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http://www.muschealth.com/multimedia/Podcasts/index.aspx?type=main

The MUSChealth.com Podcast Library, featuring podcasts on a variety of topics related to your health and our services here at MUSC. These medical podcasts are hosted by MUSC faculty, physicians and special guests and are produced and directed by Linda Austin, M.D. Current topics include: * Academics and Education * Aging, Geriatrics and Caregiving * Alcohol and Drug Dependency * Allergies and Asthma * Ashley River Tower * Bones, Joints, Muscles and Spine * Cancer * Children''s Health * Cosmetic Surgery * Dental * Dermatology/Skin Problems * Diabetes, Endocrinology and Metabolism * Digestive Health * ENT: Ear, Nose and Throat * Executive Health * Eye Health * General Health and Wellness * Heart and Vascular Health * Hospice * Kohl''s Take a Minute for Kids * Lungs and Breathing * Men''s Health * Mental Health * MUSC News and Events * Neurological Health * Organ Transplant * Osteoporosis * Pregnancy - Week by Week * Pregnancy and Childbirth * Radiology * Research and Clinical Trials * SC Health, Leadership and Policy * Sports Medicine * Stroke * Urology * Weight Loss Surgery Follow-up * Weight Management * Women''s Health

Proper citation: MUSC Health Podcast Library (RRID:SCR_008827) Copy   

•   Source: SciCrunch Registry

http://bcb.cs.tufts.edu/dflat/

We are an interdisciplinary team dedicated to annotating gene function related to human fetal development. We are contributing new functional annotation to the Gene Ontology, curating and mining gene sets suitable for the interpretation of developmental genomic data, and creating the computational tools needed to apply genomics for better understanding the molecular mechanisms of human development. Our GO annotation is in the process of being incorporated into the GOA public release. The GONE (Gene Ontology Non-Eligible) database is where we store annotations relevant to our research but that don''t quite meet GOA''s standards. Usually an annotation falls into this category because either the gene/protein described is a family of genes/proteins rather than a specific one, there is no UniProt ID to identify the gene/protein in the system, a GO term does not yet exist to describe the particular function, process, or location of the gene/protein, the species is not clearly identifiable in the paper, or the evidence is not as reliable (GO evidence codes TAS and NAS). As individual annotations these are more suspect than current GO annotation. However, for functional analysis of expression data, these gene sets can be valuable even with a certain amount of noise. We also include here a link to the supplementary data from our forthcoming PSB 2011 paper on gene set mining.

Proper citation: DFLAT (RRID:SCR_010738) Copy   

•   Source: SciCrunch Registry

http://brainandsociety.org/the-brain-observatory

Formerly a topical portal studying the brain which collected and imaged 1000 human brains, the Brain Observatory has partnered with the Institute for Brain and Society to build virtual laboratories that will feed directly into the database of images and knowledge created in the context of the Human Brain Library. The Brain Observatory will also host exhibits, conferences, and events aimed at promoting a heightened awareness of brain research and how its results can benefit personal brain fitness and mental health.

Proper citation: Brain Observatory (RRID:SCR_010641) Copy   

•   Source: SciCrunch Registry

http://bio-bwa.sourceforge.net/

Software for aligning sequencing reads against large reference genome. Consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. First for sequence reads up to 100bp, and other two for longer sequences ranged from 70bp to 1Mbp.

Proper citation: BWA (RRID:SCR_010910) Copy   

•   Source: SciCrunch Registry

http://www.viprbrc.org/brc/home.do?decorator=vipr

Provides searchable public repository of genomic, proteomic and other research data for different strains of pathogenic viruses along with suite of tools for analyzing data. Data can be shared, aggregated, analyzed using ViPR tools, and downloaded for local analysis. ViPR is an NIAID-funded resource that support the research of viral pathogens in the NIAID Category A-C Priority Pathogen lists and those causing (re)emerging infectious diseases. It provides a dedicated gateway to SARS-CoV-2 data that integrates data from external sources (GenBank, UniProt, Immune Epitope Database, Protein Data Bank), direct submissions, analysis pipelines and expert curation, and provides a suite of bioinformatics analysis and visualization tools for virology research.

