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http://jcb-dataviewer.rupress.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. A web-based, multi-dimensional image data-viewing application for original microscopy image datasets associated with articles published in The Journal of Cell Biology, a peer-reviewed journal published by The Rockefeller University Press. The JCB DataViewer can host multidimensional fluorescence microscopy images, 3D tomogram data, very large (gigapixel) images, and high content imaging screens. Images are presented in an interactive viewer, and the scores from high content screens are presented in interactive graphs with data points linked to the relevant images. The JCB DataViewer uses the Bio-Formats library to read over 120 different imaging file formats and convert them to the OME-TIFF image data standard. Image data are archived by the Journal and may be freely accessed by readers using the JCB DataViewer. Download of author-provided image data and associated metadata in OME-TIFF format is also possible with author permission, allowing for independent analysis of image data irrespective of acquisition or viewing software. Although the JCB DataViewer is designed to host and facilitate sharing and analysis of original microscopy image data, authors may also upload other types of original image data as supplements to their manuscripts, including histology and electron micrographs and digital scans of gels or blots.

Proper citation: JCB DataViewer (RRID:SCR_002633) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/bio-rainbow/

Software developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq.

Proper citation: Rainbow (RRID:SCR_002724) Copy   

•   Source: SciCrunch Registry

http://biohealth.snu.ac.kr/software/TRAP/

A comprehensive software package integrating all necessary tasks such as mapping short reads, measuring gene expression levels, finding differentially expressed genes (DEGs), clustering and pathway analysis for time-series data in a single environment.

Proper citation: Time-series RNA-seq Analysis Package (RRID:SCR_002935) Copy   

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http://www.fmrib.ox.ac.uk/fsl/

Software library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. Include registration, atlases, diffusion MRI tools for parameter reconstruction and probabilistic taractography, and viewer. Several brain atlases, integrated into FSLView and Featquery, allow viewing of structural and cytoarchitectonic standard space labels and probability maps for cortical and subcortical structures and white matter tracts. Includes Harvard-Oxford cortical and subcortical structural atlases, Julich histological atlas, JHU DTI-based white-matter atlases, Oxford thalamic connectivity atlas, Talairach atlas, MNI structural atlas, and Cerebellum atlas.

Proper citation: FSL (RRID:SCR_002823) Copy   

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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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.nematodes.org/

Nematode & Neglected Genomics (at) The Blaxter Lab is a nematode related portal including databases and services. Resources include genomic and transcriptomic databases for nematodes and other metazoan phyla and freely downloadable software tools for expressed sequence tag analysis, DNA barcode analysis and phylogenomics. Major categories include: * GenePool * 959 Nematode Genomes * Teaching * Research Projects * Bioinformatics Software Tools * Lab Personnel * Lab Wiki * Genomics Databases * NEMBASE4 * Tardigrada: Hypsibius dujardini * Earthworm: Lumbricus rubellus * MolluscDB * ArthropodDB * other Neglected Genomes

Proper citation: nematodes.org (RRID:SCR_003267) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/software/genepattern

A powerful genomic analysis platform that provides access to hundreds of tools for gene expression analysis, proteomics, SNP analysis, flow cytometry, RNA-seq analysis, and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.

Proper citation: GenePattern (RRID:SCR_003201) Copy   

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http://www.cma.mgh.harvard.edu/iatr/

A centrally available listing of all image analysis tools that are available to the neuroscience community in order to facilitate the development, identification, and sharing of tools. It is hoped that this helps the tool developers to get their tools to a larger user community and to reduce redundancy (or at least utilize tool redundancy to facilitate optimal tool design) in tool development. This also helps tool users in identification of the existing tools for specific problems as they arise. The registry is designed to be self-moderated. This means that all tool entries are owned by some responsible party who enters the tool information, and keeps it up to date via the Web.

