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https://hirnetwork.org/consortium/chib

Consortium that is an independent research initiative of the Human Research Information Network (HIRN). It is combining advances in beta cell biology and cell biology with tissue engineering technologies to develop microdevices that support functional human islets.

Proper citation: HIRN Consortium on Human Islet Biomimetics (RRID:SCR_016199) 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://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://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://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

http://aws.amazon.com/1000genomes/

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

Proper citation: 1000 Genomes Project and AWS (RRID:SCR_008801) Copy   

•   Source: SciCrunch Registry

http://www.cs.tau.ac.il/~shlomito/tissue-net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Network visualizations in which the expression and predicted flux data are projected over the global human network. These network visualizations are accessible through the supplemental website using the publicly available Cytoscape software (Cline, Smoot et al. 2007). Since many high degree nodes exist in the network, special layouts are required to produce network visualizations that are readily interpretable. To this end we produced network visualizations in which hub nodes are repeated multiple times and hence layouts with a small number of edge crossings can be generated. Contains entries for brain compartments and brain pathways.

Proper citation: Network-based Prediction of Human Tissue-specific Metabolism (RRID:SCR_007392) Copy   

•   Source: SciCrunch Registry

https://confluence.crbs.ucsd.edu/display/NIF/StemCellInfo

Data tables providing an overview of information about stem cells that have been derived from mice and humans. The tables summarize published research that characterizes cells that are capable of developing into cells of multiple germ layers (i.e., multipotent or pluripotent) or that can generate the differentiated cell types of another tissue (i.e., plasticity) such as a bone marrow cell becoming a neuronal cell. The tables do not include information about cells considered progenitor or precursor cells or those that can proliferate without the demonstrated ability to generate cell types of other tissues. The tables list the tissue from which the cells were derived, the types of cells that developed, the conditions under which differentiation occurred, the methods by which the cells were characterized, and the primary references for the information.

Proper citation: National Institutes of Health Stem Cell Tables (RRID:SCR_008359) Copy   

•   Source: SciCrunch Registry

http://harvard.eagle-i.net/i/0000012a-2518-fb6c-5617-794280000000

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 27, 2023. Core provides services: RT PCR service, Gene expression profiling service, Proteomics analysis service, Bioinformatics and Systems Biology analyses, Next Generation Sequencing Service, Affymetrix Human and Mouse Gene 2.0 ST Arrays and 2.1 ST Arrayplates. Core proteomics facility for the Dana-Farber/Harvard Cancer Center. Workflows and algorithms for analysis of next-generation sequencing data including RNA-Seq, ChIP-Seq, Epigenetics-Seq and DNA seq, Comprehensive workflow for analysis of Microbiome sequencing data, Integrated systems biology analysis of transcriptome, miRNA, epigenome, metabolomics and proteomics data. Pipelines: MALDI Tissue imaging and targeted quantitative proteomics.

Proper citation: Beth Israel Deaconess Medical Center Genomics Proteomics Bioinformatics and Systems Biology Center (RRID:SCR_009668) Copy   

•   Source: SciCrunch Registry

https://www.msu.edu/~brains/index.html

The Brain Biodiversity Bank refers to the repository of images of and information about brain specimens contained in the collections associated with the National Museum of Health and Medicine at the Armed Forces Institute of Pathology in Washington, DC. Atlases and brain sections are available for a variety of mammals, and we are also developing a series of labeled atlases of stained sections for educators, students, and researchers. These collections include, besides the Michigan State University Collection, the Welker Collection from the University of Wisconsin, the Yakovlev-Haleem Collection from Harvard University, the Meyer Collection from the Johns Hopkins University, and the Huber-Crosby and Crosby-Lauer Collections from the University of Michigan. What we are doing currently at Michigan State is a series of demonstration projects for publicizing the contents of the collections and ways in which they can be used. For example, the images from the collection can be used for comparative brain study. We have prepared databases of the contents of the collections for presentation and use on this site, as well as for downloading by users in several formats. We are also developing a series of labeled atlases of stained sections for educators, students, and researchers. This internet site is associated with the Comparative Mammalian Brain Collections site. All of the images are in JPEG or GIF format.

Proper citation: Michigan State University Brain Biodiversity Bank (RRID:SCR_003289) Copy   

•   Source: SciCrunch Registry

http://en.wikibooks.org/wiki/Human_Physiology

Human Physiology is a featured book on Wikibooks because it contains substantial content, it is well-formatted, and the Wikibooks community has decided to feature it on the main page or in other places. Please continue to improve it and thanks for the great work so far! A printable and PDF version are available. You can edit its advertisement template. Contents: 1. Homeostasis 2. Cell Physiology 3. Integumentary System 4. The Nervous System 5. Senses 6. The Muscular System 7. Blood Physiology 8. The Cardiovascular System 9. The Immune System 10. The Urinary System 11. The Respiratory System 12. The Gastrointestinal System 13. Nutrition 14. The Endocrine System 15. The Male Reproductive System 16. The Female Reproductive System 17. Pregnancy and Birth 18. Genetics and Inheritance 19. Development: Birth through Death 20. Appendix 1: Answers to Review Questions 21. Authors 22. Further Reading