Proper citation: Virus Pathogen Resource (ViPR) (RRID:SCR_012983) Copy   

•   Source: SciCrunch Registry

https://www.nia.nih.gov/alzheimers

Portal for Alzheimer's disease that compiles, archives and disseminates information about current treatments, diagnostic tools and ongoing research for health professions, people with AD, their families and the public. The Center provides informational services and referrals for AD symptoms, diagnosis and treatment for patients; clinical trial information and literature searches for researchers; training materials and guidelines for caregivers; and Spanish language resources.

Proper citation: Alzheimer's Disease Education and Referral Center (RRID:SCR_012787) Copy   

•   Source: SciCrunch Registry

http://www.kegg.jp/

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

Proper citation: KEGG (RRID:SCR_012773) Copy   

•   Source: SciCrunch Registry

https://omictools.com/l2l-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 26, 2019.

Database of published microarray gene expression data, and a software tool for comparing that published data to a user''''s own microarray results. It is very simple to use - all you need is a web browser and a list of the probes that went up or down in your experiment. If you find L2L useful please consider contributing your published data to the L2L Microarray Database in the form of list files. L2L finds true biological patterns in gene expression data by systematically comparing your own list of genes to lists of genes that have been experimentally determined to be co-expressed in response to a particular stimulus - in other words, published lists of microarray results. The patterns it finds can point to the underlying disease process or affected molecular function that actually generated the observed changed in gene expression. Its insights are far more systematic than critical gene analyses, and more biologically relevant than pure Gene Ontology-based analyses. The publications included in the L2L MDB initially reflected topics thought to be related to Cockayne syndrome: aging, cancer, and DNA damage. Since then, the scope of the publications included has expanded considerably, to include chromatin structure, immune and inflammatory mediators, the hypoxic response, adipogenesis, growth factors, hormones, cell cycle regulators, and others. Despite the parochial origins of the database, the wide range of topics covered will make L2L of general interest to any investigator using microarrays to study human biology. In addition to the L2L Microarray Database, L2L contains three sets of lists derived from Gene Ontology categories: Biological Process, Cellular Component, and Molecular Function. As with the L2L MDB, each GO sub-category is represented by a text file that contains annotation information and a list of the HUGO symbols of the genes assigned to that sub-category or any of its descendants. You don''''t need to download L2L to use it to analyze your microarray data. There is an easy-to-use web-based analysis tool, and you have the option of downloading your results so you can view them at any time on your own computer, using any web browser. However, if you prefer, the entire L2L project, and all of its components, can be downloaded from the download page. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: L2L Microarray Analysis Tool (RRID:SCR_013440) Copy   

•   Source: SciCrunch Registry

http://www.brainsimagebank.ac.uk

A searchable collection of anonymised images and associated clinical data. It includes normal individuals at all ages (from prenatal to old age). The image bank contains integrated data sets already collected as part of research studies which include control subjects. New data is added as they become available.

Proper citation: BRAINS Imagebank (RRID:SCR_014576) Copy   

•   Source: SciCrunch Registry

https://www.rebuildingakidney.org

A consortium of research projects working to optimize approaches for the isolation, expansion, and differentiation of appropriate kidney cell types and their integration into complex structures that replicate human kidney function. Their goal is to coordinate and integrate research to support the development and implementation of strategies such as de novo repair of nephrons, the re-generation of nephrons, and the in vitro engineering of a biological kidney to enhance renal repair and promote the generation of new nephrons in the postnatal organ. Investigators may apply for funding of a kidney-related project through the RBK Partnership Project. Funded projects would join the consortium.

Proper citation: ReBuilding a Kidney (RRID:SCR_014442) Copy   

•   Source: SciCrunch Registry

https://hirnetwork.org/project/hirncc

Consortium that provides infrastructure to promote communication and collaboration among current and future HIRN participants, facilitating scientific advances and the sharing of data, tools, and reagents among HIRN members and the research community at large.

