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http://openccdb-dev-web.crbs.ucsd.edu/software/index.shtm

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 2, 2019. Ontology-based segmentation and analysis tools for electron tomographic data.

Proper citation: Jinx (RRID:SCR_007012) Copy   

•   Source: SciCrunch Registry

http://www.cns.atr.jp/dni/en/downloads/tools-for-brain-behavior-data-sharing/

This is MATLAB library to create Neuroshare data format. You can convert your own data into Neuroshare format file.

Proper citation: Matlab Neuroshare Library (RRID:SCR_006957) Copy   

•   Source: SciCrunch Registry

http://ceolas.org/VL/mo/

Catalog of internet resources relating to biological model organisms, and is part of the Biosciences area of the Virtual Library project. The main Model Organisms Library discussed in this website are: * E. coli (bacterium) * Yeasts (Saccharomyces cerevisiae, and other species) * Dictyostelium discoideum (slime mold) * Drosophila melanogaster (fruit fly) * Xenopus laevis (African clawed frog) Many aspects of biology are similar in most or all organisms, but it is frequently much easier to study particular aspects in particular organisms - for instance, genetics is easier in small organisms that breed quickly, and very difficult in humans! The most popular model organisms have strong advantages for experimental research, and become even more useful when other scientists have already worked on them, discovering techniques, genes and other useful information.

Proper citation: The WWW Virtual Library: Model Organisms (RRID:SCR_007007) Copy   

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http://math.mcb.berkeley.edu/~meromit/MetMap/

A computational pipeline for the analysis of MethylSeq experiments., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MetMap (RRID:SCR_006954) Copy   

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http://smallrna.udel.edu/index.php

This project has developed a sequence dataset of plant small RNAs based on the hypothesis that most if not all plants utilize important small RNA signaling networks. Different plant families are likely to have both common and lineage-specific miRNAs or other small RNAs with important biological roles. Comparative genomics approaches can be applied to distinguish potential miRNAs from siRNAs and to match the miRNAs to the target sequences. This project develops an unparalleled resource of millions of plant small RNAs for comparative analyses. The project includes sequencing of small RNAs from a diverse and agronomically-relevant set of plant species, focused analyses of important members of the Solanaceae and Poaceae, and development of a small RNA database and web interface for public access and analysis of data. These data will allow the experimental characterization of the majority of biologically important small RNAs for a range of plant species, and will be tremendously useful to a broad set of plant biologists interested in development, stress responses, epigenetics, evolution, RNA biology and other traits impacted by small RNAs. We offer a variety of tools to query the small RNA data set, with options to identify sequences based on homology, expression levels, conservation, or potential function: 1. Small RNA mapping tool: searches for small RNAs perfectly matching a genomic sequence provided by the user. 2. Small RNA mismatch tool: searches the database for small RNAs or other short sequences provided by the user, allowing mismatches. 3. Library-comparison tool to identify conserved small RNAs. 4. Library-comparison tool to identify differentially regulated small RNAs. 5. Reverse Target Prediction.

Proper citation: Comparative Sequencing of Plant Small RNAs (RRID:SCR_007003) Copy   

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http://bowtie-bio.sourceforge.net/myrna/index.shtml

A cloud computing tool for calculating differential gene expression in large RNA-seq datasets. It uses Bowtie for short read alignment and R/Bioconductor for interval calculations, normalization, and statistical testing. These tools are combined in an automatic, parallel pipeline that runs in the cloud (Elastic MapReduce in this case) on a local Hadoop cluster, or on a single computer, exploiting multiple computers and CPUs wherever possible.

Proper citation: Myrna (RRID:SCR_006951) Copy   

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http://openccdb-dev-web.crbs.ucsd.edu/software/index.shtm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 4th,2023. A command line program in Unix to convert images to a variety of formats (PNG, TIFF, JPEG, PPM..etc). It is uniquely different from other programs such as Adobe Photoshop or ImageMagick because it is designed for dealing with the high-resolution images with file sizes of several gigabytes. Image Converter does not require any additional RAM or virtual memory to run. Also, run-time is relatively fast for high resolution data.

Proper citation: CCDB Image Converter (RRID:SCR_007005) Copy   

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https://mctfr.psych.umn.edu/

Composed of many projects, including the Minnesota Twin Family Study (MTFS) and The Sibling Interaction and Behavior Study (SIBS), this research center seeks to identify genetic and environmental influences on development and psychological traits. Both projects are longitudinal research studies including twins, siblings, and parents. Over 9800 individuals have contributed to these exciting projects! By studying twins and siblings and their families, we can estimate how genes and environment interact to influence character, strengths, vulnerabilities and values. Participants in the MTFS include families with same-sex identical or fraternal twins who were born in Minnesota. The SIBS study is comprised of adoptive and biological siblings and their parents. Most participants partake in day-long visits to the MCTFR, and due to the longitudinal nature of our projects, they return every 3-4 years for follow-up visits.

