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https://www.perkinelmer.com/uk/product/harmony-4-8-office-hh17000001

Harmony high content imaging and analysis software. Used to quantify complex cellular phenotypes. Designed for PerkinElmer high content screening systems.

Proper citation: Harmony (RRID:SCR_018809) Copy   

•   Source: SciCrunch Registry

http://tuskegee.eagle-i.net/i/00000136-648c-c32f-ee37-018280000000

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 30,2023. Core provides services and training in computational biology, bioinformatics, experimental design and statistical analysis to the RCMI researchers and the biomedical research community at Tuskegee University.

Proper citation: Tuskegee University Computational Biology and Bioinformatics - Biomedical Information Management Services (RRID:SCR_010065) Copy   

•   Source: SciCrunch Registry

http://www.esri.com/software/arcgis/arcgis-for-desktop

Geographical information system software produced by Esri.

Proper citation: ArcGIS for Desktop Basic (RRID:SCR_011081) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/dna-microarray-core-facility-ualbany

Core provides microarray services for Affymetrix GeneChip arrays, Agilent microarrays, NimbleGen microarrays and custom-produced spotted cDNA microarrays. Projects developed through DNA Microarray Center have made use of arrays from variety of genomes, eukaryotic, prokaryotic, and plant. Core services includes RNA/DNA isolation, gene expression, miRNA, Chip-chip, Rip-chip and DNA methylation services. Provides bioinformatics tools for further analysis of results of expression experiments.

Proper citation: University at Albany Center for Functional Genomics DNA Microarray Core Facility (RRID:SCR_012502) Copy   

•   Source: SciCrunch Registry

https://github.com/cobilab/altair

Software C toolkit for alignment free and spatial temporal analysis of multi-FASTA data. Used for entangling presence of multiple sequences from epidemic and pandemic events.

Proper citation: AltaiR (RRID:SCR_024752) Copy   

•   Source: SciCrunch Registry

https://pepatac.databio.org/en/latest/

Software standardized pipeline for ATAC-seq data analysis with serial alignments. Leverages unique features of ATAC-seq data to optimize for speed and accuracy, and provides several unique analytical approaches. Downstream analysis is simplified by standard definition format, modularity of components, and metadata APIs in R and Python. Restartable, fault-tolerant, and can be run on local hardware, using any cluster resource manager, or in provided Linux containers. We also emphasize the advantage of aligning to the mitochondrial genome serially, which improves alignment and quality control metrics. Includes quality control plots, summary statistics, and variety of data formats.

Proper citation: PEPATAC (RRID:SCR_024758) Copy   

•   Source: SciCrunch Registry

https://www.mcgill.ca/cian/

Core facility at Biology Department in McGill Faculty of Science. Expertise in Light Microscopy and Image Analysis. Provides light microscopes, ranging from Point Scanning and Spinning Disc Confocals to Multi-Photon, TIRF, Light Sheet and Super-Resolution microscopes. Provides services in Automation/High throughput screening (liquid handler, pinning robot), Protein expression and antibody production. Users get training.

Proper citation: McGill Cell Imaging and Analysis Network Core Facility (RRID:SCR_012623) Copy   

•   Source: SciCrunch Registry

http://www.sbpdiscovery.org/technology/sr/Pages/LaJolla_MedicinalChemistry.aspx

Core facility that provides general synthetic and medicinal chemistry resources and expertise to the biomedical research community. Services include chemistry consulting for projects, grant applications, synthetic chemistry, medicinal chemistry, and analytical chemistry, as well as access to equipment for synthesis, purification, and analysis.

Proper citation: Sanford Burnham Prebys Medical Discovery Institute Medicinal Chemistry Facility (RRID:SCR_014872) Copy   

•   Source: SciCrunch Registry

http://diabetesresearch.med.umich.edu/Core_MCDTR_Methods.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on November 6,2024. Research core that works to assist investigators in designing studies, collecting data, and analyzing data to examine questions related to the causes, prevention, and control of diabetes, its complications, and comorbidities.

Proper citation: Michigan Center for Diabetes Translational Research Methods and Measurements Core (RRID:SCR_015188) Copy   

•   Source: SciCrunch Registry

http://www.tmanavigator.org/

A free web-based service open to all users for analysis of tissue microarray (TMA) data and related information, accommodating categorical, semi-continuous and continuous expression scores. There is no login requirement.

