Meta search method for gene tissue-specific sequence pattern and search result assessment method

Abstract

The invention discloses a meta search method for a gene tissue-specific sequence pattern and a search result assessment method and belongs to the field of biological information science. The search method comprises the following steps: extracting promoter sequences of tissue-specific genes and housekeeping (HK) genes from a bioinformatics database as input initial data; carrying out local a search algorithm and an exhaustive search algorithm on the input initial data respectively; storing result tissue generated from the operation of the two search algorithms into a filter matrix; estimating the pattern probability by utilizing the data in the filter matrix; and merging the motifs. In the assessment method, Bayes factor analysis evaluation statistics are utilized to obtain the significance of the search result of the gene tissue-specific motifs. Compared with prior art, the methods provided by the invention have the advantages that the pattern search frame used in the invention integrates multiple algorithms, the principle of 'average result overcomes single choice' which prevails in bioinformatics is conformed, the robustness and creditability of results are improved, the creditability of search results is increased, and over estimation and low estimation of the pattern are avoided.

Description

technical field [0001] The invention relates to the field of biological information science, in particular to a search method for gene tissue-specific sequence pattern elements. Background technique [0002] Tissue-specific genes refer to genes that are specifically expressed in different cell types. Tissue-specific gene expression includes information such as binding sites between transcription factors and gene promoter sequences, sequence characteristics of gene promoter regions, alternative splicing (Alternative Splice), and epigenetic characteristics. in: [0003] Transcription factors are a group of protein molecules that can specifically bind to a specific sequence at the 5' end of a gene to ensure that the target gene is expressed at a specific time and space with a specific intensity. Transcription factors, also known as sequence-specific DNA-binding factors, bind to specific DNA sequences, thereby controlling the transfer of genetic information from DNA to mRNA. ...

AI Technical Summary

Problems solved by technology

Its advantage is that it has low computational complexity, fast calculation speed, and is suitable for searching solutions in a large space; the disadvantage is that it cannot guarantee the optimal solution of the problem, and can only obtain a suboptimal solution similar to the optimal solution.

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