Tools   Select Another Resource Report Type

http://tritrypdb.org/tritrypdb/

An integrated genomic and functional genomic database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. ''''User Comments'''' may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate. TriTrypDB provides programmatic access to its searches, via REST Web Services. The result of a web service request is a list of records (genes, ESTs, etc) in either XML or JSON format. REST services can be executed in a browser by typing a specific URL. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).

Proper citation: TriTrypDB (RRID:SCR_007043) Copy   

•   Source: SciCrunch Registry

http://yetfasco.ccbr.utoronto.ca/

Collection of all available transcription factor (TF) specificities for the yeast Saccharomyces cerevisiae in Position Frequency Matrix (PFM) or Position Weight Matrix (PWM) formats. The specificities are evaluated for quality using several metrics. With this website, you can scan sequences with the motifs to find where potential binding sites lie, inspect precomputed genome-wide binding sites, find which TFs have similar motifs to one you have found, and download the collection of motifs. Submissions are welcome.

Proper citation: YeTFaSCo (RRID:SCR_006893) Copy   

•   Source: SciCrunch Registry

http://sites.huji.ac.il/malaria/

Data set of metabolic pathways for the malaria parasite based on the present knowledge of parasite biochemistry and on pathways known to occur in other unicellular eukaryotes. This site extracted the pertinent information from the universal sites and presented them in an educative and informative format. The site also includes, cell-cell interactions (cytoadherence and rosetting), invasion of the erythrocyte by the parasite and transport functions. It also contains an artistic impression of the ultrastructural morphology of the interaerythrocytic cycle stages and some details about the morphology of mitochondria and the apicoplast. Most pathways are relevant to the erythrocytic phase of the parasite cycle. All maps were checked for the presence of enzyme-coding genes as they are officially annotated in the Plasmodium genome (http://plasmodb.org/). The site is constructed in a hierarchical pattern that permits logical deepening: * Grouped pathways of major chemical components or biological process ** Specific pathways or specific process *** Chemical structures of substrates and products or process **** Names of enzymes and their genes or components of process Each map is linked to other maps thus enabling to verify the origin of a substrate or the fate of a product. Clicking on the EC number that appears next to each enzyme, connects the site to BRENDA, SWISSPROT ExPASy ENZYME, PlasmoDB and to IUBMB reaction scheme. Clicking of the name of a metabolite, connects the site to KEGG thus providing its chemical structure and formula. Next to each enzyme there is a pie that depicts the stage-dependent transcription of the enzyme''s coding gene. The pie is constructed as a clock of the 48 hours of the parasite cycle, where red signifies over-transcription and green, under-transcription. Clicking on the pie links to the DeRisi/UCSF transcriptome database.

Proper citation: Malaria Parasite Metabolic Pathways (RRID:SCR_007072) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/node/305

The Connectivity Map aims to generate a detailed map that links gene patterns associated with disease to corresponding patterns produced by drug candidates and a variety of genetic manipulations. The Connectivity Map is the most comprehensive effort yet for using genomics in a drug-discovery framework. It allows researchers to screen compounds against genome-wide disease signatures, rather than a pre-selected set of target genes. Drugs are paired with diseases using sophisticated pattern-matching methods with a high level of resolution and specificity. To build a Connectivity Map, the Broad Institute brings together molecular biologists, genomics specialists, computational scientists, pharmacologists, chemists and chemical biologists, as well as expertise from across the breadth and depth of medicine.Connectivity map is a large public database of signatures of drugs and genes, and pattern-matching tools to detect similarities among these signatures.The parent site for the Broad Institute at MIT has a software library of software applications developed for use in genetic analysis.

Proper citation: National Institute of Mental Health (NIMH) Human Genetics Initiative (RRID:SCR_007436) Copy   

•   Source: SciCrunch Registry

http://www.geisha.arizona.edu/geisha/

Online repository for chicken in situ hybridization information. This site presents whole mount in situ hybridization images and corresponding probe and genomic information for genes expressed in chicken embryos in Hamburger Hamilton stages 1-25 (0.5-5 days). The GEISHA project began in 1998 to investigate using high throughput whole mount in situ hybridization to identify novel, differentially expressed genes in chicken embryos. An initial expression screen of approximately 900 genes demonstrated feasibility of the approach, and also highlighted the need for a centralized repository of in situ hybridization expression data. Objectives: The goals of the GEISHA project are to obtain whole mount in situ hybridization expression information for all differentially expressed genes in the chicken embryo between HH stages 1-25, to integrate expression data with the chicken genome browsers, and to offer this information through a user-friendly graphical user interface. In situ hybridization images are obtained from three sources: 1. In house high throughput in situ hybridization screening: cDNAs obtained from several embryonic cDNA libraries or from EST repositories are screened for expression using high throughput in situ hybridization approaches. 2. Literature curation: Agreements with journals permit posting of published in situ hybridization images and related information on the GEISHA site. 3. Unpublished in situ hybridization information from other laboratories: laboratories generally publish only a small fraction of their in situ hybridization data. High quality images for which probe identity can be verified are welcome additions to GEISHA.