Proper citation: Minnesota Center for Twin and Family Research (RRID:SCR_006948) Copy   

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https://github.com/jstjohn/SimSeq

An illumina paired-end and mate-pair short read simulator. This project attempts to model as many of the quirks that exist in Illumina data as possible. Some of these quirks include the potential for chimeric reads, and non-biotinylated fragment pull down in mate-pair libraries .

Proper citation: SimSeq (RRID:SCR_006947) Copy   

•   Source: SciCrunch Registry

http://www.histmed.org/

A professional association of historians, physicians, nurses, archivists, curators, librarians, and others that promotes and encourages research, study, writing, and interest in the history of medicine and allied fields.

Proper citation: American Association for the History of Medicine (RRID:SCR_003161) Copy   

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http://pir.georgetown.edu/pirwww/dbinfo/pirsf.shtml

A SuperFamily classification system, with rules for functional site and protein name, to facilitate the sensible propagation and standardization of protein annotation and the systematic detection of annotation errors. The PIRSF concept is being used as a guiding principle to provide comprehensive and non-overlapping clustering of UniProtKB sequences into a hierarchical order to reflect their evolutionary relationships. The PIRSF classification system is based on whole proteins rather than on the component domains; therefore, it allows annotation of generic biochemical and specific biological functions, as well as classification of proteins without well-defined domains. There are different PIRSF classification levels. The primary level is the homeomorphic family, whose members are both homologous (evolved from a common ancestor) and homeomorphic (sharing full-length sequence similarity and a common domain architecture). At a lower level are the subfamilies which are clusters representing functional specialization and/or domain architecture variation within the family. Above the homeomorphic level there may be parent superfamilies that connect distantly related families and orphan proteins based on common domains. Because proteins can belong to more than one domain superfamily, the PIRSF structure is formally a network. The FTP site provides free download for PIRSF.

Proper citation: PIRSF (RRID:SCR_003352) Copy   

•   Source: SciCrunch Registry

http://biomed.emory.edu/PROGRAM_SITES/MSP/

The Molecular and Systems Pharmacology graduate program at Emory University offers broad training in the biomedical sciences for students interested in learning how the drugs of today work and how the novel therapeutics of tomorrow can be developed. The Program offers a specialization in toxicology. Emory University was recently rated by The Scientist magazine as the number 1 university in the world in terms of impact in pharmacology and toxicology research. Particular strengths within the MSP graduate school program at Emory include neuropharmacology, cancer biology, AIDS research, cardiovascular pharmacology, toxicology, and chemical biology. Ph.D. training in the Emory MSP program provides students with an ideal preparation for successful careers in the biotechnology and pharmaceutical industries as well as in academic research, teaching, government research, patent law and other disciplines that depend upon knowledge of fundamental pharmacological principles.

Proper citation: Emory University, Molecular and Systems Pharmacology (RRID:SCR_003351) Copy   

•   Source: SciCrunch Registry

http://www.gwumc.edu/pharm/

The Department of Pharmacology & Physiology at the George Washington University provides unique research opportunities at the predoctoral and postdoctoral levels. They also offer courses in Pharmacology and Physiology for Medical and Health Sciences students, as well as a number of graduate-level courses. Our mission is to provide the highest quality of educational opportunities to our community, and to advance scientific knowledge and improve human health through leading-edge research in the biomedical sciences.

Proper citation: George Washington University, Department of Pharmacology and Physiology (RRID:SCR_003358) Copy   

•   Source: SciCrunch Registry

http://mouseNET.princeton.edu

A functional network for laboratory mouse based on integration of diverse genetic and genomic data. It allows the users to accurately predict novel functional assignments and network components. MouseNET uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the mouseNET algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. The graph may be explored further. As you move the mouse over genes in the network, interactions involving these genes are highlighted.If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed.

