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http://www.scripps.edu/florida/technologies/cbs/index.html

Core facility that provides access to genome-wide collections of cDNAs and siRNAs that can be used to interrogate cellular models of signal transduction pathways and phenotypes. Services include cell lines, hit-picking clones and various screening sets, and access to equipment.Provides instruments:Analyst Molecular Devices,Embla Molecular Devices, Envision Perkin Elmer, Platemate Matrix, Tecan M200, Wellmate Matrix.

Proper citation: Scripps Research Institute Florida Cell Based High Throughput Screening Core Facility (RRID:SCR_014877) Copy   

•   Source: SciCrunch Registry

https://www.wadsworth.org/research/cores/applied-genomics

Advanced Genomic Technologies Cluster provides next-generation sequencing and Sanger sequencing. Next-generation sequencing services are provided using Illumina MiSeq and NextSeq sequencers. Services are available for amplicon re-sequencing, viral or microbial whole genome sequencing and 16S microbiome sequencing. Sanger DNA Sequencing can be performed on DNA templates such as PCR products and plasmids using ABI 3730xl and ABI3130xl instruments.

Proper citation: New York State Advanced Genomic Technology Core Facility (RRID:SCR_017687) Copy   

•   Source: SciCrunch Registry

https://cell-innovation.nig.ac.jp/maser/Tools/visualization_top_en.html

One stop platform for NGS big data from analysis to visualization. There are about 400 analysis pipelines integrated on Maser. List of all analysis pipelines, including descriptions and approximate execution times, can be found on page for ‘All pipelines’ in the User Guide.. Regist custom genome software registers custom genomes to Genome Explorer (IN: FASTA).

Proper citation: regist custom genome (RRID:SCR_015999) Copy   

•   Source: SciCrunch Registry

http://www.stowers-institute.org/research/core/molecular-biology

Core services include DNA sequencing, site directed mutagenesis, genome engineering (TALENs & CRISPRS), plasmid preparations and distributing clones/vectors from in house collections. Supports real time quantitative PCR through instrument training, troubleshooting and experimental design. Stowers researchers also have access to Illumina Next Generation Sequencing technology. Constructs libraries, performs sequencing and assists with high throughput genome sequencing, RNA-seq and ChIP-seq projects. Utilizes liquid handling and colony manipulation robots to automate many of services. Provides automation expertise and collaborate with researchers on custom automation projects.

Proper citation: Stowers Institute for Medical Research Molecular Biology Core Facility (RRID:SCR_017776) Copy   

•   Source: SciCrunch Registry

https://med.miami.edu/centers-and-institutes/hihg/research-centers/center-for-genome-technology/biorepository-core

Core provides services and houses samples collected over the last 30 years. Biorepository processes, archives, and retrieves biological samples for genomic research. Offers variety of sample processing options including but not limited to automated DNA extraction using Autogen FLEXSTAR+ instrument, automated DNA/RNA extraction using Qiagen QIASymphony, peripheral blood mononuclear cell (PBMC) isolation, serum, plasma and buffy coat isolation, creation of blood cards, DNA/RNA quantitation and qualitation, whole genome amplification, cell-line lymphoblast immortalization and primary fibroblast tissue culture. Offers sample solutions tos uit customized needs.Services also include DNA/RNA Extraction,Sample archiving, retrieval and allocation,Unique and custom labels printing,DNA/RNA quantitation and qualitation,Tissue culture,Whole genome amplification.

Proper citation: University of Miami Hussman Institute for Human Genomics Biorepository Core Facility (RRID:SCR_017816) Copy   

•   Source: SciCrunch Registry

https://med.miami.edu/centers-and-institutes/hihg/research-centers/center-for-genome-technology/sequencing-core

Core Facility offers services utilizing Illumina Novaseq X Plus, Pacific Biosciences Revio, ONT Promethion, and 10x Genomics platforms. The core has extensive knowledge of DNA/RNA library preparation for short-read, long-read and single cell sequencing. Sample preparation is fully automated on Perkin Elmer robotic workstations and tracked via the Clarity LIMS. Services include, but are not limited to, whole genome, exome and custom capture protocols, as well as, bulk RNAseq, small RNAseq, and single cell RNA sequencing.

