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https://cell-innovation.nig.ac.jp/GNP/index_e.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Integrated database of experiment data generated by participating research institutes and public databases relating to: 1) transcription starting position of human genes in the human genome, 2) conjunction to control region on transcriptional factors and the human genome 3) protein-protein interaction with a central focus on transcription factors organized for use in genome level research. Gene Search is the function to search the integrated database by using keywords and public IDs. The search results can be visualized by: * Genome Explorer : provides annotation of landmarks (genes, transcription start sites, etc.) aligned in accordance with their genome locations. * PPI Network : provides a graphical view of protein-protein interaction (PPI) network from the experimental data generated under the project and the public datasets. * Expression Profile : clusters genes by expression pattern and display the result with heatmap. The function provides genes which have relation of coregulation and anti-coregulation. * Comparison Viewer : This function gives the view to compare the genomic regions between human and mouse homologous genes. The viewer shows the distribution of transcription start sites (TSS) as the way of separable by tissues or time points with other landmarks on genome region. * Gene Stock : This is the function to save the gene list that you are interested until the session is closed.

Proper citation: Genome Network Platform (RRID:SCR_001737) Copy   

•   Source: SciCrunch Registry

http://www.jubilantbiosys.com/pathart.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. A comprehensive collection of manually curated information from literature as well as public domain databases on signaling and metabolic pathways. PathArt includes a dynamic pathway articulator component, which builds molecular interaction networks from curated databases. PathArt provides a tool for analysis, biological interpretation and visualization of microarray data results in these curated pathways. In addition, PathArt provides a collection of high priority disease and physiology pathways with emphasis on pathway responsive genes and knockouts. The coverage is for pathways of Human, Rat and Mouse for cell specific, tissue specific and organism specific data. The present version of PathArt covers the following: -Includes 3527 regulatory and signaling pathways across diseases and physiologies. -Provides information on 39 high priority diseases, and pathway and disease responsive genes. -Provides pathway information on 23 diverse physiologies. -Covers information on ~8783 Knockouts and ~18000 mutation data points. -Coverage of pathways for Human, Mouse and Rat for cell specificity, tissue specificity and organism specific data.

Proper citation: Pathway Articulator (RRID:SCR_002101) Copy   

•   Source: SciCrunch Registry

http://bioinf.scri.sari.ac.uk/cgi-bin/atnopdb/home

Database of proteins found in the nucleoli of Arabidopsis, identified through proteomic analysis. The Arabidopsis Nucleolar Protein database (AtNoPDB) provides information on the plant proteins in comparison to human and yeast proteins, and images of cellular localizations for over a third of the proteins. A proteomic analysis was carried out of nucleoli purified from Arabidopsis cell cultures and to date 217 proteins have been identified. Many proteins were known nucleolar proteins or proteins involved in ribosome biogenesis. Some proteins, such as spliceosomal and snRNP proteins, and translation factors, were unexpected. In addition, proteins of unknown function which were either plant-specific or conserved between human and plant, and proteins with differential localizations were identified.

Proper citation: Arabidopsis Nucleolar Protein Database (RRID:SCR_001793) Copy   

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http://hupi.ircm.qc.ca/hupi/

The Human Proteotheque Initiative is a multidisciplinary project aimed at building a repertoire of comprehensive maps of human protein interaction networks. The information contained in the Proteotheque is made publicly available through an interactive web site that can be consulted to visualize some of the fundamental molecular connections formed in human cells and to determine putative functions of previously uncharacterized proteins based on guilt by association. The process governing the evolution of HuPI towards becoming a repository of accurate and complete protein interaction maps is described.

Proper citation: Database of the Human Proteotheque Initiative (RRID:SCR_002076) Copy   

•   Source: SciCrunch Registry

http://toxnet.nlm.nih.gov/cgi-bin/sis/htmlgen?HSDB

A toxicology database that focuses on the toxicology of potentially hazardous chemicals. It provides information on human exposure, industrial hygiene, emergency handling procedures, environmental fate, regulatory requirements, nanomaterials, and related areas. The information in HSDB has been assessed by a Scientific Review Panel.