Proper citation: Human Physiology (RRID:SCR_003525) Copy   

•   Source: SciCrunch Registry

http://national_databank.mclean.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented September 6, 2016. A publicly accessible data repository to provide neuroscience investigators with secure access to cohort collections. The Databank collects and disseminates gene expression data from microarray experiments on brain tissue samples, along with diagnostic results from postmortem studies of neurological and psychiatric disorders. All of the data that is derived from studies of the HBTRC collection is being incorporated into the National Brain Databank. This data is available to the general public, although strict precautions are undertaken to maintain the confidentiality of the brain donors and their family members. The system is designed to incorporate MIAME and MAGE-ML based microarray data sharing standards. Data from various types of studies conducted on brain tissue in the HBTRC collection will be available from studies using different technologies, such as gene expression profiling, quantitative RT-PCR, situ hybridization, and immunocytochemistry and will have the potential for providing powerful insights into the subregional and cellular distribution of genes and/or proteins in different brain regions and eventually in specific subregions and cellular subtypes.

Proper citation: National Brain Databank (RRID:SCR_003606) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/educational-resources/index.shtml

A portal to educational resources.

Proper citation: NIMH Educational Resources (RRID:SCR_004045) Copy   

•   Source: SciCrunch Registry

http://www.abc.net.au/rn/allinthemind/default.htm

Radio National''s weekly foray into all things mental a program (podcast) about the mind, brain and behavior, hosted by Lynne Malcolm (previously by Natasha Mitchell). From dreaming to depression, addiction to artificial intelligence, consciousness to coma, psychoanalysis to psychopathy, free will to forgetting ��All in the Mind��explores the human condition through the mind''s eye. All in the Mind brings together unexpected voices, themes and ideas and engages with both leading thinkers and personal stories. Psychology and human behavior are only part of the equation. The program''s scope is considerably broader and explores themes in science, religion, health, philosophy, education, history and pop culture, with the mind as the key focus.

Proper citation: All In The Mind (RRID:SCR_004240) Copy   

•   Source: SciCrunch Registry

http://openconnectomeproject.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. Connectomes repository to facilitate the analysis of connectome data by providing a unified front for connectomics research. With a focus on Electron Microscopy (EM) data and various forms of Magnetic Resonance (MR) data, the project aims to make state-of-the-art neuroscience open to anybody with computer access, regardless of knowledge, training, background, etc. Open science means open to view, play, analyze, contribute, anything. Access to high resolution neuroanatomical images that can be used to explore connectomes and programmatic access to this data for human and machine annotation are provided, with a long-term goal of reconstructing the neural circuits comprising an entire brain. This project aims to bring the most state-of-the-art scientific data in the world to the hands of anybody with internet access, so collectively, we can begin to unravel connectomes. Services: * Data Hosting - Their Bruster (brain-cluster) is large enough to store nearly any modern connectome data set. Contact them to make your data available to others for any purpose, including gaining access to state-of-the-art analysis and machine vision pipelines. * Web Viewing - Collaborative Annotation Toolkit for Massive Amounts of Image Data (CATMAID) is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by Google Maps, enhanced to allow the exploration of 3D image data. View the fork of the code or go directly to view the data. * Volume Cutout Service - RESTful API that enables you to select any arbitrary volume of the 3d database (3ddb), and receive a link to download an HDF5 file (for matlab, C, C++, or C#) or a NumPy pickle (for python). Use some other programming language? Just let them know. * Annotation Database - Spatially co-registered volumetric annotations are compactly stored for efficient queries such as: find all synapses, or which neurons synapse onto this one. Create your own annotations or browse others. *Sample Downloads - In addition to being able to select arbitrary downloads from the datasets, they have also collected a few choice volumes of interest. * Volume Viewer - A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels. The code and program can be downloaded. * Machine Vision Pipeline - They are building a machine vision pipeline that pulls volumes from the 3ddb and outputs neural circuits. - a work in progress. As soon as we have a stable version, it will be released. * Mr. Cap - The Magnetic Resonance Connectome Automated Pipeline (Mr. Cap) is built on JIST/MIPAV for high-throughput estimation of connectomes from diffusion and structural imaging data. * Graph Invariant Computation - Upload your graphs or streamlines, and download some invariants. * iPad App - WholeSlide is an iPad app that accesses utilizes our open data and API to serve images on the go.

