RNA secondary structure prediction method for quantum genetic algorithm based on multi-population assistance

Abstract

The invention belongs to the technical field of bioinformatics and discloses an RNA secondary structure prediction method for a quantum genetic algorithm based on multi-population assistance. According to the method, a stem pool and a stem compatibility matrix of an RNA sequence is established according to the RNA sequence; quantum bit vectors are used to initialize multiple chromosome populations; quantum measurement is performed on each population; optimal individuals are acquired according to measurement results; the optimal individual b in all the populations is obtained and used to replace worst individuals, nonhomologous to b, among the optimal individuals in other populations, then all the populations are updated by use of different rotational angles, and other populations not participating in replacement are updated by use of a fixed rotational angle; and the process is iterated till a stop condition is met. Through the method, the global search capability and search efficiencyof the quantum genetic algorithm are effectively improved, and the evolution algebra of the genetic algorithm is lowered. Meanwhile, all the populations suppress competition and cooperate mutually, so that the globality of the algorithm is improved, and prediction accuracy is substantially enhanced.

Description

Technical field [0001] The invention belongs to the technical field of bioinformatics, and in particular relates to an RNA secondary structure prediction method based on a quantum genetic algorithm assisted by multiple groups. Background technique [0002] At present, the existing technology commonly used in the industry is as follows: RNA secondary structure refers to the stem-loop structure formed by the RNA sequence folded back by itself. It is a structure between the primary structure and the tertiary structure, and stores more high-level structural information. Therefore, the study of secondary structure is biological An important research topic in the field of informatics. There are two main methods for determining secondary structure: experimental methods of physical chemistry and prediction methods of mathematical calculations. The experimental methods mainly include X-ray crystal diffraction and nuclear magnetic resonance (NMR). Although the results obtained by the exp...

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Problems solved by technology

[0003] In summary, the problems in the prior art are: The existing RNA secondary structure prediction algorithm has the problems of slow convergence speed and poor search ability

If the three can be coordinated well, it can have strong global search ability and strong local search ability, and the convergence speed is fast, then the accuracy and operation efficiency of the algorithm will be greatly improved. The prediction accuracy and algorithm convergence speed of RNA secondary structure will be greatly increased

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