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https://amp.pharm.mssm.edu/geneshot/

Software tool as search engine for ranking genes from arbitrary text queries. Enables to enter arbitrary search terms, to receive ranked lists of genes relevant to search terms. Returned ranked gene lists contain genes that were previously published in association with search terms, as well as genes predicted to be associated with terms based on data integration from multiple sources. Search results are presented with interactive visualizations.

Proper citation: Geneshot (RRID:SCR_017582) Copy   

•   Source: SciCrunch Registry

http://taylor0.biology.ucla.edu/structureHarvester/

Web based program for collating results generated by program STRUCTURE. Provides assess and visualize likelihood values across multiple values of K and hundreds of iterations for easier detection of number of genetic groups that best fit data. Reformats data for use in downstream programs, such as CLUMPP.It is complement for using software Structure in genetics population. Website and program for visualizing STRUCTURE output and implementing Evanno method., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Structure Harvester (RRID:SCR_017636) Copy   

•   Source: SciCrunch Registry

https://delaney.shinyapps.io/FairSubset/

Web tool to choose representative subsets of data for use with replicates or groups of different sample sizes. Used to retain distribution information at single datum level and may be considered for standardized use in fair publishing practices.

Proper citation: FairSubset (RRID:SCR_019102) Copy   

•   Source: SciCrunch Registry

https://www.rdocumentation.org/packages/DGCA/versions/1.0.2

Software R package to perform differential gene correlation analysis. Performs differential correlation analysis on input matrices, with multiple conditions specified by design matrix.

Proper citation: Differential Gene Correlation Analysis (RRID:SCR_020964) Copy   

•   Source: SciCrunch Registry

https://github.com/KrishnaswamyLab/MAGIC

Software tool for imputing missing values restoring structure of large biological datasets.Method that shares information across similar cells, via data diffusion, to denoise cell count matrix and fill in missing transcripts.

Proper citation: Markov Affinity based Graph Imputation of Cells (RRID:SCR_022371) Copy   

•   Source: SciCrunch Registry

https://github.com/greenelab/miQC

Software tool as flexible, probablistic metrics for quality control of scRNA-seq data. Adaptive probabilistic framework for quality control of single-cell RNA-sequencing data. Data driven QC metric that jointly models proportion of reads mapping to mtDNA and number of detected genes with mixture models in probabilistic framework to predict which cells are low quality in given dataset.

Proper citation: miQC (RRID:SCR_022697) Copy   

•   Source: SciCrunch Registry

https://www.miti-consortium.org/

Consortium provides guidelines for highly multiplexed tissue images. Standard that applies best practices developed for genomics and other microscopy data to highly multiplexed tissue images and traditional histology. Data and metadata standards consistent with Findable, Accessible, Interoperable, and Reusable (FAIR) standards that guide data deposition, curation and release.

Proper citation: Minimum Information about Tissue Imaging (RRID:SCR_022830) Copy   

•   Source: SciCrunch Registry

http://cahub.cancer.gov/about/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. A national center for biospecimen science and standards to advance cancer research and treatment. It was created in response to the critical and growing need for high-quality, well-documented biospecimens for cancer research. The initiative builds on resources already developed by the NCI, including the Biospecimen Research Network and the NCI Best Practices for Biospecimen Resources, both of which were developed to address challenges around standardization of the collection and dissemination of quality biospecimens. caHUB will develop the infrastructure for collaborative biospecimen research and the production of evidence-based biospecimen standard operating procedures.

Proper citation: caHUB (RRID:SCR_009657) Copy   

•   Source: SciCrunch Registry

http://drugtargetontology.org/

Ontology of drug targets to be used as a reference for drug targets, with the longer-term goal of creating a community standard that will facilitate the integration of diverse drug discovery information from numerous heterogeneous resources. The project itself aims to develop a novel semantic framework to formalize knowledge about drug targets with a focus on the current IDG protein families.

Proper citation: Drug Target Ontology (RRID:SCR_015581) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/gen3va/

Software tool for aggregation and analysis of gene expression signatures from related studies.Used to aggregate and analyze gene expression signatures extracted from GEO by crowd using GEO2Enrichr. Used to view aggregated report that provides global, interactive views, including enrichment analyses, for collections of signatures from multiple studies sharing biological theme.

Proper citation: GEN3VA (RRID:SCR_015682) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/CREEDS/

Software resource that allows students or the general public find variants that may be significantly associated with some disease. CREEDS also visualizes and analyzes gene expression signatures.

Proper citation: CRowd Extracted Expression of Differential Signatures (RRID:SCR_015680) Copy   

•   Source: SciCrunch Registry

https://www.rosettacommons.org/home

Molecular modeling software package for 3D structure prediction and high resolution design of proteins, nucleic acids, and non natural polymers. Used in computational biology, including de novo protein design, enzyme design, ligand docking, and structure prediction of biological macromolecules and macromolecular complexes.

