The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

Subjects:

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

Flowchart of the general algorithm for one trial. by Junying Wang (509009)

Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. by Tristan Mary-Huard (3864)

The performance of our proposed method in four scenarios (I to IV) uses simulated data that mimics real-world data distribution with the complete version. by Yi-Wen Hsiao (13767916)

Subjects:

Performance of our proposed method in four scenarios (I to IV) using naïve simulated data with the complete version. by Yi-Wen Hsiao (13767916)

Subjects:

Simulation parameters. by Hend Bayoumi (22693738)

Joint Detection of Change Points in Multichannel Single-Molecule Measurements by Hugh Wilson (11797444)

Subjects:

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. by Olaide N. Oyelade (14047002)

Subjects:

Performance of the ceRNAR package using synthetic data with randomly selected correlation values from 0.8 to 0.9. by Yi-Wen Hsiao (13767916)

Subjects:

Performance comparisons between ceRNIA, JAMI, SPONGE, GDCRNATools and ceRNAR packages using synthetic data that mimic the real-world case. by Yi-Wen Hsiao (13767916)

Subjects:

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with a fixed correlation value (0.9). by Yi-Wen Hsiao (13767916)

Subjects:

Performance of the ceRNAR package in five scenarios under the fast version using synthetic data with a fixed correlation value (0.9). by Yi-Wen Hsiao (13767916)

Subjects:

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with a fixed correlation value (0.6). by Yi-Wen Hsiao (13767916)

Subjects:

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with a fixed correlation value (0.3). by Yi-Wen Hsiao (13767916)

Subjects:

A graphic overview illustrates the random walk and permutation test in the <i>ceRNApairFiltering</i> method. by Yi-Wen Hsiao (13767916)

Subjects:

A graphic overview illustrates sorting and correlation calculation in the <i>ceRNApairFiltering</i> method. by Yi-Wen Hsiao (13767916)

Subjects:

Run time comparisons between published tools and our package. by Yi-Wen Hsiao (13767916)

Subjects: