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http://crispr-era.stanford.edu/index.jsp

Software comprehensive design tool for CRISPR mediated gene editing, repression and activation. Fast and comprehensive guide RNA design tool for genome editing, repression and activation. Used for automated genome wide sgRNA design.

Proper citation: CRISPR-ERA (RRID:SCR_018710) Copy   

•   Source: SciCrunch Registry

http://www.einstein.yu.edu/departments/genetics/resources/molecular-cytogenetics-core.aspx

Core provides tools for preparation of human and murine samples suitable for molecular genetic and cytogenetic analysis of entire genome. These tools include establishment of EBV transformed cell lines; isolation of DNA and mRNA from variety of tissue culture samples as well as primary biopsies; preparation of metaphase chromosomes suitable for fluorescence in situ hybridization (FISH) and Spectral Karyotyping (SKY) or whole chromosome paints for human and mouse genome. Core personnel is trained to hybridize commercial probes and to designed locus specific probes for regions of interest to investigators. All probes are custom designed and in house generated.

Proper citation: Albert Einstein College of Medicine Molecular Cytogenetics Core Facility (RRID:SCR_017815) Copy   

•   Source: SciCrunch Registry

http://htbc.stanford.edu

Core provides fully automated high throughput screening (HTS) of Compound Libraries (130,000+ compounds) for both enzyme/protein-based assays and cell-based assays, using Caliper Life Sciences Staccato system;Genomic siRNA screening with siARRAY whole human genome siRNA library from Dharmacon targeting 21,000 genes, using Agilent Bravo system;High-Content Screening using ImageXpress Micro automated fluorescent microscope with live cell, bright field, phase contrast and integrated plate handling with Thermo Catalyst CRS, and image analysis using MetaXpress software;High Throughput Molecular Biology reagents and services, including access to cDNA libraries (Human ORFeome collection, 15,000 genes) and 96 and 384-well bead clean-ups and PCR setup (Biomek FX and Agilent Bravo), and other automation steps in collaboration with SFGF;High-throughput assay development assistance with cell culture, experiment design, robotic programming and Standard Operating Procedure drafting;Screening data analysis assistance with protocols, hit determination and structure activity analyses using MDL chemical database ISIS/HOST, Plate Manager, Assay Explorer and Report Manager. Use of microplate reader detection systems, including Tecan Infinite M1000 and Infinite M1000 PRO and Molecular Devices Analyst GT for fluorescence; fluorescence polarization; time-resolved fluorescence; absorbance and luminescence (with injectors and AlphaScreen); and Flexstation II 384, for kinetic fluorescence reads to measure calcium mobilization and ion channels.Use of liquid-handling robots, including Sciclone ALH3000 (96- and 384-well pipetting), Agilent Bravo (96- and 384-well pipetting), Velocity11 VPrep (96-well pipetting), Bio-Tek plate washers/dispensers, Matrix Wellmate and Titertek/Labsystems Multidrop microplate dispensers, and Velocity11 PlateLoc plate heat sealer;Training for most of these services.

Proper citation: Stanford University School of Medicine High Throughput Bioscience Center Core Facility (RRID:SCR_017794) Copy   

•   Source: SciCrunch Registry

https://med.nyu.edu/research/scientific-cores-shared-resources/genome-technology-center

Core provides range of services related to genome, epigenome, and transcriptome analysis. Offers technologies including Illumina deep sequencing and sample preparation for variety of applications, including DNA and RNA sequencing (DNA- and RNA-seq), exome sequencing, targeted capture, chromatin immunoprecipitation sequencing (ChIP-seq), methylation sequencing (Methyl-seq), metagenomics, and many others;Automation of Illumina library and targeted capture preps, including 16S ribosomal RNA (rRNA) sequencing;Oxford Nanopore sequencing (long reads);Bio-Rad Droplet Digita polymerase chain reaction (PCR);Nanostring nCounter;Single-cell RNA- and DNA-seq using the C1 Auto Prep System from Fluidigm, and 10x Genomics Chromium System.Provides expertise on strategies to achieve research goals in any field related to genomics, and can tailor bioinformatics analysis to individual project. If you supply us with nucleic acids, we can perform every step required to help you achieve your desired results.

Proper citation: New York University School of Medicine Langone Health Genome Technology Center Core Facility (RRID:SCR_017929) Copy   

•   Source: SciCrunch Registry

http://mousebiology.org

Core located on campus of UC Davis, providing fully customized support for scientific research using genetically altered mice. Provides access to develop, plan, execute, and analyze research project involving genetically-altered mice. Provides description of project, including alternative approaches, accurate timelines, and cost estimates.Provides regular and informative communication throughout project, including email updates on completion of each milestone. Project progress can be followed at each stage by viewing detailed information anytime by accessing our online and secure project tracking system (PTS) available 24 hours a day.

