Machine and deep learning meet genome-scale metabolic modeling
Omic data analysis is steadily growing as a driver of basic and applied molecular biology
research. Core to the interpretation of complex and heterogeneous biological phenotypes …
research. Core to the interpretation of complex and heterogeneous biological phenotypes …
Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications
M Su, T Pan, QZ Chen, WW Zhou, Y Gong, G Xu… - Military Medical …, 2022 - Springer
The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has
advanced our understanding of the pathogenesis of disease and provided valuable insights …
advanced our understanding of the pathogenesis of disease and provided valuable insights …
[HTML][HTML] Metabolic modeling of single Th17 cells reveals regulators of autoimmunity
Metabolism is a major regulator of immune cell function, but it remains difficult to study the
metabolic status of individual cells. Here, we present Compass, an algorithm to characterize …
metabolic status of individual cells. Here, we present Compass, an algorithm to characterize …
Analyzing cell-type-specific dynamics of metabolism in kidney repair
A common drawback of metabolic analyses of complex biological samples is the inability to
consider cell-to-cell heterogeneity in the context of an organ or tissue. To overcome this …
consider cell-to-cell heterogeneity in the context of an organ or tissue. To overcome this …
Decoding aging hallmarks at the single-cell level
S Ma, X Chi, Y Cai, Z Ji, S Wang, J Ren… - Annual Review of …, 2023 - annualreviews.org
Organismal aging exhibits wide-ranging hallmarks in divergent cell types across tissues,
organs, and systems. The advancement of single-cell technologies and generation of rich …
organs, and systems. The advancement of single-cell technologies and generation of rich …
A graph neural network model to estimate cell-wise metabolic flux using single-cell RNA-seq data
The metabolic heterogeneity and metabolic interplay between cells are known as significant
contributors to disease treatment resistance. However, with the lack of a mature high …
contributors to disease treatment resistance. However, with the lack of a mature high …
Tumor heterogeneity: preclinical models, emerging technologies, and future applications
Heterogeneity describes the differences among cancer cells within and between tumors. It
refers to cancer cells describing variations in morphology, transcriptional profiles …
refers to cancer cells describing variations in morphology, transcriptional profiles …
[HTML][HTML] Toward modeling metabolic state from single-cell transcriptomics
Background Single-cell metabolic studies bring new insights into cellular function, which can
often not be captured on other omics layers. Metabolic information has wide applicability …
often not be captured on other omics layers. Metabolic information has wide applicability …
A review of computational strategies for denoising and imputation of single-cell transcriptomic data
Motivation The advancements of single-cell sequencing methods have paved the way for
the characterization of cellular states at unprecedented resolution, revolutionizing the …
the characterization of cellular states at unprecedented resolution, revolutionizing the …
INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation
Metabolism is directly and indirectly fine-tuned by a complex web of interacting regulatory
mechanisms that fall into two major classes. On the one hand, the expression level of the …
mechanisms that fall into two major classes. On the one hand, the expression level of the …