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Map** cancer biology in space: applications and perspectives on spatial omics for oncology
Technologies to decipher cellular biology, such as bulk sequencing technologies and single-cell sequencing technologies, have greatly assisted novel...
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Introduction to Multi-Omics
The rapid development of technologies and informatics tools for producing and interpreting massive biological data sets (omics data) has resulted in...
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Graph machine learning for integrated multi-omics analysis
Multi-omics experiments at bulk or single-cell resolution facilitate the discovery of hypothesis-generating biomarkers for predicting response to...
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Omics-based molecular classifications empowering in precision oncology
BackgroundIn the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and...
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Challenges and best practices in omics benchmarking
Technological advances enabling massively parallel measurement of biological features — such as microarrays, high-throughput sequencing and mass...
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Multimodal Omics Approaches to Aging and Age-Related Diseases
Aging is associated with a progressive decline in physiological capacities and an increased risk of aging-associated disorders. An increasing body of...
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Biomedical Applications: The Need for Multi-Omics
Multi-omics studies are urgently required for biomedical applications, not only because of the comprehensiveness of the omics that such multi-omics...
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Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases
Spatial multi-omic studies have emerged as a promising approach to comprehensively analyze cells in tissues, enabling the joint analysis of multiple...
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BANKSY unifies cell ty** and tissue domain segmentation for scalable spatial omics data analysis
Spatial omics data are clustered to define both cell types and tissue domains. We present Building Aggregates with a Neighborhood Kernel and Spatial...
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Multi-Omics Data Mining Techniques: Algorithms and Software
With the aid of cost-effective next-generation sequencing technologies, the datasets with multiple dimensions, called multi-omics or integrated...
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Cardiometabolic health, diet and the gut microbiome: a meta-omics perspective
Cardiometabolic diseases have become a leading cause of morbidity and mortality globally. They have been tightly linked to microbiome taxonomic and...
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Spatial multi-omics at subcellular resolution via high-throughput in situ pairwise sequencing
Technology for spatial multi-omics aids the discovery of new insights into cellular functions and disease mechanisms. Here we report the development...
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Introduction to Pulmonary Diseases and OMICS Approaches
Incidence of diseases affecting the respiratory tract and lungs have increased in the past few decades. Exposure to harmful environmental triggers,...
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Multi-omics integration with weighted affinity and self-diffusion applied for cancer subtypes identification
BackgroundCharacterizing cancer molecular subtypes is crucial for improving prognosis and individualized treatment. Integrative analysis of...
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Methods and applications for single-cell and spatial multi-omics
The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell...
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Technologies Used for Analysis of Extracellular Vesicle-Omics
Extracellular vesicles (EVs) are naturally occurring and secreted membrane vesicles that carry proteins, lipids, and RNAs (mRNAs, microRNAs [miRNAs],...
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Gene regulatory network inference in the era of single-cell multi-omics
The interplay between chromatin, transcription factors and genes generates complex regulatory circuits that can be represented as gene regulatory...
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Applying genomics in regulatory toxicology: a report of the ECETOC workshop on omics threshold on non-adversity
In a joint effort involving scientists from academia, industry and regulatory agencies, ECETOC’s activities in Omics have led to conceptual proposals...
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Parkinson’s Disease: Bioinspired Optimization Algorithms for Omics Datasets Monitoring
Omics data create several computational challenges related to their volume, high dimensionality, and complexity. A subfield of the computational...
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Parkinson’s Disease: Bioinspired Optimization Algorithms for Omics Datasets Monitoring
Omics data create several computational challenges related to their volume, high dimensionality, and complexity. A subfield of the computational...