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http://linux1.softberry.com/spldb/SpliceDB.html

Database of canonical and non-canonical mammalian splice sites. The information about verified splice site sequences for canonical and non-canonical sites is presented with the supporting evidence. Weight matrices were built for the major splice groups, which can be incorporated into gene prediction programs.

Proper citation: SpliceDB (RRID:SCR_006262) Copy   

•   Source: SciCrunch Registry

http://aws.amazon.com/1000genomes/

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

Proper citation: 1000 Genomes Project and AWS (RRID:SCR_008801) Copy   

•   Source: SciCrunch Registry

https://www.unmc.edu/vcr/cores/vcr-cores/mgec/index.html

Core Facility provides expertise and advice for experimental design of transgenic or gene knockout experiments, including DNA construct production and genotyping assays, makes reagents available for generation of transgene or gene targeting constructs, and performs all experimental aspects, which include pronuclear injection of transgene constructs, generation of recombinant mouse ES cells, blastocyst injection, and embryo transfer surgeries, for generation or rederivation of genetically manipulated mouse strains. Transgenic founder mice or chimeric animals with targeted alleles are then transferred to individual investigator for analysis.

Proper citation: Nebraska University Medical Center Mouse Genome Engineering Core Facility (RRID:SCR_017755) Copy   

•   Source: SciCrunch Registry

http://einstein.yu.edu/shRNA

Core Facility was closed in November 2016. Services of shRNA Core were redistibuted to other existing facilities at Einstein.Gene Modulation Services: CRISPR, RNAi and ORF. CRISPR-Cas9 services for cell lines will now be performed in Gene Modification Facility. Gene Modification Facility already offers CRISPR services for genetic modification of mice and will utilize this scientific expertise to provide CRISPR services for the gene modification of cell lines as well. You can access these services through core's site in iLab.The human and mouse whole genome shRNA library has been relocated to the Molecular Cytogenetic Core. The core staff will pull requested shRNA and ORF clones from our collection for investigators. You can access this service through the core's site in iLab.Access and operation of the Operetta instrument for high-content imaging will now be coordinated through the Macromolecular Therapeutics Development Facility (MTDF). You can access this service through the core's site in iLab. Lentivirus prep from shRNA and CRSPR constructs can be obtained from our Gene Therapy Core from clones obtained from the Molecular Cytogenetic Core. You can access this service through the core's site in iLab.

Proper citation: Albert Einstein College of Medicine shRNA Core Facility (RRID:SCR_017846) Copy   

•   Source: SciCrunch Registry

https://ki.mit.edu/sbc/escell

Core provides service support to all MIT investigators who utilize specialized in vitro cells such as stem cells, organoids, or primary cell lines and/or novel mouse models to study human diseases such as cancer. Projects involve generation of new model system, such as CRISPR-mediated gene editing in mouse to introduce mutation that mimics one found in patients. Helps with projects required optimization of finicky cell cultures and other challenges.Provides customizable set of service options to match specific needs of each project, including consultative advice and troubleshooting, complete tissue culture and microinjection services within our facilities or hands-on training to enable investigators to perfom these experiments either at their own laboratory or within our facilities.Services Include:Gene Targeting genomic modification through traditional or CRISPR/Cas9 locus targeting, assistance with targeting strategies and vector designs;Embryonic Stem Cells generation of new ES lines from mouse strains, importation and testing of lines from outside sources, differentiation of ES lines into specific cell lineages or cell types and more;Microinjection injection of mouse ES cells into blastocysts to generate chimeras and injection of DNA, RNA or CRISPR RNPs into the pronucleus of fertilized mouse eggs to generate transgenic and edited mice;Specialized Tissue Culture establishemnt of new primary cell cultures from a tumor, tissue or organ; Isolation of fibroblasts (MEFs) from mice for culture and analysis;Tissue Culture for Xenograft and Syngenic Modeling optimization, validation and testing of cell lines for orthotopic placement into mice, coordinated with Preclinical Testing Facility;Repository of Reagent Mice Commonly used wild type mice such as C57BL/6j as well as KrasG12D-based models of cancers are maintained on campus for efficient distrubution;Training and Troubleshooting for all aspects of embryonic stem cells, primary cultures, animal breeding etc.;Serum, DMEM, LIF and other media components that have been tested and verified for use with ES cells.

Proper citation: Massachusetts Institute of Technology Koch Institute Preclinical Modeling Core Facility (RRID:SCR_017899) 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

http://www.uwtransgenics.org/

Core facility that creates transgenic and gene-targeted mice using pronuclear microinjection, targeted ES cell microinjection, and CRISPR/Cas9 gene editing. Offers mouse rederivation services to create specific pathogen free mice or to rederive cryopreserved mouse lines. Additionally, embryo and sperm cryopreservation services are available to provide long-term storage of valuable mouse strains or stocks. Services include:Pronuclear Microinjection,ES Cell Microinjection,ES Cell Electroporation CRISPR/Cas9,In Vitro Fertilization,Sperm Cryopreservation,Embryo Cryo,Embryo Rederivation.

