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https://github.com/yousra291987/ChiCMaxima

Pipeline for analyzing and identificantion of chromatin loops in CHi-C promoters data. Used to capture Hi-C visualization and interaction calling.

Proper citation: ChiCMaxima (RRID:SCR_018178) Copy   

•   Source: SciCrunch Registry

https://github.com/santeripuranen/SpydrPick

Software command line tool for performing direct coupling analysis of aligned categorical datasets. Used for analysis at scale of pan genomes of many bacteria. Incorporates correction for population structure, which adjusts for phylogenetic signal in data without requiring explicit phylogenetic tree.

Proper citation: SpydrPick (RRID:SCR_018176) Copy   

•   Source: SciCrunch Registry

https://github.com/santeripuranen/SuperDCA

Software tool for global direct coupling analysis of input genome alignments. Implements variant of pseudolikelihood maximization direct coupling analysis, with emphasis on optimizations that enable its use on genome scale. May be used to discover co evolving pairs of loci.Used for genome wide epistasis analysis.

Proper citation: SuperDCA (RRID:SCR_018175) Copy   

•   Source: SciCrunch Registry

http://www.innovision-systems.com/Products/MaxTraq.html

Software package for motion capture analysis by Innovision Systems Inc.

Proper citation: MaxTRAQ (RRID:SCR_018188) Copy   

•   Source: SciCrunch Registry

https://nemoanalytics.org/

Portal enabling web based visualization and analysis of multi omic data describing cell types in developing and adult brain, powered by gEAR and EpiViz. Release 1 on April 2019 includes single cell and bulk tissue RNAseq, ATACseq, and ChIPseq from fetal human prefrontal cortex, as well as from stem cell models of neural induction. Portal will expand to include multiple regions of developing and adult brain and additional analytical tools.

Proper citation: NeMO Analytics (RRID:SCR_018164) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/TCGAbiolinks/

Software R Bioconductor package for integrative analysis with TCGA data.TCGAbiolinks is able to access National Cancer Institute Genomic Data Commons thorough its GDC Application Programming Interface to search, download and prepare relevant data for analysis in R.

Proper citation: TCGAbiolinks (RRID:SCR_017683) Copy   

•   Source: SciCrunch Registry

http://compbio.mit.edu/ChromHMM/

Software tool for chromatin state discovery and characterization. Used for chromatin state discovery and genome annotation of non coding genome using epigenomic information across one or multiple cell types. Combines multiple genome wide epigenomic maps, and uses combinatorial and spatial mark patterns to infer complete annotation for each cell type. Provides automated enrichment analysis of resulting annotations.

Proper citation: ChromHMM (RRID:SCR_018141) Copy   

•   Source: SciCrunch Registry

https://biit.cs.ut.ee/gprofiler/page/r

Software R interface to g:Profiler. Uses publicly available APIs of g:Profiler web tool which ensures that results from all of interfaces are consistent. Used for gene list functional enrichment analysis and namespace conversion. gprofiler2 package supports all the same organisms, namespaces and data sources as the web tool.

Proper citation: gProfiler2 (RRID:SCR_018190) Copy   

•   Source: SciCrunch Registry

https://www.mbfbioscience.com/wormlab

Software tool for imaging, tracking, and analyzing C. elegans and other nematodes. It has user friendly software interface with patented model specific tracking algorithm that collects data about single worm or multiple worms, even through omega bends, coiling, reversals, and entanglements. Provides quantitative analysis of locomotory behavior with user configurable metrics for crawling and swimming assays.

Proper citation: Worm Lab (RRID:SCR_017669) Copy   

•   Source: SciCrunch Registry

http://www.milesculabs.org/QuB.html

Integrated software platform for ion channel biophysics and neurophysiology.Used to explore dynamics of hidden states in memoryless system. Open source software suite for solving kinetic models, for report generation with publishable graphics, function fitting and scripting for new and repeated processing and AD/DA I/O. Can be applied to any data modeled with Markov kinetics., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: QuB (RRID:SCR_018076) Copy   

•   Source: SciCrunch Registry

http://www.diploid.com/moon

Software package that autonomously diagnoses rare diseases from next generation sequencing NGS data using artificial intelligence by Diploid.

Proper citation: MOON (RRID:SCR_018005) Copy   

•   Source: SciCrunch Registry

http://ultrascan.aucsolutions.com/

Software package for hydrodynamic data from analytical ultracentrifugation experiments. Features integrated data editing and analysis environment with portable graphical user interface. Provides resolution for sedimentation velocity experiments using high-performance computing modules for 2-dimensional spectrum analysis, genetic algorithm, and for Monte Carlo analysis.

Proper citation: UltraScan (RRID:SCR_018126) Copy   

•   Source: SciCrunch Registry

https://www.mbfbioscience.com/help/vesselucida-explorer/Content/VesselucidaExplorer.html

Vesselucida Explorer is Vesselucida 360 companion analysis software, to perform analyses. Provides vasculature specific metrics such as segments and nodes counts, frequency of anastomoses, vessel surface and volume, and more.

