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Gene Expression

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Associations of maternal stress, gene expression, and newborn birthweight in the Democratic Republic of Congo.

American journal of biological anthropology
OBJECTIVES: Maternal stress has long been associated with lower birthweight, which is associated with adverse health outcomes including many adult diseases. The underlying mechanisms remain elusive although changes in gene expression may play a role....

Curcumin Modulates NOX Gene Expression and ROS Production via P-Smad3C in TGF-β-Activated Hepatic Stellate Cells.

Iranian biomedical journal
BACKGROUND: Liver fibrosis, associated with hepatic stellate cells (HSCs), occurs when a healthy liver sustains damage, thereby impairing its function. NADPH oxidases (NOXs), specifically isoforms 1, 2, and 4, play a role in reactive oxygen species (...

Machine learning ranking of plausible (un)explored synergistic gene combinations using sensitivity indices of time series measurements of Wnt signaling pathway.

Integrative biology : quantitative biosciences from nano to macro
Combinations of genes or proteins work in synergy at different times and durations in a signaling pathway. However, which combinations are prevalent at a particular time point or duration is mostly not known. Sensitivity analysis plays a major role i...

Self-supervised deep learning of gene-gene interactions for improved gene expression recovery.

Briefings in bioinformatics
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to gain biological insights at the cellular level. However, due to technical limitations of the existing sequencing technologies, low gene expression values are often omitted, lead...

Deep model predictive control of gene expression in thousands of single cells.

Nature communications
Gene expression is inherently dynamic, due to complex regulation and stochastic biochemical events. However, the effects of these dynamics on cell phenotypes can be difficult to determine. Researchers have historically been limited to passive observa...

An effective deep learning-based approach for splice site identification in gene expression.

Science progress
A crucial stage in eukaryote gene expression involves mRNA splicing by a protein assembly known as the spliceosome. This step significantly contributes to generating and properly operating the ultimate gene product. Since non-coding introns disrupt e...

Enhancing Gene Expression Predictions Using Deep Learning and Functional Annotations.

Genetic epidemiology
Transcriptome-wide association studies (TWAS) aim to uncover genotype-phenotype relationships through a two-stage procedure: predicting gene expression from genotypes using an expression quantitative trait locus (eQTL) data set, then testing the pred...

A Multi-Omics, Machine Learning-Aware, Genome-Wide Metabolic Model of Bacillus Subtilis Refines the Gene Expression and Cell Growth Prediction.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Given the extensive heterogeneity and variability, understanding cellular functions and regulatory mechanisms through the analysis of multi-omics datasets becomes extremely challenging. Here, a comprehensive modeling framework of multi-omics machine ...

Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-Terminal Coding Sequences.

ACS synthetic biology
N-terminal coding sequence (NCS) influences gene expression by impacting the translation initiation rate. The NCS optimization problem is to find an NCS that maximizes gene expression. The problem is important in genetic engineering. However, current...