Supplementary Table 3 from A Novel Functional Splice Variant of <i>AKT3</i> Defined by Analysis of Alternative Splice Expression in HPV-Positive Oropharyngeal Cancers by Theresa Guo (687267)

Supplemental Table 2 from A Novel Functional Splice Variant of <i>AKT3</i> Defined by Analysis of Alternative Splice Expression in HPV-Positive Oropharyngeal Cancers by Theresa Guo (687267)

Supplemental Table 1 from A Novel Functional Splice Variant of <i>AKT3</i> Defined by Analysis of Alternative Splice Expression in HPV-Positive Oropharyngeal Cancers by Theresa Guo (687267)

Multimodal reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Risk Groups Immune Infiltration Analysis by ssGSEA Algorithm. by Yongling Wang (13261656)

F1 obtained for PFP-WGAN and DeepGO-Seq for GO terms as a function of number of available positive training samples. by Seyyede Fatemeh Seyyedsalehi (10196767)

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Functional validation of the metastasis-predictive genes inferred by PLUS from TCGA data. by Junyi Zhou (495644)

LOTUS: A single- and multitask machine learning algorithm for the prediction of cancer driver genes by Olivier Collier (7444844)

Functional enrichment analysis of DEGs. by Huiling Deng (4427161)

Table_3_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

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Table_2_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

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Table_2_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

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Table_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

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Table_3_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

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Table_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

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Table_4_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

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Table_4_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

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Highly interrelated genes and their biological functions among 21 cancers. by Qunlun Shen (11668968)

Table 6_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…Improved performances of the algorithms via feature selection from the raw gene features identified 235 unique genes as top candidate genes across all models for all stresses. …”

Table 7_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…Improved performances of the algorithms via feature selection from the raw gene features identified 235 unique genes as top candidate genes across all models for all stresses. …”