Proper citation: MouseNET (RRID:SCR_003357) Copy   

•   Source: SciCrunch Registry

http://niftilib.sourceforge.net

Niftilib is a set of i/o libraries for reading and writing files in the nifti-1 data format. nifti-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. Niftilib currently has C, Java, MATLAB, and Python libraries; we plan to add some MATLAB/mex interfaces to the C library in the not too distant future. Niftilib has been developed by members of the NIFTI DFWG and volunteers in the neuroimaging community and serves as a reference implementation of the nifti-1 file format. In addition to being a reference implementation, we hope it is also a useful i/o library. Niftilib code is released into the public domain, developers are encouraged to incorporate niftilib code into their applications, and, to contribute changes and enhancements to niftilib. Please contact us if you would like to contribute additonal functionality to the i/o library.

Proper citation: Niftilib (RRID:SCR_003355) Copy   

•   Source: SciCrunch Registry

http://www.etsu.edu/com/pharmacology/default.aspx

Faculty members of our Department are actively engaged in delivering outstanding teaching to undergraduate students, graduate students, medical students, and residents. Our Doctor of Philosophy (graduate) students matriculate to Pharmacology through the Biomedical Sciences Graduate Program at the Quillen College of Medicine. Students pursuing Master of Science and Doctor of Philosophy degrees may pursue a focus in Toxicology. Our faculty members are trained in several medical disciplines and our research applies methodological approaches that span molecular biology, cellular biology, systems biology, and human biology and pathology. Through research, our department strives to understand human disease pathology and use this understanding to develop new therapeutic entities (e.g. drugs) for the treatment of major human diseases. The primary foci of department research efforts are cardiovascular and neuropsychiatric diseases, although other areas of interest and activity exist. Our laboratories are funded by the National Institutes of Health, American Heart Association, the American Foundation for Suicide Prevention and a variety of other agencies and sources.

Proper citation: East Tennessee State University, Department of Pharmacology (RRID:SCR_003350) Copy   

•   Source: SciCrunch Registry

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

An ontology that describes the LIPIDMAPS nomenclature classification explicitly using description logics (OWL-DL). Lipid classes are organized hierarchically with the super-classes restricted by generic necessary conditions. More specific necessary conditions are used to define membership requirements for sub classes of lipid according to appropriate functional groups. Lipid research is increasingly integrated within systems level biology such as lipidomics where lipid classification is required before appropriate annotation of chemical functions can be applied.

Proper citation: Lipid Ontology (RRID:SCR_003349) Copy   

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http://unp.aas.duke.edu//

The major and minor in Neuroscience at Duke University was approved by the Arts and Sciences Council of Trinity College of Arts and Sciences on April 9, 2009. The program offers three academic plans: Bachelor of Science (B.S.) degree in Neuroscience, Bachelor of Arts (A.B.) degree in Neuroscience, and a Minor in Neuroscience. Although Neuroscience is a new major/minor, there is a rich and long-standing tradition of excellence in undergraduate neuroscience research and education at Duke. Groups of faculty in the Department of Psychology and Neuroscience and the Department of Biology, as well as the Department of Neurobiology in the Duke University School of Medicine, have been especially engaged in teaching neuroscience in undergraduate classes and hosting independent study projects in their research laboratories. Building upon this broad foundation, the new Undergraduate Studies in Neuroscience program is a truly interdisciplinary experience reflecting the diverse sources of knowledge that advance our understanding of the brain sciences. Undergraduate Studies in Neuroscience is a unique collaboration among many Departments and Schools , with administrative support provided by Trinity College of Arts and Sciences and the Duke Institute for Brain Sciences.

Proper citation: Duke University Trinity College of Arts and Sciences Undergraduate Neuroscience (RRID:SCR_003345) Copy   

•   Source: SciCrunch Registry

http://www.xpmutations.org

Interactive repository of mutations and other allelic variations of the genes involved in the DNA repair disorders, Xeroderma Pigmentosum (XP), Cockayne Syndrome (CS), Trichothiodystrophy (TTD), and other UV-sensitivity disorders. Any omitted data or new data may be submitted by using the on-line data submission form. There is a message board system to support discussions amongst those interested in XP and DNA Repair. RESOURCES * Educational module of the molecular biology of Nucleotide Excision Repair * Introduction to the DNA Repair disorders (XP, CS, TTD, UVs) * Background on each of the XP genes * A searchable database of mutations and sequence variations for the XP genes * Contact point for the submission of new mutation data * Discussion Forums and a Guest Book * Web Links to Additional Resources

Proper citation: Allelic Variations of The XP Genes (RRID:SCR_003376) Copy   

•   Source: SciCrunch Registry

https://www.fishersci.com/us/en/brands/IAOCLVV5/fisher-bioreagents.html

An Antibody supplier

Proper citation: Fisher BioReagents (RRID:SCR_003374) Copy   

•   Source: SciCrunch Registry