Proper citation: Hazardous Substances Data Bank (RRID:SCR_002374) Copy   

•   Source: SciCrunch Registry

http://research.nhgri.nih.gov/dog_genome/

The Dog Genome Project at the National Human Genome Research Institute is working to develop resources necessary to map and clone canine genes in an effort to utilize dogs as a model system for genetics and cancer research. The US National Human Genome Research Institute (NHGRI) agreed to fund a project to sequence the entire genome of a boxer dog named Tasha, because it recognized the value of the dog as an unrivaled model for the study of human disease. The National Human Genome Research Institute (NHGRI) led the National Institutes of Health's (NIH) contribution to the International Human Genome Project, which had as its primary goal the sequencing of the human genome. This project was successfully completed in April 2003. Now, the NHGRI's mission has expanded to encompass a broad range of studies aimed at understanding the structure and function of the human genome and its role in health and disease. To that end NHGRI supports the development of resources and technology that will accelerate genome research and its application to human health. A critical part of the NHGRI mission continues to be the study of the ethical, legal and social implications (ELSI) of genome research. NHGRI also supports the training of investigators and the dissemination of genome information to the public and to health professionals.

Proper citation: NHGRI Dog Genome Project (RRID:SCR_002256) Copy   

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http://www.allgenes.org/

DoTS (Database Of Transcribed Sequences) is a human and mouse transcript index created from all publicly available transcript sequences. The input sequences are clustered and assembled to form the DoTS Consensus Transcripts that comprise the index. These transcripts are assigned stable identifiers of the form DT.123456 (and are often referred to as dots). The transcripts are in turn clustered to form putative DoTS Genes. These are assigned stable identifiers of the form DG.1234356. As of September 1, 2004, the DoTS annotation team has manually annotated 43,164 human and 78,054 mouse DoTS Transcripts (DTs), corresponding to 3,939 human and 7,752 mouse DoTS Genes (DGs). Use the manually annotated gene query to see the DoTS Transcripts that have been manually annotated. The focus of the DoTS project is integrating the various types of data (e.g., EST sequences, genomic sequence, expression data, functional annotation) in a structured manner which facilitates sophisticated queries that are otherwise not easy to perform. DoTS is built on the GUS Platform which includes a relational database that uses controlled vocabularies and ontologies to ensure that biologically meaningful queries can be posed in a uniform fashion. An easy way to start using the site is to search for DoTS Transcripts using an existing cDNA or mRNA sequence. Click on the BLAST tab at the top of the page and enter your sequence in the form provided. All the transcripts with significant sequence similarity to your query sequence will be displayed. Or use one of the provided queries to retrieve transcripts using a number of criteria. These queries are listed on the query page, which can also be reached by clicking on the tab marked query at the top of the page. Finally, the boolean query page allows these queries to be combined in a variety of ways. Sponsors: Funding provided by -NIH grant RO1-HG-01539-03 -DOE grant DE-FG02-00ER62893

Proper citation: Database of Transcribed Sequences (RRID:SCR_002334) Copy   

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http://sonorus.princeton.edu/hefalmp/

HEFalMp (Human Experimental/FunctionAL MaPper) is a tool developed by Curtis Huttenhower in Olga Troyanskaya's lab at Princeton University. It was created to allow interactive exploration of functional maps. Functional mapping analyzes portions of these networks related to user-specified groups of genes and biological processes and displays the results as probabilities (for individual genes), functional association p-values (for groups of genes), or graphically (as an interaction network). HEFalMp contains information from roughly 15,000 microarray conditions, over 15,000 publications on genetic and physical protein interactions, and several types of DNA and protein sequence analyses and allows the exploration of over 200 H. sapiens process-specific functional relationship networks, including a global, process-independent network capturing the most general functional relationships. Looking to download functional maps? Keep an eye on the bottom of each page of results: every functional map of any kind is generated with a Download link at the bottom right. Most functional maps are provided as tab-delimited text to simplify downstream processing; graphical interaction networks are provided as Support Vector Graphics files, which can be viewed using the Adobe Viewer, any recent version of Firefox, or the excellent open source Inkscape tool.

Proper citation: Human Experimental/FunctionAL MaPper: Providing Functional Maps of the Human Genome (RRID:SCR_003506) Copy   

•   Source: SciCrunch Registry

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

IPI provides a top level guide to the main databases (UniProtKB/Swiss-Prot, UniProtKB/TrEMBL, RefSeq, Ensembl, TAIR, H-InvDB, Vega) that describe the proteomes of higher eukaryotic organisms. IPI: :1. effectively maintains a database of cross references between the primary data sources :2. provides minimally redundant yet maximally complete sets of proteins for featured species (one sequence per transcript) :3. maintains stable identifiers (with incremental versioning) to allow the tracking of sequences in IPI between IPI releases. IPI is updated monthly in accordance with the latest data released by the primary data sources. As previously announced, the closure of IPI has been proposed for some time. Replacement data sets are now available through UniProt for human and mouse; sets for the other species contained within IPI are expected to be included as part of the UniProt release 2011_07. To allow users time to transition to using the new UniProt data sets, IPI releases will continue to be produced throughout the summer. The final release will be made in September 2011. Thereafter, the IPI website will cease to be maintained, although previous releases of the dataset will continue to be available from the FTP site. We would like to thank our users for their support and interest in this service.

