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Application of mutual information estimation for predicting the structural stability of pentapeptides

  • A. I. Mikhalskii EMAIL logo , I. V. Petrov , V. V. Tsurko , A. A. Anashkina and A. N. Nekrasov
Published/Copyright: October 30, 2020

Abstract

A novel non-parametric method for mutual information estimation is presented. The method is suited for informative feature selection in classification and regression problems. Performance of the method is demonstrated on problem of stable short peptide classification.

MSC 2010: 92-04; 62-07; 62G07

Funding statement: The work was supported by the RFBR (project No. 20–04–01085).

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Appendix A. Nonparametric estimation of mutual information

Substituting representation (1.5) into functional Je(ŵ, λ), we get

Je(w^,λ)=12n2i=1nj=1nl=1nαlK(xi,yj,xl,yl)21ni=1nl=1nαlK(xi,yi,xl,yl)+λ2l=1nαlK(xi,yi,xl,yl)L2+C.

The first summand is transformed to the form

12n2i=1nj=1nl=1nαlK(xi,yj,xl,yl)2=12n2i=1nj=1nl=1nm=1nαlK(xi,yj,xl,yl)αmK(xi,yj,xm,ym)=12n2l=1nm=1nαlαmi=1nj=1nK(xi,yj,xl,yl)K(xi,yj,xm,ym)=12l=1nm=1nαlαmHlm

where Hlm=1n2i=1nj=1nK(xi,yj,xl,yl)K(xi,yj,xm,ym).

The second summand is transformed to the form

1ni=1nl=1nαlK(xi,yi,xl,yl)=1nl=1nαli=1nK(xi,yi,xl,yl)=l=1nαlhl

where hl=1ni=1nK(xi,yi,xl,yl).

Calculate the last summand

λ2l=1nαlK(xi,yi,xl,yl)L2=λ2l=1nαlK(xi,yi,xl,yl),m=1nαmK(xi,yi,xm,ym)λ2l=1nm=1nαlαmK(xi,yi,xl,yl),K(xi,yi,xm,ym)=λ2l=1nm=1nαlαmK(xl,yl,xm,ym).

The calculation uses the property of the scalar product in the Hilbert space with the reproducing kernel K(z, t), namely, < K(z, u), K(t, u) > = K(z, t). Denoting the matrix with the elements Kij = K(xi, yi, xj, yj), by K, we finally obtain the expression

Je(α,λ)=12αTHααTh+λ2αTKα+C.

The minimum of the later functional is attained at the vector

α=(H+λK)1h.
Received: 2019-10-18
Revised: 2020-07-09
Accepted: 2020-09-18
Published Online: 2020-10-30
Published in Print: 2020-10-27

© 2020 Walter de Gruyter GmbH, Berlin/Boston

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