Extending the evolvability model to the prokaryotic world: Simulations and results on real data

Ben Yohay, Sagi Snir

Research output: Contribution to journalArticlepeer-review


In 2006, Valiant introduced a variation to his celebrated PAC (Probably Approximately Correct) model to biology, by which he wished to explain how, with two simple mechanisms - random variation and natural selection - complex life mechanisms evolved in such a short time. Subsequently, several works extended and specialized the evolvability framework to more specific processes. In this study, we extend the evolvability framework to accommodate horizontal gene transfer, the transfer of genetic material between unrelated organisms. While in a separate work, we focused on the theoretical aspects of this extension and its learnability power; here, the focus is on more practical and biological facets of this new model. Specifically, we focus on the evolutionary process of developing a trait and model it as the conjunction function. We demonstrate the speedup in learning time for a variant of conjunction to which learning algorithms are known. We also confront the new model with the recombination model on real data of Escherichia coli strains under the task of developing pathogenicity and obtain results adhering to current existing knowledge. Apart from the sheer extension to the understudied prokaryotic world, our work offers comparisons of three different models of evolution under the same conditions, which we believe is unique and of a separate interest.

Original languageEnglish
Pages (from-to)794-805
Number of pages12
JournalJournal of Computational Biology
Issue number8
StatePublished - Aug 2019

Bibliographical note

Funding Information:
The authors wish to acknowledge the Israel Science Foundation (ISF) for its kind support in performing this research.

Publisher Copyright:
© Copyright 2019, Mary Ann Liebert, Inc., publishers 2019.


  • E. coli
  • PAC learning
  • evolvability
  • horizontal gene transfer
  • prokaryotic evolution

ASJC Scopus subject areas

  • Computational Mathematics
  • Genetics
  • Molecular Biology
  • Computational Theory and Mathematics
  • Modeling and Simulation


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  • Extending the evolvability model to the prokaryotic world: Simulations and results on real data

    Snir, S. & Yohay, B., 2018, Bioinformatics Research and Applications - 14th International Symposium, ISBRA 2018, Proceedings. Zhang, F., Zhang, S., Cai, Z. & Skums, P. (eds.). Springer Verlag, p. 299-313 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10847 LNBI).

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

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