A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data حسب Anthony S. Barente (14035175)

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An expectation-maximization algorithm for finding noninvadable stationary states. حسب Robert Marsland (8616483)

The ERAD pathway also contributes to ROMK mutant turnover in HEK293 cells. حسب Nga H. Nguyen (2075920)

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Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements حسب Pascal Wang (10130612)

"…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …"

Maximum values of overlapping normalized mutual information (LFK) producced by clustering algorithms. حسب Alexander Ponomarenko (3163383)

Top 15 biological process concepts from GO that are enriched and linked to the TMGs. حسب Ravinder Sharma (13154079)

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GLIM: Greedy algorithm for edge selection in LIM. حسب Maurits H. W. Oostenbroek (11331123)

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit حسب Gonzalo Colmenarejo (650249)

"…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …"

Functional enrichment of DEGs. حسب Man Wang (110466)

"…</p><p>Methods</p><p>The study employed a combination of differential expression analysis, weighted gene co-expression network analysis (WGCNA), and various machine learning algorithms to screen for characteristic genes. Gene set enrichment analysis (GSEA), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to evaluate relevant biological functions and pathways. …"

Performance of optimization algorithms in six different network types. حسب Maurits H. W. Oostenbroek (11331123)

Plot depicting the feature importance of the top 15 features of each model. حسب Aastha Vatsyayan (9981916)

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Scatterplot of class probability vs the predicted class for the XGBoost model across all VUS variants 251 exonic VUS variants that were a part of the validation dataset. حسب Aastha Vatsyayan (9981916)

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A complete list of the 73 features used in training the model, along with the ACMG attribute they provide information about, along with their description, as well as their datatype... حسب Aastha Vatsyayan (9981916)

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Scatterplot of class probability vs the actual ACMG class for the TabNet model across the validation set of 156 variants. حسب Aastha Vatsyayan (9981916)

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Model hyperparameters used for the XGBoost model. حسب Aastha Vatsyayan (9981916)

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The Precision-Recall curve of both the models. حسب Aastha Vatsyayan (9981916)

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S4 Table - حسب Aastha Vatsyayan (9981916)

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Train and validation accuracies of the TabNet model across 187 epochs. حسب Aastha Vatsyayan (9981916)

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Primers used in site-directed mutagenesis. حسب Aastha Vatsyayan (9981916)

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The overview of the workflow followed for model development and variant classification with TabNet and XGBoost models. حسب Aastha Vatsyayan (9981916)

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