The algorithm of the AWGE-ESPCA model.

<p>The steps are as follows: (A) Input Data: It includes sample data and gene pathway data. (B) Data Processing: It involves two core modules. First, Adaptive Noise Elimination Regularization is used to eliminate noise; then, Weighted Gene Network is constructed. (C) Result Output: It obtains...

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Bibliographic Details
Main Author:	Rui Miao (1592461) (author)
Other Authors:	Hao-Yang Yu (8219421) (author), Bing-Jie Zhong (20721810) (author), Hong-Xia Sun (1282485) (author), Qiang Xia (289073) (author)
Published:	2025
Subjects:	Microbiology Genetics Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified unsupervised baseline models network weighting module initially construct experiments important insect resource experimental results demonstrate existing models assume researchers usually pay hermetia illucens </ weighted gene network gene selection capabilities pathway quantitative information pathway enrichment region innovative unsupervised model three major challenges ablation experiments validate available genomic data genomic data analysis espca model code growth genome dataset genomic data limits researchers genome analysis known gene gene probes gene probe superior pathway model performance espca model sparse pca serious problem rich regions representative supervised priori weight paper presents genes located effectively addressing awge_espca </ artificial intelligence also provide also integrate adaptive regularizer
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The algorithm of the AWGE-ESPCA model.

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