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http://ki.se/en/meb/twingene-and-genomeeutwin

In collaboration with GenomeEUtwin, the TwinGene project investigates the importance of quantitative trait loci and environmental factors for cardiovascular disease. It is well known that genetic factors are of considerable importance for some familial lipid syndromes and that Type A Behavior pattern and increased lipid levels infer increased risk for cardiovascular disease. It is furthermore known that genetic factors are of importance levels of blood lipid biomarkers. The interplay of genetic and environmental effects for these risk factors in a normal population is less well understood and virtually unknown for the elderly. In the TwinGene project twins born before 1958 are contacted to participate. Health and medication data are collected from self-reported questionnaires, and blood sampling material is mailed to the subject who then contacts a local health care center for blood sampling and a health check-up. In the simple health check-up, height, weight, circumference of waist and hip, and blood pressure are measured. Blood is sampled for DNA extraction, serum collection and clinical chemistry tests of C-reactive protein, total cholesterol, triglycerides, HDL and LDL cholesterol, apolipo��protein A1 and B, glucose and HbA1C. The TwinGene cohort contains more than 10000 of the expected final number of 16000 individuals. Molecular genetic techniques are being used to identify Quantitative Trait Loci (QTLs) for cardiovascular disease and biomarkers in the TwinGene participants. Genome-wide linkage and association studies are ongoing. DZ twins have been genome-scanned with 1000 STS markers and a subset of 300 MZ twins have been genome-scanned with Illumina 317K SNP platform. Association of positional candidate SNPs arising from these genomscans are planned. The TwinGene project is associated with the large European collaboration denoted GenomEUtwin (www.genomeutwin.org, see below) which since 2002 has aimed at gathering genetic data on twins in Europe and setting up the infrastructure needed to enable pooling of data and joint analyses. It has been the funding source for obtaining the genome scan data. Types of samples: * EDTA whole blood * DNA * Serum Number of sample donors: 12 044 (sample collection completed)

Proper citation: KI Biobank - TwinGene (RRID:SCR_006006) Copy   

•   Source: SciCrunch Registry

http://protists.ensembl.org

The Ensembl Genomes project produces genome databases for important species from across the taxonomic range, using the Ensembl software system. Five sites are now available, one of which is Ensembl Protists, which houses protists species. Sponsors: EnsembProtists is a project run by EMBL - EBI to maintain annotation on selected genomes, based on the software developed in the Ensembl project developed jointly by the EBI and the Wellcome Trust Sanger Institute.

Proper citation: Ensembl Protists (RRID:SCR_013154) Copy   

•   Source: SciCrunch Registry

http://giardiadb.org

GiardiaDB is a resource for information on Giardia lamblia. It contains gene information, including genomic attributes, protein expression patterns, evolution, and EST sequence information. The website provides tools for BLASTing, sequence retrieval, graphic visualization, and PubMed information.

Proper citation: GiardiaDB (RRID:SCR_013377) Copy   

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http://epsf.bmad.bii.a-star.edu.sg/cube/db/html/home.html

Cube-DB is a database of pre-evaluated conservation and specialization scores for residues in paralogous proteins belonging to multi-member families of human proteins. Protein family classification follows (largely) the classification suggested by HUGO Gene Nomenclature Committee. Sets of orhtologous protein sequences were generated by mutual-best-hit strategy using full vertebrate genomes available in Ensembl. The scores, described on documentation page, are assigned to each individual residue in a protein, and presented in the form of a table (html or downloadable xls formats) and mapped, when appropriate, onto the related structure (Jmol, Pymol, Chimera).

Proper citation: Cube-DB (RRID:SCR_013233) Copy   

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http://planteome.org

An international collaborative effort to develop and enrich new and existing reference ontologies for plants, improve ontology use and cross-references, and to develop data annotation standards. Users can search for ontology terms and bioentities and submit the ontology-related term requests by visiting the following GitHub request trackers.

Proper citation: Planteome (RRID:SCR_014411) Copy   

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http://www.hgsc.bcm.tmc.edu/

Center for high-throughput DNA sequence generation and the accompanying analysis. The sequence data generated by the center's machines are analyzed in a complex bioinformatics pipeline, and the data are deposited regularly in the public databases at the National Center for Biotechnology Information (NCBI).

Proper citation: Baylor College of Medicine Human Genome Sequencing Center (RRID:SCR_013605) Copy   

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http://signal.salk.edu/cgi-bin/RiceGE

Gene database for Japonica rice. RiceGE is associated with SIGnAL at the Salk Institute.

