<i>In silico</i> prediction of blood cholesterol levels from genotype data حسب Francesco Reggiani (5727733)

"…<div><p>In this work we present a framework for blood cholesterol levels prediction from genotype data. The predictor is based on an algorithm for cholesterol metabolism simulation available in literature, implemented and optimized by our group in the R language. …"

GSE96058 information. حسب Sepideh Zununi Vahed (9861298)

"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"

The performance of classifiers. حسب Sepideh Zununi Vahed (9861298)

"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"

DataSheet1_A machine learning-based radiomics model for prediction of tumor mutation burden in gastric cancer.docx حسب Tingting Ma (228102)

DataSheet_1_A Novel Radiogenomics Biomarker Based on Hypoxic-Gene Subset: Accurate Survival and Prognostic Prediction of Renal Clear Cell Carcinoma.doc حسب Jiahao Gao (7799222)

"…Building on this, a hypoxia-gene related radiogenomics biomarker (prediction of hypoxia-genes signature by contrast-enhanced CT radiomics) was constructed in the TCIA-KIRC database by extracting features in the venous phase of contrast-enhanced CT images, selecting features using the mRMR and LASSO algorithms, and building logistic regression models. …"

DataSheet1_PINet 1.0: A pathway network-based evaluation of drug combinations for the management of specific diseases.PDF حسب Yongkai Hong (13973343)

Bioinformatics pipeline for circadian function. حسب Patrick B. Schwartz (14782608)

"…<i>e</i>., pancreas) are inputted into CYCLOPS, and the population level data is reduced to two vectors (Eigengene 1 and Eigengene 2) derived from the seed genes. When plotted, the optimal Eigengene pair will demonstrate an ellipse, which indicates that the two Eigengenes are rhythmic and anti-phasic–this pair can then be used for each patient sample to determine the sample ‘time’, and thus the order of that sample relative to the 24-hr period (phase). …"