Proper citation: University of Miami Hussman Institute for Human Genomics Sequencing Core Facility (RRID:SCR_017828) Copy   

•   Source: SciCrunch Registry

http://gif.biotech.iastate.edu/

Provides help with grant review, information on data management plans,suggestion best practices for bionformatics analyses, advise on experimental design for Next Gen Sequencing (NGS) projects.Services include:Genome assembly and annotation,Transcriptome assembly and annotation,SNP/InDel calling,RNA-Seq analysis,ChiP-seq,Introgression mapping,novel gene discovery,Personalized GBrowse instances for data visualization,Access to high performance computing, Custom big data projects.

Proper citation: Iowa State University Genome Informatics Core Facility (RRID:SCR_017790) Copy   

•   Source: SciCrunch Registry

http://ssom.luc.edu/genomics/

Core provides next-generation sequencing capabilities using Illumina MiSeq. Helps with experimental design, quality control analysis, library preparation, and data analysis. MiSeq desktop sequencer allows to access applications such as targeted gene sequencing, metagenomics, small genome sequencing, targeted gene expression, amplicon sequencing, and HLA typing.MiSeq is capable of delivering up to 15 Gb of output with 25 million sequencing reads and 2x300 basepair read lengths.

Proper citation: Loyola University Genomics Core Facility (RRID:SCR_017857) Copy   

•   Source: SciCrunch Registry

https://jmorp.megabank.tohoku.ac.jp/

Japanese multi omics reference panel. Provides multidimensional approach to diversity of Japanese population. Public database for plasma metabolome and proteome analyses. Updated to metabolome, genome, transcriptome, metagenome, number of samples, analysis methods of each dataset, expanding links between each layer and links between hierarchies.

Proper citation: jMORP (RRID:SCR_024755) Copy   

•   Source: SciCrunch Registry

http://cqls.oregonstate.edu/

Formerly Center for Genome Research and Biocomputing Core Facility. Functions and facilities include services in genomics, functional genomics, genotyping and imaging.Biocomputing facilities with computing infrastructure, which includes managed cloud and shared resources, data analyses and training are customized to individual needs, including genome assembly and annotation, analysis of RNAseq, GBS, and metagenomics data, and GPU-enabled deep learning analyses.

Proper citation: Oregon State University Center for Quantitative Life Sciences Core Facility (RRID:SCR_018373) Copy   

•   Source: SciCrunch Registry

http://gmdd.shgmo.org/Computational-Biology/GRS/

A compression tool for efficient storage of Genome Re-Sequencing data. GRS processes genome sequence data without use of reference SNPs and other variants. It can also automatically rebuild the individual genome sequence data using the reference genome sequence.

Proper citation: GRS (RRID:SCR_001008) Copy   

•   Source: SciCrunch Registry

http://ntap.cbi.pku.edu.cn/usage.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software for tiling array data analysis to survey the genome-wide binding sites of transcription factor HY5 in Arabidopsis and the genome-wide histone modifications/DNA methylation level in rice. It was developed in the process of generating NimbleGen analysis. Written in R and Perl.

Proper citation: NTAP (RRID:SCR_001488) Copy   

•   Source: SciCrunch Registry

http://www.patricbrc.org/portal/portal/patric/Home

A Bioinformatics Resource Center bacterial bioinformatics database and analysis resource that provides researchers with an online resource that stores and integrates a variety of data types (e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data) and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. The PATRIC project includes three primary collaborators: the University of Chicago, the University of Manchester, and New City Media. The University of Chicago is providing genome annotations and a PATRIC end-user genome annotation service using their Rapid Annotation using Subsystem Technology (RAST) system. The National Centre for Text Mining (NaCTeM) at the University of Manchester is providing literature-based text mining capability and service. New City Media is providing assistance in website interface development. An FTP server and download tool are available.

