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http://www.uimcimes.es/contenidos/golink?p=1

Software toolbox for Statistical Parametric Mapping (SPM) to fit reference-region kinetic models (SRTM, SRTM2, Patlak Reference and Logan Reference Plot) are currently available in QModeling to dynamic PET studies. Used for the analysis of brain imaging data sequences.

Proper citation: QModeling (RRID:SCR_016358) Copy   

•   Source: SciCrunch Registry

https://brainiak.org

Open source software package of Python modules for neuroscience, primarily focused on functional Magnetic Resonance Imaging (fMRI) analysis. Used for analyzing neuroimaging data.

Proper citation: Brain Imaging Analysis Kit (RRID:SCR_014824) Copy   

•   Source: SciCrunch Registry

https://github.com/xsun28/CloudMerge/

Software for merging massive VCF files into a single VCF file or TPED file. Source codes can be slightly modified to fit into other types of sorted merging of Omics data.

Proper citation: CloudMerge (RRID:SCR_016051) Copy   

•   Source: SciCrunch Registry

http://dmriprep.org

Software tool as preprocessing pipeline for diffusion MRI. Pipeline used for preprocessing of diverse dMRI data. Workflow dispenses of manual intervention, thereby ensuring reproducibility of results.

Proper citation: dMRIPrep (RRID:SCR_017412) Copy   

•   Source: SciCrunch Registry

https://www.addgene.org/collections/covid-19-resources/

Collections of Addgene plasmids, open access articles, protocols, and other resource collections related to COVID-19 that may be of use to scientists. Ordering or depositing plasmids related to COVID-19 research.

Proper citation: COVID-19 and Coronavirus plasmids and resources (RRID:SCR_018347) Copy   

•   Source: SciCrunch Registry

http://web.stanford.edu/group/vista/cgi-bin/wiki/index.php/MrDiffusion

Software package for diffusion imaging analysis and visualization. Module of Vistasoft for processing diffusion weighted data and measuring and visualizing fractional anisotropy, mean diffusivity, axial and radial diffusivity, RGB fiber direction maps and analysis of MRI data., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MrDiffusion (RRID:SCR_016567) Copy   

•   Source: SciCrunch Registry

https://github.com/OpenGene/fastp

Software tool to provide fast all in one preprocessing for FastQ files. Developed in C++ with multithreading supported to afford high performance. Performs quality control, adapter trimming, quality filtering, per read quality pruning and many other operations with a single scan of the FASTQ data.

Proper citation: fastp (RRID:SCR_016962) Copy   

•   Source: SciCrunch Registry

http://fit.genomics.lbl.gov/cgi-bin/myFrontPage.cgi

Web tool for browsing genome wide fitness experiments for diverse bacteria from Deutschbauer lab, the Arkin lab, and collaborators. Collection of mutant phenotypes for bacterial genes of unknown function.

Proper citation: Fitness Browser (RRID:SCR_018981) Copy   

•   Source: SciCrunch Registry

https://www.thegpm.org/crap/

List of proteins commonly found in proteomics experiments that are present either by accident or through unavoidable contamination of protein samples. List is based on analysis of current version of GPMDB, as well as suggestions by users. Current version of cRAP in FASTA format can be obtained from the GPM FTP site.

Proper citation: cRAP protein sequences (RRID:SCR_018187) Copy   

•   Source: SciCrunch Registry

https://github.com/mizutanilab/RecView

Software tool as a program for tomographic reconstruction and image processing of micro/nano-CT data taken at SPring8 and APS Argonne.

Proper citation: RecView (RRID:SCR_016531) Copy   

•   Source: SciCrunch Registry

https://support.10xgenomics.com/single-cell-gene-expression/software/visualization/latest/what-is-loupe-cell-browser

Desktop application that provides interactive visualization functionality to analyze data from different 10x Genomics solutions. Used to interrogate different views of 10x data to gain insights into underlying biology.

Proper citation: Loupe Browser (RRID:SCR_018555) Copy   

•   Source: SciCrunch Registry

https://www.spyder-ide.org

Interactive scientific development environment package for Python. Used for editing, analysis, debugging, and profiling functionality of comprehensive development tool with data exploration, interactive execution, deep inspection, and visualization.

Proper citation: Spyder (RRID:SCR_017585) Copy   

•   Source: SciCrunch Registry

https://github.com/ruanjue/smartdenovo

Software tool as de novo assembler for PacBio and Oxford Nanopore data. It produces assembly from all-vs-all raw read alignments without error correction stage. Allows to read overlapping, rescue missing overlaps, identify low-quality regions and chimaera and produce better consensus.

