Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

“…We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In particular, we show that our algorithms find sets which are better than the ones obtained by the state-of-the-art method, even when sets are evaluated using the statistical score employed by the latter. …”

Pathway activity and single-cell level functional states of CEDGs in cancer. by Yuxi Gu (11386081)

Identification and functional analysis of hub genes. by Wei Ya Lan (22403712)

“…(E) GO enrichment analysis of shared candidate genes, showing the top three terms for biological process (BP), cellular component (CC), and molecular function (MF).…”

Genetic Algorithm (GA) and CAGE-based personalization block diagrams. by Dmitrii Smirnov (8822324)

“…(<b>B</b>) Algorithm verification with molecular (mRNA expression) and functional data (optical mapping). …”

Multimodal reference functions. by Ruiyu Zhan (21602031)

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

Algorithm timings on a laptop computer with Intel i9–9900K CPU, 32GB RAM and an NVIDIA RTX2080 GPU. by Adam L. Tyson (10892822)

Subjects:

Performance comparison of PortalCG with the state-of-the-art methods for designing selective dual-DRD antagonists. by Tian Cai (4227052)

Subjects:

Data_Sheet_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.PDF by Hong Gu (68558)

Subjects:

Data_Sheet_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.PDF by Hong Gu (68558)

Subjects:

The convergence curves of the test functions. by Ruiyu Zhan (21602031)

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”

Single-peaked reference functions. by Ruiyu Zhan (21602031)

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”

NLDock: a Fast Nucleic Acid–Ligand Docking Algorithm for Modeling RNA/DNA–Ligand Complexes by Yuyu Feng (11371729)

Subjects: