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http://www.disprot.org/

The Database of Protein Disorder (DisProt) is a curated database that provides information about proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. Users can BLAST sequences, browse by protein name, or view by protein function and functional subclass.

Proper citation: DisProt - Database of Protein Disorder (RRID:SCR_007097) Copy   

•   Source: SciCrunch Registry

http://www.biologie.ens.fr/diatomics/EST3

A searchable databases of diatom ESTs (expressed sequence tags) that can be used to explore diatom biology. Research has generated approximately 90,000 ESTs from P. tricornutum cells grown in a range of conditions. Here we present a database of these sequences, that can be used for digital gene expression studies to explore this organisms responses to a range of environmental conditions. Such studies should provide a foundation for interpreting the ecological success of diatoms.

Proper citation: The Diatom EST Database (RRID:SCR_007090) Copy   

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http://blogs.nature.com/actionpotential

Action Potential is a forum operated by neuroscience editors at Nature for the entire neuroscience community. We''ll discuss what''s new and exciting in science, be it in our journals or elsewhere, as well as science policy and publishing and provide updates from major meetings. Although we provide the opportunity to comment as a service to the community, we do not endorse all viewpoints represented here. To contact the contributors directly with confidential questions or suggestions for future entries, please e-mail n.gray (at) us.nature.com.

Proper citation: Action Potential (RRID:SCR_006836) Copy   

•   Source: SciCrunch Registry

http://www.athamap.de/

Genome wide map of putative transcription factor binding sites in Arabidopsis thaliana genome.Data in AthaMap is based on published transcription factor (TF) binding specificities available as alignment matrices or experimentally determined single binding sites.Integrated transcriptional and post transcriptional data.Provides web tools for analysis and identification of co-regulated genes. Provides web tools for database assisted identification of combinatorial cis-regulatory elements and the display of highly conserved transcription factor binding sites in Arabidopsis thaliana.

Proper citation: AthaMap (RRID:SCR_006717) Copy   

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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   

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http://molonc.bccrc.ca/platforms/btb/

The Molecular Oncology department hosts the breast cancer tumour tissue repository (BREAST-TTR), a project within the agency-wide tumour tissue repository. The BREAST-TTR comprises several important banks of breast tissues, contemporaneous as well as archival. The main banks are: * 3000 frozen breast cancers, linked to 15 year outcomes data from the BCCA Breast Cancer Outcomes Unit. This archival bank consists of frozen tissue, DNA and RNA, and a tissue microarray of the cases. * Live-cryopreserved cancers. At present around 50 individual cases of metastatic breast cancer, with tumour material cryopreserved for subsequent cell culture/xenograft work. * Comptemporary bank. Between the TTR in Victoria and the accrual site in Vancouver, approximately 1300 contemporaneous (within last 4 years) breast cancers with matched normal DNA and outcomes linkages.

Proper citation: British Columbia Breast Cancer Tumour Bank (RRID:SCR_006671) Copy   

•   Source: SciCrunch Registry

http://www.biomedcentral.com/developingcountries/

Free, immediate and permanent online access to the full text of all articles published within its portfolio of over 200 peer-reviewed journals, and through its open access waiver fund, ensuring that scientific authors in low-income countries do not face financial barriers to publishing in open access journals. Open access provides a way for researchers from low-income countries to participate more fully in the international research community, and so BioMed Central has created a set of initiatives designed to increase the visibility and output of scientific research from these countries.

Proper citation: Open Access and the developing world (RRID:SCR_006672) Copy   

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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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://digestive.niddk.nih.gov/statistics/statistics.aspx

A collection of statistics about specific digestive diseases, including prevalence, mortality, care delivery and cost.

Proper citation: Digestive Diseases Statistics for the United States (RRID:SCR_006703) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://omictools.com/fusiondb-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. FusionDB is a database of bacterial and archaeal gene fusion events - also known as Rosetta stones. Gene-fusion events are not the only resource to determine functional links between two proteins. Similar phylogenetic profiles and conserved chromosomal co-localization can also be used as an indicator for such interactions.

Proper citation: FusionDB (RRID:SCR_013314) Copy   

•   Source: SciCrunch Registry

http://epi.grants.cancer.gov/CFR/about_colon.html

It is an international research infrastructure for investigators interested in conducting population and clinic-based interdisciplinary studies on the genetic and molecular epidemiology of colon cancer and its behavioral implications. A central goal of the C-CFR is the translation of this research to the clinical and prevention setting for the benefit of Registry participants and the general public. The C-CFR has information and biospecimens contributed by greater than 11,300 families across the spectrum of risk for colon cancers and from population-based or relative controls. Of particular interest are: identification and characterization of cancer susceptibility genes definition of gene-gene and gene-environment interactions in cancer etiology translational, preventive, and behavioral implications of research findings Special features include: population-based and clinic-based ascertainment systematic collection of validated family history epidemiologic risk factor data clinical and follow-up data biospecimens (including tumor blocks and EBV transformed cell lines) ongoing molecular characterization of the participating families Goals: to contribute to the development of public health measures for the general population by increasing knowledge on genetic factors affecting cancer susceptibility and modification by environmental and lifestyle factors to protect those with increased susceptibility from developing cancer to provide life-prolonging treatment to genetically susceptible individuals Objectives: to establish a comprehensive research resource infrastructure to assist with the implementation of collaborative, interdisciplinary research protocols in the genetic epidemiology of cancer to identify, characterize, and follow-up a cohort of individuals and their family members, spanning the spectrum of cancer risk to identify diverse genetically susceptible populations that could benefit from enrollment in preventive and therapeutic interventions to develop an adaptive and evolving informatics model to support ongoing and future research consortia Sponsor. This study was supported by National Cancer Institute Grants R01 CA47147, R01 CA47305, and R01 CA69664.

Proper citation: Colon CFR (RRID:SCR_013162) Copy   

•   Source: SciCrunch Registry

http://www.abrn.net/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 32,2023.

Proper citation: Austrailasian Biospecimen Network (RRID:SCR_013161) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/thornton-srv/databases/MACiE/

MACiE, which stands for Mechanism, Annotation and Classification in Enzymes, is a collaborative project on enzyme reaction mechanisms. MACiE currently contains 223 fully annotated enzyme reaction mechanisms, which comprise 218 EC numbers (161 EC sub-subclasses) and 310 distinct CATH codes. It is a joint effortbetween the Mitchell Group at the Unilever Centre for Molecular Informatics part of the University of Cambridge and the Thornton Group at the European Bioinformatics Institute.

Proper citation: MACiE (RRID:SCR_013296) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions/index.html

The Division of Acquired Immunodeficiency Syndrome (DAIDS) of the National Institute of Allergy and Infectious Diseases (NIAID) has initiated a project, in collaboration with Southern Research Institute and the National Center for Biotechnology Information (NCBI), designed to compile a comprehensive database of the described interactions between HIV-1 and cellular proteins. The goal of this project is to provide scientists in the field of HIV/AIDS research a concise, yet detailed, summary of all known interactions of HIV-1 proteins with host cell proteins, other HIV-1 proteins, or proteins from disease organisms associated with HIV/AIDS. This database has been designed to track the following information for each protein-protein interaction identified in the literature: * NCBI Reference Sequence (RefSeq) protein accession numbers. * NCBI Entrez Gene ID numbers. * Amino acids from each protein that are known to be involved in the interaction. * Brief description of the protein-protein interaction. * Keywords to support searching for interactions. * National Library of Medicine (NLM) PubMed identification numbers (PMIDs) for all journal articles describing the interaction.

Proper citation: HIV-1, Human Protein Interaction Database (RRID:SCR_013214) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ena/search/

A nucleotide sequence similiary search tool which is far faster than BLAST for large datasets, with only a marginal loss in search sensitivity.

Proper citation: ENA Sequence Search (RRID:SCR_013170) Copy   

•   Source: SciCrunch Registry

http://www.phenomicdb.de/

PhenomicDB is a multi-organism phenotype-genotype database including human, mouse, fruit fly, C.elegans, and other model organisms. The inclusion of gene indices (NCBI Gene) and orthologs (same gene in different organisms) from HomoloGene allows to compare phenotypes of a given gene over many organisms simultaneously. PhenomicDB contains data from publicly available primary databases: FlyBase, Flyrnai.org, WormBase, Phenobank, CYGD, MatDB, OMIM, MGI, ZFIN, SGD, DictyBase, NCBI Gene, and HomoloGene. We brought this wealth of data into a single integrated resource by coarse-grained semantic mapping of the phenotypic data fields, by including common gene indexes (NCBI Gene), and by the use of associated orthology relationships (HomoloGene). PhenomicDB is thought as a first step towards comparative phenomics and will improve the understanding of the gene functions by combining the knowledge about phenotypes from several organisms. It is not intended to compete with the much more dedicated primary source databases but tries to compensate its partial loss of depth by linking back to the primary sources. The basic functional concept of PhenomicDB is an integrated meta-search-engine for phenotypes. Users should be aware that comparison of genotypes or even phenotypes between organisms as different as yeast and man can have serious scientific hurdles. Nevertheless finding that the phenotype of a given mouse gene is described as ��similar to psoriasis�� and at the same time that the human ortholog has been described as a gene causing skin defects can lead to novelty and interesting hypotheses. Similarly, a gene involved in cancer in mammalian organisms could show a proliferation phenotype in a lower organism such as yeast and thus, give further insights to a researcher.

Proper citation: PhenomicDB (RRID:SCR_013051) Copy   

•   Source: SciCrunch Registry