Proper citation: University of California-Davis Mouse Biology Program CRISPR Based Genome Editing Service Core Facility (RRID:SCR_017851) Copy   

•   Source: SciCrunch Registry

http://hihg.med.miami.edu/cgt/gene-expression

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 27,2025. CGT gene expression core utilizes Affymetrix GeneChip Arrays and Illumina BeadChips to identify gene expression variation in single genes, targeted set of genes, or entire genomes. Affymetrix GeneChip Arrays Human Gene ST,Human Transcriptome Array 2.0, Human Exon ST, Human miRNA, Illumina Expression, HumanHT-12 v4 BeadChip.

Proper citation: University of Miami Miller School of Medicine Gene Expression Core Facility (RRID:SCR_017825) Copy   

•   Source: SciCrunch Registry

http://mus.well.ox.ac.uk/mouse/INBREDS/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. Data set of genotypes available for 480 strains and 13370 successful SNP assays that are mapped to build34 of the mouse genome, including 107 SNPs that are mapped to random unanchored sequence 13374 SNPs are mapped onto Build 33 of the mouse genome. You can access the data relative to Build 33 or Build 34.

Proper citation: Wellcome-CTC Mouse Strain SNP Genotype Set (RRID:SCR_003216) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/node/549

Genomic data set on Type 2 Diabetes in African-Americans derived via admixture mapping, a method for genome-wide association analysis based on admixture-generated linkage disequilibrium. This collaborative group has identified 1,478 African Americans with Type 2 Diabetes (T2D) from the Jackson Heart Study and Multiethnic Cohort Study, as well as 498 controls from the Jackson Heart Study who are normoglycemic despite high body mass index and older age. All samples were genotyped (using the Illumina BeadLab platform) for 1,291 polymorphic markers chosen to be extremely different in frequency between west Africans and European Americans. Evidence for association to diabetes at each marker as reported by the ANCESTRYMAP software are reported in the downloadable table. They calculate that this study has statistical power to detect loci where African or European ancestry on average confers multiplicative increased risk of 1.35-fold or more. The fact that they did not detect a statistically significant signal of association in the scan suggests that any genetic risk factors for T2D do not confer different risks due to ancestry that differ by this factor. The genome scan results are publicly available (Excel file) prior to publication so that researchers interested in the genetics of T2D can use the results of the scan to prioritize follow-up of any regions of interest.

Proper citation: A Whole Genome Admixture Scan for Type 2 Diabetes in African Americans (RRID:SCR_006984) Copy   

•   Source: SciCrunch Registry

http://eyebrowse.cit.nih.gov/

EyeBrowse displays expressed sequence tag (EST) cDNA clones from eye tissues (derived from NEIBank and other sources) aligned with current versions of the human, rhesus, mouse, rat, dog, cow, chicken, or zebrafish genomes, including reference sequences for known genes. This gives a simplified view of gene expression activity from different parts of the eye across the genome. The data can be interrogated in several ways. Specific gene names can be entered into the search window. Alternatively, regions of the genome can be displayed. For example, entering two STS markers separated by a semicolon (e.g. RH18061;RH80175) allows the display of the entire chromosomal region associated with the mapping of a specific disease locus. ESTs for each tissue can then be displayed to help in the selection of candidate genes. In addition, sequences can be entered into a BLAT search and rapidly aligned on the genome, again showing eye derived ESTs for the same region. EyeBrowse includes a custom track display SAGE data for human eye tissues derived from the EyeSAGE project. The track shows the normalized sum of SAGE tag counts from all published eye-related SAGE datasets centered on the position of each identifiable Unigene cluster. This indicates relative activity of each gene locus in eye. Clicking on the vertical count bar for a particular location will bring up a display listing gene details and linking to specific SAGE counts for each eye SAGE library and comparisons with normalized sums for neural and non-neural tissues. To view or alter settings for the EyeSAGE track on EyeBrowse, click on the vertical gray bar at the left of the display. Other custom tracks display known eye disease genes and mapped intervals for candidate loci for retinal disease, cataract, myopia and cornea disease. These link back to further information at NEIBank. For mouse, there is custom track data for ChIP-on-Chip of RNA-Polymerase-II during photoreceptor maturation.

