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https://kpmp.org

Project to ethically obtain and evaluate human kidney biopsies from participants with Acute Kidney Injury (AKI) or Chronic Kidney Disease (CKD), create a kidney tissue atlas, define disease subgroups, and identify critical cells, pathways, and targets for novel therapies. Used to develop the next generation of software tools to visualize and understand the various components of kidney diseases and to optimize data collection. Multi site collaboration comprised of patients, clinicians, and investigators from across the United States.

Proper citation: Kidney Precision Medicine Project (RRID:SCR_016920) Copy   

•   Source: SciCrunch Registry

http://datahub.io/dataset/kupkb/resource/8c1e0082-e958-493b-83e6-111bc1c2f0a5

Ontology describing kidney and urinary pathways cell, anatomy, and disease.

Proper citation: Kidney and Urinary Pathway Ontology (RRID:SCR_006690) Copy   

•   Source: SciCrunch Registry

http://datahub.io/dataset/kupkb

A collection of omics datasets (mRNA, proteins and miRNA) that have been extracted from PubMed and other related renal databases, all related to kidney physiology and pathology giving KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. Some microarray raw datasets have also been downloaded from the Gene Expression Omnibus and analyzed by the open-source software GeneArmada. The Semantic Web technologies, together with the background knowledge from the domain's ontologies, allows both rapid conversion and integration of this knowledge base. SPARQL endpoint http://sparql.kupkb.org/sparql The KUPKB Network Explorer will help you visualize the relationships among molecules stored in the KUPKB. A simple spreadsheet template is available for users to submit data to the KUPKB. It aims to capture a minimal amount of information about the experiment and the observations made.

Proper citation: Kidney and Urinary Pathway Knowledge Base (RRID:SCR_001746) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=renal

An integrated resource for information on genes, QTLs and strains associated with a variety of kidney and renal system conditions such as Renal Hypertension, Polycystic Kidney Disease and Renal Insufficiency, as well as Kidney Neoplasms.

Proper citation: Renal Disease Portal (RRID:SCR_009030) Copy   

•   Source: SciCrunch Registry

http://www.capitalbiosciences.com/

Biological products including Cell Immortalization Products, Clinically Defined Human Tissue, cDNA ORF Clones, Premade Adenoviruses, Purified Proteins, Viral Expression Systems and others as well as services like Custom Recombinant Adenovirus Production, Custom Recombinant Lentivirus Production, Protein Detection and Quantification and Stable Cell Line Production for academic and governmental research institutes, pharmaceutical and biotechnology industry. Capital Biosciences offers most types of human tissues, normal and diseased, with extensive clinical history and follow up information. Standard specimen format: Snap-frozen(flash-frozen), Formalin fixed and paraffin embedded (FFPE) tissues, Blood and blood products, Bone marrow, Total RNA, Genomic DNA, Total Proteins, Primary cell cultures, Viable frozen tissue. Tumor tissue samples include: Bladder cancer, Glioblastoma, Medulloblastoma, Breast Carcinoma, Cervical Cancer, Colorectal Cancer, Endometrial Cancer, Esophageal Cancer, Head and Neck (H&N) Carcinoma, Hepatocellular Carcinoma (HCC), Hodgkin's lymphoma, Kidney, Renal Cell Carcinoma, Lung Cancer, Non-Small Cell (NCSLC), Lung Cancer, Small Cell (SCLC), Melanoma, Mesothelioma, non-Hodgkin's Lymphoma, Ovarian Adenocarcinoma, Pancreatic Cancer, Prostate Cancer, Stomach Cancer.

Proper citation: Capital Biosciences (RRID:SCR_004879) Copy   

•   Source: SciCrunch Registry

http://dknet.org/

The NIDDK Information Network (dkNET) is a community-based network to serve needs of basic and clinical investigators that includes large pools of data and research resources relevant to mission of National Institute of Diabetes and Digestive and Kidney Disease.

Proper citation: NIDDK Information Network (dkNET) (RRID:SCR_001606) Copy   

•   Source: SciCrunch Registry

https://glomcon.org

Consortium to bring together clinicians, pathologists, researchers, and biotech innovators to create scalable network of stakeholders interested in helping patients with glomerular kidney disease. Makes collective expertise of its members available for discussion of individual cases, provides infrastructure for biomarker studies, enables genomic research, and facilitates clinical trials.

Proper citation: Glomerular Disease Study & Trial Consortium (RRID:SCR_017264) Copy   

•   Source: SciCrunch Registry

https://hirnetwork.org/consortium/cbds

Consortium that is an independent research initiative of the Human Research Information Network (HIRN). It is using human tissues to discover highly specific biomarkers of beta cell injury in asymptomatic T1D and developing strategies to stop beta cell destruction early in the disease process.

