Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.03.11.532170v1?rss=1
Authors: Blum, C. F., Kolkhof, P., Kollmann, M.
Abstract:
The ability to design RNA molecules with specific structures and functions could facilitate research and developments in biotechnology, biology and pharmacy. Here we present a flexible RNA design framework based on deep learning that locally optimizes sequences by gradient-guided search methods. We demonstrate its effectiveness by designing bi-stable RNA molecules by superimposing conformer target structures.
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