Proper citation: EyeBrowse (RRID:SCR_008000) Copy   

•   Source: SciCrunch Registry

http://www.hgvs.org/dblist/dblist.html

A list of various databases freely available to the public, including several mutation and variation resources, such as education resources for teachers students provided by the Human Genome Variation Society. Databases listed include: * Locus Specific Mutation Databases * Disease Centered Central Mutation Databases * Central Mutation and SNP Databases * National and Ethnic Mutation Databases * Mitochondrial Mutation Databases * Chromosomal Variation Databases * Other Mutation Databases ( i.e. your round holes don''''t fit our square pegs) * Clinical and Patient Aspects Databases * Non Human Mutation Databases * Artificial Mutations Only * Other Related Databases * Education Resources for Teachers and Students

Proper citation: Human Genome Variation Society: Databases and Other Tools (RRID:SCR_006876) Copy   

•   Source: SciCrunch Registry

https://github.com/adigenova/fast-sg

Algorithm for alignment-free scaffolding graph construction from short or long reads. It allows the reuse of efficient algorithms designed for short read data and permits the definition of novel modular hybrid assembly pipelines.

Proper citation: Fast-SG (RRID:SCR_015934) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/sites/batchentrez

Software program for loading numbers of genome records. Allows the retrieval of a large number of nucleotide sequences or protein sequences, in a batch mode, by importing a file containing a list of the desired GI or accession numbers.

Proper citation: Batch Entrez (RRID:SCR_016634) Copy   

•   Source: SciCrunch Registry

http://gerg01.gsc.riken.jp/cage/mm5

A web system, which could search and display to current CAGE library information in CAGE Database.

Proper citation: CAGE Basic Viewer for Mus musculus (RRID:SCR_000451) Copy   

•   Source: SciCrunch Registry

http://mouse.perlegen.com/mouse/index.html

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on August 12, 2014. Data, grouped by chromosome, available as flat files for download, of identified DNA polymorphisms (SNPs) in 15 commonly used strains of inbred laboratory mice. Perlegen's SNP, genotype (empirical and imputed), haplotype, trace, and PCR primer data has been compiled with NCBI Mouse Build information to produce data files for public use. Using high-density oligonuclueotide array technology, the study identified over 8 million SNPs and other genetic differences between these strains and the previously sequenced C57BL/6J reference strains (Phase 1). By leveraging data provided by Mark Daly's research team at the Broad Institute, genotypes were also predicted for 40 other common strains (Phase 2). Under an extension to the contract, Eleazar Eskin's group at UCLA has used this data to evaluate SNP associations with phenotypes from the Mouse Phenome Project (the Mouse Phenome Database), and to construct haplotype maps for a total of 94 inbred strains (the Mouse HapMap Project). SNP and genotype positions have been mapped from their original reference coordinates to NCBI Mouse Build 37 coordinates. Note that C57BL6/J strain was not selected for re-sequencing as this data would have been almost entirely redundant with the NCBI reference sequence. Since we did not actually determine genotypes for C57BL6/J, we did not submit genotypes for this strain to dbSNP. However, implicit genotypes for C57BL6/J can be obtained from the reference sequence at each SNP position (the reference allele is the first allele in the ALLELES column). The data is available for download in two different compressed file formats. The files are saved as both PC .zip files and Unix compressed .gz files. At this website, you can: * Learn more about the goals of the Perlegen mouse resequencing project. * Learn more about the array-based resequencing technology used in the project. * Download the SNPs, genotypes, and other data generated by the project, plus sequences of the long-range PCR primers used for SNP discovery. * Browse the mouse genome for SNPs. * View the haplotype blocks within the mouse genome. Mouse Genome Browser The Mouse Genome Browser can be used to visualize genes and the SNPs discovered in this study of genome-wide DNA variation in 15 commonly used, genetically diverse strains of inbred laboratory mice. The reference genome is the C57BL/6J strain NCBI build 37 mouse sequence. In addition to the experimentally-derived genotypes for the original 15 strains, the imputed genotypes for 40 additional inbred mouse strains can also be accessed. Mouse Haplotype Analysis The sequences of 16 commonly used, genetically diverse strains of inbred laboratory mice were analyzed to determine their haplotype structure. The Ancestry Browser shows which ancestral sequence each inbred strain most resembles, along with statistics on the pairwise similarity between the ancestral strains. The Haplotype Viewer shows the haplotype block boundaries and the pairwise similarity for all 56 strains: the 15 used for SNP discovery, the reference strain (C57BL/6J), and the 40 additional strains for which the genotypes were imputed.

Proper citation: Perlegen/NIEHS National Toxicology: Mouse Genome Resequencing Project (RRID:SCR_000726) Copy   

•   Source: SciCrunch Registry

https://www.integromics.com/omicsoffice-for-ngs/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 18,2025. Software for secondary and tertiary analysis of Next Generation Sequencing (NGS) data.