Proper citation: HIRN Consortium on Beta Cell Death and Survival (RRID:SCR_016198) Copy   

•   Source: SciCrunch Registry

http://www.biobanks.se/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 6th, 2022. The biobank comprises paraffin blocks of surgical and autopsy tissue samples and corresponding histological slides as well as cytological material consisting of slides of vaginal smears, fine needle aspiration biopsies and exfoliative cytological material. The tissue samples date back until 1944 and most of the cytological samples until 1970. A subunit of the bank constitutes the National Tissue Microarray Centre. This center is supported by SWEGENE with the purpose to organize and construct tissue microarrays (TMA:s) for high throughput molecular pathology research on various kinds of tumors and other diseases. By linking the TMA.s to long-term and complete clinical follow-up data, prognostic and predictive studies will be facilitated. Biobank content: * Approximately 2,4 million paraffin blocks of surgical tissue specimens, * 1,1 million paraffin blocks of tissue samples from autopsies, * 3,8 million histological slides and * 1,6 million cytology slides. At present, the Tissue Microarray Centre includes: * A consecutive series of all invasive breast cancers (n=600) diagnosed in Malmo between 1988 and 1992. * All incident breast cancers within the Malmo Diet and Cancer cohort (n=400). * A subgroup of 600 pre-menopausal primary breast cancers within the nationwide, population-based randomized tamoxifen trial SBII:2. * 180 primary breast cancers from post-menopausal women included in a similar study. * A set of 120 extremely well characterized primary breast cancer samples with a clinical follow-up of 10 years. More than 40 relevant tumor biological parameters have been recorded in this material and it is therefore useful for a first screening of a marker in order to identify associations to other gene products. * 350 renal cell carcinomas (In collaboration with NUS). We provide researchers with state-of-the-art population based tissue microarrays with long-term and complete follow-up data on survival and treatment. With the TMA-technology, valuable biobank material will be preserved, allowing high throughput in-situ analyses of various tumors and other diseases with a minimal waste of tissue.

Proper citation: UMAS University Hospital - Biobanks of the Department of Clinical Pathology and Cytology (RRID:SCR_005957) Copy   

•   Source: SciCrunch Registry

http://www.animalgenome.org/pigs/nagrp.html

Database and resources on the pig genome.

Proper citation: U.S. Pig Genome Project (RRID:SCR_008151) Copy   

•   Source: SciCrunch Registry

http://www.bumc.bu.edu/busm-pathology/pathology-core-services/biospecimen-archive-research-core-barc/

Biospecimen repository of normal and diseased human material from a variety of tissues and conditions along with clinical annotation. Both frozen aliquots and paraffin embedded tissue are available. Biospecimens are available to qualified researchers with IRB approval. * Preliminary inquires please contact Cheryl Spencer at cheryl.spencer (at) bmc.org

Proper citation: Boston University Biospecimen Archive Research Core (RRID:SCR_005363) Copy   

•   Source: SciCrunch Registry

http://www.digestive.niddk.nih.gov

Information dissemination service of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) established to increase knowledge and understanding about digestive diseases among people with these conditions and their families, health care professionals, and the general public: online, in booklets and fact sheets, by email, and over the phone. To carry out this mission, NDDIC works closely with a coordinating panel of representatives from Federal agencies, voluntary organizations on the national level, and professional groups to identify and respond to informational needs about digestive diseases. NDDIC provides the following informational products and services: * Response to inquiries about digestive diseases - ranging from information about available patient and professional education materials to statistical data. By phone (8:30 a.m. to 5 p.m. eastern time, M-F), fax, mail, and email. * Publications about specific digestive diseases, provided free of copyright, in varying reading levels. Available online or as booklets and brochures. NDDIC also sends publications to health fairs and community events. * Referrals to health professionals through the National Library of Medicine''''s MEDLINEplus includes a consumer-friendly listing of organizations that will assist you in your search for physicians and other health professionals. * Exhibits at professional meetings specific to digestive diseases, as well as cross-cutting professional meetings. NDDIC exhibits at nine professional meetings each year, including Digestive Diseases Week, American College of Gastroenterology, Society of Gastroenterology Nurses and Associates, American Academy of Family Physicians, American Academy of Physician Assistants, American Nurses Association, and the National Conference for Nurse Practitioners.

