The landscape of aging

Y Cai, W Song, J Li, Y **g, C Liang, L Zhang… - Science China Life …, 2022‏ - Springer
Aging is characterized by a progressive deterioration of physiological integrity, leading to
impaired functional ability and ultimately increased susceptibility to death. It is a major risk …

Applications of multi‐omics analysis in human diseases

C Chen, J Wang, D Pan, X Wang, Y Xu, J Yan… - MedComm, 2023‏ - Wiley Online Library
Multi‐omics usually refers to the crossover application of multiple high‐throughput screening
technologies represented by genomics, transcriptomics, single‐cell transcriptomics …

Current progress and open challenges for applying deep learning across the biosciences

N Sapoval, A Aghazadeh, MG Nute… - Nature …, 2022‏ - nature.com
Deep Learning (DL) has recently enabled unprecedented advances in one of the grand
challenges in computational biology: the half-century-old problem of protein structure …

Multimodal data fusion for cancer biomarker discovery with deep learning

S Steyaert, M Pizurica, D Nagaraj… - Nature machine …, 2023‏ - nature.com
Technological advances have made it possible to study a patient from multiple angles with
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …

Web-based multi-omics integration using the Analyst software suite

JD Ewald, G Zhou, Y Lu, J Kolic, C Ellis, JD Johnson… - Nature …, 2024‏ - nature.com
The growing number of multi-omics studies demands clear conceptual workflows coupled
with easy-to-use software tools to facilitate data analysis and interpretation. This protocol …

Using machine learning approaches for multi-omics data analysis: A review

PS Reel, S Reel, E Pearson, E Trucco… - Biotechnology advances, 2021‏ - Elsevier
With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …

Bayesian statistics and modelling

R Van de Schoot, S Depaoli, R King… - Nature Reviews …, 2021‏ - nature.com
Bayesian statistics is an approach to data analysis based on Bayes' theorem, where
available knowledge about parameters in a statistical model is updated with the information …

Computational principles and challenges in single-cell data integration

R Argelaguet, ASE Cuomo, O Stegle… - Nature biotechnology, 2021‏ - nature.com
The development of single-cell multimodal assays provides a powerful tool for investigating
multiple dimensions of cellular heterogeneity, enabling new insights into development …

A roadmap for multi-omics data integration using deep learning

M Kang, E Ko, TB Mersha - Briefings in Bioinformatics, 2022‏ - academic.oup.com
High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …

DNA methylation-based predictors of health: applications and statistical considerations

PD Yousefi, M Suderman, R Langdon… - Nature Reviews …, 2022‏ - nature.com
DNA methylation data have become a valuable source of information for biomarker
development, because, unlike static genetic risk estimates, DNA methylation varies …