Proper citation: GEISHA - Gallus Expression in Situ Hybridization Analysis: A Chicken Embryo Gene Expression Database (RRID:SCR_007440) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/

Non profit research organization for genome sequences to advance understanding of biology of humans and pathogens in order to improve human health globally. Provides data which can be translated for diagnostics, treatments or therapies including over 100 finished genomes, which can be downloaded. Data are publicly available on limited basis, and provided more extensively upon request.

Proper citation: Wellcome Trust Sanger Institute; Hinxton; United Kingdom (RRID:SCR_011784) Copy   

•   Source: SciCrunch Registry

http://www.g-language.org/GenomeProjector/

A searchable database browser with zoomable user interface using Google Map API. Genome Projector currently contains 4 views: Genome map, Plasmid map, Pathway map, and DNA walk.

Proper citation: Genome Projector (RRID:SCR_011790) Copy   

•   Source: SciCrunch Registry

http://www.genestack.com

A universal collaborative platform for bioinformatics application development that allows users to store and share large data sets securely within and across organizations, with free access to public data from major databases. The platform includes open-source and proprietary genomics applications, working together independent of file formats. For developers an SDK, APIs and a marketplace are provided.

Proper citation: Genestack (RRID:SCR_011885) Copy   

•   Source: SciCrunch Registry

http://www.genboree.org/java-bin/EpigenomeAtlas/workbench.jsp?isPublic=yes&context=EpigenomeAtlas

Service where users are able to upload and store data, access bioinformatics tools, and perform analyses.

Proper citation: Genboree Workbench (RRID:SCR_011864) Copy   

•   Source: SciCrunch Registry

http://bioinfo-out.curie.fr/projects/snp_gap/

Software for automatic detection of absolute segmental copy numbers and genotype status in complex cancer genome profiles measured by single-nucleotide polymorphism (SNP) arrays. The method is based on pattern recognition of segmented and smoothed copy number and allelic imbalance profiles. The method performs well even for poor-quality data, low tumor content, and highly rearranged tumor genomes.

Proper citation: Genome Alteration Print (RRID:SCR_012016) Copy   

•   Source: SciCrunch Registry

http://www.hgvs.org

The Society aims to foster discovery and characterization of genomic variations including population distribution and phenotypic associations. We promote collection, documentation and free distribution of genomic variation information and associated clinical variations and endeavor to foster the development of the necessary methodology and informatics. Mission Statement To enhance human health through identification and characterization of changes in the genome that lead to susceptibility to illness. To this end, to collate the genomic information necessary for molecular diagnosis, research on basic mechanisms and design of treatments of human ailments. Society Journal Human Mutation is the Society journal. Members will receive a reduced subscription to the journal if they choose to subscribe. Meetings The Society holds two scientific meetings per year. One as a satellite to either the HUGO (Human Genome Organization) annual meeting or the ESHG (European Society of Human Genetics) annual meeting and one meeting is a satellite to the ASHG (American Society of Human Genetics annual meeting. The meetings are a forum for scientists to exchange ideas and form collaborations. Prominent speakers in the field are invited as well as a call for abstracts at large. The meetings are designed to update and increase knowledge of human genome variation and generally attract a stimulating and interesting collection of abstracts in all fields of human genome variation making it an ideal forum to share information and results. Past themes include: copy number variation, pathogenic or not?, pharmacogenomics, new DNA sequencing technologies, and genotype to pheontype relationships. We invite members and non-members alike to attend these meetings. The Society holds the Annual General Meeting of the members after the scientific meeting that is a satellite of the ASHG. Exhibitor''s booths The Society usually takes out an Exhibitor''s booth at the American & European Societies of Human Genetics annual meetings and sometimes the HUGO HGM meeting. GUIDELINES & RECOMMENDATIONS Members of the Society have formulated Guidelines & Recommendations on a number of topics, but especially for nomenclature of gene variations and guidelines on variation databases.

Proper citation: Human Genome Variation Society (RRID:SCR_012989) Copy   

•   Source: SciCrunch Registry

http://commonfund.nih.gov/GTEx/

Project to study human gene expression and regulation in multiple tissues, providing valuable insights into mechanisms of gene regulation and its disease related perturbations. Genetic variation between individuals will be examined for correlation with differences in gene expression level to identify regions of the genome that influence whether and how much a gene is expressed. Includes initiatives: Novel Statistical Methods for Human Gene Expression Quantitative Trait Loci (eQTL) Analysis ,Laboratory, Data Analysis, and Coordinating Center (LDACC), caHUB Acquisition of Normal Tissues in Support of GTEx Project.

