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https://github.com/hakyimlab/PrediXcan

Software tool to detect known and novel genes associated with disease traits and provide insights into the mechanism of these associations. Used to test the molecular mechanisms through which genetic variation affects phenotype.

Proper citation: PrediXcan (RRID:SCR_016739) Copy   

•   Source: SciCrunch Registry

https://www.sciencescott.com/pyminer

Software tool to automate cell type identification, cell type-specific pathway analyses, graph theory-based analysis of gene regulation, and detection of autocrine-paracrine signaling networks. Finds Gene and Autocrine-Paracrine Networks from Human Islet scRNA-Seq.

Proper citation: PyMINEr (RRID:SCR_016990) Copy   

•   Source: SciCrunch Registry

https://pachterlab.github.io/sleuth/about

Software tool for analysis of RNA-Seq experiments for which transcript abundances have been quantified with kallisto. Used for the differential analysis of gene expression data that utilizes bootstrapping in conjunction with response error linear modeling to decouple biological variance from inferential variance.

Proper citation: sleuth (RRID:SCR_016883) Copy   

•   Source: SciCrunch Registry

http://www.bx.psu.edu/~giardine/vision/

International project to analyze mouse and human hematopoiesis, and provide a tractable system with clear clinical significance and importance to NIDDK. Collection of information from the flood of epigenomic data on hematopoietic cells as catalogs of validated regulatory modules, quantitative models for gene regulation, and a guide for translation of research insights from mouse to human.

Proper citation: ValIdated Systematic IntegratiON of epigenomic data (RRID:SCR_016921) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

https://www.zurich.ibm.com/cellcycletracer/

Software tool as supervised machine learning algorithm that classifies and sorts single cell mass cytometry data according to their cell cycle, which allows to correct for cell cycle state and cell volume heterogeneity. Reveals signaling relationships and cell heterogeneity that were otherwise masked. Computational method to quantify cell cycle and cell volume variability.

Proper citation: CellCycleTRACER (RRID:SCR_017128) Copy   

•   Source: SciCrunch Registry

https://github.com/epistasislab/hibachi

Software tool that creates data sets with particular characteristics. Method and open source software for simulating complex biological and biomedical data to aid in comparing and evaluating machine learning methods.

Proper citation: Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (RRID:SCR_017140) Copy   

•   Source: SciCrunch Registry

http://oligogenome.stanford.edu/

The Stanford Human OligoGenome Project hosts a database of capture oligonucleotides for conducting high-throughput targeted resequencing of the human genome. This set of capture oligonucleotides covers over 92% of the human genome for build 37 / hg19 and over 99% of the coding regions defined by the Consensus Coding Sequence (CCDS). The capture reaction uses a highly multiplexed approach for selectively circularizing and capturing multiple genomic regions using the in-solution method developed in Natsoulis et al, PLoS One 2011. Combined pools of capture oligonucleotides selectively circularize the genomic DNA target, followed by specific PCR amplification of regions of interest using a universal primer pair common to all of the capture oligonucleotides. Unlike multiplexed PCR methods, selective genomic circularization is capable of efficiently amplifying hundreds of genomic regions simultaneously in multiplex without requiring extensive PCR optimization or producing unwanted side reaction products. Benefits of the selective genomic circularization method are the relative robustness of the technique and low costs of synthesizing standard capture oligonucleotide for selecting genomic targets.

Proper citation: OligoGenome (RRID:SCR_006025) Copy   

•   Source: SciCrunch Registry

http://nmri.niddk.nih.gov/

Communication network of current and potential biomedical research investigators and technical personnel from traditionally under-served communities: African American, Hispanic American, American Indian, Alaskan Native, Native Hawaiian, and other Pacific Islanders. The major objective of the network is to encourage and facilitate participation of members of underrepresented racial and ethnic minority groups in the conduct of biomedical research in the fields of diabetes, endocrinology, metabolism, digestive diseases, nutrition, kidney, urologic and hematologic diseases. A second objective is to encourage and enhance the potential of the underrepresented minority investigators in choosing a biomedical research career in these fields. An important component of this network is promotion of two-way communications between network members and the NIDDK.

Proper citation: Network of Minority Health Research Investigators (RRID:SCR_006589) Copy   

•   Source: SciCrunch Registry

http://nkdep.nih.gov/

Educational resource to increase awareness of kidney disease and its risk factors, improve early detection of chronic kidney disease (CKD), reduce the burden of CKD, facilitate identification of patients at greatest risk for progression to kidney failure, stress the importance of testing those at risk, promote evidence-based interventions to slow progression of CKD, and support the coordination of Federal responses to CKD. Target audiences include individuals at risk, particularly those with diabetes, high blood pressure, and a family history of kidney disease, and primary care providers.

