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http://cytoscape.org

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

Proper citation: Cytoscape (RRID:SCR_003032) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics.babraham.ac.uk/projects/chipmonk/

Software tool to visualize and analyse ChIP-on-chip array data. Main features: * Import of data from Nimblegen arrays (other formats can be added if people send us examples) * Normalization of data (both per array and per probe) * Various data plotting options to assess data quality and the effectiveness of normalization * Creation of data groups for visualization and analysis * Visualization of data against an annotated genome. * Statistical analysis of data to find probes of interest * Creation of reports containing probes, data and genome annotation Note: This project is no longer being developed, but critical bug fixes will still be provided

Proper citation: ChIPMonk (RRID:SCR_002975) Copy   

•   Source: SciCrunch Registry

https://bioimagesuiteweb.github.io/webapp/index.html

Web applications for analysis of multimodal/multispecies neuroimaging data. Image analysis software package. Has facilities for DTI and fMRI processing. Capabilities for both neuro/cardiac and abdominal image analysis and visualization. Many packages are extensible, and provide functionality for image visualization and registration, surface editing, cardiac 4D multi-slice editing, diffusion tensor image processing, mouse segmentation and registration, and much more. Can be intergrated with other biomedical image processing software, such as FSL, AFNI, and SPM.

Proper citation: BioImage Suite (RRID:SCR_002986) Copy   

•   Source: SciCrunch Registry

http://www.bioperl.org

BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: BioPerl (RRID:SCR_002989) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry

http://iimcb.genesilico.pl/MetaLocGramN/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.A tool for subcellular localization prediction of Gram-negative proteins. You can also use MetaGramLocN via SOAP. SOAP enables you to invoke our method from scripts written in your programming language of choice.

Proper citation: MetaLocGramN (RRID:SCR_003154) Copy   

•   Source: SciCrunch Registry

http://www.plexon.com/products/map-software

A suite of client / server programs that control spike sorting in the Multichannel Acquisition Processor (MAP) Data Acquisition System (MAP System) and provides real-time data visualization and analysis. Plexon's original program supporting multichannel data acquisition is a suite of programs referred to as the Real-Time Acquisition System Programs for Unit Timing in Neuroscience software (RASPUTIN). This combination of software and hardware enables users to view waveforms, acquire action potential waveforms around a voltage-threshold crossing, sort them in real time according to their shape, record continuous analog signals, such as field potentials, eye position, blood pressure, as well as capture external digital-event data, such as individual TTL lines or multi-bit strobed word data. RASPUTIN utilizes a client/server architecture on a Microsoft Windows operating system. The server program runs the MAP box and distributes the data among a set of cooperating client programs. The program can record analog signals and spike and digital-event data in a single data file, and supports 16, 32, 48, 64, 96 and 128 channel configurations. RASPUTIN's operation is based on two primary programs: Sort Client and MAP Server. The Sort Client is the primary control program for the MAP System hardware and may be used to adjust the MAP operating parameters (e.g., amplification, filtering) and to set the specific sorting parameters for each channel. MAP Server is the low-level interface for configuring the MAP, which transfers commands such as gain and filter changes or parameter settings from the various clients to the MAP box. MAP Server also accumulates data coming from the MAP box in a circular buffer memory. The client programs connect to MAP Server to gain access to that data. MAP Server also mediates communication between the clients, keeping them informed of commands sent to the MAP from other clients. RASPUTIN is not sold separately, but rather arrives pre-loaded on the MAP Control Computer with the purchase of any MAP System. As the MAP System has been replaced by the advanced OmniPlex D Neural Data Acquisition System, Plexon is no longer developing the RASPUTIN software program.

Proper citation: MAP Software (RRID:SCR_003170) Copy   

•   Source: SciCrunch Registry

http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/

Software R package for weighted correlation network analysis. WGCNA is also available as point-and-click application. Unfortunately this application is not maintained anymore. It is known to have compatibility problems with R-2.8.x and newer, and the methods it implements are not all state of the art., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Weighted Gene Co-expression Network Analysis (RRID:SCR_003302) Copy   

•   Source: SciCrunch Registry

http://socialbrain.wordpress.com/2009/09/30/neurovia-download-neuro-imaging-tools-software-brain-project-matlab-program-package-for-the-analysis-of-functional-neuroimages/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 24, 2013. These distribution sets contain software modules and/or data sets extracted from the Visualization and Analysis Software Tools (VAST) library developed at the Minneapolis VA Medical Center, the University of Minnesota and/or the International Consortium for Neuroimaging (INC) (partially funded by the Human Brain Project )