Proper citation: University of Washington Transgenic Resources Program Core Facility (RRID:SCR_017863) Copy   

•   Source: SciCrunch Registry

http://www.salk.edu/science/core-facilities/integrative-genomics-and-bioinformatics-core/

Core facility established to assist the Salk community with integrating genomics data into their research. The primary focus of the core is to provide analysis support for next-generation sequencing applications.

Proper citation: Salk Institute Razavi Newman Integrative Genomics and Bioinformatics Core Facility (IGC) (RRID:SCR_014842) Copy   

•   Source: SciCrunch Registry

https://sc.edu/study/colleges_schools/pharmacy/research_and_practice/research_centers_and_facilities/functional_genomics_core/index.php

Core offers resources and solutions for conducting genomics, transcriptomics, epigenomics and functional genomics projects. We work with researchers to determine project goals and design custom solutions. We assist at all stages of the project, from support in grant development to generation of publication-quality data. Services include Consultations, Bioinformatics, Nucleic Acids purification, quantification and QC DNA Sequencing (SANGER and NGS), Library Constructions for NGS applications,Microarray Hybridization, Real Time PCR, Custom epigenomics applications, Lentiviral vectors and lentiviruses construction and production, CRIPR-CAS9sgRNAs and RNAi/shRNAs knockdown of individual genes and functional screening of sgRNA and shRNA libraries for target identification.

Proper citation: University of South Carolina Functional Genomics Core Facility (RRID:SCR_026178) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/babelgene/index.html

Software R package to convert between human and non-human gene orthologs/homologs. Integrates orthology assertion predictions sourced from multiple databases as compiled by the HGNC Comparison of Orthology Predictions (HCOP) (Wright et al. 2005 , Eyre et al. 2007 , Seal et al. 2011 ).

Proper citation: babelgene (RRID:SCR_027117) Copy   

•   Source: SciCrunch Registry

http://sherlock.ucsf.edu/

Service to discover disease genes in GWAS using eQTL signature matching by simply submitting your list of GWAS associations (SNPs and p-values). It is important to upload all SNPs in your association study, not just the top hits. Sherlock may be able to group multiple lower-confidence SNPs to discover functionally-important genes.

Proper citation: Sherlock (RRID:SCR_001628) Copy   

•   Source: SciCrunch Registry

http://www-personal.umich.edu/~jianghui/rseqdiff/

An R package that can detect differential gene and isoform expressions from RNA-seq data of multiple biological conditions. The approach considers three cases for each gene: 1) no differential expression, 2) differential expression without differential splicing and 3) differential splicing.

Proper citation: rSeqDiff (RRID:SCR_001683) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/src/contrib/Archive/QuasiSeq/

Software package to apply the QL, QLShrink and QLSpline methods to quasi-Poisson or quasi-negative binomial models for identifying differentially expressed genes in RNA-seq data.

Proper citation: QuasiSeq (RRID:SCR_001715) Copy   

•   Source: SciCrunch Registry

http://datahub.io/dataset/kupkb

A collection of omics datasets (mRNA, proteins and miRNA) that have been extracted from PubMed and other related renal databases, all related to kidney physiology and pathology giving KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. Some microarray raw datasets have also been downloaded from the Gene Expression Omnibus and analyzed by the open-source software GeneArmada. The Semantic Web technologies, together with the background knowledge from the domain's ontologies, allows both rapid conversion and integration of this knowledge base. SPARQL endpoint http://sparql.kupkb.org/sparql The KUPKB Network Explorer will help you visualize the relationships among molecules stored in the KUPKB. A simple spreadsheet template is available for users to submit data to the KUPKB. It aims to capture a minimal amount of information about the experiment and the observations made.

Proper citation: Kidney and Urinary Pathway Knowledge Base (RRID:SCR_001746) Copy   

•   Source: SciCrunch Registry

http://gmod.org/wiki/Main_Page

A collection of open source software tools for creating and managing genome-scale biological databases. GMOD is made up databases, applications, and adaptor software that connects these components together. You can use it to create a small laboratory database of genome annotations, or a large web-accessible community database. At first GMOD just featured model organisms but now any organism with any kind of sequence associated with it is a good candidate as a subject for a GMOD database. There are GMOD databases with just protein sequence in them, with EST sequence only, those that are concerned primarily with gene expression, and even those dedicated to collections of RNA sequence. They have also heard of GMOD databases for oligonucleotides and plasmids.

