Regulation of genome organization and gene expression by nuclear mechanotransduction

C Uhler, GV Shivashankar - Nature reviews Molecular cell biology, 2017 - nature.com
It is well established that cells sense chemical signals from their local microenvironment and
transduce them to the nucleus to regulate gene expression programmes. Although a number …

Machine learning meets omics: applications and perspectives

R Li, L Li, Y Xu, J Yang - Briefings in Bioinformatics, 2022 - academic.oup.com
The innovation of biotechnologies has allowed the accumulation of omics data at an
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …

Enter the matrix: factorization uncovers knowledge from omics

GL Stein-O'Brien, R Arora, AC Culhane, AV Favorov… - Trends in Genetics, 2018 - cell.com
Omics data contain signals from the molecular, physical, and kinetic inter-and intracellular
interactions that control biological systems. Matrix factorization (MF) techniques can reveal …

Dissecting super-enhancer hierarchy based on chromatin interactions

J Huang, K Li, W Cai, X Liu, Y Zhang, SH Orkin… - Nature …, 2018 - nature.com
Recent studies have highlighted super-enhancers (SEs) as important regulatory elements
for gene expression, but their intrinsic properties remain incompletely characterized …

Epigenetic landscapes reveal transcription factors that regulate CD8+ T cell differentiation

B Yu, K Zhang, JJ Milner, C Toma, R Chen… - Nature …, 2017 - nature.com
Dynamic changes in the expression of transcription factors (TFs) can influence the
specification of distinct CD8+ T cell fates, but the observation of equivalent expression of TFs …

DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops

FY Dao, H Lv, D Zhang, ZM Zhang… - Briefings in …, 2021 - academic.oup.com
Abstract The protein Yin Yang 1 (YY1) could form dimers that facilitate the interaction
between active enhancers and promoter-proximal elements. YY1-mediated enhancer …

Epigenetics analysis and integrated analysis of multiomics data, including epigenetic data, using artificial intelligence in the era of precision medicine

R Hamamoto, M Komatsu, K Takasawa, K Asada… - Biomolecules, 2019 - mdpi.com
To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations
have been actively conducted for a long time, and a large number of achievements have …

DeepTACT: predicting 3D chromatin contacts via bootstrap** deep learning

W Li, WH Wong, R Jiang - Nucleic acids research, 2019 - academic.oup.com
Interactions between regulatory elements are of crucial importance for the understanding of
transcriptional regulation and the interpretation of disease mechanisms. Hi-C technique has …

A supervised learning framework for chromatin loop detection in genome-wide contact maps

TJ Salameh, X Wang, F Song, B Zhang… - Nature …, 2020 - nature.com
Accurately predicting chromatin loops from genome-wide interaction matrices such as Hi-C
data is critical to deepening our understanding of proper gene regulation. Current …

Predicting enhancer‐promoter interaction from genomic sequence with deep neural networks

S Singh, Y Yang, B Póczos, J Ma - Quantitative Biology, 2019 - Wiley Online Library
Background In the human genome, distal enhancers are involved in regulating target genes
through proximal promoters by forming enhancer‐promoter interactions. Although recently …