[HTML][HTML] Machine learning: a new prospect in multi-omics data analysis of cancer
B Arjmand, SK Hamidpour, A Tayanloo-Beik… - Frontiers in …, 2022 - frontiersin.org
Cancer is defined as a large group of diseases that is associated with abnormal cell growth,
uncontrollable cell division, and may tend to impinge on other tissues of the body by different …
uncontrollable cell division, and may tend to impinge on other tissues of the body by different …
[HTML][HTML] Artificial intelligence (AI)-based systems biology approaches in multi-omics data analysis of cancer
N Biswas, S Chakrabarti - Frontiers in Oncology, 2020 - frontiersin.org
Cancer is the manifestation of abnormalities of different physiological processes involving
genes, DNAs, RNAs, proteins, and other biomolecules whose profiles are reflected in …
genes, DNAs, RNAs, proteins, and other biomolecules whose profiles are reflected in …
[HTML][HTML] Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis
O Menyhárt, B Győrffy - Computational and structural biotechnology journal, 2021 - Elsevier
While cost-effective high-throughput technologies provide an increasing amount of data, the
analyses of single layers of data seldom provide causal relations. Multi-omics data …
analyses of single layers of data seldom provide causal relations. Multi-omics data …
Artificial intelligence-based multi-omics analysis fuels cancer precision medicine
With biotechnological advancements, innovative omics technologies are constantly
emerging that have enabled researchers to access multi-layer information from the genome …
emerging that have enabled researchers to access multi-layer information from the genome …
The crucial role of multiomic approach in cancer research and clinically relevant outcomes
M Lu, X Zhan - EPMA Journal, 2018 - Springer
Cancer with heavily economic and social burden is the hot point in the field of medical
research. Some remarkable achievements have been made; however, the exact …
research. Some remarkable achievements have been made; however, the exact …
A systematic review on biomarker identification for cancer diagnosis and prognosis in multi-omics: from computational needs to machine learning and deep learning
Biomarkers, also known as biological markers, are substances like transcripts,
deoxyribonucleic acid (DNA), genes, proteins, and metabolites that indicate whether a …
deoxyribonucleic acid (DNA), genes, proteins, and metabolites that indicate whether a …
Onco‐multi‐OMICS approach: a new frontier in cancer research
The acquisition of cancer hallmarks requires molecular alterations at multiple levels
including genome, epigenome, transcriptome, proteome, and metabolome. In the past …
including genome, epigenome, transcriptome, proteome, and metabolome. In the past …
Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration
Multiomics data including imaging radiomics and various types of molecular biomarkers
have been increasingly investigated for better diagnosis and therapy in the era of precision …
have been increasingly investigated for better diagnosis and therapy in the era of precision …
Multi-omics model applied to cancer genetics
In this review, we focus on bioinformatic oncology as an integrative discipline that
incorporates knowledge from the mathematical, physical, and computational fields to further …
incorporates knowledge from the mathematical, physical, and computational fields to further …
Epigenetics analysis and integrated analysis of multiomics data, including epigenetic data, using artificial intelligence in the era of precision medicine
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 …
have been actively conducted for a long time, and a large number of achievements have …