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Two Challenging Difficulties of Protein Complex Prediction

  • Osamu Maruyama
Conference paper
Part of the Mathematics for Industry book series (MFI, volume 28)

Abstract

A protein complex is a group of proteins which carries out particular functions in the cell. The component proteins of a protein complex are connected via weak physical contacts, called protein–protein interactions (PPIs). Proteome-wide PPIs are determined by high-throughput assays. Thus, it is interesting to computationally predict protein complexes from such PPIs. In this paper, we describe two challenging difficulties of the problem. The first difficulty is that the smallest protein complexes are of size two. It is quite difficult to predict them due to their simple inherent structure. The second difficulty is that some known complexes are overlapped with each other, because it is not trivial how to model such overlaps mathematically. For these issues, we have proposed our own approaches. In both methods, we design a scoring function and algorithms based on Markov chain Monte Carlo to optimize the scoring function. In this article, we briefly show our key regularization terms included in the whole scoring function.

Keywords

Protein complex Protein–protein interaction Markov chain Monte Carlo 

Notes

Acknowledgements

This work was partially supported by JSPS KAKENHI Grant Number 26330330.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Institute of Mathematics for Industry, Kyushu UniversityFukuokaJapan

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