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Dagstuhl-Seminar 24511

Coding Theory and Algorithms for Emerging Technologies in Synthetic Biology

( 15. Dec – 20. Dec, 2024 )

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Kontakt

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Gemeinsame Dokumente

Programm

Motivation

The progress in understanding genes and genomes has given a boost to the use of synthetic DNA for biological and technological applications. Synthetic nucleic acids play a central role in synthetic biology and in emerging therapeutic paradigms, e.g., genome editing and nucleic acid vaccines. DNA-based data storage is making significant progress, and thanks to its extreme data-density, its high durability and its timelessness, it is promising to be the next standard for data archival systems.

Synthetic biology and the use of synthetic DNA for information storage applications bring important algorithmic and data analysis challenges. In synthetic biology, reagent and assay design are often driven by algorithmic approaches. Novel synthesis technologies offer cost-reduction by several orders of magnitude at the cost of increased error-rate, raising new coding-theoretic questions.

This Dagstuhl Seminar aims to bring together leading biologists, chemists, engineers, computer/data scientists, and theoreticians working on synthetic biology and on DNA-based data storage, to enable joint work in small groups leading to discussing and exploring recent advancements and current challenges. The seminar will also facilitate the initiation of collaborative work and thus possibly pave the way to addressing open challenges.

The topics envisaged to be discussed include: (i) coding-theoretic challenges and methods for native DNA-based data storage systems; (ii) implications of emerging sequencing technologies, novel synthesis methods, and application-specific data structures; and (iii) information aspects of high throughput synthetic biology, including CRISPR screening experiments.

Copyright Rawad Bitar, Olgica Milenkovic, Zohar Yakhini, and Yonatan Yehezkeally

Teilnehmer

Klassifikation
  • Emerging Technologies
  • Information Theory

Schlagworte
  • Synthetic biology
  • DNA-based data storage
  • Edit error-correcting codes