Method and system for predicting amino acid mutation
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A technology of amino acids and algorithms, applied in the field of bioinformatics, can solve the problems of blindness and cost of biological experiments, achieve the effect of solving blindness and high cost, improving accuracy and effect
Inactive Publication Date: 2017-05-10
CENT SOUTH UNIV
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[0004] The purpose of the present invention is to disclose a method and system for predicting amino acid mutations, so as to improve the accuracy and effect of prediction, and effectively solve the problems of blindness and high cost of biological experiments
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Embodiment 1
[0028] This embodiment discloses a method for predicting amino acid mutations, such as figure 1 shown, including:
[0029] Step S1, constructing a protein sample set, classifying the samples that are neutral after amino acid mutation as negative samples, and classifying the samples that are pathological after amino acid mutation as positive samples.
[0030] In this step, the data of negative samples can be extracted from the Ensemble human variation database. The data of the positive samples can be extracted from the UniProt human sequence variations database.
[0031] Preferably, in the process of constructing the protein sample set, repetitive data with a protein sequence similarity greater than 0.4 can be eliminated first.
[0032] Step S2, determine the characteristics of the pre-screening, and calculate the eigenvalues of each sample, determine the size of the sliding window centered on the mutated amino acid, and integrate the eigenvalues of the same sample into a...
Embodiment 2
[0060] Corresponding to the above method embodiments, this embodiment discloses a system for predicting amino acid mutations, including the following first to fifth processing modules. The functions of each module are described as follows:
[0061] The first processing module is used to construct a protein sample set, classify the samples that are neutral after amino acid mutations as negative samples, and classify the samples that are pathological after amino acid mutations as positive samples. Among them, the data of the negative sample can be extracted from the Ensemblehumanvariation database; the data of the positive sample can be extracted from the UniProt human sequence variations database. Preferably, the first processing module is also used to eliminate repetitive data with a protein sequence similarity greater than 0.4 during the process of constructing the protein sample set, thereby increasing the gold content of the data samples.
[0062] The second processing mod...
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Abstract
The invention relates to the technical field of biological information, and discloses a method and system for predicting amino acid mutation. The method and system for predicting amino acid mutation aim at improving the accuracy and the effect of prediction and effectively solving the problems that bioexperiment is blind, the cost of the bioexperiment is high and the like. The method for predicting amino acid mutation comprises the steps of establishing a protein sample set; determining characteristics of prefiltering, and integrating characteristics of the same sample into one characteristic sequence to combinedly establish an initial characteristic set of the sample; screening out relatively important characters through a stable character selection algorithm to combinedly establish a first screening out characteristic set of the sample; screening out important characters through a sequence forward selection algorithm to combinedly establish the final screening out characteristic set of the sample; selecting a positive sample and a negative sample to establish a training set and an independent test set, substituting the final screening out characteristic set of samples in the training set into a gradient promoting tree algorithm to be subjected to training so as to obtain a final disaggregated model, and conducting assessment on a prediction result of the disaggregated model by combining the final screening out characteristic set of the independent test set.
Description
technical field [0001] The invention relates to the technical field of biological information, in particular to a method and system for predicting amino acid mutations. Background technique [0002] Amino acid mutations, also known as non-synonymous single-nucleotide mutations, are the most valuable part of research on human disease variants. Amino acid mutation is due to the change of some single bases, resulting in the change of the amino acid sequence in the protein product. Changes in amino acids can affect protein stability, interactions, and enzyme activity, leading to disease. According to the latest results of whole human genome sequencing, each person will have three to five million amino acid mutations, and this number is still growing rapidly. Among the many amino acid mutations, some mutations cause disease, while others are neutral mutations that have no effect on protein function. With the rapid development of genomic analysis technologies such as single nuc...
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