Proper citation: Pathosystems Resource Integration Center (RRID:SCR_004154) Copy   

•   Source: SciCrunch Registry

http://www.GeneWeaver.org

Freely accessible phenotype-centered database with integrated analysis and visualization tools. It combines diverse data sets from multiple species and experiment types, and allows data sharing across collaborative groups or to public users. It was conceived of as a tool for the integration of biological functions based on the molecular processes that subserved them. From these data, an empirically derived ontology may one day be inferred. Users have found the system valuable for a wide range of applications in the arena of functional genomic data integration.

Proper citation: Gene Weaver (RRID:SCR_003009) Copy   

•   Source: SciCrunch Registry

http://ww2.sanbi.ac.za/Dbases.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The STACKdb is knowledgebase generated by processing EST and mRNA sequences obtained from GenBank through a pipeline consisting of masking, clustering, alignment and variation analysis steps. The STACK project aims to generate a comprehensive representation of the sequence of each of the expressed genes in the human genome by extensive processing of gene fragments to make accurate alignments, highlight diversity and provide a carefully joined set of consensus sequences for each gene. The STACK project is comprised of the STACKdb human gene index, a database of virtual human transcripts, as well as stackPACK, the tools used to create the database. STACKdb is organized into 15 tissue-based categories and one disease category. STACK is a tool for detection and visualization of expressed transcript variation in the context of developmental and pathological states. The data system organizes and reconstructs human transcripts from available public data in the context of expression state. The expression state of a transcript can include developmental state, pathological association, site of expression and isoform of expressed transcript. STACK consensus transcripts are reconstructed from clusters that capture and reflect the growing evidence of transcript diversity. The comprehensive capture of transcript variants is achieved by the use of a novel clustering approach that is tolerant of sub-sequence diversity and does not rely on pairwise alignment. This is in contrast with other gene indexing projects. STACK is generated at least four times a year and represents the exhaustive processing of all publicly available human EST data extracted from GenBank. This processed information can be explored through 15 tissue-specific categories, a disease-related category and a whole-body index

Proper citation: Sequence Tag Alignment and Consensus Knowledgebase Database (RRID:SCR_002156) Copy   

•   Source: SciCrunch Registry

http://www.projects.roslin.ac.uk/sheepmap/front.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The project aims to apply genome mapping research to sheep, utilizing previous research in sheep (in other countries) and in other species (in the UK and abroad) to the benefit of the UK sheep industry. The project itself uses existing breeding structures, knowledge of the sheep genome and experimental resources. It has three main aims: i) To use the Suffolk, Texel and Charollais Sire Referencing Schemes to detect and verify quantitative trait loci (QTLs) for growth and carcass composition traits ii) To investigate candidate genes and/or chromosomal regions for associations with production traits. iii) To investigate approaches for optimizing future genotyping strategies within the sire referencing schemes for practical and cost effective application of marker-assisted selection By using commercial breeding populations for the research, immediate application of beneficial results is possible. Potential benefits include increased genetic progress through marker assisted selection which utilizes the genotype information, correction of possible parentage errors (ultimately leading to additional genetic progress) and opportunities for using marker information for product certification. The project will benefit the UK sheep industry by the use of Marker Assisted Selection (MAS) utilizing QTL or gene variants identified in the project. Additional benefits may arise from parentage verification and correction of errors e.g. misallocation of lamb to ewe. In the longer term, opportunities may exist to use markers for quality control, tracing products to their source. The major advantage of the design of this project is that the results are immediately applicable to the breeding schemes within which the QTLs and/or genes are detected. The time lag in the application of the results that is often seen with experimental populations is minimized. The project requires close involvement with the Sire Reference Schemes, in return for their assistance the results have immediate benefit to animals within these groups.

Proper citation: UK Sheep Genome Mapping Project (RRID:SCR_002272) Copy   

•   Source: SciCrunch Registry

http://soybase.org

Professionally curated repository for genetics, genomics and related data resources for soybean that contains the most current genetic, physical and genomic sequence maps integrated with qualitative and quantitative traits. SoyBase includes annotated Williams 82 genomic sequence and associated data mining tools. The genetic and sequence views of the soybean chromosomes and the extensive data on traits and phenotypes are extensively interlinked. This allows entry to the database using almost any kind of available information, such as genetic map symbols, soybean gene names or phenotypic traits. The repository maintains controlled vocabularies for soybean growth, development, and traits that are linked to more general plant ontologies. Contributions to SoyBase or the Breeder''s Toolbox are welcome.

