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ergänzende Hinweise |
This is a two-part module: (1) Six lecturesintroduce biological mechanisms, experimental assays, and computational models for regulatory genomics. The six lectures are supported with modeling exercises in python. This is followed by (2) an eight-week hands-on project. The lectures are organized around steps of gene expression:● Introduction to gene regulation and sequence-based computational models of gene regulation● Transcriptional regulation● Chromatin-mediated regulation● RNA splicing● RNA modification and degradation● Translation Over these lectures, computational methods are introduced including:● Fitting procedures of deep neural network● Convolutional Neural Networks● LSTM and transformers● Embeddings for sequence data● Multi-task learning and transfer learning● End-to-end learning● Analytical and visualisation techniques for model interpretation |
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TUMonline-Eintrag
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