (GO) Consortium to describe molecular function, biological process, and cellular component for genes and gene products in agricultural species. AgBase will also accept annotations from any interested party in the research communities. AgBase develops freely available tools for functional analysis, including tools for using GO. We appreciate any and all questions, comments, and suggestions. AgBase uses the NCBI Blast program for searches for similar sequences. And the Taxonomy Browser allows users to find the NCBI defined taxon ID for or taxon name for different organisms.

Proper citation: AgBase (RRID:SCR_007547) Copy   

•   Source: SciCrunch Registry

http://biobases.ibch.poznan.pl/5SData/

A database on nucleotide sequences of 5S rRNAs and their genes. The database contains 1985 primary structures of 5S rRNA and 5S rDNA, and was last updated in 2002, according to the website. They include 60 archaebacterial, 470 eubacterial, 63 plastid, nine mitochondrial and 1383 eukaryotic sequences. The nucleotide sequences of the 5S rRNAs or 5S rDNAs are divided according to the taxonomic position of the source organisms. The sequences for particular organisms can be retrieved as single files using a taxonomic browser or in multiple sequence structural alignments. The multiple sequence alignments of 5S ribosomal RNAs can be downloaded in TAB-delimited and FASTA formats.

Proper citation: 5S Ribosomal RNA Database (RRID:SCR_007545) Copy   

•   Source: SciCrunch Registry

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   

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http://www.jncasr.ac.in/cremofac/

CREMOFAC is a database for chromatin remodeling factors has been developed. The database harbors 64 types of remodeling factors from 49 different organisms reported in literature and facilitates a comprehensive search for them. In addition, it also provides in-depth information for the factors reported in the three widely studied mammals namely, human, mouse and rat. Further, information on literature, pathways, and phylogenetic relationships has also been covered.

Proper citation: CREMOFAC: A web-database of Chromatin Remodeling Factors (RRID:SCR_007613) Copy   

•   Source: SciCrunch Registry

http://pgrc.ipk-gatersleben.de/cr-est

The Crop EST Database (CR-EST) is a public available online resource providing access to sequence, classification, clustering, and annotation data of crop EST projects at the IPK. Summarized numbers about genomic data of species are listed in tables. The main database content is original sequence data and cDNA library information from different organisms as well as results from BlastX searches against major protein sequence databases contained in NRPEP. Additionally sequence alignments of stackPACK clustering projects are available. This web application allows to BLAST against CR-EST ESTs and to query and retrieve data from Gene Ontology and metabolic pathway annotations as well as sequence similarities from stored results of BLASTX searches against the NRPEP database. CR-EST also features interactive JAVA-based tools, such as open reading frame visualization and explorative analysis of Gene Ontology mappings to ESTs.

Proper citation: CR-EST - Crop ESTs (RRID:SCR_007612) 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.mrc-lmb.cam.ac.uk/genomes/FlyTF/

The FlyTF database contains information on the manual curation of FlyBase identifiers based on FlyBase/Gene Ontology annotation or the DBD Transcription Factor Database. FlyBase identifiers are putative site-specific transcription factors. There are currently1052 of them in this database.

Proper citation: FlyTF (RRID:SCR_007611) Copy   

•   Source: SciCrunch Registry

http://corg.molgen.mpg.de

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. Non-coding DNA segments that are conserved across multiple homologous genomic sequences are good indicators of putative regulatory elements. We use a systematic approach to delineate such conserved non-coding blocks from a collection of vertebrate species. Upstream regions of homologous gene pairs from man, rhesus monkey, mouse, rat, dog, cow, chicken, tetraodon, zebrafish and xenopus are considered for this purpose. Pairwise as well as Multiple alignments based on the pairwise ones are available. Sequence conservation in non-coding, upstream regions of orthologous genes from man and mouse is likely to reflect common regulatory DNA sites. Motivated by this assumption we have delineated a catalogue of conserved non-coding sequence blocks and provide the CORG-''COmparative Regulatory Genomics''-database. The data were computed based on statistically significant local suboptimal alignments of 15 kb regions upstream of the translation start sites of, currently, 10 793 pairs of orthologous genes. The resulting conserved non-coding blocks were annotated with EST matches for easier detection of non-coding mRNA and with hits to known transcription factor binding sites. CORG data are accessible from the ENSEMBL web site via a DAS service as well as a specially developed web service for query and interactive visualization of the conserved blocks and their annotation.

Proper citation: CORG - A database for COmparative Regulatory Genomics (RRID:SCR_007610) Copy   

•   Source: SciCrunch Registry