[HTML][HTML] Integration strategies of multi-omics data for machine learning analysis
Increased availability of high-throughput technologies has generated an ever-growing
number of omics data that seek to portray many different but complementary biological …
number of omics data that seek to portray many different but complementary biological …
Unsupervised multi-omics data integration methods: a comprehensive review
Through the developments of Omics technologies and dissemination of large-scale
datasets, such as those from The Cancer Genome Atlas, Alzheimer's Disease Neuroimaging …
datasets, such as those from The Cancer Genome Atlas, Alzheimer's Disease Neuroimaging …
Computational approaches for network-based integrative multi-omics analysis
Advances in omics technologies allow for holistic studies into biological systems. These
studies rely on integrative data analysis techniques to obtain a comprehensive view of the …
studies rely on integrative data analysis techniques to obtain a comprehensive view of the …
Association predictions of genomics, proteinomics, transcriptomics, microbiome, metabolomics, pathomics, radiomics, drug, symptoms, environment factor, and …
Currently, the research of multi‐omics, such as genomics, proteinomics, transcriptomics,
microbiome, metabolomics, pathomics, and radiomics, are hot spots. The relationship …
microbiome, metabolomics, pathomics, and radiomics, are hot spots. The relationship …
[HTML][HTML] Effect of Hilbert-Huang transform on classification of PCG signals using machine learning
Ö Arslan, M Karhan - Journal of King Saud University-Computer and …, 2022 - Elsevier
Heartbeat sounds are biological signals used in the early diagnosis of cardiovascular
diseases. Digital heartbeat sound recordings, called phonocardiogram (PCG), are used in …
diseases. Digital heartbeat sound recordings, called phonocardiogram (PCG), are used in …
Machine learning-integrated omics for the risk and safety assessment of nanomaterials
With the advancement in nanotechnology, we are experiencing transformation in world
order with deep insemination of nanoproducts from basic necessities to advanced …
order with deep insemination of nanoproducts from basic necessities to advanced …
Advance computational tools for multiomics data learning
The burgeoning field of bioinformatics has seen a surge in computational tools tailored for
omics data analysis driven by the heterogeneous and high-dimensional nature of omics …
omics data analysis driven by the heterogeneous and high-dimensional nature of omics …
Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection
F Mikaeloff, M Gelpi, R Benfeitas, AD Knudsen… - Elife, 2023 - elifesciences.org
Multiomics technologies improve the biological understanding of health status in people
living with HIV on antiretroviral therapy (PWH). Still, a systematic and in-depth …
living with HIV on antiretroviral therapy (PWH). Still, a systematic and in-depth …
A denoised multi-omics integration framework for cancer subtype classification and survival prediction
J Pang, B Liang, R Ding, Q Yan… - Briefings in …, 2023 - academic.oup.com
The availability of high-throughput sequencing data creates opportunities to
comprehensively understand human diseases as well as challenges to train machine …
comprehensively understand human diseases as well as challenges to train machine …
Similarity network fusion for the integration of multi-omics and microbiomes in respiratory disease
Similarity network fusion (SNF) is increasingly employed for multi-omics and microbiome
data integration and assists patient endoty**. This Methods article describes its …
data integration and assists patient endoty**. This Methods article describes its …