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The landscape of aging
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 …
impaired functional ability and ultimately increased susceptibility to death. It is a major risk …
Applications of multi‐omics analysis in human diseases
Multi‐omics usually refers to the crossover application of multiple high‐throughput screening
technologies represented by genomics, transcriptomics, single‐cell transcriptomics …
technologies represented by genomics, transcriptomics, single‐cell transcriptomics …
Current progress and open challenges for applying deep learning across the biosciences
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 …
challenges in computational biology: the half-century-old problem of protein structure …
Multimodal data fusion for cancer biomarker discovery with deep learning
Technological advances have made it possible to study a patient from multiple angles with
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …
Web-based multi-omics integration using the Analyst software suite
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 …
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
With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …
become essential for biomedical studies to undertake an integrative (combined) approach to …
Bayesian statistics and modelling
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 …
available knowledge about parameters in a statistical model is updated with the information …
Computational principles and challenges in single-cell data integration
The development of single-cell multimodal assays provides a powerful tool for investigating
multiple dimensions of cellular heterogeneity, enabling new insights into development …
multiple dimensions of cellular heterogeneity, enabling new insights into development …
A roadmap for multi-omics data integration using deep learning
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 …
amount of multi-omics data for various applications. These data have revolutionized …
DNA methylation-based predictors of health: applications and statistical considerations
DNA methylation data have become a valuable source of information for biomarker
development, because, unlike static genetic risk estimates, DNA methylation varies …
development, because, unlike static genetic risk estimates, DNA methylation varies …