Proper citation: Generic Model Organism Database Project (RRID:SCR_001731) Copy   

•   Source: SciCrunch Registry

http://www.cbgrits.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Time-series data sets spanning twelve time-points between E12-P9 for exploring cerebellar development of the mouse in time and space. The database contains a number of mutant / wildtype microarray datasets including two complete wildtype microarray time-series (C57BL/6 and DBA/2J). The dataset also includes in situ hybridization and bioinformatic analyses. Exploration of this dataset will allow the investigator to assess differential gene expression profiles from a developing mutant cerebella, to assess the temporal changes in gene expression in the wildtype, and to verify the cellular expression of these genes in images from our in situ hybridization library. Using the database, the investigator can explore the developmental expression or differential expression patterns of a particular gene, or create lists of similarly expression genes by building simple search algorithms. These lists can then be mined across all the datasets in both space and time. Cb GRiTS's current datasets represent gene expression analyses from multiple cerebellar mutant and wildtype single time-point and developmental series.

Proper citation: Cerebellar Gene Regulation in Time and Space Database (RRID:SCR_001699) Copy   

•   Source: SciCrunch Registry

https://physiomeproject.org/

The Physiome Project is a worldwide public domain effort to provide a computational framework for understanding human and other eukaryotic physiology. It aims to develop integrative models at all levels of biological organization, from genes to the whole organism via gene regulatory networks, protein pathways, integrative cell function, and tissue and whole organ structure/function relations. Additionally, an important goal of the project is to develop applications for teaching physiology. Current projects include the development of: - ontologies to organize biological knowledge and access to databases - markup languages to encode models of biological structure and function in a standard format for sharing between different application programs and for re-use as components of more comprehensive models - databases of structure at the cell, tissue and organ levels - software to render computational models of cell function such as ion channel electrophysiology, cell signaling and metabolic pathways, transport, motility, the cell cycle, etc. in 2 & 3D graphical form - software for displaying and interacting with the organ models which will allow the user to move across all spatial scales Sponsors: This project is supported by the International Union of Physiological Sciences (IUPS), the IEEE Engineering. in Medicine and Biology (EMBS), and the International Federation for Medical and Biological Engineering (IFMBE)

Proper citation: International Union of Physiological Sciences: Physiome Project (RRID:SCR_001760) Copy   

•   Source: SciCrunch Registry

http://incf.org/about/programs/modeling/blue-gene-access

Through this site, INCF provides he neuroinformatics community with access to an IBM Blue Gene/L supercomputer. INCF owns a share of a BlueGene/L (BG/L) supercomputer located at the Parallel Computer Center (PDC) at The Royal Institute of Technology (KTH) in Stockholm. Allocations are now available through the INCF Secretariat. During an initial evaluation phase, a limited numbers of large-scale computing projects will be selected, based on the suitability of the project for supercomputing. Research groups with limited access to supercomputers at their home institutions are given priority. Approved projects are regularly re-evaluated. New projects are approved based on availability and usage load of the BG/L. The Blue Gene/L supercomputer project is aimed at expanding the horizon of high-performance computing to unprecedented levels of scale and performance. Blue Gene/L is the first supercomputer in the Blue Gene family. The full Blue Gene/L consists of 64 racks containing 65,536 high-performance compute nodes. Each node (nodes and chips are the same in the Blue Gene system) contains two embedded 32-bit PowerPC processors. Furthermore, the same chip that is used for compute nodes is also used for the 1,024 I/O nodes. A three-dimensional torus network and a collective network are used to interconnect all nodes. The full system contains 33 terabytes of main memory; it is designed to achieve 183.5 teraflops peak performance using one of the processors of each node for computation and the other processor for communication, and 367 teraflops using both processors for computation. Another key architectural feature of this supercomputer is the link chip component and five Blue Gene/L networks, the PowerPC 440 core and floating-point enhancements, the on-chip and off-chip distributed memory system, the node- and system-level design for high reliability, and the comprehensive approach to fault isolation. One of the key objectives in Blue Gene/L design is to achieve cost/performance comparable to the COTS (Commodity Off The Shelf) approach, while at the same time incorporating a processor and network combination so powerful that it revolutionizes the performance of supercomputer systems. Sponsors: This resource is supported by the INCF.

Proper citation: International Neuroinformatics Coordinating Facility: Blue Gene/L Access (RRID:SCR_001755) Copy   

•   Source: SciCrunch Registry

http://csg.sph.umich.edu//abecasis/MACH/index.html

A Markov Chain based software tool for haplotyping, genotype imputation and disease association analysis that can resolve long haplotypes or infer missing genotypes in samples of unrelated individuals.

Proper citation: MACH 1.0 (RRID:SCR_001759) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/projects/homology/maps/

This page provides quick access to the Comparative mapping functions available in the Map Viewer. Currently, comparative maps are calculated using HomoloGene orthology predictions. Once the gene pairs have been established, blocks of conserved syteny can be established using the positions of each gene object in their respective builds. Sponsors: This resource is supported by NCBI.

Proper citation: Homology Maps Page (RRID:SCR_001666) Copy   

•   Source: SciCrunch Registry