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http://nipy.org/nitime/

Software library for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code.

Proper citation: Nitime (RRID:SCR_002504) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/geo/

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

Proper citation: Gene Expression Omnibus (GEO) (RRID:SCR_005012) Copy   

•   Source: SciCrunch Registry

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

Microarrays are at the center of a revolution in biotechnology, allowing researchers to screen tens of thousands of genes simultaneously. Typically, they have been used in exploratory research to help formulate hypotheses. In most cases, this phase is followed by a more focused, hypothesis driven stage in which certain specific biological processes and pathways are thought to be involved. Since a single biological process can still involve hundreds of genes, microarrays are still the preferred approach as proven by the availability of focused arrays from several manufacturers. Since focused arrays from different manufacturers use different sets of genes, each array will represent any given regulatory pathway to a different extent. We argue that a functional analysis of the arrays available should be the most important criterion used in the array selection. We developed Onto-Compare as a database that can provide this functionality, based on the GO nomenclature. Compare commercially available microarrays based on GO. User account required. Platform: Online tool

Proper citation: Onto-Compare (RRID:SCR_005669) Copy   

•   Source: SciCrunch Registry

http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

•   Source: SciCrunch Registry

https://atlas.kpmp.org/

Atlas is set of interactive tools built to promote retrieval, exploration, discovery, and analysis of Kidney Precision Medicine Project data by greater research community. Datasets available in repository are combination of raw and processed data from KPMP participant biopsies and reference tissue samples.

Proper citation: Kidney Tissue Atlas (RRID:SCR_021626) Copy   

•   Source: SciCrunch Registry

https://ualr.edu/bioinformatics/midsouth-bioinformatics-center/

Core provides bioinformatics consulting, training, technical assistance, and access to computational infrastructure for faculty, students, and researchers in region with their bioscience computational needs. Offers private sessions, workshops and training on specialty topics. Computing resources including software, computing cluster, technical advice.

Proper citation: University of Arkansas at Little Rock MidSouth Bioinformatics Center Core Facility (RRID:SCR_017168) Copy   

•   Source: SciCrunch Registry

http://structuralbiology.cau.edu.cn/PlantGSEA/

Websever for gene set enrichment analysis of plants. Used for interpreting biological meaning of a list of genes by computing the overlaps with various previously defined gene sets.

Proper citation: PlantGSEA (RRID:SCR_016866) Copy   

•   Source: SciCrunch Registry

http://www.clcbio.com/products/clc-main-workbench/

A suite of software for DNA, RNA and protein sequence data analysis. The software allows for the analysis and visualization of Sanger sequencing data as well as gene expression analysis, molecular cloning, primer design, phylogenetic analyses, and sequence data management.

Proper citation: CLC Main Workbench (RRID:SCR_000354) Copy   

•   Source: SciCrunch Registry

http://www.biochem.mpg.de/en/rd/baumeister/research/ContentCEM/Software_development

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A software platform for low dose electron tomography (ET) for all processing steps: acquisition, alignment, reconstruction, and analysis. Requires: Matlab R2008a and Image Processing Toolbox (V6.1)

Proper citation: Acquisition and Analysis for Electron Tomography (RRID:SCR_000192) Copy   

•   Source: SciCrunch Registry

http://imaging.indyrad.iupui.edu/projects/SPHARM/

A matlab-based 3D shape modeling and analysis toolkit, and is designed to aid statistical shape analysis for identifying morphometric changes in 3D structures of interest related to different conditions. SPHARM-MAT is implemented based on a powerful 3D Fourier surface representation method called SPHARM, which creates parametric surface models using spherical harmonics.

Proper citation: SPHARM-MAT (RRID:SCR_002545) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/targetgene/

MATLAB tool to effectively identify potential therapeutic targets and drugs in cancer using genetic network-based approaches. It can rapidly extract genetic interactions from a precompiled database stored as a MATLAB MAT-file without the need to interrogate remote SQL databases. Millions of interactions involving thousands of candidate genes can be mapped to the genetic network within minutes. While TARGETgene is currently based on the gene network reported in (Wu et al.,Bioinformatics 26:807-813, 2010), it can be easily extended to allow the optional use of other developed gene networks. The simple graphical user interface also enables rapid, intuitive mapping and analysis of therapeutic targets at the systems level. By mapping predictions to drug-target information, TARGETgene may be used as an initial drug screening tool that identifies compounds for further evaluation. In addition, TARGETgene is expected to be applicable to identify potential therapeutic targets for any type or subtype of cancers, even those rare cancers that are not genetically recognized. Identification of Potential Therapeutic Targets * Prioritize potential therapeutic targets from thousands of candidate genes generated from high-throughput experiments using network-based metrics * Validate predictions (prioritization) using user-defined benchmark genes and curated cancer genes * Explore biologic information of selected targets through external databases (e.g., NCBI Entrez Gene) and gene function enrichment analysis Initial Drug Screening * Identify for further evaluation existing drugs and compounds that may act on the potential therapeutic targets identified by TARGETgene * Explore general information on identified drugs of interest through several external links Operating System: Windows XP / Vista / 7

