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http://cssb.biology.gatech.edu/skolnick/files/gpcr/gpcr.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 19,2019.Database of tertiary structural modeling results of threading assembly refinement (TASSER) method for all 907 G protein-coupled receptors (GPCRs) in human genome. All sequences were collected from GPCR database http://www.gpcr.org/7tm/ and http://www.expasy.org/cgi-bin/lists?7tmrlist.txt. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. G protein-coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha) root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness of the in silico models for GPCR functional analysis. Sponsors: GPCR is funded by the University at Buffalo, Buffalo, New York.

Proper citation: Structure modeling of 907 G protein coupled receptors in the human genome (RRID:SCR_008351) Copy   

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http://www.nia.nih.gov/ResearchInformation/ScientificResources/LongitudinalStudies.htm

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 11, 2015. A searchable database for epidemiologic research on aging changes across the lifespan. In 2003, the National Institute on Aging (NIA) established the Longitudinal Data on Aging (LDA) working group to assist with the development of research initiatives for identifying the physiologic and other types of factors across the lifespan, affecting onset and progression of disease with advancing age, as well as elucidation of protective factors contributing to exceptionally healthy aging. This database was developed based on input from the LDA working group which indicated that establishing a database of existing sources of longitudinal data on aging (e.g., ongoing longitudinal cohorts, longitudinal data sets, biospecimen repositories) would be a valuable resource for facilitating future research on aging changes across the lifespan. The longitudinal studies, data sets and repositories included in this database encompass a wide range of age groups (childhood to old age), studies in minority populations, as well as sources of longitudinal data existing in the United States and abroad. Our primary purpose for establishing this database is to provide a resource for potential applicants for grants to the NIA. No part of this database can be used for commercial purposes.

Proper citation: National Institute on Aging, Database of Longitudinal Studies (RRID:SCR_008259) Copy   

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https://www.med.upenn.edu/scxc/

Offers in vivo services specializing in immunodeficient and xenograft models (PDX, humanized immune system). Facility has dedicated BSL2 barrier space equipped with optical imaging, for applications ranging from immunotherapy, cancer biology, infectious diseases and regenerative medicine. Offers services centered around repository of live and fully annotated cells from adult patients with hematologic malignancies (AML, ALL, MPN, MDS), and hematopoietic stem/progenitor cells from healthy donors (BM, CB, and FL).

Proper citation: Pennsylvania University Perelman School of Medicine Stem Cell and Xenograft Core Facility (RRID:SCR_010035) Copy   

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http://www.nimh.nih.gov/about/director/index.shtml

Blog by the NIMH Director, Thomas R. Insel, M.D. Users may sort posts by topic and/or subsribe to the RSS Feed, http://www.nimh.nih.gov/site-info/feed-directors-blog.atom

Proper citation: NIMH Director's Blog (RRID:SCR_008841) Copy   

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http://cgap.nci.nih.gov/Chromosomes/Mitelman

The web site includes genomic data for humans and mice, including transcript sequence, gene expression patterns, single-nucleotide polymorphisms, clone resources, and cytogenetic information. Descriptions of the methods and reagents used in deriving the CGAP datasets are also provided. An extensive suite of informatics tools facilitates queries and analysis of the CGAP data by the community. One of the newest features of the CGAP web site is an electronic version of the Mitelman Database of Chromosome Aberrations in Cancer. The data in the Mitelman Database is manually culled from the literature and subsequently organized into three distinct sub-databases, as follows: -The sub-database of cases contains the data that relates chromosomal aberrations to specific tumor characteristics in individual patient cases. It can be searched using either the Cases Quick Searcher or the Cases Full Searcher. -The sub-database of molecular biology and clinical associations contains no data from individual patient cases. Instead, the data is pulled from studies with distinct information about: -Molecular biology associations that relate chromosomal aberrations and tumor histologies to genomic sequence data, typically genes rearranged as a consequence of structural chromosome changes. -Clinical associations that relate chromosomal aberrations and/or gene rearrangements and tumor histologies to clinical variables, such as prognosis, tumor grade, and patient characteristics. It can be searched using the Molecular Biology and Clinical (MBC) Associations Searcher -The reference sub-database contains all the references culled from the literature i.e., the sum of the references from the cases and the molecular biology and clinical associations. It can be searched using the Reference Searcher. CGAP has developed six web search tools to help you analyze the information within the Mitelman Database: -The Cases Quick Searcher allows you to query the individual patient cases using the four major fields: aberration, breakpoint, morphology, and topography. -The Cases Full Searcher permits a more detailed search of the same individual patient cases as above, by including more cytogenetic field choices and adding search fields for patient characteristics and references. -The Molecular Biology Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to gene rearrangements as a consequence of cytogenetic aberrations. -The Clinical Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to clinical associations of cytogenetic aberrations and/or gene rearrangements. -The Recurrent Chromosome Aberrations Searcher provides a way to search for structural and numerical abnormalities that are recurrent, i.e., present in two or more cases with the same morphology and topography. -The Reference Searcher queries only the references themselves, i.e., the references from the individual cases and the molecular biology and clinical associations. Sponsors: This database is sponsored by the University of Lund, Sweden and have support from the Swedish Cancer Society and the Swedish Children''s Cancer Foundation

Proper citation: Mitelman Database of Chromosome Aberrations in Cancer (RRID:SCR_012877) Copy   

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http://www.epa.gov/iris/

IRIS is a toxicology data file on the National Library of Medicine''s (NLM) Toxicology Data Network. It contains data in support of human health risk assessment. It is compiled by the U.S. Environmental Protection Agency (EPA) and contains over 500 chemical records. It is a compilation of electronic reports on specific substances found in the environment and their potential to cause human health effects. IRIS was initially developed for EPA staff in response to a growing demand for consistent information on substances for use in risk assessments, decision-making and regulatory activities. The information in IRIS is intended for those without extensive training in toxicology, but with some knowledge of health sciences. The Integrated Risk Information System (IRIS) is an electronic database containing information on human health effects that may result from exposure to various substances in the environment. IRIS is prepared and maintained by the EPAs National Center for Environmental Assessment (NCEA) within the Office of Research and Development (ORD). The heart of the IRIS system is its collection of searchable documents that describe the health effects of individual substances and that contain descriptive and quantitative information in the following categories: -Noncancer effects: Oral reference doses and inhalation reference concentrations (RfDs and RfCs, respectively) for effects known or assumed to be produced through a nonlinear (possibly threshold) mode of action. In most instances, RfDs and RfCs are developed for the noncarcinogenic effects of substances. -Cancer effects: Descriptors that characterize the weight of evidence for human carcinogenicity, oral slope factors, and oral and inhalation unit risks for carcinogenic effects. Where a nonlinear mode of action is established, RfD and RfC values may be used.

Proper citation: Integrated Risk Information System (RRID:SCR_013005) Copy   

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http://www.homd.org/index.php

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on April 14,2022. Database of comprehensive information on the approximately 600 prokaryote species that are present in the human oral cavity. The majority of these species are uncultivated and unnamed, recognized primarily by their 16S rRNA sequences. The HOMD presents a provisional naming scheme for the currently unnamed species so that strain, clone, and probe data from any laboratory can be directly linked to a stably named reference entity. The HOMD links sequence data with phenotypic, phylogenetic, clinical, and bibliographic information. Full and partial oral bacterial genome sequences determined as part of this project and the Human Microbiome Project, are being added to the HOMD as they become available. HOMD offers easy to use tools for viewing all publicly available oral bacterial genomes. Data is also downloadable.

Proper citation: HOMD (RRID:SCR_012770) Copy   

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http://www.antibodypedia.com/

Open-access database of antibodies against human proteins developed through collaboration between Antibodypedia AB and the Nature Publishing Group. It aims to provide the scientific community and antibody distributors alike with information on the effectiveness of specific antibodies in specific applications--to help scientists select the right antibody for the right application. Antibodypedia's mission is to promote the functional understanding of the human proteome and expedite analysis of potential biomarkers discovered through clinical efforts. To this end, they have developed an open-access, curated, searchable database containing annotated and scored affinity reagents to aid users in selecting antibodies tailored to specific biological and biomedical assays. They envisage Antibodypedia as a virtual repository of validated antibodies against all human, and ultimately most model-organism, proteins. Such a tool will be exploitable to identify affinity reagents to document protein expression patterns in normal and pathological states and to purify proteins alone and in complex for structural and functional analyses. They hope to promote characterization of the roles and interplay of proteins and complexes in human health and disease. They encourage commercial providers to submit information regarding their inventory of antibodies with links to quality control data. Independent users can submit their own application-specific experimental data using standard validation criteria (supportive or non-supportive) developed with the assistance of an international advisory board recruited from academic research institutions. Users can also comment on specific antibodies without submitting validation data.

