Irina Pushel

This study integrates transcriptomic, proteomic, and phosphoproteomic data from two pediatric B-ALL subtypes to identify subtype-specific regulatory interactions and potential therapeutic targets.

This study presents a comprehensive bulk and single-cell transcriptional dataset of 69 pediatric leukemia patients, demonstrating its utility in improving leukemia characterization and clinical testing.

DeepSomatic is a deep learning method for detecting somatic variants from short-read and long-read sequencing data, outperforming existing callers, especially for indels.

Severus detects and characterizes somatic structural variations in tumor genomes using long reads, outperforming existing methods in accuracy and revealing clinically relevant rearrangements.

The paper identifies conserved and divergent transcriptional signatures in neural crest cells across chick and mouse embryos during migration.

This study shows that HiFi long-read sequencing can detect clinically relevant structural variants in pediatric leukemia, improving subtype classification.

The paper investigates how Hoxa2 specifies axial identity in mouse cranial neural crest cells using RNAseq, finding that Hoxa2-/- mutants show PA2 NCCs retaining PA2 signature without strong PA1 upregulation.

The paper identifies combinatorial binding of Hoxa1 and TALE proteins on genome-wide targets and reveals their cross-regulatory interactions.