On the Capacity of DNA Labeling

Dganit Hanania, Daniella Bar-Lev, Yevgeni Nogin, Yoav Shechtman, Eitan Yaakobi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


DNA labeling is a powerful tool in molecular biology and biotechnology that allows for the visualization, detection, and study of DNA at the molecular level. Under this paradigm, a DNA molecule is being labeled by specific k patterns and is then imaged. Then, the resulted image is modeled as a (k +1)-ary sequence in which any non-zero symbol indicates on the appearance of the corresponding label in the DNA molecule. The primary goal of this work is to study the labeling capacity, which is defined as the maximal information rate that can be obtained using this labeling process. The labeling capacity is computed for any single label and several results are provided for multiple labels as well. Moreover, we provide the optimal minimal number of labels of length one or two that are needed in order to gain labeling capacity of 2.

Original languageEnglish
Title of host publication2023 IEEE International Symposium on Information Theory, ISIT 2023
Number of pages6
ISBN (Electronic)9781665475549
StatePublished - 2023
Event2023 IEEE International Symposium on Information Theory, ISIT 2023 - Taipei, Taiwan, Province of China
Duration: 25 Jun 202330 Jun 2023

Publication series

NameIEEE International Symposium on Information Theory - Proceedings


Conference2023 IEEE International Symposium on Information Theory, ISIT 2023
Country/TerritoryTaiwan, Province of China

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics


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