Proper citation: RiceGE (RRID:SCR_015061) Copy   

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http://hb.flatironinstitute.org/

Formerly known as GIANT (Genome-scale Integrated Analysis of gene Networks in Tissues), HumanBase applies machine learning algorithms to learn biological associations from massive genomic data collections. These integrative analyses reach beyond existing "biological knowledge" represented in the literature to identify novel, data-driven associations.

Proper citation: HumanBase (RRID:SCR_016145) Copy   

•   Source: SciCrunch Registry

http://gnomad.broadinstitute.org/

Database that aggregates exome and genome sequencing data from large-scale sequencing projects. The gnomAD data set contains individuals sequenced using multiple exome capture methods and sequencing chemistries. Raw data from the projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects.

Proper citation: Genome Aggregation Database (RRID:SCR_014964) Copy   

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http://www.regulomedb.org/

Database that annotates SNPs with known and predicted regulatory elements in intergenic regions of H. sapiens genome. Known and predicted regulatory DNA elements include regions of DNAase hypersensitivity, binding sites of transcription factors, and promoter regions that have been biochemically characterized to regulation transcription. Source of these data include public datasets from GEO, ENCODE project, and published literature.

Proper citation: RegulomeDB (RRID:SCR_017905) Copy   

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http://mouse.brain-map.org/

Genome wide database of gene expression in mouse brain. Genome-wide atlas of gene expression in the adult mouse brain.

Proper citation: ABA Mouse Brain: Atlas (RRID:SCR_017479) Copy   

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http://software.broadinstitute.org/gsea/msigdb/index.jsp

Collection of annotated gene sets for use with Gene Set Enrichment Analysis (GSEA) software.

Proper citation: Molecular Signatures Database (RRID:SCR_016863) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

https://www.gencodegenes.org

Human and mouse genome annotation project which aims to identify all gene features in the human genome using computational analysis, manual annotation, and experimental validation.

Proper citation: GENCODE (RRID:SCR_014966) Copy   

•   Source: SciCrunch Registry

http://david.abcc.ncifcrf.gov/content.jsp?file=/ease/ease1.htm&type=1

Windows(c) desktop software application, customizable and standalone, that facilitates the biological interpretation of gene lists derived from the results of microarray, proteomic, and SAGE experiments. Provides statistical methods for discovering enriched biological themes within gene lists, generates gene annotation tables, and enables automated linking to online analysis tools. Offers statistical models to deal with multi-test comparison problem. Platform: Windows compatible

Proper citation: EASE: the Expression Analysis Systematic Explorer (RRID:SCR_013361) Copy   

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http://www-sequence.stanford.edu/group/yeast_deletion_project/

Database and project to reveal open reading frames (ORFs) in the yeast genome in order to discover their functions. A PCR-based gene deletion strategy is used to assign functions through phenotypic analysis of mutants.

Proper citation: Saccharomyces Genome Deletion Project (RRID:SCR_014961) Copy   

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https://www.4dnucleome.org

Research project to understand the principles underlying nuclear organization in space and time, the role nuclear organization plays in gene expression and cellular function, and how changes in nuclear organization affect normal development and diseases. Portal provides free access to datasets, software packages, and protocols to advance biomedical research of nuclear architecture. Aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes.

Proper citation: 4D Nucleome (RRID:SCR_016925) Copy   

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http://cab.spbu.ru/software/rnaquast/

Software tool for evaluating RNA-Seq assembly quality and benchmarking transcriptome assemblers using reference genome and gene database. Capable to estimate gene database coverage by raw reads and de novo quality assessment using third party software.

Proper citation: rnaQUAST (RRID:SCR_016994) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/genbank/wgs/

Project for assemblies of incomplete genomes or incomplete chromosomes of prokaryotes or eukaryotes that are being sequenced by a whole genome shotgun strategy. WGS projects may be annotated, but annotation is not required. The nucleotide and protein data from all WGS projects go into the BLAST database.

Proper citation: Whole Genome Shotgun (WGS) Project (RRID:SCR_016637) Copy   

•   Source: SciCrunch Registry

https://github.com/asdcid/Gene-conservation-informed-contig-alignment

Software tool for separation haplotigs from genome assembly. Method to separate haplotigs based on sequence similarity.

Proper citation: Gene-conservation-informed-contig-alignment (RRID:SCR_017617) Copy   

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https://github.com/BGI-Qingdao/TGS-GapCloser

Software tool that uses long reads to enhance genome assembly. Fast and accurate gap closing software tool that uses low coverage of error-prone long reads generated by third generation sequence techniques (Pacbio, Oxford Nanopore, etc.) or preassembled contigs for large genomes.

Proper citation: TGS-GapCloser (RRID:SCR_017633) Copy   

•   Source: SciCrunch Registry