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http://www.genedata.com/products/expressionist/genomic-profiling.html

Software that provides data processing, analysis, management, and reporting of metabolomics, proteomics and biotherapeutics characterization studies based on mass spectrometry. It can process raw data from various MS instruments, serve MS processing, analysis and reporting needs, and ensure reproducibility and traceability of results.

Proper citation: Genedata Expressionist (RRID:SCR_003298) Copy   

•   Source: SciCrunch Registry

http://www.bioontology.org/wiki/index.php/CARO:Main_Page

An ontology developed to facilitate interoperability between existing anatomy ontologies for different species, and to provide a template for building new anatomy ontologies.

Proper citation: Common Anatomy Reference Ontology (RRID:SCR_003296) Copy   

•   Source: SciCrunch Registry

http://edoctoring.ncl.ac.uk/Public_site/

Online educational tool that brings challenging clinical practice to your computer, providing medical education that is engaging, challenging and interactive. While there is no substitute for real-life direct contact with patients or colleagues, research has shown that interactive online education can be a highly effective and enjoyable method of learning many components of clinical medicine, including ethics, clinical management, epidemiology and communication skills. eDoctoring offers 25 simulated clinical cases, 15 interactive tutorials and a virtual library containing numerous articles, fast facts and video clips. Their learning material is arranged in the following content areas: * Ethical, Legal and Social Implications of Genetic Testing * Palliative and End-of-Life Care * Prostate Cancer Screening and Shared Decision-Making

Proper citation: eDoctoring (RRID:SCR_003336) Copy   

•   Source: SciCrunch Registry

http://www.decode.com/

A biopharmaceutical company applying its discoveries in human genetics to develop drugs and diagnostics for common diseases. They specialize in gene discovery - their population approach and resources have enabled them to isolate key genes contributing to major public health challenges from cardiovascular disease to cancer. The company's genotyping capacity is now one of the highest in the world. They have a large population-based biobank containing whole blood and DNA samples with extensive relevant phenotypic information from around 120.000 Icelanders. In the company's work in more than 50 disease projects, their statistical and informatics departments have established themselves in data processing and analysis. deCODE genetics is widely recognized as a center of excellence in genetic research.

Proper citation: deCODE genetics (RRID:SCR_003334) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CMO

An ontology designed to be used to standardize morphological and physiological measurement records generated from clinical and model organism research and health programs.

Proper citation: Clinical Measurement Ontology (RRID:SCR_003291) Copy   

•   Source: SciCrunch Registry

http://primerseq.sourceforge.net/

Software that designs RT-PCR primers that evaluate alternative splicing events by incorporating RNA-Seq data. It is particularly advantageous for designing a large number of primers for validating alternative splicing events found in RNA-Seq data. It incorporates RNA-Seq data in the design process to weight exons by their read counts. Essentially, the RNA-Seq data allows primers to be placed using actually expressed transcripts. This could be for a particular cell line or experimental condition, rather than using annotations that incorporate transcripts that are not expressed for the data. Alternatively, you can design primers that are always on constitutive exons. PrimerSeq does not limit the use of gene annotations and can be used for a wide array of species.

Proper citation: PrimerSeq (RRID:SCR_003295) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/OmicCircos.html

An R software application and package used to generate high-quality circular plots for visualizing genomic variations, including mutation patterns, copy number variations (CNVs), expression patterns, and methylation patterns.

