Peyman Zarrineh

The paper uses machine learning on RNA-seq data to identify subtype-specific and prognostic enhancer RNAs in breast cancers, linking them to gene pathways and transcription factors.

The paper shows MEIS transcription factors are essential for activating cardiac-specific gene expression by working with lineage-restricted TFs to drive cardiac differentiation.

The paper identifies TEAD1 as a repressor of tissue-specific transcription factors in human organ development by analyzing combinatorial TF binding in enhancers.

The paper reconstructs a gene regulatory network directed by PBX1/2 and HAND2 in mouse limb development, showing their genetic interaction and tissue-specific function.

Motif2Site improves TF binding site detection by recentering motifs based on ChIP-seq signal, enhancing accuracy in mouse embryonic stem cells and heart tissues.

The paper investigates how HOX paralogs interact with TALE TFs to generate tissue-specific enhancer activation patterns in mouse embryos.

The paper uses deep learning to identify tissue-specific TF binding sites by analyzing ChIP-seq data from MEIS and HOXA2 in mouse branchial arches.