Proper citation: National Kidney Disease Education Program (RRID:SCR_006527) Copy   

•   Source: SciCrunch Registry

https://www.proteinspire.org/MOPED/

An expanding multi-omics resource that enables rapid browsing of gene and protein expression information from publicly available studies on humans and model organisms. MOPED also serves the greater research community by enabling users to visualize their own expression data, compare it with existing studies, and share it with others via private accounts. MOPED uniquely provides gene and protein level expression data, meta-analysis capabilities and quantitative data from standardized analysis utilizing SPIRE (Systematic Protein Investigative Research Environment). Data can be queried for specific genes and proteins; browsed based on organism, tissue, localization and condition; and sorted by false discovery rate and expression. MOPED links to various gene, protein, and pathway databases, including GeneCards, Entrez, UniProt, KEGG and Reactome. The current version of MOPED (MOPED 2.5) The current version of MOPED (MOPED 2.5, 2014) contains approximately 5 million total records including ~260 experiments and ~390 conditions.

Proper citation: MOPED - Model Organism Protein Expression Database (RRID:SCR_006065) Copy   

•   Source: SciCrunch Registry

http://www.ccehindy.org

Research center for hematology research. It provides services through four scientific core facilities: the Experimental Mouse Resources Core, the Optical Microscopy Services Core, the Angiogenesis Core, and the Flow Cytometry Core in addition to the Enrichment Program of the Center.

Proper citation: Indiana University Cooperative Center of Excellence in Hematology (RRID:SCR_015343) Copy   

•   Source: SciCrunch Registry

http://zfrhmaps.tch.harvard.edu/cemh/

Research center investigating molecular hematology through mouse and zebrafish models.

Proper citation: Boston Children's Hospital Center of Excellence in Molecular Hematology (RRID:SCR_015348) Copy   

•   Source: SciCrunch Registry

http://www.cumc.columbia.edu/derc/

Research center which provides research support for investigators pursuing research on diabetes and metabolic disorders.

Proper citation: Columbia Diabetes Research Center (RRID:SCR_015075) Copy   

•   Source: SciCrunch Registry

http://hms-dbmi.github.io/scde/index.html

Software package that implements a set of statistical methods for analyzing single-cell RNA-seq data, including differential expression analysis (Kharchenko et al.) and pathway and geneset overdispersion analysis (Fan et al.)

Proper citation: SCDE (RRID:SCR_015952) Copy   

•   Source: SciCrunch Registry

http://www.cfrc.pitt.edu/index.html

Research center whose goal is to understand and translate the basic mechanisms of cystic fibrosis. It uses the molecular and cell biology of CFTR, CFTR mutants, infection, and inflammation with the overall theme of translating preclinical science into clinical investigations.

Proper citation: Cystic Fibrosis Center University of Pittsburgh (RRID:SCR_015400) Copy   

•   Source: SciCrunch Registry

http://cdmd.indiana.edu

Center that includes over seventy investigators engaged in basic and translational research in diabetes and related metabolic disorders, and their complications. It contains four Research Cores that serve for innovative and translational research.

Proper citation: Indiana Diabetes Research Center (RRID:SCR_015080) Copy   

•   Source: SciCrunch Registry

https://hirnetwork.org

Network helps to organize and support collaborative research related to loss of functional beta cell mass in Type 1 Diabetes (T1D). Project consists of four independent research initiatives: Consortium on Beta Cell Death and Survival (CBDS), Consortium on Human Islet Biomimetics (CHIB), Consortium on Modeling Autoimmune Interactions (CMAI), Consortium on Targeting and Regeneration (CTAR), and Human Pancreas Analysis Program (HPAP).

Proper citation: Human Islet Research Network (HIRN) (RRID:SCR_014393) Copy   

•   Source: SciCrunch Registry

https://github.com/compbiolabucf/APA-Scan

Software Python tool for detection and visualization of annotated and potential alternative polyadenylation events in downstream 3'-UTR of gene among two different biological conditions. Used for detection and visualization of 3'-UTR alternative polyadenylation with RNA-seq and 3'-end-seq data.

Proper citation: APA-Scan (RRID:SCR_022974) Copy   

•   Source: SciCrunch Registry

https://sites.duke.edu/pomms/

Biorepository of clinical, metabolomic, and microbiome samples from adolescents with obesity as they undergo lifestyle modification.Biorepository is available as shared resource.

Proper citation: Pediatric Obesity Microbiome and Metabolism Study (RRID:SCR_021071) Copy   

•   Source: SciCrunch Registry

http://secrepedia.org

Encyclopedia of white and brown adipocyte secretome in mouse models and humans as key prerequisite to elucidating role of these mediators in normal physiology and disease.

Proper citation: Secrepedia (RRID:SCR_022590) Copy   

•   Source: SciCrunch Registry