Proper citation: Open Connectome Project (RRID:SCR_004232) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/proj/ppi/

The MIPS mammalian protein-protein interaction database (MPPI) is a new resource of high-quality experimental protein interaction data in mammals. The content is based on published experimental evidence that has been processed by human expert curators. It is a collection of manually curated high-quality PPI data collected from the scientific literature by expert curators. We took great care to include only data from individually performed experiments since they usually provide the most reliable evidence for physical interactions. To suit different users needs we provide a variety of interfaces to search the database: -Expert interface Simple but powerful boolean query language. -PPI search form Easy to use PPI search -Protein search Just find proteins of interest in the database Sponsors: This work is funded by a grant from the German Federal Ministry of Education and Research.

Proper citation: MIPS Mammalian Protein-Protein Interaction Database (RRID:SCR_008207) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/asd/altsplice/index.html

AltSplice is a computer generated high quality data set of human transcript-confirmed splice patterns, alternative splice events, and the associated annotations. This data is being integrated with other data that is generated by other members of the ASD consortium. The ASD project will provide the following in its three year duration: -human curated database of alternative spliced genes and their properties -a computer generated database of alternatively spliced genes and their properties -the integration of the above and newly found knowledge in a user-friendly interface and research workbench for both bioinformaticists and biologists -DNA chips that are based on the data in the above databases -the DNA chips will be used to test against predisposition for and diagnoses of human diseases ASD aims to analyse this mechanism on a genome-wide scale by creating a database that contains all alternatively spliced exons from human, and other model species. Disease causing mutations seem to induce aberrations in the process of splicing and its regulation. The ASD consortium will develop a DNA microarray (chip) that contains cDNAs of all the splicing regulatory proteins and their isoforms, as well as a chip that contains a number of disease relevant genes. We will concentrate on three models of disease (breast cancer, FTDP-17, male infertility) in which a connection between mis-splicing and a pathological state has been observed. Finally, these chips will be developed as demonstrative kits to detect predisposition for and diagnosis of such diseases. Categories: Nucleotide Sequences: Gene Structure, Introns and Exons, & Splice Sites Databases

Proper citation: AltSplice Database of Alternative Spliced Events (RRID:SCR_008162) Copy   

•   Source: SciCrunch Registry

http://agricola.nal.usda.gov/

A database, catalog and index to the collections of the National Agricultural Library, as well as a primary public source for world-wide access to agricultural information. This database resource covers materials in all formats and periods, including printed works from as far back as the 15th century. AGRICOLA is a bibliographic database of citations to the agricultural literature created by the National Agricultural Library and its cooperators. The records describe publications and resources encompassing all aspects of agriculture and allied disciplines, including animal and veterinary sciences, entomology, plant sciences, forestry, aquaculture and fisheries, farming and farming systems, agricultural economics, extension and education, food and human nutrition, and earth and environmental sciences. Although the NAL Catalog (AGRICOLA) does not contain the text of the materials it cites, thousands of its records are linked to full-text documents online, with new links added daily. The NAL Catalog (AGRICOLA) is organized into two bibliographic data sets: *The NAL Online Public Access Catalog (AGRICOLA NAL) contains citations to books, audiovisuals, serials, and other materials, most of which are in the Library''s collection. (The Catalog does contain some records for items not held at NAL.) *The Article Citation Database (AGRICOLA IND) includes citations, many with abstracts, to journal articles (see Journals Indexed in AGRICOLA), book chapters, reports, and reprints, selected primarily from the materials found in the NAL Catalog.

Proper citation: AGRICOLA (RRID:SCR_008158) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/services/genomes/uwe25/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. This is the official database of the environmental chlamydia genome project. This resource provides access to finished sequence for Parachlamydia-related symbiont UWE25 and to a wide range of manual annotations, automatical analyses and derived datasets. Functional classification and description has been manually annotated according to the Annotation guidelines. Chlamydiae are the major cause of preventable blindness and sexually transmitted disease. Genome analysis of a chlamydia-related symbiont of free-living amoebae revealed that it is twice as large as any of the pathogenic chlamydiae and had few signs of recent lateral gene acquisition. We showed that about 700 million years ago the last common ancestor of pathogenic and symbiotic chlamydiae was already adapted to intracellular survival in early eukaryotes and contained many virulence factors found in modern pathogenic chlamydiae, including a type III secretion system. Ancient chlamydiae appear to be the originators of mechanisms for the exploitation of eukaryotic cells. Environmental chlamydiae have recently been recognized as obligate endosymbionts of free-living amoebae and have been implicated as potential human pathogens. Environmental chlamydiae form a deep branching evolutionary lineage within the medically important order Chlamydiales. Despite their high diversity and ubiquitous distribution in clinical and environmental samples only limited information about genetics and ecology of these microorganisms is available. The Parachlamydia-related Acanthamoeba symbiont UWE25 was therefore selected as representative environmental chlamydia strain for whole genome sequencing. Comparative genome analysis was performed using PEDANT and simap. Sponsors: The environmental chlamydia genome project was funded by the bmb+f (German Federal Ministry of Education and Research) and is part of the Competence Network PathoGenoMiK.

Proper citation: Protochlamydia amoebophila UWE25 (RRID:SCR_008222) Copy   

•   Source: SciCrunch Registry