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http://cran.r-project.org/web/packages/VennDiagram/

Software providing a set of functions to generate high-resolution Venn and Euler plots. Includes handling for several special cases, including two-case scaling, and extensive customization of plot shape and structure.

Proper citation: VennDiagram (RRID:SCR_002414) Copy   

•   Source: SciCrunch Registry

https://neuro-jena.github.io/software.html#tom

Software toolbox for creating customized pediatric templates. It provides reference data based on imaging data from the NIH study of normal brain development. Using the general linear model, they statistically isolate the influence of external variables of interest on brain structure, allowing us to generate high-quality matched templates for any given group of subjects. The toolbox offers two options: # to create pediatric templates (T1) and tissue maps (GM, WM, and CSF) based on the objective 1 NIH data (n = 404), in the age range of 5-18 years, or # to assess a new reference population with regard to your variables of interest. Of note, this approach is generally applicable and in no way restricted to analyzing pediatric imaging data: for example, if you aim at investigating the effects of aging in elderly subjects, the toolbox will also allow you to create more appropriate reference (if your group is large enough to isolate such effects).

Proper citation: Template-O-Matic Toolbox (RRID:SCR_003220) 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

https://omictools.com/prolinks-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 7, 2017. Collection of inference methods used to predict functional linkages between proteins. These methods include the Phylogenetic Profile method which uses the presence and absence of proteins across multiple genomes to detect functional linkages; the Gene Cluster method which uses genome proximity to predict functional linkage; Rosetta Stone which uses a gene fusion event in a second organism to infer functional relatedness; and the Gene Neighbor method which uses both gene proximity and phylogenetic distribution to infer linkage.

Proper citation: ProLinks Database of Functional Linkages (RRID:SCR_003185) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/tools/cobalt/cobalt.cgi?link_loc=BlastHomeAd

COBALT is a multiple sequence alignment tool that finds a collection of pairwise constraints derived from conserved domain database, protein motif database, and sequence similarity, using RPS-BLAST, BLASTP, and PHI-BLAST. Pairwise constraints are then incorporated into a progressive multiple alignment. A Linux executable for COBALT, and CDD and PROSITE data used is available at ftp://ftp.ncbi.nlm.nih.gov/pub/agarwala/cobalt/ COBALT has reasonable runtime performance and alignment accuracy comparable to or exceeding that of other tools for a broad range of problems.

Proper citation: COBALT: Constraint-based Multiple Alignment Tool (RRID:SCR_004152) Copy   

•   Source: SciCrunch Registry

http://www.fmri.wfubmc.edu/cms/software

Research group based in the Department of Radiology of Wake Forest University School of Medicine devoted to the application of novel image analysis methods to research studies. The ANSIR lab also maintains a fully-automated functional and structural image processing pipeline supporting the image storage and analysis needs of a variety of scientists and imaging studies at Wake Forest. Software packages and toolkits are currently available for download from the ANSIR Laboratory, including: WFU Biological Parametric Mapping Toolbox, WFU_PickAtlas, and Adaptive Staircase Procedure for E-Prime.

Proper citation: Advanced Neuroscience Imaging Research Laboratory Software Packages (RRID:SCR_002926) Copy   

•   Source: SciCrunch Registry

http://sig.biostr.washington.edu/projects/wirm/

WIRM is an innovative software toolkit that allows the creation of web applications that facilitate the acquisition, integration, and dissemination of multimedia biomedical data over the web, thereby reducing the cost of knowledge sharing. WIRM reduces the complexity of building custom biomedical web applications and it's visual modeling tools enable domain experts to describe the structure of their knowledge, from which WIRM automatically generates full-featured, customizable content management systems. WIRM is a Perl-based application server that provides a high-level programming environment for developing web information systems. WIRM consists of an object-relational database and a suite of Perl interfaces for visualizing, integrating and analyzing heterogeneous multimedia data. WIRM provides facilities for creating context-sensitive views over a multimedia database, allowing developers to rapidly build dynamic web sites that adapt their content and presentation to multiple classes of end-users. WIRM was developed by Rex Jakobovits as part of his PhD dissertation at the University of Washington Computer Science department, under the guidance of Dr. James F. Brinkley of the Department of Biological Structure. The system was generalized from work funded by NIH SBIR grant R43-MH61277-01 and Human Brain Project grant DC/LM02310.

Proper citation: WIRM - Web Interfacing Repository Manager (RRID:SCR_002039) Copy   

•   Source: SciCrunch Registry

http://www.yandell-lab.org/software/maker.html

Software genome annotation pipeline. Portable and easily configurable genome annotation pipeline. Used to allow smaller eukaryotic and prokaryotic genomeprojects to independently annotate their genomes and to create genome databases. MAKER identifies repeats, aligns ESTs and proteins to genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence based quality values.

Proper citation: MAKER (RRID:SCR_005309) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/multimpute/

A software toolkit that performs multiple imputation for group level, single sample t-tests. Whole brain group level statistic maps from fMRI rarely cover the entire brain as a result of missing data. Missingness between subjects in fMRI datasets can result from susceptibility artifacts, bounding box (acquisition parameters), and small differences in post-normalized morphology. The toolkit consists of several interactive command line scripts that guide the user to map the spatial distribution of missing data across contrast images, calculate spatial neighborhood averages that help impute values, perform conventional and multiple imputed t-statistics, save the results to brain maps, and create result tables. The toolkit contains an instruction manual (pdf), two Matlab scripts and one R-Statistics script, which depend on functions defined in the popular SPM toolbox and functions defined in the MICE package for (R).

Proper citation: Group Level Imputation of Statistic Maps (RRID:SCR_002397) Copy   

•   Source: SciCrunch Registry

http://cran.r-project.org/web/packages/metaMA/

Software R package for meta-analysis for microarrays. It combines either p-values or modified effect sizes from different studies to find differentially expressed genes.

