Melissa J. Fullwood

AI4Loop uses deep learning to infer chromatin interactions from RNA-seq data, revealing increased interactions in tumors and identifying potential therapeutic compounds.

PlantConnectome extracts 5 million functional relationships from 71,000 plant biology abstracts using large language models and provides a database for gene-metabolite interactions and regulatory networks.

This study identifies NYH0002 as a compound that blocks ILF2, leading to DNA breaks and lethality in cancers with specific genetic profiles.

This study shows c-MYC can form phase condensates using its DNA binding domain, using optoDroplet system for dynamics analysis.

The paper demonstrates that disrupting super-silencers via EZH2 and REST inhibition reduces chromatin interactions and cancer growth.

MCIBox is a toolkit for analyzing single-molecule chromatin interactions and identifying micro-domains through visualization and clustering algorithms.

This study investigates how MYC overexpression affects chromatin interactions and c-Myc binding in cancer cells, revealing its role in stabilizing enhancer-promoter interactions and driving oncogene expression.

The paper identifies DiSCs, regions co-bound by SETDB1 and Cohesin, which regulate genome topology and stem cell fate in mouse embryonic stem cells.

The paper identifies 'super-silencers' formed by chromatin interactions that regulate apoptotic genes and shows that combining GSK343 and X5050 disrupts these silencers to induce antitumor effects.

ChINN predicts chromatin interactions from DNA sequences, showing good performance across samples and identifying sequence features associated with interactions in CLL patient data.

The paper identifies H3K27me3-rich regions as silencers that repress gene expression through chromatin interactions and shows their functional impact on cell identity and tumor growth.

The paper introduces Biop-C, a modified Hi-C method for analyzing 3D genome organization in solid cancer needle biopsy samples, and identifies TADs, loops, and FIREs in nasopharyngeal cancer.

The paper identifies essential enhancers for pluripotency in mouse ES cells using a CRISPR-Cas9 screen and characterizes their target genes and regulatory networks.

NanoVar accurately detects structural variants using low-depth Nanopore sequencing, achieving high F1 score in simulated data and uncovering normal alleles in patient samples.

This paper introduces CHINN, a method predicting chromatin interactions from DNA sequences, showing good performance across samples and detecting differences in CLL samples.

This study shows that loss of CTCF in mouse cardiomyocytes disrupts gene neighbourhoods, leading to ectopic enhancer-promoter interactions and heart failure.