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Multi-Omics Databases
The omics technology has been increasingly used in medical research since the emergence of the next-generation sequencing technology and big data...
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TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology
Cancer is a complex disease composing systemic alterations in multiple scales. In this study, we develop the Tumor Multi-Omics pre-trained Network...
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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...
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Multi-omics and Its Clinical Application
With the rise of the severity of diseases the need to devise a predictive mechanism that ensures early and precise detection has increased. To...
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Technology for Studying Multi-omics
The transformation and advancements over the recent decade in technology have undoubtedly reshaped and revolutionized insight as well as the research...
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Deciphering spatial domains from spatial multi-omics with SpatialGlue
Advances in spatial omics technologies now allow multiple types of data to be acquired from the same tissue slice. To realize the full potential of...
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The technological landscape and applications of single-cell multi-omics
Single-cell multi-omics technologies and methods characterize cell states and activities by simultaneously integrating various single-modality omics...
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Multi-omics integration identifies regulatory factors underlying bovine subclinical mastitis
BackgroundMastitis caused by multiple factors remains one of the most common and costly disease of the dairy industry. Multi-omics approaches enable...
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Multi-Omics Analysis of the Human Microbiome From Technology to Clinical Applications
This book introduces the rapidly evolving field of multi-omics in understanding the human microbiome. The book focuses on the technology used to...
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Single Cell Atlas: a single-cell multi-omics human cell encyclopedia
Single-cell sequencing datasets are key in biology and medicine for unraveling insights into heterogeneous cell populations with unprecedented...
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MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder
BackgroundIntegrating multi-omics data is emerging as a critical approach in enhancing our understanding of complex diseases. Innovative...
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Multi-omics in Viral Microbiome
The human virus microbiome, also known as the human virome, comprises the viruses that reside on or within the human body, either as pathogens or as...
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Multi-omics in Study of Oral Microbiome
Dental health and disease correlate with the ability of oral microbes to compose and perform their functions, along with interactions between...
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Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials
Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack...
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A semi-supervised approach for the integration of multi-omics data based on transformer multi-head self-attention mechanism and graph convolutional networks
Background and objectivesComprehensive analysis of multi-omics data is crucial for accurately formulating effective treatment plans for complex...
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Multi-omics in Prospecting of Genes of Biotechnological Importance
A novel multi-omics method combines the data sets from several omics grou**s such as genomics, transcriptomics, proteomics, metabolomics,...
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Multi-omics in Study of Lung Microbiome
The lung microbiome influences the pathophysiology of pulmonary diseases, including asthma, chronic obstructive pulmonary disease (COPD), and cystic...
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Progress in single-cell multimodal sequencing and multi-omics data integration
With the rapid advance of single-cell sequencing technology, cell heterogeneity in various biological processes was dissected at different omics...
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Holomics - a user-friendly R shiny application for multi-omics data integration and analysis
An organism’s observable traits, or phenotype, result from intricate interactions among genes, proteins, metabolites and the environment. External...
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Classifying breast cancer subtypes on multi-omics data via sparse canonical correlation analysis and deep learning
BackgroundClassifying breast cancer subtypes is crucial for clinical diagnosis and treatment. However, the early symptoms of breast cancer may not be...
