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http://www.iiserpune.ac.in/~coee/histome/

Database of human histone variants, sites of their post-translational modifications and various histone modifying enzymes. The database covers 5 types of histones, 8 types of their post-translational modifications and 13 classes of modifying enzymes. Many data fields are hyperlinked to other databases (e.g. UnprotKB/Swiss-Prot, HGNC, OMIM, Unigene etc.). Additionally, this database also provides sequences of promoter regions (-700 TSS +300) for all gene entries. These sequences were extracted from the UCSC genome browser. Sites of post-translational modifications of histones were manually searched from PubMed listed literature. Current version contains information for about ~50 histone proteins and ~150 histone modifying enzymes. HIstome is a combined effort of researchers from two institutions, Advanced Center for Treatment, Research and Education in Cancer (ACTREC), Navi Mumbai and Center of Excellence in Epigenetics (CoEE), Indian Institute of Science Education and Research (IISER), Pune.

Proper citation: HIstome: The Histone Infobase (RRID:SCR_006972) Copy   

•   Source: SciCrunch Registry

http://epi.grants.cancer.gov/CFR/

The Breast Cancer Family Registry (Breast CFR) and the Colon Cancer Family Registry (Colon CFR) were established by the National Cancer Institute (NCI) as a unique resource for investigators to use in conducting studies on the genetics and molecular epidemiology of breast and colon cancer. Known collectively as the CFRs, they share a central goal: the translation of research to the clinical and prevention settings for the benefit of Registry participants and the general public. The CFRs are particularly interested in: * Identifying and characterizing cancer susceptibility genes; * Defining gene-gene and gene-environment interactions in cancer etiology; and * Exploring the translational, preventive, and behavioral implications of research findings. The CFRs do not provide funding for studies; however, researchers can apply to access CFR data and biospecimens contributed by thousands of families from across the spectrum of risk for these cancers and from population-based or relative controls. Special features of the CFRs include: * Population-based and clinic-based ascertainment; * Systematic collection of validated family history; * Epidemiologic risk factor , clinical, and followup data; * Biospecimens (including tumor blocks and Epstein-Barr virus (EBV)-transformed cell lines); * Ongoing molecular characterization of the participating families; and * A combined informatics center.

Proper citation: NCI Breast and Colon Cancer Family Registries (RRID:SCR_006664) Copy   

•   Source: SciCrunch Registry

https://med.stanford.edu/lucasmri.html

Biomedical technology research center that develops innovative technologies in five core research areas of magnetic resonance imaging and spectroscopy (MRI/MRS): # image reconstruction, fast imaging and radiofrequency (RF) pulse design methods, # R hardware development, # body imaging methods, # neuroimaging methods. # MR spectroscopy methods. In each of these areas, they capitalize on the long-standing, successful partnership and extensive experience in Stanford's Radiology and Electrical Engineering departments to improve and expand imaging technology for use in basic research and clinical care, and to provide cutting edge opportunities to the extramural community for biomedical research with MRI. Over its more than 18 years of existence, CAMRT has been motivated by and has served a wide base of extramurally sponsored collaborators and service users from leading medical and research institutions. Examples of collaborative projects are the development of real-time functional MRI biofeedback methods for neuroscience and clinical applications such as pain remediation, development of methods to mitigate metal artifacts in musculoskeletal imaging, development of novel RF pulses for many applications, and studies of breast cancer with efficient MRS methods.

Proper citation: Richard M. Lucas Center for Imaging (RRID:SCR_001406) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/

Biomedical technology resource center dedicated to the advancement of the state-of-the-art in biomedical modeling and simulation through Core and Collaborative Research projects, as well as the dissemination of this knowledge and related software through Service, Training and Dissemination activities aimed at the biomedical community at large. The BMSR includes four core research projects: * Pharmacokinetic/Pharmacodynamic Systems Analysis * Nonlinear Modeling of Complex Biomedical Systems * Modeling of Autonomic, Metabolic and Vascular Control Interactions * Nonlinear Modeling of the Hippocampus Fifteen Collaborative Research Projects serve as challenging test grounds for the Resource's methodologies and expertise.

Proper citation: Biomedical Simulations Resource (RRID:SCR_001952) Copy   

•   Source: SciCrunch Registry

http://www.utsouthwestern.edu/education/medical-school/departments/airc/southwestern-nmr-center/index.html

Biomedical technology research center that develops and applies new methods for analysis of metabolic networks in intact tissues, animals and human patients. The importance of understanding abnormal metabolism in common diseases such as cancer, diabetes and heart disease has long been appreciated. Because of constraints in technology, however, much of this research has been conducted in isolated systems where clinical relevance may be uncertain. Progress in magnetic resonance technology provides a foundation for major advances towards new ways of imaging metabolism in patients. These new techniques offer the advantage of imaging biochemical pathways without radiation. The focus of this Resource is to bring these technologies to a level where clinical research is feasible through the development of new MR contrast agents, NMR spectroscopy at high fields, and imaging of hyperpolarized 13C.

