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DTSTAMP:20260821T090020Z
UID:d97d85ef-0bae-4be7-9292-985784fdc76a
DTSTART:20200810T100000Z
DTEND:20200810T120000Z
DESCRIPTION:One of the most important tasks of systems biology is to create
  explanatory and predictive models of complex biological systems. Availabi
 lity of gene expression data in different conditions has paved the way for
  reconstructing direct or indirect regulatory connections between various 
 genes and gene products. Most often\, we are not interested in single inte
 ractions between gene products\; instead\, we try to reconstruct networks 
 that provide insights into the investigated biological processes or the en
 tire system as a whole.\n\nThis webinar will expand upon the concept of Ge
 ne Co-expression Networks to elucidate Weighted Gene Co-expression Network
  Analysis (WGCNA)\, and introduce the importance of visualising clustered 
 gene expression profiles as single ‘Eigengenes’. It will describe the 
 complete protocol for WGCNA analysis starting from normalised Gene Express
 ion Datasets (Microarrays or RNA-Seq). This will be followed by a discussi
 on on methods of extraction and analysis of consensus modules and Network 
 motifs from Gene Co-Expression Networks and Transcriptional Regulatory Net
 works. \n\nThe webinar will be presented in the form of a lecture and tuto
 rial with screenshots that enable listeners to emulate the protocols in R.
  Note that this is a webinar and not a coding exercise.  Links to further 
 reading and practice will be shared.\n\nPlease note that if you are not el
 igible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs
 /faq/raven/n5) account you will need to book or register your interest by 
 linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id
 =3516410&amp\;course-title=Identification%20of%20Eigen-genes%20in%20co-exp
 ression%20networks%20webinar).''
LOCATION:Craik-Marshall Building
SUMMARY:Identification of Eigen-genes\, consensus modules and Network Motif
 s in co-expression (or other biological) networks. (Webinar)
URL;VALUE=URI:http://training.csx.cam.ac.uk/bioinformatics/event/3516410
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