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

Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics by Paolo Cifani (1575613)

“…Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. …”

Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics by Paolo Cifani (1575613)

“…Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. …”

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

“…GEM-guided predictions of growth phenotypes rely on the accurate definition of a biomass objective function (BOF) that is designed to include key cellular biomass components such as the major macromolecules (DNA, RNA, proteins), lipids, coenzymes, inorganic ions and species-specific components. …”

datasheet1_ThermoScan: Semi-automatic Identification of Protein Stability Data From PubMed.xlsx by Paola Turina (10431428)

“…The collection of such data has been essential for the development and assessment of tools predicting the impact of protein variants at functional and structural levels. …”

presentation1_ThermoScan: Semi-automatic Identification of Protein Stability Data From PubMed.pdf by Paola Turina (10431428)

“…The collection of such data has been essential for the development and assessment of tools predicting the impact of protein variants at functional and structural levels. …”

Known compounds and new lessons: structural and electronic basis of flavonoid-based bioactivities by Rohan J. Meshram (6563189)

“…The current report thus focuses on providing an electronic explanation of these bioactivities using density functional theory-based quantum chemical descriptors. …”

Code by Baoqiang Chen (21099509)

“…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”

Core data by Baoqiang Chen (21099509)

“…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”

Expression vs genomics for predicting dependencies by Broad DepMap (5514062)

“…</p><p dir="ltr"><br></p><p dir="ltr">PerturbationInfo.csv: Additional drug annotations for the PRISM and GDSC17 datasets</p><p dir="ltr"><br></p><p dir="ltr">ApproximateCFE.hdf5: A set of Cancer Functional Event cell features based on CCLE data, adapted from Iorio et al. 2016 (10.1016/j.cell.2016.06.017)</p><p dir="ltr"><br></p><p dir="ltr">DepMapSampleInfo.csv: sample info from DepMap_public_19Q4 data, reproduced here as a convenience.…”