Proper citation: Southwestern NMR Center for In Vivo Metabolism (RRID:SCR_001429) Copy   

•   Source: SciCrunch Registry

http://ranchobiosciences.com/gse27831/

Curated data set from gene expression profiles of 29 unique samples from uveal melanoma patients that were measured on Affymetrix microarray. In addition, expression of syntenin-1 was measured by RT-PCR and this data is also available in the study.

Proper citation: GSE27831 (RRID:SCR_003646) Copy   

•   Source: SciCrunch Registry

http://ranchobiosciences.com/gse20194/

Curated data set of gene expression data from 230 stage I-III breast cancers that were generated from fine needle aspiration specimens of newly diagnosed breast cancers before any therapy. The biopsy specimens were collected sequentially during a prospective pharmacogenomic marker discovery study between 2000 and 2008. These specimens represent 70-90% pure neoplastic cells with minimal stromal contamination. In the study, patients received 6 months of preoperative (neoadjuvant) chemotherapy including paclitaxel, 5-fluorouracil, cyclophosphamide and doxorubicin followed by surgical resection of the cancer.

Proper citation: GSE20194 (RRID:SCR_003645) Copy   

•   Source: SciCrunch Registry

http://ranchobiosciences.com/gse4698/

Curated data set where gene expression profiling was performed on 60 prospectively collected samples of children with first relapse of acute lymphoblastic leukemia enrolled on the relapse trial ALL-REZ BFM 2002 of the Berlin-Frankfurt-Muenster study group.

Proper citation: GSE4698 (RRID:SCR_003644) Copy   

•   Source: SciCrunch Registry

http://ranchobiosciences.com/gse4271/

Curated data set from a study that investigated 77 primary high-grade astrocytomas and 23 matched recurrences so that changes in gene expression related to both survival and disease progression can be identified. Samples in the study include WHO grade III and IV astrocytomas with a wide range of survival times.

Proper citation: GSE4271 (RRID:SCR_003643) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/~rnusse/pathways/targets.html

A list of target genes of Wnt/beta-catenin signaling. Suggestions for additions are welcome. Direct targets are defined as those with Tcf binding sites and demonstrating that these sites are important.

Proper citation: Target genes of Wnt/beta-catenin signaling (RRID:SCR_007022) 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.dna-network.ac.uk/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on October 6, 2011. A project to collect, store and study DNA samples from tens of thousands of healthy volunteers and patients with diseases of major public importance. It aims to identify genes that are risk factors for the conditions. The network consists of 13 collections led by different clinicians throughout the UK. At its heart is an archive infrastructure which manages the DNA and the information associated with it. The European Collection of Cell Cultures in Porton Down handles the blood, peripheral blood lymphocytes and EBV-transformed cell lines, while the Centre for Integrated Genomic Medical Research at Manchester University manages the DNA. These banked samples are available to UK and international researchers, who can examine data and set up collaborative work by registering at the DNA Network's website. The conditions for which samples are currently collected and stored are: Acute leukemia, Asthma and eczema, Late onset Alzheimer's disease, Breast cancer, Colorectal cancer, Coronary artery disease, Glomerulonephritis, Hypertension, Age-related macular degeneration, Multiple sclerosis, Parkinson's disease, Type 2 diabetes, Unipolar depression.

Proper citation: UK DNA Banking Network (RRID:SCR_010619) Copy   

•   Source: SciCrunch Registry

http://www.istge.it/crb/english.htm

The Centro di Risorse Biologiche (CRB-IST), institutional facility of IST, has been recently established by the General Director (Deliberation number 624 July 11, 2008). It aims at co-ordinating already existing biobanking activities, and participating in the European Infrastructure of Biobanks and Biomolecular Resources (BBMRI), in preparation in the frame of the 7th FP of the European Community. Aims: * to facilitate high quality translational research dependent on biological material and data * to address ethical issues on biobanking * to promote the project at the population level * to co-ordinate the IST biobanks and cell banks * to harmonize technical and management SOPs, according to international best practices * to help reduce costs for collection and storage of biological material * to favor institutional recognition at a regional, national and international level - to sustain the role of the Institute in the European infrastructure.

Proper citation: Biological Resource Centre - National Institute for Cancer Research (RRID:SCR_010548) Copy   

•   Source: SciCrunch Registry

http://research-public.gene.com/Research/genentech/canpredict/index.html

Web application that uses a combination of computational methods to identify those changes most likely to be cancer-associated.