Proper citation: Software Distribution Sets (RRID:SCR_003465) Copy   

•   Source: SciCrunch Registry

http://www.scripps.edu/researchservices/dna_array/pages/Data_Analysis_GCOS.htm

Affymetrix has recently released a new software for the acquisition, management, and analysis of gene expression data. The new GeneChip Operating Software (GCOS) platform enables researchers to perform gene expression, SNP mapping and resequencing analysis with integrated data management and scalable client server configurations. * Compatible with additional Affymetrix analysis software such as Data Mining Tool (DMT) and GeneChip DNA Analysis Software (GDAS) * Supports Gene Expression, Resequencing and Genotyping Applications * Baseline Comparison Analysis Input: Affymetrix .DAT file Output: Affymetrix files (.CEL, .CHP, .RPT, .EXP, .TXT) Availability: The Core Facility has a copy of GCOS, as well as an older version of the Affymetrix software, Microarray Suite (MAS), available for use upon request.

Proper citation: GeneChip Operating Software (RRID:SCR_003408) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/cancer/software/genecluster2/gc2.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A software package for analyzing gene expression and other bioarray data, giving users a variety of methods to build and evaluate class predictors, visualize marker lists, cluster data and validate results. GeneCluster 2.0 greatly expands the data analysis capabilities of GeneCluster 1.0 by adding supervised classification, gene selection, class discovery and permutation test methods. It includes algorithms for building and testing supervised models using weighted voting (WV) and k-nearest neighbor (KNN) algorithms, a module for systematically finding and evaluating clustering via self-organizing maps, and modules for marker gene selection and heat map visualization that allow users to view and sort samples and genes by many criteria. It enhances the clustering capabilities of GeneCluster 1.0 by adding a module for batch SOM clustering, and also includes a marker gene finder based on a KNN analysis and a visualization module. GeneCluster 2.0 is a stand-alone Java application and runs on any platform that supports the Java Runtime Environment version 1.3.1 or greater.

Proper citation: GeneCluster 2: An Advanced Toolset for Bioarray Analysis (RRID:SCR_008446) Copy   

•   Source: SciCrunch Registry

http://bdtnp.lbl.gov/Fly-Net/index.jsp?w=home

The goal of this project is to decipher the transcriptional information contained in the extensive cis-acting DNA sequences that direct the patterns of gene expression that underlie animal development. Using the early embryo of the fruitfly Drosophila melanogaster as a model, these researchers are developing experimental and computational methods to systematically characterize and dissect the complex expression patterns and regulatory interactions already present prior to gastrulation. They have identified 37 principal regulatory factors within this network for initial analysis together with their target genes. Sponsors: This project is chiefly funded by a grant from NIGMS and NHGRI, R01 GM070444. Additional funding comes from grants to Michael Eisen, Sue Celniker, and Bernd Hamann.

Proper citation: Berkeley Drosophila Transcription Network Project (RRID:SCR_008640) Copy   

•   Source: SciCrunch Registry

http://www.rad.upenn.edu/sbia/braid/braid_web/index.html

Large-scale archive of normalized digital spatial and functional data with an analytical query mechanism. One of its many applications is the elucidation of brain structure-function relationships. BRAID stores spatially defined data from digital brain images which have been mapped into normalized Cartesian coordinates, allowing image data from large populations of patients to be combined and compared. The database also contains neurological data from each patient and a query mechanism that can perform statistical structure-function correlations. The project is developing database technology for the manipulation and analysis of 3-dimensional brain images derived from MRI, PET, CT, etc. BRAID is based on the PostgreSQL server, an object/relational DBMS, which allows a standard relational DBMS to be augmented with application-specific datatypes and operators. The BRAID project is adding operations and datatypes to support querying, manipulation and analysis of 3D medical images, including: * Image Datatypes: BRAID supports a family of 3D image datatypes, each having an abstract type and an implementation type. Abstract types include boolean (for regions of interest), integer, float, vector (for representing morphological changes), tensor (for representing derivatives and standard deviations of vector images) and color. Implementation types at present include line-segment format and voxel array. * Image Operators: BRAID supports addition of images, multiplication (which is interpreted as intersection for boolean images), coercion of an image''s abstract or implementation type to another value, and determination of volumes of regions of interest. * Statistical Operators: A chi-squared test has been added to SQL as an aggregate operator on pairs of boolean values. * Web Interface: A general-purpose Web gateway allows the results of queries that return computed images to be displayed. You can download the BRAID source code 2.0. This version is developed under postgreSQL 7.3.4., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BRAID (RRID:SCR_008702) Copy   

•   Source: SciCrunch Registry

http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Software:Jackal

Jackal is a collection of programs designed for the modeling and analysis of protein structures. Its core program is a versatile homology modeling package. It contains twelve individual programs, each with their own function.