Proper citation: National Digestive Diseases Information Clearinghouse (RRID:SCR_006771) Copy   

•   Source: SciCrunch Registry

https://ndriresource.org/for-researchers/services-capabilities-sample/htorr

NDRI’s Human Tissue and Organs for Research Resource (HTORR) Program has been funded by the National Institutes of Health (NIH) for over 30 consecutive years to support research programs across multiple disciplines. It is through the HTORR program that NDRI provides academic biomedical investigators with donated normal and diseased human tissues and organs recovered from a diverse donor pool using customized procurement, processing, and preservation and distribution protocols. Our HTORR Program supports academic biomedical research investigators needs by providing: Access to a wide array of human biospecimens from any body system * Customized procurement in a variety of preservation formats including fresh, frozen, and fixed suitable for various analytical techniques * Reduced costs for tissue procurement * Technical support to design your studies utilizing human biospecimens * Letters of support and budgetary information for grant applications

Proper citation: Human Tissue and Organ for Research Resource (HTORR) (RRID:SCR_002859) Copy   

•   Source: SciCrunch Registry

http://www.gudmap.org

Project aggregates and provides experimental gene expression data from genito-urinary system. International consortium providing molecular atlas of gene expression for developing organs of GenitoUrinary (GU) tract. Mouse strains to facilitate developmental and functional studies within GU system. Experimental protocols and standard specifications. Tutorials describing GU organogenesis and primary data via database. Data are from large-scale in situ hybridization screens (wholemount and section) and microarray gene expression data of microdissected, laser-captured and FACS-sorted components of developing mouse genitourinary (GU) system.

Proper citation: GenitoUrinary Development Molecular Anatomy Project (RRID:SCR_001554) Copy   

•   Source: SciCrunch Registry

https://motrpac-data.org/

National research consortium designed to discover and perform preliminary characterization of range of molecular transducers that underlie effects of physical activity in humans. Used to study molecular changes that occur during and after exercise and to advance understanding of how physical activity improves and preserves health. Six year program into mechanisms of how physical activity improves health and prevents disease led by NIH Office of Strategic Coordination, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute on Aging, and National Institute of Biomedical Imaging and Bioengineering.

Proper citation: MoTrPAC Data Hub (RRID:SCR_017611) Copy   

•   Source: SciCrunch Registry

http://rarediseasesnetwork.epi.usf.edu/index.htm

The Rare Diseases Clinical Research Network (RDCRN) was created to facilitate collaboration among experts in many different types of rare diseases. Our goal is to contribute to the research and treatment of rare diseases by working together to identify biomarkers for disease risk, disease severity and activity, and clinical outcome, while also encouraging development of new approaches to diagnosis, prevention, and treatment. The Rare Diseases Clinical Research Network (RDCRN) is made up of 19 distinctive consortia that are working in concert to improve availability of rare disease information, treatment, clinical studies, and general awareness for both patients and the medical community. The RDCRN also aims to provide up-to-date information for patients and to assist in connecting patients with advocacy groups, expert doctors, and clinical research opportunities.

Proper citation: Rare Diseases Clinical Research Network (RRID:SCR_004372) Copy   

•   Source: SciCrunch Registry

http://www.lamhdi.org/

THIS RESOURCE IS NO LONGER IN SERVICE, it has been replaced by Monarch Initiative. LAMHDI, the initiative to Link Animal Models to Human DIsease, is designed to accelerate the research process by providing biomedical researchers with a simple, comprehensive Web-based resource to find the best animal model for their research. LAMDHI is a free, Web-based, resource to help researchers bridge the gap between bench testing and human trials. It provides a free, unbiased resource that enables scientists to quickly find the best animal models for their research studies. LAMHDI includes mouse data from MGI, the Mouse Genome Informatics website; zebrafish data from ZFIN, the Zebrafish Model Organism Database; rat data from RGD, the Rat Genome Database; yeast data from SGD, the Saccharomyces Genome Database; and fly data from FlyBase. LAMHDI.org is operational today, and data is added regularly. Enhancements are planned to let researchers contribute their knowledge of the animal models available through LAMHDI. The LAMHDI goal is to allow researchers to share information about and access to animal models so they can refine research and testing, and reduce or replace the use of animal models where possible. LAMHDI Database Search: LAMHDI brings together scientifically validated information from various sources to create a composite multi-species database of animal models of human disease. To do this, the LAMHDI database is prepared from a variety of sources. The LAMHDI team takes publicly available data from OMIM, NCBI''s Entrez Gene database, Homologene, and WikiPathways, and builds a mathematical graph (think of it as a map or a web) that links these data together. OMIM is used to link human diseases with specific human genes, and Entrez provides universal identifiers for each of those genes. Human genes are linked to their counterpart genes in other species with Homologene, and those genes are linked to other genes tentatively or authoritatively using the data in WikiPathways. This preparatory work gives LAMHDI a web of human diseases linked to specific human genes, orthologous human genes, homologous genes in other species, and both human and non-human genes involved in specific metabolic pathways associated with those diseases. LAMHDI includes model data that partners provide directly from their data structures. For instance, MGI provides information about mouse models, including a disease for each model, as well as some genetic information (the ID of the model, in fact, identifies one or more genes). ZFIN provides genetic information for each zebrafish model, but no diseases, so zebrafish models are integrated by using the genes as the glue. For instance, a zebrafish model built to feature the zebrafish PKD2 gene would plug into the larger disease-gene map at the node representing the zebrafish PKD2 gene, which is connected to the node representing the human PKD2 gene, which in turn is connected to the node representing the human disease known as polycystic kidney disease. (Some of the partner data LAMHDI receives can even extend the base map. MGI provides a disease for every model, and in some cases this allows the creation of a disease-to-gene relationship in the LAMHDI database that might not already be documented in the OMIM dataset.) With curatorial and model information in hand, LAMHDI runs a lengthy automated process that exhaustively searches for every possible path between each model and each disease in the data, up to a set number of hops, producing for each disease-to-model pair a set of links from the disease to the model. The algorithm avoids circular paths and paths that include more than one disease anywhere in the middle of the path. At the end of this phase, LAMHDI has a comprehensive set of paths representing all the disease-to-model relationships in the data, varying in length from one hop to many hops. Each disease-to-model path is essentially a string of nodes in the data, where each node represents a disease, a gene, a linkage between genes (an orthologue, a homologue, or a pathway connection, referred to as a gene cluster or association), or a model. Each node has a human-friendly label, a set of terms and keywords, and - in most cases - a URL linking the node to the data source where it originated. When a researcher submits a search on the LAMHDI website, LAMHDI searches for the user''s search terms in its precomputed list of all known disease-to-model paths. It looks for the terms not only in the disease and model nodes, but also in every node along each path. The complete set of hits may include multiple paths between any given disease-to-model pair of endpoints. Each of these disease-to-model pair sets is ordered by the number of hops it involves, and the one involving the fewest hops is chosen to represent its respective disease-to-model pair in the search results presented to the user. Results are sorted by scores that represent their matches. The number of hops is one barometer of the strength of the evidence linking the model and the disease; fewer hops indicates the relationship is stronger, more hops indicates it may be weaker. This indicator works best for comparing models from a single partner dataset: MGI explicitly identifies a disease for each mouse model, so there can be disease-to-model hits for mice that involve just one hop. Because ZFIN does not explicitly identify a disease for each model, no zebrafish model will involve fewer than four hops to the nearest disease, from the zebrafish model to a zebrafish gene to a gene cluster to a human gene to a human disease.