Proper citation: CanPredict (RRID:SCR_008216) Copy   

•   Source: SciCrunch Registry

http://clinicalinformatics.stanford.edu/services/biobank.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 7th, 2023. An online, searchable record of biospecimen attributes and storage location for the following three biobanks at Stanford: * The Bone Marrow Transplant (BMT) program * The Hematology biospecimen bank is a research sample repository focusing on blood, plasma and bone marrow, primarily from leukemia patients. * Cancer Center Pathology Core: The Stanford Comprehensive Cancer Center Tissue Bank stores research samples of both solid tumor and blood from cancer patients, with an emphasis on prostate. As of November 2009, the system contains data on 50,000 biospecimens stored in multiple banks at Stanford. An anonymous Biospecimen Locator allows Stanford researchers to search the STRIDE Virtual Biospecimen Bank for suitable samples without having to know, or expose, any protected patient-specific information. Having determined that suitable specimens exist in one of the constituent biospecimens banks, the researcher can generate a Web-based request form to obtain additional information from the appropriate bank operator(s). Access to specimens is restricted to Stanford Faculty and Staff or affiliates., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: STRIDE Virtual Biospecimen Bank (RRID:SCR_008667) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000674.v1.p1

Human genetics data from an immense (78,000) and ethnically diverse population available for secondary analysis to qualified researchers through the database of Genotypes and Phenotypes (dbGaP). It offers the opportunity to identify potential genetic risks and influences on a broad range of health conditions, particularly those related to aging. The GERA cohort is part of the Research Program on Genes, Environment, and Health (RPGEH), which includes more than 430,000 adult members of the Kaiser Permanente Northern California system. Data from this larger cohort include electronic medical records, behavioral and demographic information from surveys, and saliva samples from 200,000 participants obtained with informed consent for genomic and other analyses. The RPGEH database was made possible largely through early support from the Robert Wood Johnson Foundation to accelerate such health research. The genetic information in the GERA cohort translates into more than 55 billion bits of genetic data. Using newly developed techniques, the researchers conducted genome-wide scans to rapidly identify single nucleotide polymorphisms (SNPs) in the genomes of the people in the GERA cohort. These data will form the basis of genome-wide association studies (GWAS) that can look at hundreds of thousands to millions of SNPs at the same time. The RPGEH then combined the genetic data with information derived from Kaiser Permanente''s comprehensive longitudinal electronic medical records, as well as extensive survey data on participants'' health habits and backgrounds, providing researchers with an unparalleled research resource. As information is added to the Kaiser-UCSF database, the dbGaP database will also be updated.

Proper citation: Resource for Genetic Epidemiology Research on Adult Health and Aging (RRID:SCR_010472) Copy   

•   Source: SciCrunch Registry

http://cancergenome.nih.gov/

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy   

•   Source: SciCrunch Registry

https://github.com/eduardporta/e-Driver

Software tool to identify cancer driver genes based on linear annotations of biological regions such as protein domains.Uses information on three-dimensional structures of mutated proteins to identify specific structural features. Then algorithm analyzes whether these features are enriched in cancer somatic mutations and are candidate driver genes.

Proper citation: e-Driver (RRID:SCR_002674) Copy   

•   Source: SciCrunch Registry

http://www.bcgsc.ca/project/pleiades-promoter-project

Project to generate human DNA promoters of less than 4 kb (MiniPromoters) to drive gene expression in defined brain regions of therapeutic interest for diseases such as Alzheimer, Parkinson, Huntington, Amyotrophic Lateral Sclerosis, Multiple Sclerosis, Spinocerebellar Ataxia, Depression, Autism, and Cancer. Project develops and shares tools like human MiniPromoters that drive region- and cell-specific gene expression in the mouse brain, expression constructs, mouse embryonic stem cell lines, and knock-in mice all of which carry brain-specific MiniPromoters. Project is daughter of Genome Canada Project, Atlas of Gene Expression in Mouse Development, within which mouse brain gene expression data have already been gathered. Project team has collaborated with International BioPharma Solutions Ltd., management and communications consulting company specializing in product development and commercialization advice. Project will explore challenging interface between science and journalism with focus on genomics and gene therapy.

Proper citation: Pleiades Promoter Project: Genomic Resources Advancing Therapies for Brain Disorders (RRID:SCR_003282) Copy   

•   Source: SciCrunch Registry

http://ki.se/en/research/ki-biobank

KI Biobank is an accredited core facility offering sample collection services. KI Biobank is located at the Department of Medical Epidemiology and Biostatistics. KI Biobank offer infrastructure for pre analytical sample handling and provide researchers guidance on how samples should be taken and labeled. The processes comprise registration, handling, storage and distribution of samples. KI Biobank also offers DNA-extraction from blood and saliva. In order to insure complete traceability on samples and belonging information all processes are controlled by a Laboratory Information Management System (LIMS). For every new study a contract is established describing the study and the disposition rights. We also help in writing Biobank agreements including multicenteravtal and Material Transfer Agreement. KI Biobank is, according to the Biobank law, responsible for all sample collections handled within the core facility and those that are stored on the departments on KI campus. Clinical sample collections are handled by the Biobank units at the respective hospitals within the Stockholm County Council. Besides the samples that are stored centrally at KI Biobank, KI Biobank is also the administrative biobank for research sample collections at Karolinska Institutet that are stored and administrated at the departments. All research sample collections must be reported to KI Biobank. The following types of sample collections are registered in the biobank; sample collections taken within the regular health care that has been transferred to Karolinska Institutet with an agreement of transfer, samples taken from healthy individuals or other persons out of the regular health care and samples that have been taken abroad.

Proper citation: Karolisnka Biobank (RRID:SCR_004355) Copy   

•   Source: SciCrunch Registry