Proper citation: OmicCircos (RRID:SCR_003292) Copy   

•   Source: SciCrunch Registry

http://cumc.columbia.edu/dept/gsas/pharm/index.html

The spirit of the Department of Pharmacology is one of collaborative and synergistic science. As such, interests of the members of the Department span such diverse problems as the identification of molecular signals that determine whether a cell lives or dies to the discovery of new drugs that control cardiac rhythm in inherited and non-inherited heart disease. We at Columbia in general, and within the Department of Pharmacology in particular, are proud to be an integral part of the intellectual and cultural life of New York. In many ways the diversity of scientific interests within the Department reflect the diversity of the rich scientific environment of Columbia University and, in addition, the unique cultural and urban environment of New York City. Within the Graduate Programs in Mechanisms of Health and Disease, the Department of Pharmacology offers a Pharmacology and Molecular Signaling Program leading to the Ph.D. degree. Training is focused on both classical principles of pharmacology and more modern biophysical, genetic and computational approaches to the development of new and more specific therapeutic agents to manage human disease. The interdisciplinary training program in the molecular and genetic basis of cardiac arrhythmias is designed to provide training to post doctoral fellows with either M.D. or Ph.D. degrees to enable them to become independent researchers and leaders in the field as we enter a period of post genomic medical science. The overall aim of the program is to train researchers who will be well-grounded in molecular and cellular biology, but who also are trained in cardiovascular systems physiology/pharmacology in order to integrate the cellular and subcellular mechanisms (genotype) with the basis of human disease expressed at the systems level (phenotype).

Proper citation: Columbia University College of Physicians and Surgeons Department of Pharmacology (RRID:SCR_003320) Copy   

•   Source: SciCrunch Registry

https://github.com/rsc-ontologies/rsc-cmo

An ontology that describes methods used to collect data in chemical experiments, such as mass spectrometry and electron microscopy; preparing and separating material for further analysis, such as sample ionization, chromatography, and electrophoresis; and synthesizing materials, such as epitaxy and continuous vapor deposition. It also describes the instruments used in these experiments, such as mass spectrometers and chromatography columns. It is intended to be complementary to the Ontology for Biomedical Investigations (OBI).

Proper citation: Chemical Methods Ontology (RRID:SCR_003286) Copy   

•   Source: SciCrunch Registry

http://shendurelab.github.io/MIPGEN/

Software for a fast, simple way to generate designs for MIP assays targeting hundreds or thousands of genomic loci in parallel. Packaged with MIPgen are scripts that aid in visualization of MIP designs and processing of MIP sequence reads to SAM files that can then be passed through any standard variant calling pipeline.

Proper citation: MIPgen (RRID:SCR_003325) Copy   

•   Source: SciCrunch Registry

http://neuroscience.med.cornell.edu/

The Weill Medical College of Cornell University has a long tradition of neuroscience research. The faculty is large, and the research programs tackle the fundamental questions in the field at all levels - from genes to cells to systems to behavior. The neuroscience community at Weill Cornell spans two campuses. The main one, containing the medical school and associated hospitals, is located on the upper east side of Manhattan, adjacent to Rockefeller University and across the street from the Memorial Sloan-Kettering Cancer Center. The second campus, with the rapidly growing Burke-Cornell Research Institute, is located in White Plains. The following graduate programs are offered: Neuroscience PhD, Tri-Institutional MD-PhD, Physiology and Biophysics, and Tri-Institutional Graduate program in Computational Biology and Medicine.

Proper citation: Cornell University Neuroscience (RRID:SCR_003324) Copy   

•   Source: SciCrunch Registry

https://www.msu.edu/~brains/index.html

The Brain Biodiversity Bank refers to the repository of images of and information about brain specimens contained in the collections associated with the National Museum of Health and Medicine at the Armed Forces Institute of Pathology in Washington, DC. Atlases and brain sections are available for a variety of mammals, and we are also developing a series of labeled atlases of stained sections for educators, students, and researchers. These collections include, besides the Michigan State University Collection, the Welker Collection from the University of Wisconsin, the Yakovlev-Haleem Collection from Harvard University, the Meyer Collection from the Johns Hopkins University, and the Huber-Crosby and Crosby-Lauer Collections from the University of Michigan. What we are doing currently at Michigan State is a series of demonstration projects for publicizing the contents of the collections and ways in which they can be used. For example, the images from the collection can be used for comparative brain study. We have prepared databases of the contents of the collections for presentation and use on this site, as well as for downloading by users in several formats. We are also developing a series of labeled atlases of stained sections for educators, students, and researchers. This internet site is associated with the Comparative Mammalian Brain Collections site. All of the images are in JPEG or GIF format.

