Mi Yang

Deciphering the Signaling Network Landscape of Breast Cancer Improves Drug Sensitivity Prediction

The paper uses single-cell proteomics and perturbation experiments to improve drug sensitivity predictions in breast cancer and identify genomic features associated with treatment response.

DreamAI: algorithm for the imputation of proteomics data

An ensemble of six imputation methods, built through the NCI-CPTAC Proteogenomics DREAM Challenge, fills missing values in labeled LC-MS/MS proteomics data, helping most for low-abundance proteins.

Stratification and prediction of drug synergy based on target functional similarity

The paper develops workflows to predict drug synergy based on target functional similarity and validates them in breast and colorectal cancer cell lines.

CELLector: Genomics Guided Selection of Cancer in vitro Models

CELLector selects relevant cancer cell lines based on patient genomic data to improve in vitro model relevance and bridge cell line screens to primary tumor sub-cohorts.

Linking drug target and pathway activation for effective therapy using multi-task learning

The paper uses multi-task learning to link drug targets and pathway activation, revealing interactions that guide tissue-specific combination therapies.

Genomic, Proteomic and Phenotypic Heterogeneity in HeLa Cells across Laboratories: Implications for Reproducibility of Research Results

This study quantifies genomic, proteomic, and phenotypic variability in HeLa cells across laboratories and passages, revealing implications for research reproducibility.

Genomic determinants of protein abundance variation in colorectal cancer cells

The paper quantifies proteomic and genomic variation in colorectal cancer cell lines to understand how mutations affect protein levels and drug responses.