The evolution of gene-specific expression noise was simulated using populations of model gene regulatory networks with mutable levels of gene-specific expression noise under select... حسب Nataša Puzović (7866440)

"…If the populations are evolved under selection, fitness is calculated as the distance of the expression level of each gene from the optimal expression level. Genotypes are reproduced based on their relative fitness and mutations in the intrinsic noise vectors are introduced. …"

Data Sheet 1_AlgaeOrtho, a bioinformatics tool for processing ortholog inference results in algae.docx حسب Mary-Francis LaPorte (20821568)

"…One of the crucial steps in this process is deciding on a bioengineering target: namely, which gene/protein to differentially express. …"

Streamlining signaling pathway reconstruction presentation حسب Chris Magnano (10760405)

"…Each individual method has its own input and output file formats, installation process, and user-specified parameters. Different algorithms employ varied objective functions and optimization strategies, and recognizing which method is appropriate for a particular dataset and how to set its unique parameters requires domain expertise in pathway reconstruction. …"

Table_1_A Novel Network Pharmacology Strategy to Decode Mechanism of Lang Chuang Wan in Treating Systemic Lupus Erythematosus.xlsx حسب Yao Gao (1420339)

"…Most of these models focus on the 2D/3D similarity of chemical structure of drug components and ignore the functional optimization space based on relationship between pathogenetic genes and drug targets. …"

Image_1_A Novel Network Pharmacology Strategy to Decode Mechanism of Lang Chuang Wan in Treating Systemic Lupus Erythematosus.tif حسب Yao Gao (1420339)

"…Most of these models focus on the 2D/3D similarity of chemical structure of drug components and ignore the functional optimization space based on relationship between pathogenetic genes and drug targets. …"

Data Sheet 1_A novel lactylation-related gene signature to predict prognosis and treatment response in lung adenocarcinoma.docx حسب Hongyi Zhang (431841)

"…Additionally, various algorithms were used to explore the relationship between the risk score and immune infiltration levels, with model genes analyzed based on single-cell sequencing. …"

Table_3_Feature Selection for Breast Cancer Classification by Integrating Somatic Mutation and Gene Expression.XLSX حسب Qin Jiang (503001)

"…In the stage of feature selection, we propose a staged feature selection algorithm, using fold change, false discovery rate to select differentially expressed genes, mutual information to remove the irrelevant and redundant features, and the embedded method based on gradient boosting decision tree with Bayesian optimization to obtain an optimal model. …"

Image_2_Feature Selection for Breast Cancer Classification by Integrating Somatic Mutation and Gene Expression.JPEG حسب Qin Jiang (503001)

"…In the stage of feature selection, we propose a staged feature selection algorithm, using fold change, false discovery rate to select differentially expressed genes, mutual information to remove the irrelevant and redundant features, and the embedded method based on gradient boosting decision tree with Bayesian optimization to obtain an optimal model. …"

Image_1_Feature Selection for Breast Cancer Classification by Integrating Somatic Mutation and Gene Expression.JPEG حسب Qin Jiang (503001)

"…In the stage of feature selection, we propose a staged feature selection algorithm, using fold change, false discovery rate to select differentially expressed genes, mutual information to remove the irrelevant and redundant features, and the embedded method based on gradient boosting decision tree with Bayesian optimization to obtain an optimal model. …"

Table_2_Feature Selection for Breast Cancer Classification by Integrating Somatic Mutation and Gene Expression.XLSX حسب Qin Jiang (503001)

"…In the stage of feature selection, we propose a staged feature selection algorithm, using fold change, false discovery rate to select differentially expressed genes, mutual information to remove the irrelevant and redundant features, and the embedded method based on gradient boosting decision tree with Bayesian optimization to obtain an optimal model. …"

Data_Sheet_2_Feature Selection for Breast Cancer Classification by Integrating Somatic Mutation and Gene Expression.docx حسب Qin Jiang (503001)

"…In the stage of feature selection, we propose a staged feature selection algorithm, using fold change, false discovery rate to select differentially expressed genes, mutual information to remove the irrelevant and redundant features, and the embedded method based on gradient boosting decision tree with Bayesian optimization to obtain an optimal model. …"

Data_Sheet_1_Feature Selection for Breast Cancer Classification by Integrating Somatic Mutation and Gene Expression.CSV حسب Qin Jiang (503001)

"…In the stage of feature selection, we propose a staged feature selection algorithm, using fold change, false discovery rate to select differentially expressed genes, mutual information to remove the irrelevant and redundant features, and the embedded method based on gradient boosting decision tree with Bayesian optimization to obtain an optimal model. …"

Table2_Comprehensive analysis of key m5C modification-related genes in type 2 diabetes.XLSX حسب Yaxian Song (10454804)

"…The CIBERSORT algorithm was applied to analyze the interactions between hub gene expression and immune infiltration.…"

Table1_Comprehensive analysis of key m5C modification-related genes in type 2 diabetes.XLSX حسب Yaxian Song (10454804)

"…The CIBERSORT algorithm was applied to analyze the interactions between hub gene expression and immune infiltration.…"

Presentation1_Comprehensive analysis of key m5C modification-related genes in type 2 diabetes.PDF حسب Yaxian Song (10454804)

"…The CIBERSORT algorithm was applied to analyze the interactions between hub gene expression and immune infiltration.…"

Image1_Comprehensive analysis of key m5C modification-related genes in type 2 diabetes.PDF حسب Yaxian Song (10454804)

"…The CIBERSORT algorithm was applied to analyze the interactions between hub gene expression and immune infiltration.…"

DataSheet_1_Integrated analysis of potential gene crosstalk between non-alcoholic fatty liver disease and diabetic nephropathy.docx حسب Qianqian Yan (4479328)

"…The PPI network built with the 80 common genes included 77 nodes and 83 edges. Ten optimal crosstalk genes were selected by LASSO regression and Boruta algorithm, including CD36, WIPI1, CBX7, FCN1, SLC35D2, CP, ZDHHC3, PTPN3, LPL, and SPP1. …"

Table3_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX حسب ZhanDong Li (11653330)

Table4_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX حسب ZhanDong Li (11653330)

Table1_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX حسب ZhanDong Li (11653330)