Proper citation: LAMHDI: The Initiative to Link Animal Models to Human DIsease (RRID:SCR_008643) Copy   

•   Source: SciCrunch Registry

http://archives.niddk.nih.gov/patient/bach/bach.aspx

An epidemiologic study being conducted in the Boston metropolitan area to examine the prevalence of symptoms for health problems such as interstitial cystitis, urinary incontinence, benign prostatic hyperplasia, prostatitis, hypogonadism, and sexual function. Of interest to the survey are health disparities and inequalities. BACH is especially concerned with lack of adequate health insurance, lack of access to adequate medical care, and how these problems influence patterns of disease. The study also focuses on social determinants of disease that are over and above the contribution of individual characteristics and risk factors. To achieve a randomly sampled population, four neighborhoods were divided into 12 strata and from them investigators selected census blocks. Households were then randomly selected from the census blocks and sampled to identify eligible study participants. Investigators conduct a two-hour, in-home, bilingual field interview of all eligible participants, looking at symptoms and asking questions about lifestyle, physical activity, alcohol use, nutrition, demographics, and morbidity. They also conduct a detailed inventory of medications, both prescribed and over-the-counter, and take two non-fasting blood samples for hormone, cholesterol, and lipid levels that will be stored for future studies. By the time the study ends, approximately 6,000 men and women, ages 30 to 79, from four Boston area neighborhoods that have density levels proportionate with minority populations will have been interviewed in their homes. One third of the randomly sampled population will be African American; one third, Hispanic; and one third, Caucasian.

Proper citation: Boston Area Community Health Survey (RRID:SCR_007115) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/SNP/

General database of genetic variations maintained by the NCBI. Database as central repository for both single base nucleotide substitutions and short deletion and insertion polymorphisms. Distinguishes report of how to assay SNP from use of that SNP with individuals and populations. This separation simplifies some issues of data representation. However, these initial reports describing how to assay SNP will often be accompanied by SNP experiments measuring allele occurrence in individuals and populations. Community can contribute to this resource.

Proper citation: dbSNP (RRID:SCR_002338) Copy   

•   Source: SciCrunch Registry

https://www.immport.org/home

Data sharing repository of clinical trials, associated mechanistic studies, and other basic and applied immunology research programs. Platform to store, analyze, and exchange datasets for immune mediated diseases. Data supplied by NIAID/DAIT funded investigators and genomic, proteomic, and other data relevant to research of these programs extracted from public databases. Provides data analysis tools and immunology focused ontology to advance research in basic and clinical immunology.

Proper citation: The Immunology Database and Analysis Portal (ImmPort) (RRID:SCR_012804) Copy   

•   Source: SciCrunch Registry