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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://www.uccs.edu/~faculty/lbecker/
Calculator for a variety of functions, including Cohen's d and the effect-size correlation, rYl, using means and standard deviations or independent groups t test values and df.
Proper citation: Effect Size Calculator (RRID:SCR_003094) Copy
A consortium of representatives from each of the NIH institutes and centers. BISTI was established in May 2000 to serve as the focus of biomedical computing issues at the NIH. The mission of BISTI is to make optimal use of computer science and technology to address problems in biology and medicine by fostering new basic understandings, collaborations, and transdisciplinary initiatives between the computational and biomedical sciences. In support of this mission, the BISTI coordinates research grants, training opportunities, and scientific symposia associated with biomedical computing. Regular monthly meetings are conducted to discuss program status, future needs and directions, and topics of interest to the bioinformatics community.
Proper citation: Biomedical Information Science and Technology Initiative (RRID:SCR_003123) Copy
http://cran.r-project.org/web/packages/gap/
GAP is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, classic twin models, probability of familial disease aggregation, kinship calculation, some statistics in linkage analysis, and association analysis involving one or more genetic markers including haplotype analysis with or without environmental covariates.
Proper citation: Genetic Analysis Package (RRID:SCR_003006) Copy
http://isps.yale.edu/research/data
Data archive to assist in the sharing of research grade information pertaining to the social and economic sciences. The majority of digital content currently consists of social science research data from experiments, program files with the code for analyzing the data, requisite documentation to use and understand the data, and associated files. Access to the ISPS Data Archive is provided at no cost and is granted for scholarship and research purposes only. When possible, Data is linked to Projects and Publications, via the ISPS KnowledgeBase. ISPS operates in accordance with the prevailing standards and practices of the digital preservation community including the Open Archival Information System (OAIS) Reference Model (ISO 14721:2003) and the Data Documentation Initiative (DDI) standard. Accordingly, ISPS supports digital life-cycle management, interoperability, and preferred methods of preservation. The ISPS Data Archive is intended for use by social science researchers, policy-makers, and practitioners who are conducting or analyzing field (and other) experiments in various social science disciplines. Currently, Replication Files originate with ISPS-affiliated scholars.
Proper citation: ISPS Data Archive (RRID:SCR_003127) Copy
http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi
A web interface to the Primer3 primer design program as an enhanced alternative for the CGI- scripts that come with Primer3.
Proper citation: Primer3Plus (RRID:SCR_003081) Copy
A XML-based description language that provides a common data format for defining and exchanging descriptions of neuronal cell and network models. It facilitates the exchange of complex neural models, allows for greater transparency and accessibility of models, enhances interoperability between simulators and other tools, and supports the development of new software and databases. Exchange of network models will aid the investigation of structure-function relationships in neuroscience including theoretical studies relating connectivity patterns to normal and neurodegenerative network states. NeuroML is a free and open community effort developed with input from many contributors. They will need your help as the standards and tools continue to evolve.
Proper citation: NeuroML (RRID:SCR_003083) Copy
https://www.ddbj.nig.ac.jp/jga/index-e.html
A service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The JGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the JGA. Once processed, all data are encrypted. The JGA accepts only de-identified data approved by JST-NBDC. The JGA implements access-granting policy whereby the decisions of who will be granted access to the data resides with the JST-NBDC. After data submission the JGA team will process the data into databases and archive the original data files. The accepted data types include manufacturer-specific raw data formats from the array-based and new sequencing platforms. The processed data such as the genotype and structural variants or any summary level statistical analyses from the original study authors are stored in databases. The JGA also accepts and distributes any phenotype data associated with the samples. For other human biological data, please contact the NBDC human data ethical committee.
Proper citation: Japanese Genotype-phenotype Archive (JGA) (RRID:SCR_003118) Copy
http://bioconductor.org/packages/release/bioc/html/tweeDEseq.html
Software for differential expression analysis of RNA-seq using the Poisson-Tweedie family of distributions.
