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ITools Resourceome
iTools{{cite journal, vauthors=Dinov ID, Rubin D, Lorensen W, Dugan J, Ma J, Murphy S, Kirschner B, Bug W, Sherman M, Floratos A, Kennedy D, Jagadish HV, Schmidt J, Athey B, Califano A, Musen M, Altman R, Kikinis R, Kohane I, Delp S, Parker DS, Toga AW , title=iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources , journal=PLOS ONE , volume=3, issue=5, pages= e2265, doi=10.1371/journal.pone.0002265 , year=2008 , pmid=18509477 , pmc=2386255, bibcode=2008PLoSO...3.2265D , doi-access=free is a distributed infrastructure for managing, discovery, comparison and integration of computational biology resources. iTools employs Biositemap technology to retrieve and service meta-data about diverse bioinformatics data services, tools, and web-services. iTools is developed by the National Centers for Biomedical Computing as part of thNIH Road Map Initiative See also * Biositemaps References External links Interactive iTools Serve ...
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Biositemap ITools NCBC
A Biositemap is a way for a Medical research, biomedical research institution of organisation to show how biological information is distributed throughout their Information Technology systems and networks. This information may be shared with other organisations and researchers. The Biositemap enables web browsers, Web search engine#How web search engines work, crawlers and Web Bot, robots to easily access and process the information to use in other systems, media and computational formats. Biositemaps protocols provide clues for the Bioinformatic Harvester, Biositemap web harvesters, allowing them to find resources and content across the whole interlink of the Biositemap system. This means that human or machine users can access any relevant information on any topic across all organisations throughout the Biositemap system and bring it to their own systems for assimilation or analysis. File framework The information is normally stored in a biositemap.rdf or biositemap.xml file which ...
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Computational Biology
Computational biology refers to the use of techniques in computer science, data analysis, mathematical modeling and Computer simulation, computational simulations to understand biological systems and relationships. An intersection of computer science, biology, and data science, the field also has foundations in applied mathematics, molecular biology, cell biology, chemistry, and genetics. History Bioinformatics, the analysis of informatics processes in biological systems, began in the early 1970s. At this time, research in artificial intelligence was using network models of the human brain in order to generate new algorithms. This use of biological data pushed biological researchers to use computers to evaluate and compare large data sets in their own field. By 1982, researchers shared information via Punched card, punch cards. The amount of data grew exponentially by the end of the 1980s, requiring new computational methods for quickly interpreting relevant information. Per ...
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Biositemap
A Biositemap is a way for a biomedical research institution of organisation to show how biological information is distributed throughout their Information Technology systems and networks. This information may be shared with other organisations and researchers. The Biositemap enables web browsers, crawlers and robots to easily access and process the information to use in other systems, media and computational formats. Biositemaps protocols provide clues for the Biositemap web harvesters, allowing them to find resources and content across the whole interlink of the Biositemap system. This means that human or machine users can access any relevant information on any topic across all organisations throughout the Biositemap system and bring it to their own systems for assimilation or analysis. File framework The information is normally stored in a biositemap.rdf or biositemap.xml file which contains lists of information about the data, software, tools material and services provided or ...
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National Centers For Biomedical Computing
The National Centers for Biomedical Computing (NCBCs) are part of the U.S. National Institutes of Health plan to develop and implement the core of a universal computing infrastructure that is urgently needed to speed progress in biomedical research. Their mission is to create innovative software programs and other tools that will enable the biomedical community to integrate, analyze, model, simulate, and share data on human health and disease. Recognizing the potential benefits to human health that can be realized from applying and advancing the field of biomedical computing, the Biomedical Information Science and Technology Initiative (BISTI) was launched at the NIH in April 2000. This initiative is aimed at making optimal use of computer science and technology to address problems in biology and medicine. The full text of the original BISTI Report is available. As of April 2016, the web site for the National Centers for Biomedical Computing (http://www.ncbcs.org) is no longer ma ...
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Biositemaps
A Biositemap is a way for a biomedical research institution of organisation to show how biological information is distributed throughout their Information Technology systems and networks. This information may be shared with other organisations and researchers. The Biositemap enables web browsers, crawlers and robots to easily access and process the information to use in other systems, media and computational formats. Biositemaps protocols provide clues for the Biositemap web harvesters, allowing them to find resources and content across the whole interlink of the Biositemap system. This means that human or machine users can access any relevant information on any topic across all organisations throughout the Biositemap system and bring it to their own systems for assimilation or analysis. File framework The information is normally stored in a biositemap.rdf or biositemap.xml file which contains lists of information about the data, software, tools material and services provided or ...
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Knowledge Representation
Knowledge representation (KR) aims to model information in a structured manner to formally represent it as knowledge in knowledge-based systems whereas knowledge representation and reasoning (KRR, KR&R, or KR²) also aims to understand, reason, and interpret knowledge. KRR is widely used in the field of artificial intelligence (AI) with the goal to represent information about the world in a form that a computer system can use to solve complex tasks, such as diagnosing a medical condition or having a natural-language dialog. KR incorporates findings from psychology about how humans solve problems and represent knowledge, in order to design formalisms that make complex systems easier to design and build. KRR also incorporates findings from logic to automate various kinds of ''reasoning''. Traditional KRR focuses more on the declarative representation of knowledge. Related knowledge representation formalisms mainly include vocabularies, thesaurus, semantic networks, axiom system ...
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