Christophe Battail

This paper benchmarks synthetic data generation methods for clinical transcriptomic cancer data, finding no single method outperforms all metrics, with Gaussian Copula showing the most balanced performance.

This study develops a decellularized adipose tissue-derived hydrogel (atdECM) that supports pancreatic organoid growth with improved transcriptional profiles compared to Matrigel.

The paper evaluates immune-infiltrated patient-derived tumor organoids as preclinical models for renal cell carcinoma, showing they retain immune signatures and hypoxic signaling relevant to the original tumors.

The paper investigates the effect of a Y685F mutation in VE-cadherin on endothelial gene expression, identifying 884 differentially expressed genes and altered signaling pathways in vivo.

The paper expands the concept of MHC Class I peptide binding promiscuity to support vaccine discovery across cancers by analyzing data from 2,323 samples.

The paper identifies novel drug candidates for ALS and monogenic diseases by analyzing drug-induced gene expression changes in human pluripotent stem cells using RNA sequencing.

The paper identifies DNA methylation subtypes from transcriptomes to guide sunitinib and immunotherapy selection in renal cancer, finding hyper-methylated tumors respond better to atezolizumab plus bevacizumab.

The paper identifies key predictors of PD-1 blockade response in renal cell carcinoma by analyzing the tumor microenvironment of metastatic sites and developing a predictive TID score.

The paper develops COD-dipp to map MHC Class I antigens from cancer studies and identifies immune-relevant genomic regions for vaccine design.

The paper examines region-specific expression of paralogs in the human central nervous system using GTEx data, finding that young small-scale duplications (ySSDs) are more region-specific than other paralogs.

This study evaluates three RNA-seq library preparation kits for different input quantities and RNA types, showing TruSeq performs best at 100 ng, SMARTer at <1 ng, and SMARTer Ultra-Low for ultra-low inputs.