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DTSTAMP:20260705T183549Z
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DTSTART:20201008T090000Z
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DESCRIPTION:---------------------------------------------------------------
 ---------------------------------------------------\n\nOn 15 &amp\; 16 Oct
 ober\, there is an online demo/hands-on session and online Q&amp\;A on Usi
 ng MOFA for integration of Omics Data.\n\n--------------------------------
 --------------------------------------------------------------------------
 --------\n\nIn the era of Big Data\, the tsunami of massive ‘omics’ da
 ta is revolutionizing the way we do science. Life science researchers are 
 no longer analyzing one data set at a time but are moving towards multi-di
 sciplinary integrative biology. It has been demonstrated that integration 
 of different ‘omics’ data types (such as on genomes\, transcriptomes\
 , proteomes\, epigenomes\, etc..)\, boosts biological discoveries and impr
 oves predictions of the underlying interactions and regulation among molec
 ular entities. Integrating different ‘omics’ datasets is a challengi
 ng task that relies heavily on data mining and machine learning algorithms
 . One must account for the specificities of each data type\, solve probl
 ems associated with processing data across different platforms\, and take 
 into account the variable reliability levels of heterogeneous data.\n\n 
 \n\nIn the second edition of this training on Multi-Omics data integration
 \, four different topics will be addressed: ‘Multi-Omics Factor Analysis
 ’\, ‘Single Cell Data Analysis’\, ‘Machine Learning\, Deep Learnin
 g &amp\; Genomics/Proteomics’\, and ‘Machine Learning in Drug Discover
 y and Disease’. We have invited top level speakers to share their insigh
 ts with you on the latest developments in the field.\n\nThis course is org
 anized in collaboration with Helis Academy. More information see https:/
 /helisacademy.com/\n\n\n  \n      \n  \n    Image
SUMMARY:Challenges in Omics Data Integration
URL;VALUE=URI:https://training.vib.be/all-trainings/challenges-omics-data-i
 ntegration
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