Supervised and unsupervised deep learning-based approaches for studying DNA replication spatiotemporal dynamics

Supervised and unsupervised deep learning-based approaches for studying DNA replication spatiotemporal dynamics

Abstract In eukaryotic cells, DNA replication is organised both spatially and temporally, as evidenced by the stage-specific spatial distribution of replication foci in the nucleus. Despite the genetic association of aberrant DNA replication with numerous human diseases, the labour-intensive methods...

Full description

Saved in:

Bibliographic Details
Main Authors:	Julian Ng-Kee-Kwong, Ben Philps, Fiona N. C. Smith, Aleksandra Sobieska, Naiming Chen, Constance Alabert, Hakan Bilen, Sara C. B. Buonomo
Format:	Article
Language:	English
Published:	Nature Portfolio 2025-02-01
Series:	Communications Biology
Online Access:	https://doi.org/10.1038/s42003-025-07744-2
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep supervised, but not unsupervised, models may explain IT cortical representation.
by: Seyed-Mahdi Khaligh-Razavi, et al.
Published: (2014-11-01)

Unsupervised selective labeling for semi-supervised industrial defect detection
by: Jian Ge, et al.
Published: (2024-10-01)

Unsupervised and Semi-Supervised Speech Recognition System: A Review
by: Mazin Al-Zakarya, et al.
Published: (2023-06-01)

Effectiveness of Supervised versus Unsupervised Exercise in Pregnancy – A Physiotherapist’s Perspective
by: Smita E. Joseph, et al.
Published: (2025-06-01)

A Workload Characterization Methodology Using Supervised and Unsupervised Deep Learning
by: Bing Hu, et al.
Published: (2024-01-01)

Unsupervised spatiotemporal classification of deformation patterns of embryonic tissues matches their fate map
by: David Pastor-Escuredo, et al.
Published: (2025-03-01)

The spatiotemporal program of DNA replication is associated with specific combinations of chromatin marks in human cells.
by: Franck Picard, et al.
Published: (2014-05-01)

EFFECTS OF TRANSITION FROM SUPERVISED CARDIAC REHABILITATION PROGRAM TO UNSUPERVISED IN INDIVIDUALS WITH HEART DISEASES
by: Mariana Romanholi Palma, et al.

From Clusters to Communities: Enhancing Wetland Vegetation Mapping Using Unsupervised and Supervised Synergy
by: Li Wen, et al.
Published: (2025-07-01)

An analytical assessment of credit card fraud detection techniques: Supervised, Unsupervised, and Reinforcement Learning
by: Abdourahman Djamal Djama
Published: (2025-01-01)

Leveraging molecular-QTL co-association to predict novel disease-associated genetic loci using a graph convolutional neural network.
by: Julian Ng-Kee-Kwong, et al.
Published: (2025-01-01)

Leveraging molecular-QTL co-association to predict novel disease-associated genetic loci using a graph convolutional neural network
by: Julian Ng-Kee-Kwong, et al.
Published: (2025-01-01)

Supervised and unsupervised self-testing for HIV in high- and low-risk populations: a systematic review.
by: Nitika Pant Pai, et al.
Published: (2013-01-01)

Optimizing Breast Cancer Classification: A Comparative Analysis of Supervised and Unsupervised Machine Learning Techniques
by: Prithwish Ghosh, et al.
Published: (2024-04-01)

Infrared Thermography-Based Insulator Fault Classification via Unsupervised Clustering and Semi-Supervised Learning
by: Usman Shafique, et al.
Published: (2024-01-01)

Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach
by: Akella S. Narasimha Raju, et al.
Published: (2025-01-01)

Optimization and Evaluation of Calibration for Low-cost Air Quality Sensors: Supervised and Unsupervised Machine Learning Models
by: Petar Zhivkov
Published: (2021-09-01)

Congestion Control Prediction Model for 5G Environment Based on Supervised and Unsupervised Machine Learning Approach
by: Mohammed B. Alshawki, et al.
Published: (2024-01-01)