Proper citation: Michigan State University Brain Biodiversity Bank (RRID:SCR_003289) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/popoolation2/

Software to compare allele frequencies for SNPs between two or more populations and to identify significant differences. PoPoolation2 requires next generation sequencing data of pooled genomic DNA (Pool-Seq). It may be used for measuring differentiation between populations, for genome wide association studies and for experimental evolution., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PoPoolation2 (RRID:SCR_003284) Copy   

•   Source: SciCrunch Registry

http://www.yaleruddcenter.org/

A non-profit research and public policy organization devoted to improving the worlds diet, preventing obesity, and reducing weight stigma.

Proper citation: Yale Rudd Center for Food Policy and Obesity (RRID:SCR_003283) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/FB-CV

A structured controlled vocabulary used for various aspects of annotation by FlyBase. This ontology is maintained by FlyBase for various aspects of annotation not covered, or not yet covered, by other OBO ontologies. If and when community ontologies are available for the domains here covered FlyBase will use them.

Proper citation: FlyBase Controlled Vocabulary (RRID:SCR_003318) Copy   

•   Source: SciCrunch Registry

http://www.brainbank.mclean.org/

Biomaterial supply resource that acquires, processes, stores, and distributes postmortem brain specimens for brain research. Various types of brain tissue are collected, including those with neurological and psychiatric disorders, along with their parents, siblings and offspring. The HBTRC maintains an extensive collection of postmortem human brains from individuals with Huntington's chorea, Alzheimer's disease, Parkinson's disease, and other neurological disorders. In addition, the HBTRC also has a collection of normal-control specimens.

Proper citation: Harvard Brain Tissue Resource Center (RRID:SCR_003316) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/FYPO

A formal ontology of phenotypes observed in fission yeast that is being developed to support the comprehensive and detailed representation of phenotypes in PomBase, the online fission yeast resource. Its scope is similar to that of the Ascomycete Phenotype Ontology (APO), but FYPO includes more detailed pre-composed terms as well as computable definitions.

Proper citation: Fission Yeast Phenotype Ontology (RRID:SCR_003315) Copy   

•   Source: SciCrunch Registry

https://github.com/outbig/DAFGA

A python script package which estimates the evolutionary rate of a particular functional gene in a standardized manner by relating its sequence divergence to that of the 16S rRNA gene. It provides gene-specific parameter sets for OTU clustering and taxonomic assignment at desired rank, and it can be implemented into the diversity measurements offered by QIIME or Mothur.

Proper citation: DAFGA (RRID:SCR_003319) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/johanneskoester/snakemake/wiki/

A Python based language and execution environment for make-like workflows. The system supports the use of automatically inferred multiple named wildcards (or variables) in input and output filenames.

Proper citation: Snakemake (RRID:SCR_003475) Copy   

•   Source: SciCrunch Registry

http://bbid.irp.nia.nih.gov/

Database of images of putative biological pathways, macromolecular structures, gene families, and cellular relationships. It is of use to those who are working with large sets of genes or proteins using cDNA arrays, functional genomics, or proteomics. The rationale for this collection is that: # Except in a few cases, information on most biological pathways in higher eukaryotes is non-existent, incomplete, or conflicting. # Similar biological pathways differ by tissue context, developmental stages, stimulatory events, or for other complex reasons. This database allows comparisons of different variations of pathways that can be tested empirically. # The goal of this database is to use images created directly by biomedical scientists who are specialists in a particular biological system. It is specifically designed to NOT use average, idealized or redrawn pathways. It does NOT use pathways defined by computer algorithm or information search approaches. # Information on biological pathways in higher eukaryotes generally resides in the images and text of review papers. Much of this information is not easily accessible by current medical reference search engines. # All images are attributable to the original authors. All pathways or other biological systems described are graphic representations of natural systems. Each pathway is to be considered a work in progress. Each carries some degree of error or incompleteness. The end user has the ultimate responsibility to determine the scientific correctness and validity in their particular biological system. Image/pathway submissions are welcome.

Proper citation: Biological Biochemical Image Database (RRID:SCR_003474) Copy   

•   Source: SciCrunch Registry