Proper citation: tweeDEseq (RRID:SCR_003038) Copy
http://www.mged.org/Workgroups/MAGE/mage-ml.html
A language / data exchange format designed to describe and communicate information about microarray based experiments that is based on XML and can describe microarray designs, microarray manufacturing information, microarray experiment setup and execution information, gene expression data and data analysis results. MAGE-ML has been automatically derived from Microarray Gene Expression Object Model (MAGE-OM), which is developed and described using the Unified Modelling Language (UML) -- a standard language for describing object models. Descriptions using UML have an advantage over direct XML document type definitions (DTDs), in many respects. First they use graphical representation depicting the relationships between different entities in a way which is much easier to follow than DTDs. Second, the UML diagrams are primarily meant for humans, while DTDs are meant for computers. Therefore MAGE-OM should be considered as the primary model, and MAGE-ML will be explained by providing simplified fragments of MAGE-OM, rather then XML DTD or XML Schema. (from the description by Ugis Sarkans) The field of gene expression experiments has several distinct technologies that a standard must include. These include single vs. dual channel experiments, cDNA vs. oligonucleotides. Because of these different technologies and different types of gene expression experiments, it is not expected that all aspects of the standard will be used by all organizations. Given the massive amount of data associated with a single set of experiments, it is felt that Extensible Markup Language (XML) is the best way to describe the data. The use of a Document Type Definition (DTD) allows a well-defined tag set, a vocabulary, to describe the domain of gene expression experiments. It also has the virtue of compressing very well so that files in an XML format compress to ten percent of their original size. XML is now widely accepted as a data exchange format across multiple platforms.
Proper citation: MicroArray and Gene Expression Markup Language (RRID:SCR_003023) Copy
http://bioconductor.org/packages/release/bioc/html/BRAIN.html
Software package for calculating aggregated isotopic distribution and exact center-masses for chemical substances (in this version composed of C, H, N, O and S).
Proper citation: BRAIN (RRID:SCR_003018) Copy
Portal for preclinical information and research materials, including web-accessible data and tools, NCI-60 Tumor Cell Line Screen, compounds in vials and plates, tumor cells, animals, and bulk drugs for investigational new drug (IND)-directed studies. DTP has been involved in the discovery or development of more than 70 percent of the anticancer therapeutics on the market today, and will continue helping the academic and private sectors to overcome various therapeutic development barriers, particularly through supporting high-risk projects and therapeutic development for rare cancers. Initially DTP made its drug discovery and development services and the results from the human tumor cell line assay publicly accessible to researchers worldwide. At first, the site offered in vitro human cell line data for a few thousand compounds and in vitro anti-HIV screening data for roughly 42,000 compounds. Today, visitors can find: * Downloadable in vitro human tumor cell line data for some 43,500 compounds and 15,000 natural product extracts * Results for 60,000 compounds evaluated in the yeast assay * In vivo animal model results for 30,000 compounds * 2-D and 3-D chemical structures for more than 200,000 compounds * Molecular target data, including characterizations for at least 1,200 targets, plus data from multiple cDNA microarray projects In addition to browsing DTP's databases and downloading data, researchers can request individual samples or sets of compounds on 96-well plates for research, or they can submit their own compounds for consideration for screening via DTP's online submission form. Once a compound is submitted for screening, researchers can follow its progress and retrieve data using a secure web interface. The NCI has collected information on almost half a million chemical structures in the past 50 years. DTP has made this information accessible and useful for investigators through its 3-D database, a collection of three-dimensional structures for more than 200,000 drugs. Investigators use the 3-D database to screen compounds for anticancer therapeutic activity. Also available on DTP's website are 127,000 connection tables for anticancer agents. A connection table is a convenient way of depicting molecular structures without relying on drawn chemical structures. As unique lists of atoms and their connections, the connection tables can be indexed and stored in computer databases where they can be used for patent searches, toxicology studies, and precursor searching, for example., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Developmental Therapeutics Program (RRID:SCR_003057) Copy
https://code.google.com/p/sasqpcr/
All-in-one computer program for robust and rapid analysis of quantitative reverse transcription real-time polymerase chain reaction (RT-qPCR) data in SAS. It incorporates all functions important for RT-qPCR data analysis including assessment of PCR efficiencies, validation of internal reference genes and normalizers, normalization of confounding variations across samples and statistical comparisons of target gene expression in parallel samples. The program is highly automatic in data analyses and result output. The input data have no limitations for the number of genes or cDNA samples. Users can simply change the macro variables to test various analytical strategies, optimize results and customize the analytical processes. The program is also extendable allowing advanced SAS users to develop particular statistical tests appropriate for their experimental designs. Thus users are the actual decision-makers controlling RT-qPCR data analyses. The program has to be used in SAS software; however, extensive SAS programming knowledge is not required.