Proper citation: TARGETgene (RRID:SCR_001392) Copy   

•   Source: SciCrunch Registry

http://nipy.org/nipype/

A package for writing fMRI analysis pipelines and interfacing with external analysis packages (SPM, FSL, AFNI). Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface. Nipype, an open-source, community-developed initiative under the umbrella of Nipy, is a Python project that solves these issues by providing a uniform interface to existing neuroimaging software and by facilitating interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., SPM, FSL), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.

Proper citation: Nipype (RRID:SCR_002502) Copy   

•   Source: SciCrunch Registry

https://www.med.upenn.edu/cbica/captk/

Software platform for analysis of radiographic cancer images. Used as quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

Proper citation: Cancer Imaging Phenomics Toolkit (RRID:SCR_017323) Copy   

•   Source: SciCrunch Registry

http://hmri.info

Software toolbox for quantitative MRI in neuroscience and clinical research. Open source and flexible tool for qMRI data handling and processing. Allows estimation of high quality multi parameter qMRI maps followed by spatial registration in common space for statistical analysis.

Proper citation: hMRI-toolbox (RRID:SCR_017682) Copy   

•   Source: SciCrunch Registry

https://www.mbfbioscience.com/stereo-investigator-cleared-tissue-edition

Software tool for unbiased stereology to be used on cleared tissue. Used to analyze intact, cleared tissue specimens imaged with light sheet or confocal microscopes. Includes number, length, area and volume analyses.

Proper citation: Stereo Investigator - Cleared Tissue Edition (RRID:SCR_017668) Copy   

•   Source: SciCrunch Registry

https://edspace.american.edu/openbehavior/project/argus/

Portal provides software tool for analysis and quantification of both single and socially interacting zebrafish. Software data extraction and analysis tool built in open source R language for tracking zebrafish behavior.

Proper citation: Argus (RRID:SCR_021585) Copy   

•   Source: SciCrunch Registry

https://gitlab.com/PlantGenomicsLab/gFACs

Software package provides comprehensive framework for evaluating, filtering, and analyzing gene models from range of input applications and preparing these annotations for formal publication or downstream analysis.

Proper citation: gFACs (RRID:SCR_022017) Copy   

•   Source: SciCrunch Registry

http://neuralensemble.org/sumatra/

A software tool for managing and tracking projects based on numerical simulation or analysis to support reproducible research. It can be thought of as an automated electronic lab notebook for simulation/analysis projects. Sumatra consists of: a command-line interface, smt, for launching simulations/analyses with automatic recording of information about the context, annotating these records, linking to data files, etc.; a web interface with a built-in web-server, smtweb, for browsing and annotating simulation/analysis results; a LaTeX package and Sphinx extension for including Sumatra-tracked figures and links to provenance information in papers and other documents; and a Python API, on which smt and smtweb are based, that can be used in personalized scripts in place of using smt.

Proper citation: Sumatra (RRID:SCR_001381) Copy   

•   Source: SciCrunch Registry

http://animaltracker.elte.hu/

A universal tracking application specifically designed to support animal behavioral analysis. AnimalTracker consists of three main modules which can be used independently: Tracker is responsible for image processing and providing the coordinates of the identified object; Zone Designer provides tools to create custom-made investigation areas in order to design a maze-setup; and Tracking Analyzer module serves to define and obtain the parameters needed for the evaluation.

Proper citation: AnimalTracker (RRID:SCR_014397) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://www.olympus-lifescience.com/en/software/cellsens/

Software suite for image acquisition and analysis. The software can be paired with high-quality cameras to maximize output quality and export it for sharing and research applications.

Proper citation: Olympus cellSens Software (RRID:SCR_014551) Copy   

•   Source: SciCrunch Registry