Proper citation: SMARTdenovo (RRID:SCR_017622) Copy   

•   Source: SciCrunch Registry

https://github.com/brentp/duphold

Software tool to annotate structural variant calls with sequence depth information that can add or remove confidence to SV predicted to affect copy number. Indicates the presence of a rapid change in depth relative to the regions surrounding the breakpoints. Allows the run time to be nearly independent of the number of variants important for large, jointly called projects with many samples. Annotates structural variant predictions made from both short read and long read data.

Proper citation: duphold (RRID:SCR_016938) Copy   

•   Source: SciCrunch Registry

https://github.com/madeluis/GENIST

Software tool as an algorithm to infer gene regulatory networks from spatial and temporal datasets. Spatial dataset or any data that can provide information about coexpression is used by the first step of the algorithm to perform clustering and separate the genes in the network in smaller coexpressed groups. Temporal dataset is used by the second step of the algorithm to infer regulations among the genes, based on Bayesian networks.

Proper citation: GENIST (RRID:SCR_016942) Copy   

•   Source: SciCrunch Registry

https://covic.lji.org/

Consortium to unite efforts and resources from experts across globe to advance effective, antibody based therapies against novel coronavirus, SARS-CoV-2. Represents multidisciplinary convergence of structural biology, virologists, immunologists, clinicians and bioinformaticians from academic and industry settings. Collects antibodies for testing as part of CoVICS. Contributed antibodies are blinded and will only be known as code name. Antibody contributors will be able to see performance of their own molecules and take part in analysis. Contributors retain ownership of their antibodies and may continue to publish on them using original antibody names. Goal is to determine relative in vitro potency and in vivo efficacy using centralized standardized assays to identify best individual mAbs and rational combinations of mAbs. Consortium will recommend ideal therapeutic molecules for human use to protect vulnerable populations from COVID-19 disease. CoVIC database (CoVIC-DB) will serve as clearinghouse for monoclonal antibodies against SARS-CoV-2. Database will catalog contributed antibodies in searchable resource and provide interactive analysis tools for comparisons among them.

Proper citation: Coronavirus Immunotherapy Consortium (RRID:SCR_018258) Copy   

•   Source: SciCrunch Registry

https://metagenote.niaid.nih.gov/

Quick and intuitive way to annotate data from genomics studies including microbiome. Project to aid researchers in applying standardized metadata describing what, where, how, and when of samples collected in genomics study. Collection of METAdata of GEnomics studies on web based NOTEbook. Metadata are stored in centralized repository and validated according to guidelines from Genomics Standard Consortium, which are also supported by repositories and large microbiome initiatives such as NCBI, European Bioinformatics Institute (EBI), and Earth Microbiome Project. Upon request from researchers, data will also be submitted for publication via NCBI Sequence Read Archive (SRA) repository.

Proper citation: METAGENOTE (RRID:SCR_018494) Copy   

•   Source: SciCrunch Registry

http://himc.stanford.edu

Core designed for immune monitoring services for clinical and translational studies. Goals include providing standardized, state-of-the art immune monitoring assays at RNA, protein, and cellular level, testing and developing new technologies for immune monitoring, archive, report, and mine data from immune monitoring studies. HIMC uses online database for integration of data from standard HIMC assays, along with de-identified clinical and demographic data.

Proper citation: Stanford University Human Immune Monitoring Center Core Facility (RRID:SCR_018266) Copy   

•   Source: SciCrunch Registry

https://broadinstitute.github.io/warp/docs/Pipelines/Optimus_Pipeline/README

Optimus is a pipeline developed by the Data Coordination Platform (DCP) of the Human Cell Atlas (HCA) Project that supports processing of any 3' single-cell and single-nuclei expression data generated with the 10x Genomic v2 or v3 assay. It is an alignment and transcriptome quantification pipeline that corrects cell barcodes, aligns reads to the genome, corrects Unique Molecular Identifiers (UMIs), generates an expression matrix in a UMI-aware manner, calculates summary metrics for genes and cells, detects empty droplets, returns read outputs in BAM format, and returns gene counts in NumPy matrix and Loom matrix formats.

Proper citation: Optimus Pipeline (RRID:SCR_018908) Copy   

•   Source: SciCrunch Registry

https://www.uke.de/english/research/core-facilities/bioinformatics-core-en.html

Core provides bioinformatics services for researchers at University Medical Center Hamburg Eppendorf and related institutions. Focusing on high throughput sequencing data. Services include data analysis, consulting, software development, and bioinformatical training.

Proper citation: University Medical Center Hamburg-Eppendorf Bioinformatics Core Facility (RRID:SCR_017144) Copy   

•   Source: SciCrunch Registry