Proper citation: Rosetta (RRID:SCR_015701) Copy   

•   Source: SciCrunch Registry

http://gigadb.org/dataset/100360

Method for uncovering mutations from RNA sequencing datasets that could be useful in further functional analysis. It also allows orthogonal validation of DNA-based mutation discovery by providing complementary sequence variation analysis from paired RNA/DNA sequencing data sets.

Proper citation: VaDiR (RRID:SCR_015797) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/L1000CDS2

LINCS L1000 characteristic direction signatures search engine. Software tool to find consensus signatures that match user’s input gene lists or input signatures. Underlying dataset is LINCS L1000 small molecule expression profiles generated at Broad Institute by Connectivity Map team. Differentially expressed genes of these profiles were calculated using multivariate method called Characteristic Direction.

Proper citation: L1000 Characteristic Direction Signature Search Engine (RRID:SCR_016177) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/Harmonizome/

Web application that allows for searching, visualization, and prediction about genes and proteins. It contains a collection of processed datasets gathered to serve and mine knowledge about genes and proteins from major online resources.

Proper citation: Harmonizome (RRID:SCR_016176) Copy   

•   Source: SciCrunch Registry

https://www.archrproject.com/

Software R package for processing and analyzing single-cell ATAC-seq data. Used for integrative single cell chromatin accessibility analysis.Provides intuitive, user focused interface for complex single cell analysis, including doublet removal, single cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing.

Proper citation: ArchR (RRID:SCR_020982) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages/release/bioc/html/GSVA.html

Open source software R package for assaying variation of gene set enrichment over sample population.Used for microarray and RNA-seq data analysis. Gene set enrichment method that estimates variation of pathway activity over sample population in unsupervised manner.

Proper citation: GSVA (RRID:SCR_021058) Copy   

•   Source: SciCrunch Registry

https://github.com/labsyspharm/cylinter

Open source software tool as interactive image segmentation filter for multiplex microscopy that aids in identification and removal of cell segmentation instances corrupted by optical and image processing artifacts.

Proper citation: CyLinter (RRID:SCR_021157) Copy   

•   Source: SciCrunch Registry

http://www.t1diabetes.nih.gov/t1d-raid/index.shtml

NOTE: The T1D-RAID program is not currently accepting applications. Cooperative program that makes available, on a competitive basis, NCI resources for the pre-clinical development of drugs, natural products, and biologics to facilitate translation to the clinic of novel, scientifically meritorious therapeutic interventions for type 1 diabetes and its complications. A partial listing of those services includes: high-throughput screening, studies in animal models, formulation, pharmacology and toxicology studies, and bulk substances acquisition. Requests to T1D-RAID are brief (20 pages or less), and should clearly outline the resources required to ready the proposed therapeutic agent for clinical trials. T1D-RAID should enable entry into the clinic of promising molecules that are not otherwise likely to receive an adequate and timely clinical test. T1D-RAID is designed to accomplish the tasks that are rate-limiting in bringing discoveries from the laboratory to the clinic. Once a project has been approved, NIDDKstaff interact directly with the Principal Investigator (PI). NCI contractors perform the T1D-RAID-approved tasks under the direction of NIDDKand NCI staff. The required tasks will vary from project to project. In some cases T1D-RAID will support only one or two key missing steps necessary to bring a compound to the clinic; in other cases it may be necessary to supply the entire portfolio of development requirements needed to file an IND. Examples of tasks that can be supported by T1D-RAID include, but are not limited to: * Definition or optimization of dose and schedule for in vivo activity * Development of pharmacology assays * Conduct of pharmacology studies with a pre-determined assay * Acquisition of bulk substance (GMP and non-GMP) * Scale-up production from lab-scale to clinical-trials lot scale * Development of suitable formulations * Development of analytical methods for bulk substances * Production of dosage forms * Stability assurance of dosage forms * Range-finding initial toxicology * IND-directed toxicology, with correlative pharmacology and histopathology * Planning of clinical trials * Regulatory affairs, so that FDA requirements are likely to be satisfied by participating investigators seeking to test new molecular entities in the clinic * IND filing advice The output of T1D-RAID activities will be both products and information that will be made fully available to the originating investigator for support of an IND application and clinical trials. T1D-RAID does not sponsor clinical trials.

Proper citation: Type 1 Diabetes - Rapid Access to Intervention Development (RRID:SCR_000203) Copy   

•   Source: SciCrunch Registry

https://www.roswellpark.edu/shared-resources/gene-targeting-and-transgenic

Facility which provides researchers with transgenic mouse technologies, methods, and animal models. Knockout mice, transgenic mice, and mice on multiple strain backgrounds are provided.

Proper citation: RPCI Gene Targeting and Transgenic Shared Resource (RRID:SCR_001020) Copy   

•   Source: SciCrunch Registry