Hilal Kazan

The paper identifies a transcriptional continuum from normal to lesional skin in psoriasis using single-cell RNA sequencing and trajectory analysis, revealing cell-type-specific state transitions.

The paper evaluates existing batch integration metrics in scRNA-seq and introduces sBEE, a new metric that provides more reliable assessments of batch mixing across diverse scenarios.

PersonaDrive identifies and prioritizes patient-specific cancer drivers by integrating genomic data, pathways, and protein connectivity, outperforming existing methods on TCGA and cell-line data.

The paper introduces a network-centric framework to evaluate mutual exclusivity tests for cancer drivers, addressing limitations in current evaluation methods by incorporating network knowledge and resolving confounding factors.

BetweenNet identifies cancer driver genes by integrating genomic data with protein-protein interaction networks using betweenness centrality and random walks, outperforming existing methods in recovering known cancer genes.

DriveWays identifies overlapping cancer driver pathways by solving an NP-hard optimization problem, outperforming existing methods on TCGA data.

MEXCOWalk identifies cancer driver modules using mutual exclusion and coverage in protein-protein interaction networks, outperforming existing methods on TCGA data.

RBPSponge identifies lncRNAs that act as sponges for RBPs by analyzing RBP binding sites and CLIP peaks on lncRNAs.