Viviana I. Risca

This paper introduces CAD-C, a new chromatin conformation capture method that improves resolution and efficiency over existing techniques like Micro-C and Hi-C.

The paper directly measures sub-kilobase chromatin structure using RICC-seq 2.0 and finds that linker histone H1 broadly compacts chromatin, with differential effects on gene expression and epigenetic states.

This study compares the SASP and transcriptional profiles induced by CDK4/6 inhibitors and DNA damage, revealing delayed NF-κB activation in CDK4/6i.

This study identifies a nucleosome switch that primes Hepatitis B Virus infection by driving X gene transcription and shows that CBL137 inhibits this process.

Learning and removing Tn5/DNase-I sequence bias lets a small base-resolution CNN (ChromBPNet) recover TF motifs and footprints from accessibility data and rival Enformer at predicting chromatin QTL effects.

This paper develops a modeling framework to interpret RICC-seq data by simulating oligonucleosome structures and extracting nucleosome repeat lengths using a convolutional neural network.

The paper introduces an open-source protocol for producing and characterizing hyperactive Tn5 transposase for use in various sequencing applications.

The paper identifies dynamic cis-regulatory elements in epidermal differentiation using multi-omic data and deep learning, revealing combinatorial motif rules linked to gene expression and polygenic skin disease.

This paper introduces ChAR-seq, a method to map RNA-to-DNA contacts genome-wide, identifying chromatin-bound RNA targets such as nascent transcripts and trans-associated RNAs.

Omni-ATAC improves ATAC-seq by reducing background noise and enabling analysis of frozen tissues, revealing disease-associated DNA element activities in human brain structures.