Proper citation: HIRN Coordinating Center (RRID:SCR_016395) Copy   

•   Source: SciCrunch Registry

https://github.com/MRCIEU/PhenoSpD

Software toolkit for phenotypic correlation estimation and multiple testing correction (Spectral Decomposition, SpD) for human phenome using genome-wide association study (GWAS) summary statistics. It is a command line R based tool.

Proper citation: PhenoSpD (RRID:SCR_016359) Copy   

•   Source: SciCrunch Registry

https://www.lungmap.net/

Portal for lung histochemistry data. For structural and molecular data regarding normal perinatal and postnatal lung development in the mouse and human. For public sharing of data sets, establishing a repository of young human lung tissues obtained through organ donor organizations, and developing a comprehensive lung ontology .Contains lung images and transcriptomic, proteomic, and lipidomic human and mouse data and provides scientific information to stimulate interest in research careers. Used to serve as a research resource and public education tool.

Proper citation: LungMap (RRID:SCR_016347) Copy   

•   Source: SciCrunch Registry

https://www.humancellatlas.org

Software tool as a catalog of comprehensive reference of human cells based on their stable properties, transient features, locations and abundances. Map to show the relationships among its elements. Open data international collaborative project involving diverse scientific communities to provide a framework for understanding cellular dysregulation in human disease.

Proper citation: Human Cell Atlas (RRID:SCR_016530) Copy   

•   Source: SciCrunch Registry

http://www.broadcvdi.org/

Platform for analysis of the genetics of cardiovascular disease.Used for searching and analysis of human genetic information linked to myocardial infarction, atrial fibrillation and related traits while protecting the integrity and confidentiality of the data.

Proper citation: Cardiovascular Disease Knowledge Portal (RRID:SCR_016536) Copy   

•   Source: SciCrunch Registry

https://commonfund.nih.gov/hubmap

Project to facilitate research on single cells within tissues by supporting data generation and technology development to explore the relationship between cellular organization and function, as well as variability in normal tissue organization at the level of individual cells. Framework for functional mapping the human body with cellular resolution.Designed to support diverse spatial and non-spatial omics and imaging data types and to integrate with a wide range of analysis workflows.

Proper citation: The Human BioMolecular Atlas Program (RRID:SCR_016922) Copy   

•   Source: SciCrunch Registry

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

https://github.com/zuoxinian/CCS

Software tool for multimodal human brain imaging data analysis. Computational pipeline for discovery science of human brain connectomes at macroscale with multimodal magnetic resonance imaging technologies.

Proper citation: Connectome Computation System (RRID:SCR_017342) Copy   

•   Source: SciCrunch Registry

https://anvilproject.org/

Portal to facilitate integration and computing on and across large datasets generated by NHGRI programs, as well as initiatives funded by National Institutes of Health or by other agencies that support human genomics research. Resource for genomic scientific community, that leverages cloud based infrastructure for democratizing genomic data access, sharing and computing across large genomic, and genomic related data sets. Component of federated data ecosystem, and is expected to collaborate and integrate with other genomic data resources through adoption of FAIR (Findable, Accessible, Interoperable, Reusable) principles, as their specifications emerge from scientific community. Will provide collaborative environment, where datasets and analysis workflows can be shared within consortium and be prepared for public release to broad scientific community through AnVIL user interfaces.

Proper citation: Analysis, Visualization, and Informatics Lab-space (AnVIL) (RRID:SCR_017469) Copy   

•   Source: SciCrunch Registry

https://portal.brain-map.org/atlases-and-data/rnaseq

Software tool to visualize and analyze transcriptomics data and transcriptomic cell types for mouse and human, all directly in web browser. To explore gene expression heatmap across cell types in datasets, search for genes of interest, explore tSNE visualization, colored by cell types or expression of genes of interest, visualize dataset’s sampling strategy to see how cells and nuclei were sampled across brain areas, cortical layer, and other dimensions, find cell type of interest in one visualization and see its characteristics in different visualization.Used for Allen Brain Map Cell Types Database to Browse Data: Human - Multiple Cortical Areas, and Mouse - Cortex and Hippocampus.

Proper citation: Transcriptomics Explorer (RRID:SCR_017567) Copy   

•   Source: SciCrunch Registry