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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://harvester.fzk.de/harvester/
Harvester is a Web-based tool that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. It is a meta search engine for gene and protein information. It searches 16 major databases and prediction servers and combines the results on pregenerated HTML pages. In this way Harvester can provide comprehensive gene-protein information from different servers in a convenient and fast manner. As full text meta search engine, similar to Google trade mark, Harvester allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. Sponsors: This work has been supported by the BMBF with grants 01GR0101 and 01KW0013.
Proper citation: Bioinformatic Harvester IV (beta) at Karlsruhe Institute of Technology (RRID:SCR_008017) Copy
https://www.amazon.com/How-Brain-Works-Mark-Dubin/dp/0632044411
THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Is the Brain (Like) a Computer is an e-book written by Prof. Mark Dubin. It consists of the following: Introduction. Why do we consider the relationship of brains and computers and what does this have to do with consciousness? What's a Brain Made Of? A thought experiment. Test Drive a Turing Machine. A theoretical approach. Interim Summary. Many of the main pages have links to additional information. When you click on one of those links a NEW page will open ON TOP of the page you are clicking from. This convention is adopted so that you can look at the additional information and then easily return to the main page you got there from.
Proper citation: Is the Brain (Like) a Computer (RRID:SCR_008809) Copy
http://rarediseases.info.nih.gov/GARD/Default.aspx
Genetic and Rare Diseases Information Center (GARD) is a collaborative effort of two agencies of the National Institutes of Health, The Office of Rare Diseases Research (ORDR) and the National Human Genome Research Institute (NHGRI) to help people find useful information about genetic conditions and rare diseases. GARD provides timely access to experienced information specialists who can furnish current and accurate information about genetic and rare diseases. So far, GARD has responded to 27,635 inquiries on about 7,147 rare and genetic diseases. Requests come not only from patients and their families, but also from physicians, nurses and other health-care professionals. GARD also has proved useful to genetic counselors, occupational and physical therapists, social workers, and teachers who work with people with a genetic or rare disease. Even scientists who are studying a genetic or rare disease and who need information for their research have contacted GARD, as have people who are taking part in a clinical study. Community leaders looking to help people find resources for those with genetic or rare diseases and advocacy groups who want up-to-date disease information for their members have contacted GARD. And members of the media who are writing stories about genetic or rare diseases have found the information GARD has on hand useful, accurate and complete. GARD has information on: :- What is known about a genetic or rare disease. :- What research studies are being conducted. :- What genetic testing and genetic services are available. :- Which advocacy groups to contact for a specific genetic or rare disease. :- What has been written recently about a genetic or rare disease in medical journals. GARD information specialists get their information from: :- NIH resources. :- Medical textbooks. :- Journal articles. :- Web sites. :- Advocacy groups, and their literature and services. :- Medical databases.
Proper citation: Genetic and Rare Diseases Information Center (RRID:SCR_008695) Copy
http://www.roslin.ed.ac.uk/alan-archibald/porcine-genome-sequencing-project/
Map of identifyied genes controlling traits of economic and welfare significance in the pig. The project objectives were to produce a genetic map with markers spaced at approximately 20 centiMorgan intervals over at least 90% of the pig genome; to produce a physical map with at least one distal and one proximal landmark locus mapped on each porcine chromosome arm and also genetically mapped; to develop a flow karyotype for the pig based on FACS sorted chromosomes; to develop PCR based techniques to enable rapid genotyping for polymorphic markers; to evaluate synteny conservation between pigs, man, mice and cattle; to develop and evaluate the statistical techniques required to analyze data from QTL mapping experiments and to plan and initiate the mapping of QTLs in the pig; to map loci affecting traits of economic and biological significance in the pig; and to develop the molecular tools to allow the future identification and cloning of mapped loci. Animal breeders currently assume that economically important traits such as growth, carcass composition and reproductive performance are controlled by an infinite number of genes each of infinitessimal effect. Although this model is known to be unrealistic, it has successfully underpinned the genetic improvement of livestock, including pigs, over recent decades. A map of the pig genome would allow the development of more realistic models of the genetic control of economic traits and the ultimately the identification of the major trait genes. This would allow the development of more efficient marker assisted selection which may be of particular value for traits such as disease resistance and meat quality.
Proper citation: Pig Genome Mapping (RRID:SCR_012884) Copy
Site for collection and distribution of clinical data related to genetic analysis of drug abuse phenotypes. Anonymous data on family structure, age, sex, clinical status, and diagnosis, DNA samples and cell line cultures, and data derived from genotyping and other genetic analyses of these clinical data and biomaterials, are distributed to qualified researchers studying genetics of mental disorders and other complex diseases at recognized biomedical research facilities. Phenotypic and Genetic data will be made available to general public on release dates through distribution mechanisms specified on website.
Proper citation: National Institute on Drug Abuse Center for Genetic Studies (RRID:SCR_013061) Copy
http://ccg.vital-it.ch/snp2tfbs
Collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. Used to investigate the molecular mechanisms underlying regulatory variation in the human genome. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs.
Proper citation: SNP2TFBS (RRID:SCR_016885) Copy
Community based, biologist friendly web platform for creating and meta analyzing annotated gene expression data compendia., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: OMiCC (RRID:SCR_016604) Copy
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
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
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
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
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
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
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
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
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
http://cerebrovascularportal.org
Portal enables browsing, searching, and analysis of human genetic information linked to cerebrovascular disease and related traits, while protecting the integrity and confidentiality of the underlying data.
Proper citation: Cerebrovascular Disease Knowledge Portal (RRID:SCR_015628) Copy
http://circadb.hogeneschlab.org/
Database of mammalian circadian gene expression profiles. Works with link outs to Wikipedia, HomoloGene, Refseq, etc.. Open source database of circadian transcriptional profiles from time course expression experiments from mice and humans.
Proper citation: CircaDB (RRID:SCR_018078) Copy
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
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
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