Using Unsupervised and Supervised Machine Learning Methods to Correct Offset Anomalies in the GOES‐16 Magnetometer Data
by: F. Inceoglu, et al.
Published: (2021-12-01)

Supervised and unsupervised machine learning approaches for tree classification using multiwavelength airborne polarimetric LiDAR
by: Zhong Hu, et al.
Published: (2025-08-01)

Use of supervised and unsupervised approaches to make zonal application maps for variable-rate application of crop growth regulators in commercial cotton fields
by: Maria C. da S. Andrea, et al.
Published: (2025-01-01)

Self‐Supervised Classification of Weather Systems Based on Spatiotemporal Contrastive Learning
by: Liwen Wang, et al.
Published: (2022-08-01)

DNA Polymerase Gamma in Mitochondrial DNA Replication and Repair
by: William C. Copeland, et al.
Published: (2003-01-01)

Pedestrian trajectory prediction model based on self-supervised spatiotemporal graph network
by: Shiji Yang, et al.
Published: (2025-06-01)

Self-Supervised Spatiotemporal Representation Learning for Skeleton-Based Human Action Recognition
by: Jinhyeok Park, et al.
Published: (2025-01-01)

A Supervised Approach for Land Use Identification in Trento Using Mobile Phone Data as an Alternative to Unsupervised Clustering Techniques
by: Manuel Mendoza-Hurtado, et al.
Published: (2025-02-01)

Adherence to Artesunate-Amodiaquine Therapy for Uncomplicated Malaria in Rural Ghana: A Randomised Trial of Supervised versus Unsupervised Drug Administration
by: Kwaku Poku Asante, et al.
Published: (2009-01-01)

Supervised and unsupervised machine learning approaches for prediction and geographical discrimination of Iranian saffron ecotypes based on flower-related and phytochemical attributes
by: Seid Mohammad Alavi-Siney, et al.
Published: (2025-03-01)

A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment.
by: Tao Yu, et al.
Published: (2025-01-01)

SMS Scam Detection Application Based on Optical Character Recognition for Image Data Using Unsupervised and Deep Semi-Supervised Learning
by: Anjali Shinde, et al.
Published: (2024-09-01)

Global effects of DNA replication and DNA replication origin activity on eukaryotic gene expression
by: Larsson Omberg, et al.
Published: (2009-10-01)

Thermodynamic and Structural Analysis of DNA Damage Architectures Related to Replication
by: Nicholas J. Amato, et al.
Published: (2013-01-01)

Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data
by: Abu Bakker Siddique, et al.
Published: (2025-07-01)

Disentangling the Relationship Between Urinary Metal Exposure and Osteoporosis Risk Across a Broad Population: A Comprehensive Supervised and Unsupervised Analysis
by: Jianing Liu, et al.
Published: (2024-11-01)

Supervised and Unsupervised Screen Time and Its Association With Physical, Mental, and Social Health of School-Going Children in Dhaka, Bangladesh: Cross-Sectional Study
by: Shahria Hafiz Kakon, et al.
Published: (2025-01-01)

Hybrid Vision System for Enhanced Situational Awareness in Unmanned Surface Vehicles: Decision-Level Camera-LiDAR Fusion With Supervised and Unsupervised Approaches
by: Yousef Abd Alhattab, et al.
Published: (2025-01-01)

The DNA replication checkpoint targets the kinetochore to reposition DNA structure-induced replication damage to the nuclear periphery
by: Tyler M. Maclay, et al.
Published: (2025-08-01)

Unveiling structural change patterns: an unsupervised machine learning approach to long-term dynamics
by: Julián Salinas
Published: (2025-07-01)

Unsupervised Deep Clustering on Spatiotemporal Objects Extracted from 4D Point Clouds for Automatic Identification of Topographic Processes in Natural Environments
by: J. Wang, et al.
Published: (2025-07-01)

Continuous DNA replication is required for late gene transcription and maintenance of replication compartments in gammaherpesviruses.
by: Dajiang Li, et al.
Published: (2018-05-01)