Proper citation: TMA Navigator (RRID:SCR_005599) Copy   

•   Source: SciCrunch Registry

http://biit.cs.ut.ee/graphweb/

GraphWeb allows the detection of modules from biological, heterogeneous and multi-species networks, and the interpretation of detected modules using Gene Ontology, cis-regulatory motifs and biological pathways. GraphWeb is a public web server for graph-based analysis of biological networks that: * analyses directed and undirected, weighted and unweighted heterogeneous networks of genes, proteins and microarray probesets for many eukaryotic genomes; * integrates multiple diverse datasets into global networks; * incorporates multispecies data using gene orthology mapping; * filters nodes and edges based on dataset support, edge weight and node annotation; * detects gene modules from networks using a collection of algorithms; * interprets discovered modules using Gene Ontology, pathways, and cis-regulatory motifs. Platform: Online tool

Proper citation: GraphWeb (RRID:SCR_005746) Copy   

•   Source: SciCrunch Registry

http://www.animalgenome.org/bioinfo/tools/catego/

CateGOrizer takes batch input of GO term IDs in a list format or unformatted plain text file, allows users to choose one of the available classifications such as GO_slim, GOA, EGAD, MGI_GO_slim, GO-ROOT, or a self-defined classification list, find its parental branch and performs an accumulative classification count, and returns the results in a sorted table of counts, percentages, and a pie chart (if it takes longer than standard time out period, it will email the user with a URL link to the results). This tool is comprised with a set of perl CGI programs coupled with a MySQL DBMS that stores the GO terms DAG data. Platform: Online tool

Proper citation: CateGOrizer (RRID:SCR_005737) Copy   

•   Source: SciCrunch Registry

https://github.com/csitron/Amino_acid_composition_and_hydrophobicity_analysis

Software package to analyze amino acid content and hydrophobicity profile of given set of protein sequences in fasta file. Used for analysis of amino acid composition and hydrophobicity of test sequences from fasta files.

Proper citation: Amino_acid_composition_and_hydrophobicity_analysis (RRID:SCR_026281) Copy   

•   Source: SciCrunch Registry

http://vortex.cs.wayne.edu/projects.htm#Onto-Design

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6,2023. Many Laboratories chose to design and print their own microarrays. At present, the choice of the genes to include on a certain microarray is a very laborious process requiring a high level of expertise. Onto-Design database is able to assist the designers of custom microarrays by providing the means to select genes based on their experiment. Design custom microarrays based on GO terms of interest. User account required. Platform: Online tool

Proper citation: Onto-Design (RRID:SCR_000601) Copy   

•   Source: SciCrunch Registry

http://cancergenome.nih.gov/

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy   

•   Source: SciCrunch Registry

http://platform.cerebellum.neuroinf.jp/

THIS RESOURCE IS NO LONGER IN SERVICE, documented January 13, 2022. Digital research archive for cerebellar research including mini-reviews of contemporary cerebellar research, list of papers and mathematical models for cerebellar operation.

Proper citation: Cerebellar Platform (RRID:SCR_001700) Copy   

•   Source: SciCrunch Registry

https://ag.purdue.edu/researchservices/

ARGE Research Services is dedicated to empowering Purdue Agriculture research by providing expert solutions in conducting team science, implementing best practices for data acquisition, stewardship, and analysis.

Proper citation: Purdue University College of Agriculture Research Services Core Facility (RRID:SCR_027377) Copy   

•   Source: SciCrunch Registry

https://qipcm.com/

Provides testing and analysis support for clinical trials to improve consistency and reliability in clinical trial data.Helps clinical investigators achieve systematic image collection and improved collaboration. Can help with handling large volume functional and dynamic imaging data.

Proper citation: University Health Network Quantitative Imaging for Personalized Cancer Medicine Advanced Imaging Core Facility (RRID:SCR_027527) Copy   

•   Source: SciCrunch Registry

https://www.ladydavis.ca/en/about/core-facilities/flow-cytometry/

Core provides complete flow cytometry analysis and cell sorting services in terms of experimental design, instrumentation, training, technical assistance and scientific guidance from sample preparation to publication.

Proper citation: Lady Davis Institute Flow Cytometry Core Facility (RRID:SCR_027644) Copy   

•   Source: SciCrunch Registry

http://sonorus.princeton.edu/hefalmp/

HEFalMp (Human Experimental/FunctionAL MaPper) is a tool developed by Curtis Huttenhower in Olga Troyanskaya's lab at Princeton University. It was created to allow interactive exploration of functional maps. Functional mapping analyzes portions of these networks related to user-specified groups of genes and biological processes and displays the results as probabilities (for individual genes), functional association p-values (for groups of genes), or graphically (as an interaction network). HEFalMp contains information from roughly 15,000 microarray conditions, over 15,000 publications on genetic and physical protein interactions, and several types of DNA and protein sequence analyses and allows the exploration of over 200 H. sapiens process-specific functional relationship networks, including a global, process-independent network capturing the most general functional relationships. Looking to download functional maps? Keep an eye on the bottom of each page of results: every functional map of any kind is generated with a Download link at the bottom right. Most functional maps are provided as tab-delimited text to simplify downstream processing; graphical interaction networks are provided as Support Vector Graphics files, which can be viewed using the Adobe Viewer, any recent version of Firefox, or the excellent open source Inkscape tool.

Proper citation: Human Experimental/FunctionAL MaPper: Providing Functional Maps of the Human Genome (RRID:SCR_003506) Copy   

•   Source: SciCrunch Registry