Proper citation: Genotype-Tissue Expression (RRID:SCR_013042) Copy   

•   Source: SciCrunch Registry

http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml

This resource gives information about the U.S. Human Genome Project, which was was a 13-year effort to to discover all the estimated 20,000-25,000 human genes and make them accessible for further biological study. The primary project goals were to: - identify all the approximately 20,000-25,000 genes in human DNA, - determine the sequences of the 3 billion chemical base pairs that make up human DNA, - store this information in databases, - improve tools for data analysis, - transfer related technologies to the private sector, and - address the ethical, legal, and social issues (ELSI) that may arise from the project. To help achieve these goals, researchers also studied the genetic makeup of several nonhuman organisms. These include the common human gut bacterium Escherichia coli, the fruit fly, and the laboratory mouse. These parallel studies helped to develop technology and interpret human gene function. Sponsors: The DOE Human Genome Program and the NIH National Human Genome Research Institute (NHGRI) together sponsored the U.S. Human Genome Project.

Proper citation: Human Genome Project Information (RRID:SCR_013028) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/nsegata/phylophlan/wiki/Home

Software pipeline for reconstructing highly accurate and resolved phylogenetic trees based on whole-genome sequence information. Pipeline is scalable to thousands of genomes and uses the most conserved 400 proteins for extracting the phylogenetic signal. PhyloPhlAn also implements taxonomic curation, estimation, and insertion operations., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PhyloPhlAn (RRID:SCR_013082) Copy   

•   Source: SciCrunch Registry

http://genetics.bwh.harvard.edu/pph2/

Software tool which predicts possible impact of amino acid substitution on structure and function of human protein using straightforward physical and comparative considerations. PolyPhen-2 is new development of PolyPhen tool for annotating coding nonsynonymous SNPs.

Proper citation: PolyPhen: Polymorphism Phenotyping (RRID:SCR_013189) Copy   

•   Source: SciCrunch Registry

http://web.bioinformatics.ic.ac.uk/eqtlexplorer/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 1,2023. eQTL Explorer was developed as a computational resource to visualize and explore data from combined genome-wide expression and linkage studies is essential for the development of testable hypotheses. This visualization tool stores expression profiles, linkage data and information from external sources in a relational database and enables simultaneous visualization and intuitive interpretation of the combined data via a Java graphical interface. eQTL Explorer also provides a new and powerful tool to interrogate these very large and complex datasets. eQTLexplorer allows users to mine and understand data from a repository of genetical genomics experiments. It will graphically display eQTL information based on a certain number of selection criteria, including: tissue type, p-value, cis/trans, probeset Affymetrix id and PQTL type. Sponsors: This work was funded by the MRC Clinical Sciences Centre and the Wellcome Trust programme for Cardiovascular Functional Genomics.

Proper citation: eQTL Visualization Tool (RRID:SCR_013413) Copy   

•   Source: SciCrunch Registry

http://www.mrc-lmb.cam.ac.uk/genomes/dolop/

DOLOP is an exclusive knowledge base for bacterial lipoproteins by processing information from 510 entries to provide a list of 199 distinct lipoproteins with relevant links to molecular details. Features include functional classification, predictive algorithm for query sequences, primary sequence analysis and lists of predicted lipoproteins from 43 completed bacterial genomes along with interactive information exchange facility. This website along will have additional information on the biosynthetic pathway, supplementary material and other related figures. DOLOP also contains information and links to molecular details for about 278 distinct lipoproteins and predicted lipoproteins from 234 completely sequenced bacterial genomes. Additionally, the website features a tool that applies a predictive algorithm to identify the presence or absence of the lipoprotein signal sequence in a user-given sequence. The experimentally verified lipoproteins have been classified into different functional classes and more importantly functional domain assignments using hidden Markov models from the SUPERFAMILY database that have been provided for the predicted lipoproteins. Other features include: primary sequence analysis, signal sequence analysis, and search facility and information exchange facility to allow researchers to exchange results on newly characterized lipoproteins.

Proper citation: DOLOP: A Database of Bacterial Lipoproteins (RRID:SCR_013487) Copy   

•   Source: SciCrunch Registry

http://ctb.pku.edu.cn/main/SheGroup/Software/MED2.htm

A non-supervised gene prediction algorithm for prokaryotic genomes with multivariate entropy distance method.

Proper citation: MED (RRID:SCR_013403) Copy   

•   Source: SciCrunch Registry

http://roadmapepigenomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 11, 2022. Project for human epigenomic data from experimental pipelines built around next-generation sequencing technologies to map DNA methylation, histone modifications, chromatin accessibility and small RNA transcripts in stem cells and primary ex vivo tissues selected to represent normal counterparts of tissues and organ systems frequently involved in human disease. Consortium expects to deliver collection of normal epigenomes that will provide framework or reference for comparison and integration within broad array of future studies. Consortium is also committed to development, standardization and dissemination of protocols, reagents and analytical tools to enable research community to utilize, integrate and expand upon this body of data.

Proper citation: Roadmap Epigenomics Project (RRID:SCR_008924) Copy   

•   Source: SciCrunch Registry

http://research-pub.gene.com/gmap/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. A software program for mapping and aligning cDNA sequences to a genome. The program maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. The program generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. Methodology underlying the program includes a minimal sampling strategy for genomic mapping, oligomer chaining for approximate alignment, sandwich DP for splice site detection, and microexon identification with statistical significance testing.

Proper citation: GMAP (RRID:SCR_008992) Copy   

•   Source: SciCrunch Registry