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DTSTAMP:20260709T155148Z
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DTSTART:20210517T090000Z
DTEND:20210520T170000Z
DESCRIPTION:Educators:\nBálint Mészáros\, Matt Rogon\, Renato Alves (HD-
 HuB)\n\nDate:\n17 - 20 May\n9:00 - 12:30\n\nLocation:\nOnline Meeting (con
 nection details after registration)\n\nContent:\nOntologies are the primar
 y means to store biological data about genes\, proteins\, and other biolog
 ical entities in an accessible and unambiguous way. These ontologies are h
 ierarchical collections of descriptive terms\, typically represented as ne
 tworks (graphs)\, serving as a fundamental structure to store biological k
 nowledge. The use of ontology-based enrichment and network representations
  to infer biological properties of gene and protein sets identified in exp
 eriments\, is now ubiquitous. Consequently\, a solid understanding and flu
 ency in ontology-based approaches is an essential skill in a wide range of
  biological fields.\n\nLearning goals:\nDuring this 4-day online course pa
 rticipants will learn how to access and utilize biological ontologies (mai
 nly Gene Ontology) to arrive at sound biological inferences using standard
  and customized enrichment analyses and network visualization.\n\nDuring t
 he course you will learn how to:\n\n- access gene and pathway ontologies t
 o build high-quality maps for data interpretation and visualisation\;\n\n-
  customize query data as well as databases themselves to deal with a wide 
 range of biases and produce reliable results using online tools\, Cytoscap
 e\, and R packages\;\n\n- explore Gene Ontology\, KEGG and Reactome databa
 ses\;\n\n- understand\, utilize and create sub-ontologies to address speci
 fic biological questions by executing enrichment analyses\;\n\n- Use R-bas
 ed packages to automate\, accelerate and create reproducible analyses\;\n\
 n- be able to interpret and assess the quality of GeneOntology analyses in
  publications by understanding the strengths and limitations of enrichment
  calculations.\n\nAfter the course you will be able to independently extra
 ct data from public resources\, assess their quality\, annotate your own n
 etworks and biomolecules in Cytoscape\, extract data using R\, and critica
 lly interpret the results.\n\nPrerequisites:\n\nThis course is an introduc
 tion to ontologies\, however we require:\n\n- working knowledge of Cytosca
 pe (e.g. introductory level course by Matt Rogon from EMBL CBNA https://gi
 t.embl.de/rogon/introduction-to-cytoscape-and-network-biology)\n\n- basic 
 knowledge of R (data structures\, file operations etc.) - e.g. introductor
 y level course by EMBL CSDA (https://git.embl.de/klaus/tidyverse_R_intro) 
 or EMBL Bio-IT (https://bio-it.embl.de/events/introduction-to-r/)\n\nKeywo
 rds:\nOntologies \,statistics\, biases\, tools\, networks\, interpretation
 \, R\, Cytoscape
SUMMARY:Ontologies - statistics\, biases\, tools\, networks\, and interpret
 ation 2021
URL;VALUE=URI:https://www.denbi.de/training/1157-ontologies-statistics-bias
 es-tools-networks-and-interpretation-2021
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