Proper citation: metaMA (RRID:SCR_000408) Copy   

•   Source: SciCrunch Registry

Issue

https://reich.hms.harvard.edu/software

EIGENSOFT package combines functionality from our population genetics methods (Patterson et al. 2006) and our EIGENSTRAT stratification method (Price et al. 2006). The EIGENSTRAT method uses principal components analysis to explicitly model ancestry differences between cases and controls along continuous axes of variation; the resulting correction is specific to a candidate marker''s variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. The EIGENSOFT package has a built-in plotting script and supports multiple file formats and quantitative phenotypes. Source code, documentation and executables for using EIGENSOFT 3.0 on a Linux platform can be downloaded. New features of EIGENSOFT 3.0 include supporting either 32-bit or 64-bit Linux machines, a utility to merge different data sets, a utility to identify related samples (accounting for population structure), and supporting multiple file formats for EIGENSTRAT stratification correction.

Proper citation: Eigensoft (RRID:SCR_004965) Copy   

•   Source: SciCrunch Registry

http://sccn.ucsd.edu/wiki/MPT

This toolbox is an EEGLAB plugin for performing Measure Projection Analysis. Measure Projection Analysis (MPA) is a novel probabilistic multi-subject inference method that overcomes EEG Independent Component (IC) clustering issues by abandoning the notion of distinct IC clusters. Instead, it searches voxel by voxel for brain regions having event-related IC process dynamics that exhibit statistically significant consistency across subjects and/or sessions as quantified by the values of various EEG measures. Local-mean EEG measure values are then assigned to all such locations based on a probabilistic model of IC localization error and inter-subject anatomical and functional differences.

Proper citation: Measure Projection Toolbox (RRID:SCR_002429) Copy   

•   Source: SciCrunch Registry

http://ugene.unipro.ru/

A multiplatform open-source software to assist molecular biologists without much expertise in bioinformatics to manage, analyze and visualize their data. UGENE integrates widely used bioinformatics tools within a common user interface. The toolkit supports multiple biological data formats and allows the retrieval of data from remote data sources. It provides visualization modules for biological objects such as annotated genome sequences, Next Generation Sequencing (NGS) assembly data, multiple sequence alignments, phylogenetic trees and 3D structures. Most of the integrated algorithms are tuned for maximum performance by the usage of multithreading and special processor instructions. UGENE includes a visual environment for creating reusable workflows that can be launched on local resources or in a High Performance Computing (HPC) environment. UGENE is written in C++ using the Qt framework. The built-in plugin system and structured UGENE API make it possible to extend the toolkit with new functionality.

Proper citation: Unipro UGENE (RRID:SCR_005579) Copy   

•   Source: SciCrunch Registry

http://integrativemodeling.org/

An open source C++ and Python toolbox for solving complex modeling problems, and a number of applications for tackling some common problems in a user-friendly way. Its broad goal is to contribute to a comprehensive structural characterization of biomolecules ranging in size and complexity from small peptides to large macromolecular assemblies, by integrating data from diverse biochemical and biophysical experiments. It can also be used from the Chimera molecular modeling system, or via one of several web applications.

Proper citation: Integrative Modeling Platform (RRID:SCR_002982) Copy   

•   Source: SciCrunch Registry

http://jena.sourceforge.net/

Java framework for building Semantic Web applications, it provides a collection of tools and Java libraries to help you to develop semantic web and linked-data apps, tools and servers. It provides extensive Java libraries for helping developers develop code that handles RDF, RDFS, RDFa, OWL and SPARQL in line with published W3C recommendations. Jena includes a rule-based inference engine to perform reasoning based on OWL and RDFS ontologies, and a variety of storage strategies to store RDF triples in memory or on disk. The Jena Framework includes: * an API for reading, processing and writing RDF data in XML, N-triples and Turtle formats; * an ontology API for handling OWL and RDFS ontologies; * a rule-based inference engine for reasoning with RDF and OWL data sources; * stores to allow large numbers of RDF triples to be efficiently stored on disk; * a query engine compliant with the latest SPARQL specification * servers to allow RDF data to be published to other applications using a variety of protocols, including SPARQL In April 2012, Jena graduated from the Apache incubator process and was approved as a top-level Apache project.

Proper citation: JENA: A Semantic Web Framework for Java (RRID:SCR_001766) Copy   

•   Source: SciCrunch Registry

https://pydicom.github.io/

Software Python package for working with DICOM files, made for inspecting and modifying DICOM data in an easy pythonic way. The modifications can be written again to a new file. As a pure python package, it should run anywhere python runs without any other requirements.

Proper citation: pydicom (RRID:SCR_002573) Copy   

•   Source: SciCrunch Registry

http://ngsutils.org/

A suite of software tools for analyzing and manipulating next-generation sequencing datasets, such as FASTQ, BED and BAM format files. These tools provide a stable and modular platform for data management and analysis.

Proper citation: NGSUtils (RRID:SCR_001236) Copy   

•   Source: SciCrunch Registry

http://www.cs.cmu.edu/~schneide/tut5/node42.html

A model evaluation method for training someone to read data. There are three methods: the holdout method, K-fold cross validation, and leave-one-out cross validation.

Proper citation: Cross Validation (RRID:SCR_000702) Copy   

•   Source: SciCrunch Registry

http://cran.r-project.org/web/packages/enviPick/

Software for sequential partitioning, clustering and peak detection of centroided LC-MS mass spectrometry data (.mzXML). Interactive result and raw data plot.

Proper citation: enviPick (RRID:SCR_003059) Copy   

•   Source: SciCrunch Registry