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https://skyline.gs.washington.edu/labkey/project/home/software/Skyline/begin.view

Software tool as Windows client application for targeted proteomics method creation and quantitative data analysis. Open source document editor for creating and analyzing targeted proteomics experiments. Used for large scale quantitative mass spectrometry studies in life sciences.

Proper citation: Skyline (RRID:SCR_014080) Copy   

•   Source: SciCrunch Registry

http://www.cscc.unc.edu/protect/

A study of how children newly diagnosed with ulcerative colitis (UC) respond to mesalamine and prednisone (corticosteroid), the standard initial therapies used to treat this disorder. Over a period of 5 years PROTECT will prospectively study the course of 430 children newly diagnosed with UC who are treated with standardized care. Biospecimens (blood, stool, colonic biopsy tissue) will be obtained and used to better understand the effects of genetics, mechanisms of inflammation, Vitamin D, and the bacteria contained in the stool (microbiome) on clinical outcomes.

Proper citation: Predicting Response to Standardized Pediatric Colitis Therapy (PROTECT) (RRID:SCR_014374) Copy   

•   Source: SciCrunch Registry

http://scgap.systemsbiology.net/project_description.php

A research organization which aims to conduct a variety of stem cell research projects. These projects include: to CD phenotype the human prostate and bladder using a confocal microscopy, to CD the phenotype of the mouse prostate and bladder, to profile samples of basal and stromal cells using uncultured cells, to confirm cell-type specific expression of genes that were identified by array analysis, and to create a database with the resulting database.

Proper citation: Stem Cell Genome Anatomy Projects (RRID:SCR_014517) 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

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://www.nature.com/articles/s41467-018-03367-w

Nanodroplet processing platform for deep and quantitative proteome profiling of 10 to 100 mammalian cells. It enhances efficiency and recovery of sample processing by downscaling processing volumes.

Proper citation: nanoPOTS (RRID:SCR_017129) 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

https://github.com/kwanjeeraw/metabox

Software R toolbox for thorough metabolomic data analysis, integration and interpretation. Metabox 2.0 is updated version of R package Metabox and includes several methods for data processing, statistical analysis, biomarker analysis, integrative analysis and data interpretation.

Proper citation: Metabox (RRID:SCR_024443) Copy   

•   Source: SciCrunch Registry

http://www.childrennetwork.org/

Database of clinical information and serum and tissue samples from children across the United States and Canada with Biliary Atresia, Idiopathic Neonatal Hepatitis, Cystic Fibrosis Liver Disease, Alagille Syndrome, Alpha-1 Antitrypsin Deficiency, Bile Acid Synthesis Defects, Mitochondrial Hepatopathies, and Progressive Familial Intrahepatic Cholestasis in order to facilitate research and to perform clinical, epidemiological, and therapeutic trials in these important pediatric liver diseases. Three NIDDK-funded consortia, Biliary Atresia Research Consortium (BARC), Cholestatic Liver Disease Consortium (CLiC), and the Cystic Fibrosis Liver Disease (CFLD) Network were consolidated to form ChiLDREN. Most of the ChiLDREN studies are natural history studies aimed at acquiring information and data that will provide a better understanding of these rare conditions. Participants will be asked to allow study personnel to obtain information from medical records and an interview, and to collect blood, urine, and tissue samples when clinically indicated, in order to understand the causes of these diseases and to improve the diagnosis and treatment of children with these diseases. All of the information obtained in these studies is confidential and no names or identifying information are used in the study.

Proper citation: Childhood Liver Disease Research and Education Network (RRID:SCR_001497) Copy   

•   Source: SciCrunch Registry

https://hpap.pmacs.upenn.edu

Program is performing deep phenotyping of human endocrine pancreas and its interaction with immune system to better understand cellular and molecular events that precede and lead to beta cell loss in Type-1 Diabetes (T1D) and islet dysfunction in Type-2 Diabetes (T2D).

Proper citation: HIRN Human Pancreas Analysis Program (RRID:SCR_016202) Copy   

•   Source: SciCrunch Registry

http://www.med.umich.edu/mgpc/cores/vivo.htm

Core facility that consists of the following 4 distinct programs: In Vivo Small Animal Studies Program, Organoid/Enteroid Modeling Program, Biospecimens Banking Service, and Clinical Design and Statistics.

Proper citation: University of Michigan Center for Gastrointestinal Research In Vivo Animal and Human Studies Core (RRID:SCR_015608) Copy   

•   Source: SciCrunch Registry

http://www.uchicagoddrcc.org/research-cores/tissue-and-cell-analysis-core

Core whose services include anatomic pathology review of human and experimental animal tissues as well as consultation in the best approaches for such analyses, cost-effective and high quality processing and staining of formalin-fixed paraffin-embedded tissues, and making collections of human tissue and imaging technologies available to researchers.

Proper citation: University of Chicago Digestive Diseases Research Core Center Tissue and Cell Imaging Core (RRID:SCR_015607) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/pubs/MitoCarta/

Collection of genes encoding proteins with strong support of mitochondrial localization. Inventory of genes encoding mitochondrial-localized proteins and their expression across 14 mouse tissues. Database is based on human and mouse RefSeq proteins that are mapped to NCBI Gene loci. MitoCarta 2.0 inventory provides molecular framework for system-level analysis of mammalian mitochondria.