Proper citation: Internet Analysis Tools Registry (RRID:SCR_005638) Copy   

•   Source: SciCrunch Registry

http://genemania.org/

Data analysis service to predict the function of your favorite genes and gene sets. Indexing 1,421 association networks containing 266,984,699 interactions mapped to 155,238 genes from 7 organisms. GeneMANIA interaction networks are available for download in plain text format. GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets. GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest. GeneMANIA is also a gene recommendation system. GeneMANIA is also accessible via a Cytoscape plugin, designed for power users. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMANIA (RRID:SCR_005709) Copy   

•   Source: SciCrunch Registry

http://estbioinfo.stat.ub.es/?page_id=2

The Statistics and Bioinformatics research group has as its main objectives the development of methods and tools to deal with problems appearing in the interface between Statistics and Bioinformatics. We started focusing in DNA microarrays but we are also interested in statistical methods for ''omics'' data integration and next generation sequencing (NGS). Our group collaborates with different research groups in the fields of biology and biomedicine, to whom it offers statistical support for problems which are specifically statistic in nature, such as experimental design or microarray data analysis, and also in more general aspects, such as modeling, analysis or data mining. After a first period of collaboration agreements with the Fundaci�� Vall d''Hebr��n Institut de Recerca we contributed to the creation of the Statistics and Bioinformatics Unit (UEB) which provides statistical and bioinformatical support to VHIR researchers.

Proper citation: University of Barcelona Statistics and Bioinformatics Research Group (RRID:SCR_005704) Copy   

•   Source: SciCrunch Registry

http://geneontology.svn.sourceforge.net/viewvc/geneontology/go-moose/

go-moose is intended as a replacement for the aging go-perl and go-db-perl Perl libraries. It is written using the object oriented Moose libraries. It can be used for performing a number of analyses on GO data, including the remapping of GO annotations to a selected subset of GO terms. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: go-moose (RRID:SCR_005666) Copy   

•   Source: SciCrunch Registry

http://www.gotaxexplorer.de/

GOTaxExplorer presents a new approach to comparative genomics that integrates functional information and families with the taxonomic classification. It integrates UniProt, Gene Ontology, NCBI Taxonomy, Pfam and SMART in one database. GOTaxExplorer provides four different query types: selection of entity sets, comparison of sets of Pfam families, semantic comparison of sets of GO terms, functional comparison of sets of gene products. This permits to select custom sets of GO terms, families or taxonomic groups. For example, it is possible to compare arbitrarily selected organisms or groups of organisms from the taxonomic tree on the basis of the functionality of their genes. Furthermore, it enables to determine the distribution of specific molecular functions or protein families in the taxonomy. The comparison of sets of GO terms allows to assess the semantic similarity of two different GO terms. The functional comparison of gene products makes it possible to identify functionally equivalent and functionally related gene products from two organisms on the basis of GO annotations and a semantic similarity measure for GO. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOTaxExplorer (RRID:SCR_005720) Copy   

•   Source: SciCrunch Registry

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

Onto-Miner (OM) provides a single and convenient interface that allows the user to interrogate our databases regarding annotations of known genes. OM will return all known information about a given list of genes. Advantages of OM include the fact it allows queries with multiple genes and allows for scripting. This is unlike GenBank which uses a single gene navigation process. Scripted search of the Onto-Tools database for gene annotations. User account required. Platform: Online tool

Proper citation: Onto-Miner (RRID:SCR_005722) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Tools/pfa/iprscan/

Software package for functional analysis of sequences by classifying them into families and predicting presence of domains and sites. Scans sequences against InterPro's signatures. Characterizes nucleotide or protein function by matching it with models from several different databases. Used in large scale analysis of whole proteomes, genomes and metagenomes. Available as Web based version and standalone Perl version and SOAP Web Service.

Proper citation: InterProScan (RRID:SCR_005829) Copy   

•   Source: SciCrunch Registry

http://www.patternlabforproteomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. Gene Ontology Explorer (GOEx) combines data from protein fold changes with GO over-representation statistics to help draw conclusions in proteomic experiments. It is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. A recent hack included in GOEx is to load the sparse matrix index file directly into GOEx, instead of going through the report generation using the AC/T-fold methods. This makes it easy for GOEx to analyze any list of proteins as long as the list follows the index file format (described in manuscript) . Please note that if using this alternative strategy, there will be no protein fold information. Platform: Windows compatible

Proper citation: GOEx - Gene Ontology Explorer (RRID:SCR_005779) Copy   

•   Source: SciCrunch Registry

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

In the annotation world, the same piece of information can be stored and viewed differently across different databases. For instance, more than one Affymetrix probe ID can refer to the same GenBank sequence (accession number) and more than one nucleotide sequence from GenBank can be grouped in a single UniGene cluster. The result of Onto-Express depends on whether the input list contains Affymetrix probe IDs, GenBank accession numbers or UniGene cluster IDs. The user has to be aware of relations between the different forms of the data in order to interpret correctly the results. Even if the user is aware of the relationships and knows how to convert them, most existing tools allow conversions of individual genes. Onto-Translate is a tool that allows the user to perform easily such translations. Affymetrix probe IDs, etc., translate GO terms into other identifiers like GenBank accession number, Uniprot IDs. User account required. Platform: Online tool

Proper citation: Onto-Translate (RRID:SCR_005725) Copy   

•   Source: SciCrunch Registry

http://neuro.imm.dtu.dk/software/brede/

A package for neuroinformatics and neuroimaging analysis mostly programmed in Matlab with a few additional programs in Python and Perl. It allows coordinate-based meta-analysis and visualization, neuroimaging analysis of voxel or regional data - not the original data but rather the summary images (e.g., statistical parametric images) and location data in stereotactic space. Among the algorithms implemented are kernel density estimation (for coordinate-based meta-analysis), independent component analysis, non-negative matrix factorization, k-means clustering, singular value decomposition, partial correlation analysis with permutation testing and partial canonical correlation analysis. Visualization of coordinate, surfaces and volumes are possible in 2D and 3D. Generation of HTML for results are possible and algorithms can be accessed from the command line or via a flexible graphical interface. With the Brede Toolbox comes the Brede Database with a small coordinate database from published neuroimaging studies, and ontologies for, e.g., brain function and brain regions.

Proper citation: Brede Toolbox (RRID:SCR_006204) Copy   

•   Source: SciCrunch Registry

http://knime.org/

KNIME (Konstanz Information Miner) is a user-friendly and comprehensive Open-Source data integration, processing, analysis, and exploration platform. KNIME (naim) is a user-friendly graphical workbench for the entire analysis process: data access, data transformation, initial investigation, powerful predictive analytics, visualization and reporting. The open integration platform provides over 1000 modules (nodes), including those of the KNIME community and its extensive partner network. KNIME can be downloaded onto the desktop and used free of charge. KNIME products include additional functionalities such as shared repositories, authentication, remote execution, scheduling, SOA integration and a web user interface as well as world-class support. Robust big data extensions are available for distributed frameworks such as Hadoop. KNIME is used by over 3000 organizations in more than 60 countries. The modular data exploration platform, initially developed at the University of Konstanz, Germany, enables the user to visually create data flows, execute selected analysis steps, and later investigate the results through interactive views on data and models. KNIME is a proven integration platform for tools of numerous vendors due to its open and modular API. The KNIME.com product pipeline includes an Enterprise Server, Cluster Execution, Reporting solutions, and professional KNIME support subscriptions. KNIME.com also offer services such as data analysis, hands-on training and the development of customized components for KNIME.

Proper citation: Knime (RRID:SCR_006164) Copy   

•   Source: SciCrunch Registry

http://cran.r-project.org/src/contrib/Archive/iFad/

An R software package implementing a bayesian sparse factor model for the joint analysis of paired datasets, the gene expression and drug sensitivity profiles, measured across the same panel of samples, e.g. cell lines.

Proper citation: iFad (RRID:SCR_000271) Copy   

•   Source: SciCrunch Registry