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

“…Then the estimation of the background distribution and the identification of driver genes were conducted in each cluster obtained by the hierarchical clustering algorithm. We applied FI-net and other 22 state-of-the-art methods to 31 datasets from The Cancer Genome Atlas project. …”

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

“…Then the estimation of the background distribution and the identification of driver genes were conducted in each cluster obtained by the hierarchical clustering algorithm. We applied FI-net and other 22 state-of-the-art methods to 31 datasets from The Cancer Genome Atlas project. …”

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

“…Then the estimation of the background distribution and the identification of driver genes were conducted in each cluster obtained by the hierarchical clustering algorithm. We applied FI-net and other 22 state-of-the-art methods to 31 datasets from The Cancer Genome Atlas project. …”

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

“…Then the estimation of the background distribution and the identification of driver genes were conducted in each cluster obtained by the hierarchical clustering algorithm. We applied FI-net and other 22 state-of-the-art methods to 31 datasets from The Cancer Genome Atlas project. …”

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

“…Then the estimation of the background distribution and the identification of driver genes were conducted in each cluster obtained by the hierarchical clustering algorithm. We applied FI-net and other 22 state-of-the-art methods to 31 datasets from The Cancer Genome Atlas project. …”

Algorithm membership function. by Mohamed Raef Smaoui (9865830)

“…<p>(Top) Input Membership Function. The algorithm classifies glucose input into 4 sets: low, medium, high, and ex_high. …”

Data_Sheet_1_Combined brain network topological metrics with machine learning algorithms to identify essential tremor.docx by Qin Li (36669)

“…</p>Conclusion<p>These results demonstrated that combining topological metrics with ML algorithms could not only achieve high classification accuracy for discrimination ET from HCs but also help us to reveal the potential topological pathogenesis of ET.…”

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

“…Then the estimation of the background distribution and the identification of driver genes were conducted in each cluster obtained by the hierarchical clustering algorithm. We applied FI-net and other 22 state-of-the-art methods to 31 datasets from The Cancer Genome Atlas project. …”

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

“…Then the estimation of the background distribution and the identification of driver genes were conducted in each cluster obtained by the hierarchical clustering algorithm. We applied FI-net and other 22 state-of-the-art methods to 31 datasets from The Cancer Genome Atlas project. …”

Python scripts used to model CPU errors by Poisson distribution density mass function and to draw graph of Poisson events (needs Matplot, SciPy, PysimpleGUI and NumPy) by Santhosh Kumar Rajamani (13023678)

Contrast enhancement of digital images using dragonfly algorithm by Soumyajit Saha (19726163)

“…The experimental observations reveal that the proposed DA-based image contrast enhancement produces high-quality images from its low-contrast counterparts. Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. …”

Python implementation from Symplectic decomposition from submatrix determinants by Jason L. Pereira (11598632)

“…Python implementation of the algorithm and demonstration of how to use the functions.…”

Identification of hub genes from common DEGs between healthy subjects and patients with ES. by Jian Wen (286688)

Subjects:

Attack and defense behaviors with the sensory–motor algorithm between a single predator and a single prey. by Hiroyuki Ichijo (13891153)

S1 File - by Yuh-Chin T. Huang (17867207)

“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”

S1 Dataset - by Yuh-Chin T. Huang (17867207)

“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”

Predictions from a Universal Value Function Approximator (UVFA) algorithm. by Sam Hall-McMaster (10343795)

Critical values of membership functions learned from the study cohort by the algorithm. by Yufeng Zhang (195768)

Table_6_Gut microbiota functional profiling in autism spectrum disorders: bacterial VOCs and related metabolic pathways acting as disease biomarkers and predictors.xls by Pamela Vernocchi (791125)

Table_1_Gut microbiota functional profiling in autism spectrum disorders: bacterial VOCs and related metabolic pathways acting as disease biomarkers and predictors.xlsx by Pamela Vernocchi (791125)