Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…Hierarchical clustering was computed using the scikit learn module in Python. C) Dendrogram of averaged functional connectivity from healthy subjects. …”

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

Effect of <i>|Δd</i>_<i>n</i><i>|</i> perturbation on 3D modeling. by Giacomo Janson (8138517)

Modeling with uniform <i>σ</i> values. by Giacomo Janson (8138517)

Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation" by Saeed Parsa (13893726)

“…</p> <p><br></p> <p>3. Algorithm</p> <p>Below is the main body of the test data generator program:</p> <p>  </p> <p>the main body of a Python program to generate test data for Python functions.…”

Tunable parameters in stimuli generation module. ^<i>a</i>The fixation cross is displayed once before an experiment starts to help subjects concentrate. <sup><i>b</i></su... by Gursimran Singh (575288)

CageCavityCalc (<i>C</i>3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages by Vicente Martí-Centelles (1422415)

“…Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce <i>CageCavityCalc</i> (<i>C</i>3), a Python-based tool for calculating the cavity size of molecular cages. …”

CageCavityCalc (<i>C</i>3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages by Vicente Martí-Centelles (1422415)

“…Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce <i>CageCavityCalc</i> (<i>C</i>3), a Python-based tool for calculating the cavity size of molecular cages. …”

CageCavityCalc (<i>C</i>3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages by Vicente Martí-Centelles (1422415)

“…Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce <i>CageCavityCalc</i> (<i>C</i>3), a Python-based tool for calculating the cavity size of molecular cages. …”

Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling by Giacomo Janson (8138517)

“…Python modules to harness this second strategy are freely available at <a href="https://github.com/pymodproject/altmod" target="_blank">https://github.com/pymodproject/altmod</a>. …”

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

“…BOFdat has a modular implementation that divides the BOF definition process into three independent modules defined here as steps: 1) the coefficients for major macromolecules are calculated, 2) coenzymes and inorganic ions are identified and their stoichiometric coefficients estimated, 3) the remaining species-specific metabolic biomass precursors are algorithmically extracted in an unbiased way from experimental data. …”

Table_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Image_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Presentation_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Integration of Morphoscanner with MDAnalysis, NGLview and Networkx. by Federico Fontana (533670)

Presentation_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Table_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Presentation_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Table_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)