Key gene identification based on two machine learning algorithms. by Lijun Guo (605276)

Spearman correlation coefficient results for classification algorithms (predicted probabilities) and regression algorithms (predicted IC50 values). by Sofia P. Miranda (11418930)

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Optimal ALARM BN discovered by CausNet. by Nand Sharma (21519845)

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Classification results for all subsampling scenarios and algorithms for Gefitinib. by Sofia P. Miranda (11418930)

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Sensitivity analysis of the TV-BayesOpt algorithm with a forgetting (orange line) or a forgetting-periodic (blue line) covariance function for a range of ε values. by John E. Fleming (8533956)

Regression results for all combinations of subsampling scenarios and algorithms for Gefitinib. by Sofia P. Miranda (11418930)

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Average RMSE rank for all combinations of subsampling scenarios and algorithms. by Sofia P. Miranda (11418930)

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List of ageing-associated genes (STRING identifier and corresponding gene symbol) within imputed genes based on the JenAge Ageing Factor Database for each tissue (brain and liver)... by Konstantina Charmpi (9901053)

Image_1_Identification of a Novel Prognostic Signature for Gastric Cancer Based on Multiple Level Integration and Global Network Optimization.TIF by Lin Cui (163750)

“…To date, there have been no reports on integrated optimization analysis based on the GC global lncRNA-miRNA-mRNA network and the prognostic mechanism has not been studied. …”

DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF by Deniz Seçilmiş (13028616)

DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF by Deniz Seçilmiş (13028616)

Summary of AUC values across all combinations of subsampling scenario and algorithm. by Sofia P. Miranda (11418930)

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UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms. by Fatemeh Keikha (20917848)

Optimal ovarian cancer BNs learned by CausNet and CausNet-partial. by Nand Sharma (21519845)

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Illustration of the BRIDES algorithm and the selection process. by Cindy Bouchard (6844979)

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Most informative genes for predicting cell-line responses for Gefitinib. by Sofia P. Miranda (11418930)

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Descriptions of the algorithms we tested and hyperparameters that we evaluated via nested cross validation. by Sofia P. Miranda (11418930)

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The flow chart of harmony search-based OED using a double nested loops. by Wei Zhang (405)

Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm by Interdis Sci Comp Life Sci (7335308)

“…This work mainly focuses on the following aspects: (1) On the basis of the IPC-MB and DPI, we presented a novel feature selection method called the improved MB discovery algorithm (IMBDA), which can accurately identify direct and indirect regulatory genes when inferring networks. (2) Isolated genes were properly processed by the IDS to optimize the network structure. (3) The performance of IMBDANET was assessed with extensive experiments. …”

Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm by Interdis Sci Comp Life Sci (7335308)

“…</p><p dir="ltr"> (2) Isolated genes were properly processed by the IDS to optimize the network structure.…”