Proper citation: IPI (RRID:SCR_003012) Copy   

•   Source: SciCrunch Registry

http://www.biobanque-picardie.com/index_En.php

A secure repository of biological samples and data dedicated for medical and research purposes. These biological samples are linked to consenting patient relative data. Biobanque de Picardie provides quality and traceability services for establishment, conservation and use of biological samples collections. It houses collections of human tissue in a variety of areas of disease. Samples are used in basic research and translational studies, physiopathology of diseases and identification of new diagnostic, and as prognostic or therapeutic biomarkers. Biobanque de Picardie also develops healthy or pathological human primary stem cell banks, such as: mesenchymal stem cells in umbilical cord (HUC-MSC), primary hepatocytes (HPH), peripheral blood mononuclear cells (PBMC), and fibroblasts. Biological samples are stored at - 80 degrees C in electric freezers, at - 196 degrees C in liquid nitrogen or -130 degrees C in nitrogen vapor.

Proper citation: Biobanque de Picardie (RRID:SCR_004731) Copy   

•   Source: SciCrunch Registry

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

A repository for data regarding membrane channels, receptor and neurotransmitters that are expressed in specific types of cells. The database is presently focused on neurons but will eventually include other cell types, such as glia, muscle, and gland cells. This resource is intended to: * Serve as a repository for data on gene products expressed in different brain regions * Support research on cellular properties in the nervous system * Provide a gateway for entering data into the cannonical neuron forms in NeuronDB * Identify receptors across neuron types to aid in drug development * Serve as a first step toward a functional genomics of nerve cells * Serve as a teaching aid

Proper citation: Cell Properties Database (RRID:SCR_007285) Copy   

•   Source: SciCrunch Registry

http://genenest.molgen.mpg.de/

GeneNest is a comprehensive visualization of gene indices of several organisms. The aim of GeneNest is to represent each gene by a single cluster of ESTs and/or mRNAs. Further subdivision of a cluster into contigs may be caused by alternative splicing, genomic sequences, or artifacts like chimeric sequences. Consensus sequence derived from GeneNest contigs are a basis for mapping genes onto the genome, and for analysis of splice isoforms. Organisms included are human, mouse, arabidopsis, zebrafish, drosophila, and sheep. human, mouse, arabidopsis, zebrafish, drosophila, sheep, EST, mRNA, alternative splicing, genomic sequences

Proper citation: GeneNest (RRID:SCR_007677) Copy   

•   Source: SciCrunch Registry

http://zlab.bu.edu/HugeSearch/nph-HugeSearch.cgi

The Human Gene Expression Index (HuGE Index) aims to provide a comprehensive database to further our understanding of the expression of human genes in normal human tissues. mRNA expression levels of thousands of genes are obtained using high-density oligonucleotide array technology and used to create a public database. The website also provides interactive tools for researchers to query and visualize data over the Internet. To facilitate data analysis, genes are alsocross-referenced with their annotation in the LocusLink database at NCBI.

Proper citation: Human Gene Expression Index (RRID:SCR_007726) Copy   

•   Source: SciCrunch Registry

http://superfly.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 23, 2013. Homophila utilizes the sequence information of human disease genes from the NCBI OMIM (Online Mendelian Inheritance in Man) database in order to determine if sequence homologs of these genes exist in the current Drosophila sequence database (FlyBase). Sequences are compared using NCBI's BLAST program. The database is updated weekly and can be searched by human disease, gene name, OMIM number, title, subtitle and/or allelic variant descriptions.

