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http://biomedical.materialise.com/mimics

Software for medical image processing. Use Mimics for the segmentation of 3D medical images (coming from CT, MRI, microCT, CBCT, Ultrasound, Confocal Microscopy) and the result will be highly accurate 3D models of your patient''s anatomy. You can then use these patient-specific models for a variety of engineering applications directly in Mimics or 3-matic, or export the 3D models and anatomical landmark points to 3rd party software, like statistical, CAD, or FEA packages.

Proper citation: Mimics (RRID:SCR_012153) Copy   

•   Source: SciCrunch Registry

http://sift.bii.a-star.edu.sg/

Data analysis service to predict whether an amino acid substitution affects protein function based on sequence homology and the physical properties of amino acids. SIFT can be applied to naturally occurring nonsynonymous polymorphisms and laboratory-induced missense mutations. (entry from Genetic Analysis Software) Web service is also available.

Proper citation: SIFT (RRID:SCR_012813) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/lumi.html

Software that provides an integrated solution for the Illumina microarray data analysis.

Proper citation: lumi (RRID:SCR_012781) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.12/bioc/html/Ringo.html

Software package that facilitates the primary analysis of ChIP-chip data.

Proper citation: Ringo (RRID:SCR_012973) Copy   

•   Source: SciCrunch Registry

https://github.com/macs3-project/MACS

Software Python package for identifying transcript factor binding sites. Used to evaluate significance of enriched ChIP regions. Improves spatial resolution of binding sites through combining information of both sequencing tag position and orientation. Can be used for ChIP-Seq data alone, or with control sample with increase of specificity.

Proper citation: MACS (RRID:SCR_013291) Copy   

•   Source: SciCrunch Registry

http://www.biomoby.org/

The MOBY-S system defines an ontology-based messaging standard through which a client will be able to automatically discover and interact with task-appropriate biological data and analytical service providers, without requiring manual manipulation of data formats as data flows from one provider to the next. The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. Sponsors: Funding was provided by Genome Prairie and Genome Alberta A Bioinformatics Platform for Genome Canada''; Canadian Institutes for Health Research; The Natural Sciences and Engineering Research Council of Canada; The Heart and Stroke Foundation for BC and Yukon; The EPSRC through the myGrid (GR/R67743/01, EP/C536444/1, EP/D044324/1, GR/T17457/01) e-Science projects; The Spanish National Institute for Bioinformatics (INB) through Fundacin Genoma Espaa; The Generation Challenge Programme (GCP; http://www.generationcp.org) of the Consultative Group for International Agricultural Research. :Keywords: Ontology, Messaging, Standard, Client, Automatically, Discovery, Biological, Data, ANalytical, Service, Model, Organism, Database, Java, Platform, Semantic, Bioinformatics,

Proper citation: BioMoby (RRID:SCR_013386) 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

https://matplotlib.org

Python 2D plotting library which produces publication quality figures in variety of hardcopy formats and interactive environments across platforms. Used in python scripts, web application servers, and six graphical user interface toolkits. Used to generate plots, histograms, power spectra, bar charts, error charts, scatter plots.

Proper citation: Matplotlib (RRID:SCR_008624) Copy   

•   Source: SciCrunch Registry

https://gmod.org/wiki/CMap.1

Web-based tool that allows users to view comparisons of genetic and physical maps. The package also includes tools for curating map data. (entry from Genetic Analysis Software)

Proper citation: CMAP (RRID:SCR_009034) Copy   

•   Source: SciCrunch Registry

http://www.sigmaplot.com/products/sigmaplot/sigmaplot-details.php

Software tool for data graphing and analysis by Systat Software, Inc.

Proper citation: SigmaStat (RRID:SCR_010285) Copy   

•   Source: SciCrunch Registry

http://bioinf.cs.ucl.ac.uk/psipred/

Web tool as secondary structure prediction method, incorporating two feed forward neural networks which perform analysis on output obtained from PSI-BLAST. Web server offering analyses of protein sequences.

Proper citation: PSIPRED (RRID:SCR_010246) Copy   

•   Source: SciCrunch Registry

http://www.qsrinternational.com/nvivo-product

Software suite for qualitative data analysis for text-based data and higher-order forms of data. Various packages are available and are dependent on the system used and the type of data analysis needed.

