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NCBO BioPortal

NCBO BioPortal

Snomed-CT Snomed-CT (Systematized Nomenclature of Medicine – Clinical Terms) es la terminología clínica integral, multilingüe y codificada de mayor amplitud, precisión e importancia desarrollada en el mundo.[1] Historia[editar] Snomed CT es un producto que nace de la fusión entre Snomed RT (Snomed Reference Terminology), creada por el College of American Pathologists (CAP) y el Clinical Terms Version 3 (CTV3), desarrollada por la National Health Service (NHS) del Reino Unido. Actualmente, esta terminología es mantenida y distribuida por la International Health Terminology Standards Development Organisation (IHTSDO). Snomed-CT se está convirtiendo en un estándar al estar apoyado por los gobiernos de Australia, Canadá, Chipre, Dinamarca, Eslovaquia, Eslovenia, España, Estados Unidos de América, Estonia, Islandia, Israel, Lituania, Malta, Nueva Zelanda, Países Bajos, Polonia, Reino Unido, Singapur, Suecia y Uruguay. [2] Véase también[editar] Referencias[editar] Bibliografía[editar] SNOMED-CT.

OBI Ontology UMLS Terminology Services -- Home Allie: Abbreviation / Long Form Search Top HEFalMp Ontology (information science) In computer science and information science, an ontology formally represents knowledge as a hierarchy of concepts within a domain, using a shared vocabulary to denote the types, properties and interrelationships of those concepts.[1][2] Ontologies are the structural frameworks for organizing information and are used in artificial intelligence, the Semantic Web, systems engineering, software engineering, biomedical informatics, library science, enterprise bookmarking, and information architecture as a form of knowledge representation about the world or some part of it. The creation of domain ontologies is also fundamental to the definition and use of an enterprise architecture framework. The term ontology has its origin in philosophy and has been applied in many different ways. What many ontologies have in common in both computer science and in philosophy is the representation of entities, ideas, and events, along with their properties and relations, according to a system of categories.

Jena Semantic Web Framework User Page - SBGN study guide Visit the Documents section for: various examples (to get a better idea of what an actual map looks like) some tutorials (very accessible, but not always up-to-date) publications about SBGN (a good start for a brief historical overview) detailed technical specifications (the ultimate reference documents, most up-to-date, but a steep learning curve for beginners) some Frequently Asked Questions Please also check the SBGN PD User Manual when you are ready to draw your own maps. Quick overview The Systems Biology Graphical Notation comprises three complementary languages suited to represent different types of pathways. Process Descriptions (PD) is a language that permits the description of the processes (e.g. biochemical reactions) taking place in a biological system. Entity Relationships (ER) is a language that permits the description of all the relations involving the entities of a biological system. Language reference cards SBGN Bricks dictionary Getting started User Manual

Open Geiger Project CTSA | Clinical & Translational Science Awards SNOMED Clinical Terms - Summary | NCBO BioPortal SNOMED CT has been created by combining SNOMED RT and a computer-based nomenclature and classification known as Read Codes Version 3, which was created on behalf of the U.K. Department of Health and is a Crown copyright. SNOMED CT Concept (SNOMED RT+CTV3) SNOMED CT January 2005 Release: 20050131 [R] SNOMED CT January 2003 Release: 20030131 [R] SNOMED Clinical Terms version: 20090731 [R] (July 2009 Release) ©2002 - 2006 College of American Pathologists. SNOMED CT July 2003 Release: 20030731 [R] © 2002-2012 International Health Terminology Standards Development Organisation (IHTSDO). SNOMED Clinical Terms version: 20100131 [R] (January 2010 Release) SNOMED Clinical Terms version: 20080131 [R] (January 2008 Release) ©2002 College of American Pathologists SNOMED Clinical Terms version: 20090131 [R] (January 2009 Release) SNOMED Clinical Terms version: 20060731 [R] (July 2006 Release) SNOMED Clinical Terms version: 20130731 [R] (July 2013 Release) SNOMED CT First Release: 20020131 [R]

MGED Welcome to the website of the ontology working group for the MGED project, which is charged with developing an ontology for describing samples used in microarray experiments. What is an Ontology? From the Stanford Knowledge Systems Lab:"An ontology is an explicit specification of some topic. For our purposes, it is a formal and declarative representation which includes the vocabulary (or names) for referring to the terms in that subject area and the logical statements that describe what the terms are, how they are related to each other, and how they can or cannot be related to each other. Ontologies therefore provide a vocabulary for representing and communicating knowledge about some topic and a set of relationships that hold among the terms in that vocabulary." An extensive definition from Tom Gruber. See also:Toward Principles for the Design of Ontologies Used for Knowledge Sharing. MGED Ontology Frequently Asked Questions (FAQ): Information about the MGED Ontology can be found here.

Data | 1000 Genomes Sample lists and sequencing progress A summary of sequencing done for each of the three pilot projects is available here. The list of samples and allocations is provided in a spreadsheet. Variant Calls Our variant calls are always released in vcf format. Alignments The main project alignments are available in BAM format. Raw sequence files The main project raw sequence data is available in fastq format. Download data The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via our mirrored ftp sites. EBI FTP: NCBI FTP: Users in the Americas should use the NCBI ftp site and users in Europe and the rest of the world should use the EBI ftp site The data is also available via an Aspera server from both sites. The plugin should automatically start when you visit either the EBI Aspera site or the NCBI Aspera site. An example command line for ascp looks like:

how to do it in Excel One common piece of feedback I get after presenting on the topic of data visualization goes something like this: Wow, that was super useful. I'm never going to use pie charts again. But when it comes to the graphs, how do you actually make them look like that? I'm not! Pretty much everything I do is in Excel. I like to refer to it as "brute-force" Excel, because in many cases the graphing application doesn't make it so straightforward to get from plotting the data to the final product. The following example may look familiar; it's from the FlowingData Challenge earlier this year (original blog post here). The full Excel file can be downloaded here. What you require most to get from Excel's original graph to the one you actually are proud to present is patience and time.