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A Method of Protein Folding Prediction Based on Ant Colony Fish Swarm Algorithm

A technology of protein folding and fish swarm algorithm, which is applied in the field of protein folding prediction based on ant colony fish swarm algorithm, can solve the problems of long calculation time and low precision, and achieves improved convergence speed, fast and fast convergence ability, and good global convergence performance. Effect

Active Publication Date: 2021-12-17
QIQIHAR UNIVERSITY
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Problems solved by technology

[0011] The purpose of the present invention is to solve the problems of low precision and long calculation time in the prediction of protein structure in the prior art. The present invention describes a method for protein folding prediction based on the ant colony fish swarm algorithm

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  • A Method of Protein Folding Prediction Based on Ant Colony Fish Swarm Algorithm
  • A Method of Protein Folding Prediction Based on Ant Colony Fish Swarm Algorithm
  • A Method of Protein Folding Prediction Based on Ant Colony Fish Swarm Algorithm

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Embodiment 1

[0030] A method for protein folding prediction based on an ant colony fish swarm algorithm, comprising the steps of:

[0031] Step 1: Ant colony algorithm initialization setting, artificial fish swarm algorithm initialization setting, forming a new initial population;

[0032] Step 2: Alternate iterations to generate a new initial solution;

[0033] Step 3: Judging the degree of congestion; if it is crowded, keep the population in its original state, move forward randomly, and repeat step 2; if it is not crowded, move forward one step toward the center of the population, and perform step 4 for the population;

[0034] Step 4: Update pheromone concentration and bulletin board information;

[0035] Step 5: Calculate fitness;

[0036] Step 6: Determine whether the condition is met; if the condition is met, output the result; if the condition is not met, return to step 2.

[0037] Further, in step 1, initialize the number of artificial ants m, heuristic factor α, hope heuristic f...

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Abstract

In order to solve the problems of low precision and long calculation time in protein structure prediction in the prior art, the present invention describes a protein folding prediction method based on the ant colony fish swarm algorithm, which relates to the field of protein structure prediction, and the technical scheme is as follows: Step 1: Ant colony algorithm initialization setting, artificial fish swarm algorithm initialization setting, forming a new initial population; Step 2: Alternate iterations to generate a new initial solution; Step 3: Judging the degree of crowding; if crowded, the population remains in its original state, random Step forward, repeat Step 2, if it is not crowded, move forward to the center of the population, and execute Step 4 for the population; Step 4: Update pheromone concentration and bulletin board information; Step 5: Calculate fitness; Step 6: Judgment Whether the condition is met; if the condition is met, output the result; if the condition is not met, return to step 2. The invention can search for the lowest energy value of the protein sequence under the condition of high operation precision and short search time.

Description

technical field [0001] The invention belongs to the field of protein structure prediction, and in particular relates to a method for protein folding prediction based on an ant colony fish swarm algorithm. Background technique [0002] Ant colony algorithm and artificial fish swarm algorithm are called two emerging swarm intelligence algorithms. Although they have been born for a short time, they have made rapid progress. They have been tried to be applied in many fields by scholars and have achieved quite good results. . While a single algorithm has many advantages, it also has various disadvantages. [0003] The ant colony algorithm has good parallelism, and the accuracy of the algorithm is high, which is a prominent advantage of the ant colony algorithm. The artificial ants can search the entire search space, and the artificial ants can also exchange information, and finally achieve the purpose of optimization. In the ant colony algorithm, in fact, each artificial ant i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B15/20G16B40/00G06N3/00
CPCG06N3/006
Inventor 王凤娟姜淑凤甄英琦崔有正高申煣王钰吴昭君姜宇超王宇清
Owner QIQIHAR UNIVERSITY
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