Proper citation: Antibodypedia (RRID:SCR_012782) Copy   

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http://geneticassociationdb.nih.gov/

The Genetic Association Database is an archive of human genetic association studies of complex diseases and disorders. The goal of this database is to allow the user to rapidly identify medically relevant polymorphism from the large volume of polymorphism and mutational data, in the context of standardized nomenclature. The data is from published scientific papers. Study data is recorded in the context of official human gene nomenclature with additional molecular reference numbers and links. It is gene centered. That is, each record is a record of a gene or marker. If a study investigated 6 genes for a particular disorder, there will be 6 records. Anyone may view this database and anyone may submit records. You do not have to be an author on the original study to submit a record. All submitted records will be reviewed before inclusion in the archive. Both genetic and environmental factors contribute to human diseases. Most common diseases are influenced by a large number of genetic and environmental factors, most of which individually have only a modest effect on the disease. Though genetic contributions are relatively well characterized for some monogenetic diseases, there has been no effort at curating the extensive list of environmental etiological factors. From a comprehensive search of the MeSH annotation of MEDLINE articles, they identified 3,342 environmental etiological factors associated with 3,159 diseases. They also identified 1,100 genes associated with 1,034 complex diseases from the NIH Genetic Association Database (GAD), a database of genetic association studies. 863 diseases have both genetic and environmental etiological factors available. Integrating genetic and environmental factors results in the etiome, which they define as the comprehensive compendium of disease etiology.

Proper citation: Genetic Association Database (RRID:SCR_013264) Copy   

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http://www.syfpeithi.de/

SYFPEITHI is a database comprising more than 7000 peptide sequences known to bind class I and class II MHC molecules. The entries are compiled from published reports only. It contains a collection of MHC class I and class II ligands and peptide motifs of humans and other species, such as apes, cattle, chicken, and mouse, for example, and is continuously updated. Searches for MHC alleles, MHC motifs, natural ligands, T-cell epitopes, source proteins/organisms and references are possible. Hyperlinks to the EMBL and PubMed databases are included. In addition, ligand predictions are available for a number of MHC allelic products. The database is based on previous publications on T-cell epitopes and MHC ligands. It contains information on: -Peptide sequences -anchor positions -MHC specificity -source proteins, source organisms -publication references Since the number of motifs continuously increases, it was necessary to set up a database which facilitates the search for peptides and allows the prediction of T-cell epitopes. The prediction is based on published motifs (pool sequencing, natural ligands) and takes into consideration the amino acids in the anchor and auxiliary anchor positions, as well as other frequent amino acids. The score is calculated according to the following rules: The amino acids of a certain peptide are given a specific value depending on whether they are anchor, auxiliary anchor or preferred residue. Ideal anchors will be given 10 points, unusual anchors 6-8 points, auxiliary anchors 4-6 and preferred residues 1-4 points. Amino acids that are regarded as having a negative effect on the binding ability are given values between -1 and -3. Sponsors: SYFPEITHI is supported by DFG-Sonderforschungsbereich 685 and theEuropean Union: EU BIOMED CT95-1627, BIOTECH CT95-0263, and EU QLQ-CT-1999-00713.

Proper citation: SYFPEITHI: A Database for MHC Ligands and Peptide Motifs (RRID:SCR_013182) Copy   

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http://www.strokecenter.org/radiology/

The Internet Stroke Center at Washington University is pleased to offer this module for viewing CT, MR, and angiogram images of cerebrovascular and neurological diseases. While this project is still being perfected -- and many more cases have yet to be added -- we hope that you will find this collection useful in your education and practice. The images presented here are for educational use only. This information may not be used for diagnosis or treatment. All images are protected property of the Internet Stroke Center at Washington University and may not be reproduced without permission. Permission may be granted to students and professionals to borrow images from this site for educational purposes and/or presentations; we just ask that an email be sent detailing both the desired material and the intended use. Please direct all comments, questions, and requests to the Site Editor of the Internet Stroke Center.