Proper citation: MitoCarta (RRID:SCR_018165) Copy   

•   Source: SciCrunch Registry

https://signalingpathways.org

Web multi omics knowledgebase based upon public, manually curated transcriptomic and cistromic datasets involving genetic and small molecule manipulations of cellular receptors, enzymes and transcription factors. Integrated omics knowledgebase for mammalian cellular signaling pathways. Web browser interface was designed to accommodate numerous routine data mining strategies. Datasets are biocurated versions of publically archived datasets and are formatted according to recommendations of the FORCE11 Joint Declaration on Data Citation Principles73, and are made available under Creative Commons CC 3.0 BY license. Original datasets are available.

Proper citation: Signaling Pathways Project (RRID:SCR_018412) Copy   

•   Source: SciCrunch Registry

https://repository.niddk.nih.gov/study/36

Data set and biosepecimens of a multi-center clinical trial to determine if treatment with beta-cell antigens can delay the onset of Type 1 Diabetes Mellitus (Type 1 DM) in non-diabetic relatives of persons with Type 1 DM. Insulin is a well characterized antigen specifically produced by beta-cells, and it was used for this purpose in the initial DPT-1 studies. The protocol for high risk subjects uses daily subcutaneous insulin injections and an annual course of intravenous insulin treatment, while the protocol for intermediate risk subjects uses daily doses of insulin administered orally. Neither injected nor oral insulin at the doses used were observed to delay or prevent diabetes, although further studies are needed to test whether oral insulin can delay diabetes in people in the intermediate risk group with high titers of insulin autoantibodies.

Proper citation: Diabetes Prevention Type 1 (RRID:SCR_001467) Copy   

•   Source: SciCrunch Registry

https://www.clinicaltrials.gov/study/NCT00360646

Prospective and retrospective registry of well-characterized cases of drug-induced liver disease. The goals of Network include the development of standardized procedures to identify and fully characterize bona fide cases of drug- and complementary and alternative medicines (CAM)-induced liver injury, and to conduct controlled, clinical studies that will include extensive collection of data, serum, DNA, and tissue specimens. Cases of liver injury due to herbal medications are also included. The network will also develop terminology and standardized definitions for DILI, and to develop causality assessment instruments that are sensitive, specific, and reproducible. DILIN is funded by a cooperative agreement and includes five clinical centers and a central data coordinating center. The research goals of DILIN are to: * Create a registry of carefully documented DILI cases * Identify clinical, immunological, and environmental risk factors for drug- and CAM-mediated hepatotoxicity * Create a bank of biological specimens consisting of DNA, plasma, and immortalized lymphocytes to facilitate detailed genetic analyses * Characterize the natural history of drug- and CAM-induced DILI for at least six months following enrollment * Develop the capability to recontact these individuals over an extended period of time so that additional studies exploring DILI mechanisms can be performed Two studies are being initiated by the network. In the Retrospective Study, the implicated drugs are restricted to isoniazid, phenytoin, combination clavulanic acid/amoxicillin, and valproic acid (Depakote), Nitrofurantoin, Trimethoprim-sulfamethoxazole, Minocycline, and Quinolone antibiotics. These drugs were chosen because they are frequently administered to patients not receiving other hepatotoxic drugs, making it easier to establish causality. Patients must be alive, and the date of onset of the DILI episode must be on or after January 1, 1994. In the Prospective Study, all incident cases of drug- and CAM-induced liver injury are being considered. Initial presentation to a healthcare professional must be within the previous six months. A detailed medication history of the implicated DILI drug together with all prescription, OTC, and herbal medications is being recorded. Liver and serological tests are being performed to characterize the injury and to exclude competing causes of liver injury. A blood sample is also being drawn for plasma storage and DNA isolation. These cases will be followed longitudinally to characterize the long-term effects of the DILI episode. For both studies, documented, clinically significant DILI must be recorded in the patient's medical charts so that a causal determination can be made. Patients will be excluded if they are unwilling or unable to provide a blood sample or participate in the genetics component. Children under two years of age at the time of enrollment are excluded due to blood-volume requirements. If you have patients who are eligible to participate in either study, please contact one the DILIN clinical sites. As a general policy, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) invites investigator-initiated research project applications for ancillary studies to ongoing, large-scale clinical trials, epidemiological studies, and disease databases supported by the Institute. These studies are focused on a wide range of diseases and conditions including diabetes, obesity, acute and chronic liver disease, chronic kidney disease, and benign prostatic hyperplasia, among others.

Proper citation: Drug-Induced Liver Injury Network (RRID:SCR_001524) Copy   

•   Source: SciCrunch Registry

http://www.prostatitis.org/symptomindex.html

Questionnaire developed by physicians in NIDDK's Chronic Prostatitis Collaborative Research Network that can help physicians to accurately measure the severity of prostatitis symptoms and their impact on a patient's lifestyle. The CPSI questionnaire assesses pain, urination, and the effect of chronic prostatitis on daily activities. With this information, researchers and physicians can reliably evaluate whether potential treatments are working. The questionnaire was originally published in the Journal of Urology in August 1999 (Vol. 162, pages 369-375). It is available as a PDF document in English, Spanish, German and Korean.

Proper citation: NIH Chronic Prostatitis Symptom Index (RRID:SCR_001482) Copy   

•   Source: SciCrunch Registry

https://gataca.cchmc.org/gataca/gudmap

A database which can be used to search for genes critical for a variety of Genito-Urinary system functions and diseases.

Proper citation: GATACA GUDMAP Gene Explorer (RRID:SCR_014518) Copy   

•   Source: SciCrunch Registry