Benjamin J. Lengerich

Cell-Level Virtual Screening

This paper introduces CellVS-Net, a cell-level virtual screening model that outperforms existing methods on two benchmarks, demonstrating its viability as an alternative to molecular-level drug screening.

Learning to Estimate Sample-specific Transcriptional Networks for 7000 Tumors

The paper introduces contextualized network inference to estimate sample-specific transcriptional networks for 7000 tumors, improving accuracy and enabling novel prognostic subtyping.

Integrating single-cell RNA-seq datasets with substantial batch effects

This paper improves scRNA-seq dataset integration by introducing regularization strategies for cVAEs, enhancing batch correction while preserving biological variation.

Differential Principal Components Reveal Patterns of Differentiation in Case/Control Studies

The paper introduces drPCA, a supervised dimensionality reduction method that improves differentiation in case/control studies by using differential vectors, and shows it outperforms PCA and PLS-DA in cancer gene expression datasets.

Personalized Regression Enables Sample-Specific Pan-Cancer Analysis

This paper introduces a personalized regression method to analyze pan-cancer gene expression data, revealing sample-specific patterns that population-level methods miss.

Opportunities And Obstacles For Deep Learning In Biology And Medicine

Deep learning rivals or beats baselines across imaging, health records, genomics and drug discovery but is not yet transformative; scarce labels, privacy and opacity remain hurdles.