Proper citation: Neurology Image Library from The Internet Stroke Center (RRID:SCR_013633) Copy   

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http://web.stanford.edu/group/barres_lab/brain_rnaseq.html

Database containing RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of cerebral cortex. Collection of RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of mouse cerebral cortex. RNA-Seq of cell types isolated from mouse and human brain.

Proper citation: Brain RNA-Seq (RRID:SCR_013736) Copy   

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https://hpap.pmacs.upenn.edu

Program is performing deep phenotyping of human endocrine pancreas and its interaction with immune system to better understand cellular and molecular events that precede and lead to beta cell loss in Type-1 Diabetes (T1D) and islet dysfunction in Type-2 Diabetes (T2D).

Proper citation: HIRN Human Pancreas Analysis Program (RRID:SCR_016202) Copy   

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Ratings or validation data are available for this resource

http://www.jdrfnpod.org

A collaborative research project that supports nPOD approved diabetes investigators by freely providing rare and difficult-to-obtain tissues from type 1 and type 2 diabetes donors. Interested researchers are encouraged to apply to obtain nPOD tissues, or to request access to analyze cases in the nPOD Online Pathology site. Interested donors can contact nPOD directly for more information.

Proper citation: Network for Pancreatic Organ Donors with Diabetes (RRID:SCR_014641) Copy   

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http://www.biorag.org/index.php

Bio Resource for array genes is a free online resource for easy access to collective and integrated information from various public biological resources for human, mouse, rat, fly and c. elegans genes. The resource includes information about the genes that are represented in Unigene clusters. This resource provides interactive tools to selectively view, analyze and interpret gene expression patterns against the background of gene and protein functional information. Different query options are provided to mine the biological relationships represented in the underlying database. Search button will take you to the list of query tools available. This Bio resource is a platform designed as an online resource to assist researchers in analyzing results of microarray experiments and developing a biological interpretation of the results. This site is mainly to interpret the unique gene expression patterns found as biological changes that can lead to new diagnostic procedures and drug targets. This interactive site allows users to selectively view a variety of information about gene functions that is stored in an underlying database. Although there are other online resources that provide a comprehensive annotation and summary of genes, this resource differs from these by further enabling researchers to mine biological relationships amongst the genes captured in the database using new query tools. Thus providing a unique way of interpreting the microarray data results based on the knowledge provided for the cellular roles of genes and proteins. A total of six different query tools are provided and each offer different search features, analysis options and different forms of display and visualization of data. The data is collected in relational database from public resources: Unigene, Locus link, OMIM, NCBI dbEST, protein domains from NCBI CDD, Gene Ontology, Pathways (Kegg, Genmapp and Biocarta) and BIND (Protein interactions). Data is dynamically collected and compiled twice a week from public databases. Search options offer capability to organize and cluster genes based on their Interactions in biological pathways, their association with Gene Ontology terms, Tissue/organ specific expression or any other user-chosen functional grouping of genes. A color coding scheme is used to highlight differential gene expression patterns against a background of gene functional information. Concept hierarchies (Anatomy and Diseases) of MESH (Medical Subject Heading) terms are used to organize and display the data related to Tissue specific expression and Diseases. Sponsors: BioRag database is maintained by the Bioinformatics group at Arizona Cancer Center. The material presented here is compiled from different public databases. BioRag is hosted by the Biotechnology Computing Facility of the University of Arizona. 2002,2003 University of Arizona.

Proper citation: Bio Resource for Array Genes Database (RRID:SCR_000748) Copy   

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http://www.eideneurolearningblog.blogspot.com/

Weekly articles related to brain-based learning and learning styles, problem-solving and creativity, kids, families, and parenting, gifted and visual learners, dyslexia, attention deficit disorders, autism, and more.

Proper citation: Eide Neurolearning Blog (RRID:SCR_000680) Copy   

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http://www.unav.es/proteomicsmeeting/video/videos.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. This website contains lecture videos from the events and discussions of the SEProt congress meeting, the theme of which is Human proteome. From Bench to Bedside. Sponsors: These videos are supported by the University of Navarra.