Proper citation: Jackal (RRID:SCR_008665) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://www.ingenuity.com/products/pathways_analysis.html

A web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.

Proper citation: Ingenuity Pathway Analysis (RRID:SCR_008653) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=nuro

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Portal that provides researchers with easy access to data on rat genes, QTLs, strain models, biological processes and pathways related to neurological diseases. This resource also includes dynamic data analysis tools.

Proper citation: Rat Genome Database: Neurological Disease Portal (RRID:SCR_008685) Copy   

•   Source: SciCrunch Registry

http://www.neurostruct.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. A built-in toolbox for the tracing and analysis of neuroanatomy from nanoscale (high-resolution) imaging. It is a project under ongoing development. The name is originating by merging the words Neuron + reconstruct. The working concept is organized in filters applied successively on the image stack to be processed (pipeline). Currently, the focus of the software is the extraction of detailed neuroanatomical profiles from nanoscale imaging techniques, such as the Serial Block-Face Scanning Electron Microscopy (SBFSEM). The techniques applied, however, may be used to analyze data from various imaging methods and neuronal versatility. The underlying idea of Neurostruct is the use of slim interfaces/filters allowing an efficient use of new libraries and data streaming. The image processing follows in voxel pipelines by using the CUDA programming model and all filters are programmed in a datasize-independent fashion. Thus Neurostruct exploits efficiency and datasize-independence in an optimal way. Neurostruct is based on the following main principles: * Image processing in voxel pipelines using the general purpose graphics processing units (GPGPU) programming model. * Efficient implementation of these interfaces. Programming model and image streaming that guarantees a minimal performance penalty. * Datasize-independent programming model enabling independence from the processed image stack. * Management of the filters and IO data through shell scripts. The executables (filters) are currently managed through shell scripts. The application focuses currently in the tracing of single-biocytin filled cells using SBFSEM imaging. : * Extraction of neuroanatomical profiles: 3D reconstrution and 1D skeletons of the imaged neuronal structure. * Complete tracing: Recognition of the full neuronal structure using envelope techniques, thereby remedying the problem of spines with thin necks of an internal diameter approaching the SBFSEM resolution. * Separation (Coloring) of subcellular structures: Algorithms for the separation of spines from their root dendritic stem. * Evaluation and analysis of the imaged neuroanatomy: Calculation of the dendritic and spine membrane''s surface, spine density and variation, models of dendrites and spines

Proper citation: Neurostruct (RRID:SCR_008861) Copy   

•   Source: SciCrunch Registry

http://spotfire.tibco.com/

The Spotfire Gene Ontology Advantage Application integrates GO annotations with gene expression analysis in Spotfire DecisionSite for Functional Genomics. Researchers can select a subset of genes in DecisionSite visualizations and display their distribution in the Gene Ontology hierarchy. Similarly, selection of any process, function or cellular location in the Gene Ontology hierarchy automatically marks the corresponding genes in DecisionSite visualizations. Platform: Windows compatible

Proper citation: Spotfire (RRID:SCR_008858) Copy   

•   Source: SciCrunch Registry

https://www.brainproducts.com/

Commercial organization for hardware and software for neurophysiological research. Provides EEG and ERP amplifier systems, EEG recording caps, Data recording and analysis software, TMS Stimulator for combined EEG/TMS coregistrations and more.

Proper citation: Brain Products (RRID:SCR_009443) Copy   

•   Source: SciCrunch Registry

http://wbiomed.curtin.edu.au/genepop/

Population genetic data analysis software package. Used to perform exact Hardy Weinberg Equilibrium test. Used for population differentiation and for genotypic disequilibrium among pairs of loci. Computes estimates of F-statistics, null allele frequencies, allele size-based statistics for microsatellites, etc. and performs analyses of isolation by distance from pairwise comparisons of individuals or population samples., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GENEPOP (RRID:SCR_009194) Copy   

•   Source: SciCrunch Registry