Rational Design of RiboNucleic Acids (Dagstuhl Seminar 22381)

Authors Sven Findeiß, Christoph Flamm, Yann Ponty and all authors of the abstracts in this report

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Author Details

Sven Findeiß
  • Leipzig University , DE
Christoph Flamm
  • University of Vienna, AT
Yann Ponty
  • Ecole Polytechnique - Palaiseau, FR
and all authors of the abstracts in this report

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Sven Findeiß, Christoph Flamm, and Yann Ponty. Rational Design of RiboNucleic Acids (Dagstuhl Seminar 22381). In Dagstuhl Reports, Volume 12, Issue 9, pp. 121-149, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


This report documents the program and outcomes of Dagstuhl Seminar 22381 "Rational Design of RiboNucleic Acids" (RNAs). The seminar covered a wide array of models, algorithmic strategies, molecular scales and modalities, all targeting in silico design of RNAs performing predefined biological functions. It consisted in a series of talks, each being allocated a generous time budget enabling frequent (welcomed!) interruptions and fruitful discussions. Applications of rational RNA design include mRNA vaccines; RNAs acting as sensors; self-replicating RNAs, relevant to RNA world/origin of life studies; populations of RNAs performing computations, e.g. through strand-displacement systems; RNA origamis forming nano-architectures through self-assembly; weakly interacting RNAs inducing the formation of droplets within cells through liquid-liquid phase separation. Those diverse applications are typically tackled by Bioinformatics-inclined scientists, contributing to distinct areas of life science and, as a result, somewhat isolated and sometimes unaware of similar pursuits in neighboring fields. The overarching goals of this meeting were to gather computational scientists from multiple fields, increase awareness of relevant efforts in distant communities, and ultimately contribute to a transversal perspective where RNA design becomes an object of study in itself.

Subject Classification

ACM Subject Classification
  • Applied computing → Bioinformatics
  • Applied computing → Molecular evolution
  • Applied computing → Molecular structural biology
  • Theory of computation → Discrete optimization
  • Theory of computation → Dynamic programming
  • Theory of computation → Parameterized complexity and exact algorithms
  • Mathematics of computing → Optimization with randomized search heuristics
  • Computing methodologies → Discrete space search
  • Computing methodologies → Reinforcement learning
  • Computing methodologies → Neural networks
  • RNA
  • RNA design
  • Inverse folding
  • RNA structure
  • mRNA design
  • RNA sensors
  • Co-transcriptional folding
  • Molecular evolution
  • Distant homology
  • Drug design


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