Proper citation: NVivo (RRID:SCR_014802) Copy   

•   Source: SciCrunch Registry

https://www.mathworks.com/products/simulink/

Block diagram environment that contains a graphical editor, customizable block libraries, and solvers for multidomain simulation and model-based design in MATLAB. It supports simulation, automatic code generation, and continuous test and verification of embedded systems.

Proper citation: Simulink (RRID:SCR_014744) Copy   

•   Source: SciCrunch Registry

http://www.chemcomp.com/MOE-Molecular_Operating_Environment.htm

Drug discovery software package which can be used in structure-based design, fragment-based design, pharmacophore discovery, medicinal chemistry, protein and antibody modelling, and molecular modeling and simulations. Each aspect of the software package has its own unique features: for example, features for structure-based design include active site detection, scaffold replacement, multi fragment search, and solvent analysis.

Proper citation: MOE (RRID:SCR_014882) Copy   

•   Source: SciCrunch Registry

http://bowtie-bio.sourceforge.net/bowtie2/index.shtml

Ultrafast and memory efficient tool for aligning sequencing reads to long reference sequences. Supports gapped, local, and paired end alignment modes. More suited to finding longer, gapped alignments in comparison with original Bowtie method.

Proper citation: Bowtie 2 (RRID:SCR_016368) Copy   

•   Source: SciCrunch Registry

http://spider.science.strath.ac.uk/sipbs/software_ses.htm

Windows software program for recording and analyzing signals from whole cell voltage and current clamp experiments. Its features include automatic waveform measurement, quantal content analysis, command voltage pulse generation, and spontaneous event detection.

Proper citation: WinWCP (RRID:SCR_014713) Copy   

•   Source: SciCrunch Registry

http://paup.sc.fsu.edu

Software which creates phylogenetic trees from molecular, morphological and/or behavioral data through high speed computer analysis.

Proper citation: PAUP (RRID:SCR_014931) Copy   

•   Source: SciCrunch Registry

https://www.vicon.com/products/software/nexus

Data capture software for use with Vicon motion capture system. Its features include MATLAB integration, Python pre-installed, customized workflow, and automated quality assessment.

Proper citation: Nexus (RRID:SCR_015001) Copy   

•   Source: SciCrunch Registry

http://www.statgraphics.com/download-statgraphics-centurion-xvii

Data analysis and visualization software with features that include a R interface, demographic maps, bivariate density estimation, multiple time series visualization, repeated ANOVA measures, and a multivariate visualizers.

Proper citation: Statgraphics Centurion (RRID:SCR_015248) Copy   

•   Source: SciCrunch Registry

https://www.statmodel.com

Statistical modeling program that provides a wide choice of models, estimators, and algorithms in a program that has graphical displays of data and analysis results. Mplus allows the analysis of both cross-sectional and longitudinal data, single-level and multilevel data, data that come from different populations with either observed or unobserved heterogeneity, and data that contain missing values. Analyses can be carried out for observed variables that are continuous, censored, binary, ordered categorical (ordinal), unordered categorical (nominal), counts, or combinations of these variable types. In addition, Mplus has extensive capabilities for Monte Carlo simulation studies, where data can be generated and analyzed according to any of the models included in the program. The Mplus modeling framework draws on the unifying theme of latent variables. The generality of the Mplus modeling framework comes from the unique use of both continuous and categorical latent variables. Continuous latent variables are used to represent factors corresponding to unobserved constructs, random effects corresponding to individual differences in development, random effects corresponding to variation in coefficients across groups in hierarchical data, frailties corresponding to unobserved heterogeneity in survival time, liabilities corresponding to genetic susceptibility to disease, and latent response variable values corresponding to missing data. Categorical latent variables are used to represent latent classes corresponding to homogeneous groups of individuals, latent trajectory classes corresponding to types of development in unobserved populations, mixture components corresponding to finite mixtures of unobserved populations, and latent response variable categories corresponding to missing data.

Proper citation: MPlus (RRID:SCR_015578) Copy   

•   Source: SciCrunch Registry