Proper citation: SASqPCR (RRID:SCR_003056) Copy
http://www.bioconductor.org/packages/release/bioc/html/survcomp.html
R package providing functions to assess and to compare the performance of risk prediction (survival) models.
Proper citation: SurvComp (RRID:SCR_003054) Copy
Software Python package for simulating spiking neural networks. Useful for neuroscientific modelling at systems level, and for teaching computational neuroscience. Intuitive and efficient neural simulator.
Proper citation: Brian Simulator (RRID:SCR_002998) Copy
http://developingmouse.brain-map.org/
Map of gene expression in developing mouse brain revealing gene expression patterns from embryonic through postnatal stages. Provides information about spatial and temporal regulation of gene expression with database. Feature include seven sagittal reference atlases created with a developmental ontology. These anatomic atlases may be viewed alongside in situ hybridization (ISH) data as well as by itself.
Proper citation: Allen Developing Mouse Brain Atlas (RRID:SCR_002990) Copy
https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/pacBioToCA
A module in the Celera Assembler software package that performs error correction on PacBio long reads by mapping shorter, high accuracy reads onto the long reads.
Proper citation: PacBioToCA (RRID:SCR_003044) Copy
http://bibiserv.techfak.uni-bielefeld.de/dialign/
Tool for multiple sequence alignment using various sources of external information that is particularly useful to detect local homologies in sequences with low overall similarity. While standard alignment methods rely on comparing single residues and imposing gap penalties, DIALIGN constructs pairwise and multiple alignments by comparing entire segments of the sequences. No gap penalty is used. This approach can be used for both global and local alignment, but it is particularly successful in situations where sequences share only local homologies. Several versions of DIALIGN are available online at GOBICS, http://dialign.gobics.de/
Proper citation: DIALIGN (RRID:SCR_003041) Copy
Cancer institute that provides expert, compassionate care to children and adults with cancer while advancing the understanding, diagnosis, treatment, cure, and prevention of cancer and related diseases. As an affiliate of Harvard Medical School and a Comprehensive Cancer Center designated by the National Cancer Institute, the Institute also provides training for new generations of physicians and scientists, designs programs that promote public health particularly among high-risk and underserved populations, and disseminates innovative patient therapies and scientific discoveries to their target community across the United States and throughout the world.
Proper citation: Dana-Farber Cancer Institute (RRID:SCR_003040) Copy
Database of journal information that provides tools to search, sort, filter, compare, and evaluate scholarly journals. In addition to searching by journal name, category or publisher, authors can use title and abstract of paper to discover journals that have already published articles on similar topics. Data sources include major industry data sets, public resources, information submitted directly by journal editors, and real-life publishing experiences submitted by authors.
Proper citation: JournalGuide (RRID:SCR_003236) Copy
An open XML-based language used to describe the formatting of citations and bibliographies. CSL has become the standard way to add citation support to software.
Proper citation: Citation Style Language (RRID:SCR_003234) Copy
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