The Blood–Brain Barrier (BBB) Score by Mayuri Gupta (1886839)

“…An algorithm, designated “BBB Score”, composed of stepwise and polynomial piecewise functions, is herein proposed for predicting BBB penetration based on five physicochemical descriptors: number of aromatic rings, heavy atoms, MWHBN (a descriptor comprising molecular weight, hydrogen bond donor, and hydrogen bond acceptors), topological polar surface area, and pKa. …”

The Blood–Brain Barrier (BBB) Score by Mayuri Gupta (1886839)

“…An algorithm, designated “BBB Score”, composed of stepwise and polynomial piecewise functions, is herein proposed for predicting BBB penetration based on five physicochemical descriptors: number of aromatic rings, heavy atoms, MWHBN (a descriptor comprising molecular weight, hydrogen bond donor, and hydrogen bond acceptors), topological polar surface area, and pKa. …”

The PS-VAE enables a detailed brain region-to-behavior mapping in the two-view mouse dataset. by Matthew R. Whiteway (11467528)

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Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

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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.…”

Data_Sheet_1_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX by Raymond Salvador (813880)

“…On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. …”

Data_Sheet_2_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX by Raymond Salvador (813880)

“…On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. …”

Data_Sheet_3_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX by Raymond Salvador (813880)

“…On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. …”

Consistency of model-derived predictive patterns as a function of sample diversity. by Oualid Benkarim (9707986)

Classification accuracy and information transfer rate (ITR) as a function of the measurement set-up and the number of combined trials. by Dovilė Kurmanavičiūtė (21072549)

Confusion matrices of machine learning models trained on data oversampled by SMOTE and data trained with class weights given to the loss function. by Lucas Teoh (12878206)

Spatial characterization and cell-type-specific genes in mouse brain tissue. by Huamei Li (8815955)

Average Friedman test ranks (left) and pairwise average Wilcoxon signed-rank test p-values (right) for all compared optimization algorithms across CL, C17, C19, C21, C22, and RWPs. by Mahmood A. Jumaah (22272371)

List of Abbreviations by Gursimran Singh (575288)

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The results of ICA performed using PyNoetic. by Gursimran Singh (575288)

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Data_Sheet_1_A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks.docx by Maria Grazia Puxeddu (10211162)

“…Finally, as a proof of concept, we show an application of the algorithms to real functional brain networks derived from EEG signals collected at rest with closed and open eyes. …”

Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

The workflow used to analyze imbalanced and balanced sequences. by Solomon Shiferaw Beyene (9143178)

Performances of Naïve Bayes (NB), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM) and K- Nearest Neighbors (KNN). by Solomon Shiferaw Beyene (9143178)