Proper citation: SoyBase (RRID:SCR_005096) Copy   

•   Source: SciCrunch Registry

http://smd.stanford.edu/cgi-bin/source/sourceSearch

SOURCE compiles information from several publicly accessible databases, including UniGene, dbEST, UniProt Knowledgebase, GeneMap99, RHdb, GeneCards and LocusLink. GO terms associated with LocusLink entries appear in SOURCE. The mission of SOURCE is to provide a unique scientific resource that pools publicly available data commonly sought after for any clone, GenBank accession number, or gene. SOURCE is specifically designed to facilitate the analysis of large sets of data that biologists can now produce using genome-scale experimental approaches Platform: Online tool

Proper citation: SOURCE (RRID:SCR_005799) Copy   

•   Source: SciCrunch Registry

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

Database of all of the publicly available, complete prokaryotic genomes. In addition to having all of the organisms on a single website, common data types across all genomes in the CMR make searches more meaningful, and cross genome analysis highlight differences and similarities between the genomes. CMR offers a wide variety of tools and resources, all of which are available off of our menu bar at the top of each page. Below is an explanation and link for each of these menu options. * Genome Tools: Find organism lists as well as summary information and analyses for selected genomes. * Searches: Search CMR for genes, genomes, sequence regions, and evidence. * Comparative Tools: Compare multiple genomes based on a variety of criteria, including sequence homology and gene attributes. SNP data is also found under this menu. * Lists: Select and download gene, evidence, and genomic element lists. * Downloads: Download gene sequences or attributes for CMR organisms, or go to our FTP site. * Carts: Select genome preferences from our Genome Cart or download your Gene Cart genes. The Omniome is the relational database underlying the CMR and it holds all of the annotation for each of the CMR genomes, including DNA sequences, proteins, RNA genes and many other types of features. Associated with each of these DNA features in the Omniome are the feature coordinates, nucleotide and protein sequences (where appropriate), and the DNA molecule and organism with which the feature is associated. Also available are evidence types associated with annotation such as HMMs, BLAST, InterPro, COG, and Prosite, as well as individual gene attributes. In addition, the database stores identifiers from other centers such as GenBank and SwissProt, as well as manually curated information on each genome or each DNA molecule including website links. Also stored in the Omniome are precomputed homology data, called All vs All searches, used throughout the CMR for comparative analysis.

Proper citation: JCVI CMR (RRID:SCR_005398) Copy   

•   Source: SciCrunch Registry

http://vmd.vbi.vt.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. Database covering a range of plant pathogenic oomycetes, fungi and bacteria primarily those under study at Virginia Bioinformatics Institute. The data comes from different sources and has genomes of 3 oomycetes pathogens: Phytophthora sojae, Phytophthora ramorum and Hyaloperonospora arabidopsidis. The genome sequences (95 MB for P.sojae and 65 MB for P.ramorum) were annotated with approximately 19,000 and approximately 16,000 gene models, respectively. Two different statistical methods were used to validate these gene models, Fickett''''s and a log-likelihood method. Functional annotation of the gene models is based on results from BlastX and InterProScan screens. From the InterProScan results, putative functions to 17,694 genes in P.sojae and 14,700 genes in P.ramorum could be assigned. An easy-to-use genome browser was created to view the genome sequence data, which opens to detailed annotation pages for each gene model. A community annotation interface is available for registered community members to add or edit annotations. There are approximately 1600 gene models for P.sojae and approximately 700 models for P.ramorum that have already been manually curated. A toolkit is provided as an additional resource for users to perform a variety of sequence analysis jobs.

Proper citation: VMD (RRID:SCR_004905) Copy   

•   Source: SciCrunch Registry