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Double-staging fused lncRNA (long non-coding ribonucleic acid) selection method

A dual, clinical staging technology, applied in the field of lncRNA selection, can solve the problems of time-consuming, neglected disease dual staging data association, and inability to give diseases, and achieve the effect of improving the global optimization ability.

Pending Publication Date: 2022-03-01
QIQIHAR UNIVERSITY
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the intricate relationship between lncRNA and diseases, it takes a lot of financial and time-consuming to carry out lncRNA-related biological experiments, and the use of computer-aided experiments has become an effective research method
Existing methods can only predict whether lncRNA is associated with the disease, but cannot give specific aspects of the association with the disease. The focus is only limited to a single lncRNA prediction, ignoring the association of the dual staging data of the disease

Method used

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  • Double-staging fused lncRNA (long non-coding ribonucleic acid) selection method
  • Double-staging fused lncRNA (long non-coding ribonucleic acid) selection method
  • Double-staging fused lncRNA (long non-coding ribonucleic acid) selection method

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Embodiment

[0074] (1) 480 lncRNA transcripts of prostate cancer patients were obtained in the lncRNAtor database, and the dual-stage DS data was obtained from the clinical data of prostate cancer patients in the TCGA database. A total of 118 effective clinical stage CT data and 174 effective PT data of pathological staging. The lncRNA data matrix M that will be used for clinical stage prediction CTP (contains 104 clinical stage available data) and lncRNA data matrix M for pathological stage prediction LC (Contains 170 available data of pathological stages) After taking the intersection, correlate the dual staging matrix DSM (contains 101 available data of dual staging), and finally obtains the lncRNA data matrix M for dual staging prediction DS .

[0075] (2) Use the DSSCA algorithm (where wei is set to 0.6) to calculate M respectively DS Medium 480 Lr i The importance of D-significance(Lr i ), according to D-significance (Lr i ) will Lr i Constructed as a linear descending queue ...

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Abstract

The invention discloses a double-staging fused lncRNA selection method, which comprises the following steps: step 1, according to an lncRNA data matrix for clinical staging prediction and an lncRNA data matrix for pathological staging prediction, proposing a conditional weighting method fused with a double-staging importance calculation method, and calculating an lncRNA data matrix for double-staging prediction; 2, a variable-length dynamic bucket VLDB generation algorithm is called to generate variable-length dynamic buckets, and the number of the buckets is output; step 3, providing a reverse inter-bucket frequency shift method for dual staging kernel variable selection; and step 4, aiming at a mobile terminal in the reverse inter-bucket frequency shift method, using a mobile terminal frequency shift updating algorithm to select the lncRNA which is relatively good in stability and is most closely associated with the cancer dual staging. According to the method, the lncRNA which is relatively good in stability and is most closely associated with cancer dual staging can be selected, and the selected final element has relatively high interpretability.

Description

technical field [0001] The invention relates to a gene selection method in bioinformatics, in particular to a lncRNA selection method most closely related to cancer dual staging. Background technique [0002] Long non-coding RNA refers to a type of non-coding RNA with a length greater than 200 nucleotides. In previous studies, it was considered to be the noise generated during the transcription process. Now it has been found to participate in all aspects of the cell life cycle, including transcription, cell differentiation, cell Translocation, apoptosis, metabolic process, etc. Not only that, LncRNA has also been found to be closely related to various human diseases including leukemia, diabetes, prostate cancer, lung cancer, colon cancer, cardiovascular disease, etc. Therefore, studying the function of lncRNA helps us understand the mechanism of disease, and predicting the association between lncRNA and disease can help prevent the occurrence of major diseases. However, due...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30G06F17/16G16B5/00G16B50/00
CPCG16H50/30G06F17/16G16B5/00G16B50/00
Inventor 王波韩瑜崔连和罗金琦姜伟
Owner QIQIHAR UNIVERSITY