Proper citation: Vesselucida Explorer (RRID:SCR_017674) 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   

•   Source: SciCrunch Registry

http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Main_Page

Laboratory portal, including software, web-based tools, databases and data sets, related to their research that focuses on the development and application of biophysical and bioinformatics methods aimed at understanding the structural and energetic origins of protein-protein, protein-nucleic acid, and protein-membrane interactions. Their work includes fundamental theoretical research, the development of software tools, and applications to problems of biological importance. In this regard they maintain an active collaborative computational and experimental research program on the molecular basis of cell-cell adhesion. Other problems of current interest include protein structure prediction, the organization of protein sequence/structure space, the prediction of protein function based on protein structure, the structural origins of specificity in protein-DNA interactions, RNA function and, more generally, the electrostatic properties of biological macromolecules.

Proper citation: Honig Lab (RRID:SCR_003410) Copy   

•   Source: SciCrunch Registry

http://cng.gmu.edu:8080/Lm

A freely available software tool available for the Windows and Linux platform, as well as the Online version Applet, for the analysis, comparison and search of digital reconstructions of neuronal morphologies. For the quantitative characterization of neuronal morphology, LM computes a large number of neuroanatomical parameters from 3D digital reconstruction files starting from and combining a set of core metrics. After more than six years of development and use in the neuroscience community, LM enables the execution of commonly adopted analyses as well as of more advanced functions, including: (i) extraction of basic morphological parameters, (ii) computation of frequency distributions, (iii) measurements from user-specified subregions of the neuronal arbors, (iv) statistical comparison between two groups of cells and (v) filtered selections and searches from collections of neurons based on any Boolean combination of the available morphometric measures. These functionalities are easily accessed and deployed through a user-friendly graphical interface and typically execute within few minutes on a set of 20 neurons. The tool is available for either online use on any Java-enabled browser and platform or may be downloaded for local execution under Windows and Linux.

Proper citation: L-Measure (RRID:SCR_003487) Copy   

•   Source: SciCrunch Registry

http://www.idoimaging.com/program/280

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023.Comprised of a large array of sophisticated programs, this comprehensive software package with tools based around the MINC file format. Utilities are provided for conversion, viewing, editing, registering, segmentation, and a wide array of analysis. Many programs are in Perl. MINC software tools for neurological imaging are free. Input format: Analyze, DICOM, Minc

Proper citation: MINC Brain Imaging Toolbox (RRID:SCR_003519) Copy   

•   Source: SciCrunch Registry

http://www.nanostring.com/products/nSolver

Data analysis software program that offers nCounter users the ability to QC, normalize, and analyze data without having to purchase additional software packages.

Proper citation: nSolver Analysis Software (RRID:SCR_003420) Copy   

•   Source: SciCrunch Registry

http://www.minituba.org

miniTUBA is a web-based modeling system that allows clinical and biomedical researchers to perform complex medical/clinical inference and prediction using dynamic Bayesian network analysis with temporal datasets. The software allows users to choose different analysis parameters (e.g. Markov lags and prior topology), and continuously update their data and refine their results. miniTUBA can make temporal predictions to suggest interventions based on an automated learning process pipeline using all data provided. Preliminary tests using synthetic data and laboratory research data indicate that miniTUBA accurately identifies regulatory network structures from temporal data. miniTUBA represents in a network view possible influences that occur between time varying variables in your dataset. For these networks of influence, miniTUBA predicts time courses of disease progression or response to therapies. minTUBA offers a probabilistic framework that is suitable for medical inference in datasets that are noisy. It conducts simulations and learning processes for predictive outcomes. The DBN analysis conducted by miniTUBA describes from variables that you specify how multiple measures at different time points in various variables influence each other. The DBN analysis then finds the probability of the model that best fits the data. A DBN analysis runs every combination of all the data; it examines a large space of possible relationships between variables, including linear, non-linear, and multi-state relationships; and it creates chains of causation, suggesting a sequence of events required to produce a particular outcome. Such chains of causation networks - are difficult to extract using other machine learning techniques. DBN then scores the resulting networks and ranks them in terms of how much structured information they contain compared to all possible models of the data. Models that fit well have higher scores. Output of a miniTUBA analysis provides the ten top-scoring networks of interacting influences that may be predictive of both disease progression and the impact of clinical interventions and probability tables for interpreting results. The DBN analysis that miniTUBA provides is especially good for biomedical experiments or clinical studies in which you collect data different time intervals. Applications of miniTUBA to biomedical problems include analyses of biomarkers and clinical datasets and other cases described on the miniTUBA website. To run a DBN with miniTUBA, you can set a number of parameters and constrain results by modifying structural priors (i.e. forcing or forbidding certain connections so that direction of influence reflects actual biological relationships). You can specify how to group variables into bins for analysis (called discretizing) and set the DBN execution time. You can also set and re-set the time lag to use in the analysis between the start of an event and the observation of its effect, and you can select to analyze only particular subsets of variables.

Proper citation: miniTUBA (RRID:SCR_003447) Copy   

•   Source: SciCrunch Registry