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A novel quantum algorithm for efficient attractor search in gene regulatory networks.

Mirko Rossini1,2, Felix M Weidner3, Joachim Ankerhold1,2

  • 1Institute for Complex Quantum Systems, Ulm University, 89069 Ulm, Germany.

Patterns (New York, N.Y.)
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We developed a quantum search algorithm to find stable states (attractors) in complex gene networks. This quantum approach overcomes classical computing limitations and guarantees new attractor discovery, aiding biological modeling on quantum computers.

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Boolean networksattractor searchgene regulatory networksquantum amplitude suppressionquantum computing

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Area of Science:

  • Computational Biology
  • Quantum Computing
  • Systems Biology

Background:

  • Modeling complex gene interactions is difficult due to limited microscopic detail.
  • Boolean networks provide a coarse-grained model for gene dynamics, with attractors linked to biological phenotypes.
  • Classical computing faces challenges with the large state space of these models.

Purpose of the Study:

  • To present a novel quantum search algorithm for identifying attractors in synchronous Boolean networks.
  • To leverage quantum computing for enhanced biological modeling.
  • To address the limitations of classical computation in analyzing complex biological systems.

Main Methods:

  • Developed a quantum search algorithm tailored for quantum computers.
  • Implemented an iterative approach to suppress known attractor basins.
  • Designed the algorithm for synchronous Boolean networks.

Main Results:

  • The algorithm guarantees the discovery of a new attractor in each run, surpassing classical methods.
  • Demonstrated strong resilience to noise on current Noisy Intermediate-Scale Quantum (NISQ) devices.
  • Successfully identified attractors in Boolean network models.

Conclusions:

  • The quantum search algorithm offers a promising advance for biological modeling.
  • Quantum computing can overcome classical limitations in analyzing complex biological dynamics.
  • The algorithm shows potential for practical applications on near-term quantum hardware.