Proper citation: Homophila (RRID:SCR_007717) Copy   

•   Source: SciCrunch Registry

http://natural.salk.edu/CREB/

CREB target gene database that uses a multi-layered approach to predict, validate and characterize CREB target genes. For each gene, the database tries to provide the following information: 1. CREB binding sites on the promoters 2. Promoter occupancy by CREB 3. Gene activation by cAMP in tissues CREB seems to occupy a large number of promoters in the genome (up to ~5000 in human), and the profiles for CREB promoter occupancy are very similar in different human tissues. However, only a small proportion of CREB occupied genes are induced by cAMP in any cell type, possibly reflecting the requirement of additional regulatory partners that assist in recruitment of the transcriptional apparatus. To use the database, choose the species, select the table you want to search, leave field (''All'') and type in the gene you want to search. A table listing the search results will be returned, followed by the description of the table. If no search result is returned, try the official gene symbol or gene ID (locuslink number) from NCBI Entrez Gene to search. Sponsors: This work was supported by National Institutes of Health Grants GM RO1-037828 (to M.M.) and DK068655 (to R.A.Y.).

Proper citation: CRE Binding-protein Target Gene Database (RRID:SCR_008027) Copy   

•   Source: SciCrunch Registry

http://statgen.ncsu.edu/asg/

Alternative splicing essentially increases the diversity of the transcriptome and has important implications for physiology, development and the genesis of diseases. This resource uses a different approach to investigate alternative splicing (instead of the conventional case-by case fashion) and integrates all transcripts derived from a gene into a single splicing graph. ASG is a database of splicing graphs for human genes, using transcript information from various major sources (Ensembl, RefSeq, STACK, TIGR and UniGene). Each transcript corresponds to a path in the graph, and alternative splicing is displayed by bifurcations. This representation preserves the relationships between different splicing variants and allows us to investigate systematically all possible putative transcripts. Web interface allows users to display the splicing graphs, to interactively assemble transcripts and to access their sequences as well as neighboring genomic regions. ASG also provide for each gene, an exhaustive pre-computed catalog of putative transcriptsin total more than 1.2 million sequences. It has found that ~65 of the investigated genes show evidence for alternative splicing, and in 5 of the cases, a single gene might produce over 100 transcripts.

Proper citation: Alternate splicing gallery (RRID:SCR_008129) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://cmbi.bjmu.edu.cn/cmbidata/cgf/CGF_Database/cytokine.medic.kumamoto-u.ac.jp/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. A collection of cDNA, gene and protein records of cytokines deposited in public databases provides various information about the cytokine members of vertebrates in other databases including NCBI GenBank, Swiss-Prot, UniGene, TIGR (The Institute for Genomic Research) Gene Indices, Ensembl, Entrez Gene, Mouse Genome Informatics (MGI) and Rat Genome Database (RGD). It also provides orthologous relationship of cytokine members and includes novel members identified in the databases.

Proper citation: Cytokine Family Database (RRID:SCR_008134) Copy   

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http://animal.dna.affrc.go.jp/agp/index.html

Database of comparative gene mapping between species to assist the mapping of the genes related to phenotypic traits in livestock. The linkage maps, cytogenetic maps, polymerase chain reaction primers of pig, cattle, mouse and human, and their references have been included in the database, and the correspondence among species have been stipulated in the database. AGP is an animal genome database developed on a Unix workstation and maintained by a relational database management system. It is a joint project of National Institute of Agrobiological Sciences (NIAS) and Institute of the Society for Techno-innovation of Agriculture, Forestry and Fisheries (STAFF-Institute), under cooperation with other related research institutes. AGP also contains the Pig Expression Data Explorer (PEDE), a database of porcine EST collections derived from full-length cDNA libraries and full-length sequences of the cDNA clones picked from the EST collection. The EST sequences have been clustered and assembled, and their similarity to sequences in RefSeq, and UniGene determined. The PEDE database system was constructed to store sequences and similarity data of swine full-length cDNA libraries and to make them available to users. It provides interfaces for keyword and ID searches of BLAST results and enables users to obtain sequence data and names of clones of interest. Putative SNPs in EST assemblies have been classified according to breed specificity and their effect on coding amino acids, and the assemblies are equipped with an SNP search interface. The database contains porcine nucleotide sequences and cDNA clones that are ready for analyses such as expression in mammalian cells, because of their high likelihood of containing full-length CDS. PEDE will be useful for researchers who want to explore genes that may be responsible for traits such as disease susceptibility. The database also offers information regarding major and minor porcine-specific antigens, which might be investigated in regard to the use of pigs as models in various medical research applications.

Proper citation: Animal Genome Database (RRID:SCR_008165) Copy   

•   Source: SciCrunch Registry