Tools   Select Another Resource Report Type

https://www.nitrc.org/search/?type_of_search=group&q=wisconsin&sa.x=0&sa.y=0&sa=Search

Atlases enable alignment of individual scans to improve localization and statistical power of results, and allow comparison of results between studies and institutions. Set of multi subject atlas templates is constructed specifically for functional and structural imaging studies of rhesus macaque.

Proper citation: Rhesus Macaque Brain Atlases (RRID:SCR_017533) Copy   

•   Source: SciCrunch Registry

https://github.com/kstreet13/slingshot

Software R package for identifying and characterizing continuous developmental trajectories in single cell data. Cell lineage and pseudotime inference for single-cell transcriptomics.

Proper citation: Slingshot (RRID:SCR_017012) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

https://github.com/BodenmillerGroup/imctools

Software Python package that implements preprocessing pipeline for imaging mass cytometry data. Can convert IMC raw files to tiff files that are used as inputs into CellProfiller, Ilastik, Fiji etc.

Proper citation: imctools (RRID:SCR_017132) Copy   

•   Source: SciCrunch Registry

https://github.com/colinvaz/nmf-toolbox

Software toolbox for performing Non-negative Matrix Factorization (NMF) and several variants. Used to factorize one non negative matrix into two non negative factors, that is basis matrix and coefficient matrix. Applied in bioinformatics as data mining approach.

Proper citation: NMF Toolbox (RRID:SCR_017069) Copy   

•   Source: SciCrunch Registry

https://github.com/AlexsLemonade/refinebio

Software tool to uniformly process and normalize large amounts of data. Harmonizes petabytes of publicly available biological data into ready-to-use datasets for cancer researchers and AI/ML scientists.

Proper citation: refine.bio (RRID:SCR_017471) Copy   

•   Source: SciCrunch Registry

http://www.biosoft.com/w/assayzap.htm

Software tool as universal assay calculator for RIA, ELISA, IRMA, colorimetric or any other type of assay by Biosoft. Maintains record for each assay, and enables standard curve and QCs to be compared and adjusted. Can process data from 96 and 384-well plate readers in any order.

Proper citation: AssayZap (RRID:SCR_016991) 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://github.com/hemberg-lab/scmap

Software tool for unsupervised projection of single cell RNA-seq data. Used for projecting cells from scRNA-seq data set onto cell types or individual cells from other experiments.

Proper citation: Scmap (RRID:SCR_017338) Copy   

•   Source: SciCrunch Registry

https://github.com/taborlab/FlowCal

Open source software tool for automatically converting flow cytometry data from arbitrary to calibrated units. Can be run using intuitive Microsoft Excel interface, or customizable Python scripts. Software accepts Flow Cytometry Standard (FCS) files as inputs and is compatible with different calibration particles, fluorescent probes, and cell types. Automatically gates data, calculates common statistics, and produces plots.

Proper citation: FlowCal (RRID:SCR_018140) Copy   

•   Source: SciCrunch Registry

https://github.com/Nevermore520/NeuronTools

Software tools for converting data files into persistence diagrams and distance matrices.

Proper citation: Neuron Tools (RRID:SCR_017450) Copy   

•   Source: SciCrunch Registry

https://github.com/wdecoster/nanofilt

Software tool written in Python to perform its filtering based on mean read quality and GC content and read length. Used for filtering and trimming of long read sequencing data.

Proper citation: NanoFilt (RRID:SCR_016966) Copy   

•   Source: SciCrunch Registry

https://github.com/mandricigor/ScaffMatch

Software tool as scaffolding algorithm based on maximum weight matching able to produce high quality scaffolds from next generation sequencing data (reads and contigs). Able to handle reads with both short and long insert sizes.

Proper citation: ScaffMatch (RRID:SCR_017025) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/nicofmay/basta-bayesian-structured-coalescent-approximation/src/master/

Software package as Bayesian method to infer migration from genetic data. Implemented in BEAST2 that combines accuracy of methods based on structured coalescent with computational efficiency required to handle more than few populations.

Proper citation: BASTA (RRID:SCR_017303) Copy   

•   Source: SciCrunch Registry

https://scienceofbehaviorchange.org/about/

Repository for behavioral science measures that have been validated or are in process of being validated in accordance with SOBC Experimental Medicine Approach.

Proper citation: Science of Behavior Change Research Network (RRID:SCR_017385) Copy   

•   Source: SciCrunch Registry

https://geomagic-studio.software.informer.com/12.0/

Software tool to convert 3D scans into parametric models. Transforms 3D scan data into highly accurate surface, polygon and native CAD models. Used for reverse engineering, product design, rapid prototyping and analysis.

Proper citation: GEOMAGIC Studio (RRID:SCR_016978) Copy   

•   Source: SciCrunch Registry

http://montana.eagle-i.net/i/0000012b-00be-4e65-df3b-3fdc80000000

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 27, 2023. Core for Microarray analysis, Database development, Systems biology analysis, Genome assembly, Pathway data analysis, Expression data analysis, Metagenomics analysis. To maintain equipment and software for bioinformatic research, promote bioinformatics education on the MSU campus, and provide training and support to biologists implementing bioinformatics tools in their research.

Proper citation: Montana State University Bioinformatics Core Facility (RRID:SCR_009937) Copy   

•   Source: SciCrunch Registry

https://wistar.org/research-discoveries/shared-resources/bioinformatics-facility

Core provides High Throughput Data Analysis, Customized Bioinformatics Services, Custom Programming, High Performance Computing, Data management. Located in the Center for Systems and Computational Biology. Provides Cancer Center investigators with database management, software application support, expertise in statistical analyses and computational modeling of biomedical research data.

Proper citation: Wistar Bioinformatics Core Facility (RRID:SCR_010203) Copy   

•   Source: SciCrunch Registry

https://core.bioinformatics.udel.edu

CBCB Bioinformatics Data Science Core builds upon infrastructure of the Center for Bioinformatics and Computational Biology. Delaware Biotechnology Institute , Delaware Data Science Institute, and Protein Information Resource. Core helps with planning your research or analyzing your current data. Services:Consultation and Collaboration, Proposal Assistance,Training, Bioinformatics Software, Computational Hardware, Database and Web Services, Next Gen Analysis, Custom Analysis.

Proper citation: University of Delaware CBCB Bioinformatics Data Science Core Facility (RRID:SCR_017696) Copy   

•   Source: SciCrunch Registry

https://www.albany.edu/repr/

Resource offers range of mass spectrometry instrumentation, expertise in analysis of RNA, RNA modifications, and proteins involved in RNA metabolism/regulation, supports projects involving analysis of biomolecules, metabolites, and small synthetic molecules, provides consulting on experimental design, sample preparation and data interpretation, whole project development and grant writing contributions.

Proper citation: Albany University RNA Epitranscriptomics and Proteomics Resource Core Facility (RRID:SCR_017695) Copy   

•   Source: SciCrunch Registry

https://sdrc.stanford.edu/sdrc-research-cores/dctc/home/

With the following services from the Diabetes Clinical and Translational Core (DCTC), members will receive training in biospecimen preservation, study design, data analysis, data management, use of statistical software and clinical trial conduct.

Proper citation: Stanford Diabetes Research Center Diabetes Clinical and Translational Core (RRID:SCR_016212) Copy   

•   Source: SciCrunch Registry