On June 25th we had a pleasure to host Why R? Webinar with Dr. Leon Eyrich Jessen who did present a In Silico Immunology: Neural Networks for Modelling Molecular Interactions using Tensorflow via Keras in R.
If you are interested in the talk check out the Webinar! Below you can find the biogram of the speaker and the abstract of the talk.
Leon Eyrich Jessen is an assistant professor of bioinformatics at department of Health Technology at Technical University of Denmark (DTU). He obtained his PhD in bioinformatics from the Center for Biological Sequences Analysis at DTU in 2014 after which he held two postdoctoral positions in clinical genetics. Hereafter, he returned to the newly formed Department of Health Technology to continue his research in the Immunoinformatics and Machine Learning Group at section for bioinformatics. Throughout his career, his research focus has been on connecting genotype to phenotype in an immunological context.
Understanding what constitutes an immune target is pivotal in vaccinology. With the advent of COVID-19 this has only become more evident. While computer-based predictions cannot replace traditional experimental validation in the laboratory, it can serve as an important tool to drastically reduce the target search space and increase understanding. In this webinar, I will demonstrate how we can model immune targets using artificial neural networks (ANNs) in R. ANNs constitute the basic building block of Deep Learning. Moreover, I will use the binding of peptides to the Major Histocompatibility Complex class I (MHCI) as a study case. pMHC formation is a precursor for activation of cytotoxic T-lymphocytes, which in turn is the primary system for ridding the body of viral infections. The webinar assumes no prior knowledge and will be followed by a Q&A.
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