Proper citation: OmicsOffice for NGS SeqSolve (RRID:SCR_001222) Copy   

•   Source: SciCrunch Registry

https://grcf.jhmi.edu/

Established to produce immortalized cell lines from human blood (EBV transformations). Offers genomics applications for single cells, including RNA-seq, gene expression profiling by qPCR and DNA amplification for whole-genome or targeted (exome or PCR-based analysis) through 10x Genomics Chromium platform (similar to Drop Seq). Offers custom genotyping to analyze short tandem repeats, variable number tandem repeats and single nucleotide polymorphisms.

Proper citation: Johns Hopkins University School of Medicine Genetic Resources Core Facility (RRID:SCR_018669) Copy   

•   Source: SciCrunch Registry

http://www.youtube.com/ncbinlm

Videos from the National Center for Biotechnology Information including presentations and tutorials about NCBI biomolecular and biomedical literature databases and tools.

Proper citation: NCBI YouTube Channel (RRID:SCR_006084) Copy   

•   Source: SciCrunch Registry

http://recountdb.cbrc.jp/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database for corrected read counts and genome mapping on NCBI's Short Read Archive. The corrected count was done using RECOUNT and the mapping with LAST. We also provide information of reference genome to which we aligned the short reads. We focus on transcriptomic data, specifically TSS-Seq and RNA-Seq. Because this is the type of data for which sequence count correction is most important. Hence we do not include the genomic reads. The current version contains 2,265 entries from 45 organisms, with read lengths from 17 to 100bp. Via a searchable and browseable interface users can obtain corrected data in formats useful for transcriptomic analysis. We provide the data grouped according to the genome, type of studies and submitter in TAB , PSL and BAM format. They contain the mapping position and annotation of reads observed and corrected counts.

Proper citation: RecountDB (RRID:SCR_006117) Copy   

•   Source: SciCrunch Registry

http://operons.ibt.unam.mx/OperonPredictor/

The Prokaryotic Operon DataBase (ProOpDB) constitutes one of the most precise and complete repository of operon predictions in our days. Using our novel and highly accurate operon algorithm, we have predicted the operon structures of more than 1,200 prokaryotic genomes. ProOpDB offers diverse alternatives by which a set of operon predictions can be retrieved including: i) organism name, ii) metabolic pathways, as defined by the KEGG database, iii) gene orthology, as defined by the COG database, iv) conserved protein motifs, as defined by the Pfam database, v) reference gene, vi) reference operon, among others. In order to limit the operon output to non-redundant organisms, ProOpDB offers an efficient protocol to select the more representative organisms based on a precompiled phylogenetic distances matrix. In addition, the ProOpDB operon predictions are used directly as the input data of our Gene Context Tool (GeConT) to visualize their genomic context and retrieve the sequence of their corresponding 5�� regulatory regions, as well as the nucleotide or amino acid sequences of their genes. The prediction algorithm The algorithm is a multilayer perceptron neural network (MLP) classifier, that used as input the intergenic distances of contiguous genes and the functional relationship scores of the STRING database between the different groups of orthologous proteins, as defined in the COG database. Nevertheless, the operon prediction of our method is not restricted to only those genes with a COG assignation, since we successfully defined new groups of orthologous genes and obtained, by extrapolation, a set of equivalent STRING-like scores based on conserved gene pairs on different genomes. Since the STRING functional relationships scores are determined in an un-bias manner and efficiently integrates a large amount of information coming from different sources and kind of evidences, the prediction made by our MLP are considerably less influenced by the bias imposed in the training procedure using one specific organism.

Proper citation: ProOpDB (RRID:SCR_006111) Copy   

•   Source: SciCrunch Registry

http://iae.fafu.edu.cn/DBM/

Database storing and integrating genomic data of diamondback moth (DBM), Plutella xylostella (L.). It provides comprehensive search tools and downloadable datasets for scientists to study comparative genomics, biological interpretation and gene annotation of this insect pest. DBM-DB contains assembled transcriptome datasets from multiple DBM strains and developmental stages, and the annotated genome of P. xylostella (version 2). They have also integrated publically available ESTs from NCBI and a putative gene set from a second DBM genome (KONAGbase) to enable users to compare different gene models. DBM-DB was developed with the capacity to incorporate future data resources, and will serve as a long-term and open-access database that can be conveniently used for research on the biology, distribution and evolution of DBM. This resource aims to help reduce the impact DBM has on agriculture using genomic and molecular tools.

Proper citation: DBM-DB (RRID:SCR_006258) Copy   

•   Source: SciCrunch Registry