Proper citation: Proteomics and Human Proteome: From Bench to Bedside (RRID:SCR_000285) Copy   

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2039752/

It aims to help researchers to utilize information more efficiently from the published association data. This database is freely accessible only for academic users under the GNU GPL PADB indexes the sentences containing "associat*" or "case-control*" or "cohort*" or "meta-analysis" or "systematic review" or "odds ratio*" or "hazard ratio*" or "risk ratio*" or "relative risk*" from PubMed abstracts and automatically extracts the numeric values of odds ratios, hazard ratios, risk ratios and relative risks data when available. PADB automatically identifies HUGO official symbols of human genes using NCBI Entrez Gene data, and each gene is linked to the UCSC genome browser and International HapMap Project database. Furthermore, molecular pathways listed in BioCarta or KEGG databases can be accessed through the link using CGAP gene annotation data. Also, each record in PADB is linked to GAD or HPLD if it is available from those databases. Currently, (Last Update of Database Contents : Dec. 20, 2006) PADB indexes more than 1,500,000 abstracts including about 190,000 risk values ranging from 0.00001 to 4878.9 and 3,442 human genes related to 461 molecular pathways. Sponsors: This work was supported by the Brain Korea 21 Project for Medical Science, Yonsei University, Seoul, Korea and a faculty research grant of Yonsei University College of Medicine for 2006, Seoul, Korea.

Proper citation: Published Association Database (RRID:SCR_001841) Copy   

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

THIS RESOURCE IS NO LONGER IS SERVICE. Documented on July,29,2022. Surface-based atlases of human, macaque, rat and mouse cerebral and cerebellar cortices derived from structural MRI volumes developed in the Van Essen laboratory can be downloaded by direct links on the SumsDB database and can be viewed using freely available Caret (offline) and WebCaret (online) software. The human and macaque atlases include a large and growing compendium of experimental data pertaining to the structural and functional organization of primate cerebral cortex.

Proper citation: Surface-Based Atlases (RRID:SCR_002099) Copy   

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http://www.dsmz.de/

The DSMZ - Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (German Collection of Microorganisms and Cell Cultures) is the most comprehensive biological resource center in Europe. With more than 18.000 microorganisms, 1.200 plant viruses, 600 human and animal cell lines, 770 plant cell cultures and more than 7.100 cultures deposited for the purposes of patenting, DSMZ has demonstrated their obligation to serve science for decades. Main functions of DSMZ are: - to collect, maintain and store microorganisms and cell lines, as well as other biological material of relevance for applied biology, biotechnology, microbiology, teaching and other areas of research and general application; - to keep the scientific and industrial community informed on the contents of the collections by the means of catalogs, special lists, databases or electronic media; - to supply scientists and institutions with DSMZ cultures, in accordance with national and international laws such as the Infektionsschutzgesetz (Act dealing with protection against infection), the Genetic Engineering Act, the Foreign Trade Laws, the Convention on Biological Diversity as well as the DSMZ terms of supply; - to function as an internationally recognized collection center for the deposit of microorganisms, cell lines, and other biological material which have been cited in scientific literature or which are used in national or international test procedures (e.g. type strains, reference strains for national and international quality control regulations or susceptibility tests, strains with special properties, such as the production of enzymes, degradation of pollutants, host strains for plasmids, etc.); - to act as an International Depositary Authority (IDA) for the deposit of biological material for patent purposes according to the Budapest Treaty; - to act, in a confidential manner, as a center for the safe deposit of biological material; - to act as an advisory center for the scientific community and to offer teaching and service facilities. The DSMZ collections contain over 26 000 cultures (including 6500 patent deposits) representing more than 16 000 cultures of microorganisms (Archaea, Bacteria, plasmids, phages, yeasts, fungi), 750 plant cell cultures, 600 plant viruses, 700 antisera and 580 human and animal cell lines. Unique subcollections are held in the prokaryotes groups of acidophiles, alkaliphiles, halophiles, methanogens, phototrophs, thermophiles, and sulfate reducers. The research is focused on collection related fields which include: - Taxonomy - Evolution - Phylogeny - Microbial diversity and molecular assessment of diversity - Molecular systematics - Research on pathobiological aspects of leukemia-lymphoma cell lines applying classical and molecular genetics, immunological and cell biological methods * Development of cultivation and preservation methods for biological material * Characterization and identification of biological material

Proper citation: German Collection of Microorganisms and Cell Cultures (RRID:SCR_001711) Copy   

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