GraSPy: an Open Source Python Package for Statistical Connectomics by Benjamin Pedigo (6580352)

“…GraSPy builds on Python’s existing graph and machine learning ecosystem by accepting input from NetworkX and complying with the scikit-learn API. …”

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

Subjects:

Algorithmic assessment reveals functional implications of GABRD gene variants linked to idiopathic generalized epilepsy by Ayla Arslan (17943365)

“…</p> <p>The study identifies specific variants (L111R, R114C, D123N, G150S, and L243P) in the coding region of the GABRD gene, which are predicted as deleterious by multiple algorithms. …”

Root mean square fluctuation (RMSF) of the backbone atoms of the protein as a function of each amino acid residue. by L. F. S. Bonet (11502082)

KA-injected rats display deficits in gross hindlimb function after two weeks. by Naëmi Kuehn (17310359)

Subjects:

Algorithm for generating virtual patients. by Adrianne L. Jenner (11133854)

“…<b>3)</b> A simulated annealing algorithm is then used to determine a parameter set that optimises the objective function <i>J</i>(<i>p</i>) (<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1009753#ppat.1009753.e059" target="_blank">Eq 17</a>). …”

Functional annotation and PPI analysis of turquoise module genes. by Minhui Xi (20114243)

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

Subjects:

Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

Fixed-dimensional multimodal reference functions. by Ruiyu Zhan (21602031)

Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

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

Predictive Mixing for Density Functional Theory (and Other Fixed-Point Problems) by L. D. Marks (1949689)

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)

Accuracy, sensitivity, specificity and F-score. by Solomon Shiferaw Beyene (9143178)

The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)

Spectrograms extracted from the generalized S-transform corresponding to the adjustment parameters λ_<i>G</i> = 0.05, λ_<i>L</i> = 0.01. by Li Jiashen (20552690)

Generalized S-transform result plots of the signal h(t) corresponding to the fixed parameter λ_<i>G</i> = 2, adjusting the size of the parameter λ_<i>L</i>. by Li Jiashen (20552690)

Generalized S-transform result plots of the signal h(t) corresponding to the fixed parameter λ_<i>L</i> = 10, adjusting the size of the parameter λ_<i>G</i>. by Li Jiashen (20552690)