Improving landscape inference by integrating heterogeneous data in the inverse ising problem

HIGHLIGHTS

• who: Pierre Barrat-Charlaix from the CNRS have published the Article: Improving landscape inference by integrating heterogeneous data in the inverse Ising problem, in the Journal: Scientific Reports Scientific Reports
• what: The authors first test the ability of the approach to predict the true single-mutant energies, when noisy measurements are presented in DE, i.e. to correct the measurement noise using the equilibrium sample Deq For every λ, J and h are inferred and used to compute predicted energies of the N configurations in DE. Using simulated data, the authors show that the integrated approach . . .
  

   

  

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