AIMC Topic: Gene Regulatory Networks

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Integrating bioinformatics and machine learning to identify glomerular injury genes and predict drug targets in diabetic nephropathy.

Scientific reports
Diabetes mellitus (DM) is a chronic metabolic disorder that poses significant challenges to public health. Among its various complications, diabetic nephropathy (DN) emerges as a critical microvascular complication associated with high mortality rate...

Transcriptomics-based exploration of ubiquitination-related biomarkers and potential molecular mechanisms in laryngeal squamous cell carcinoma.

BMC medical genomics
BACKGROUND: One of the most common and prevalent cancers is laryngeal squamous cell carcinoma (LSCC), which poses a great threat to the life and health of the patient. Nonetheless, it has been demonstrated that ubiquitination is crucial for the devel...

NetLnc: A Network-Based Computational Framework to Identify Immune Checkpoint-Related lncRNAs for Immunotherapy Response in Melanoma.

International journal of molecular sciences
Long non-coding RNAs (lncRNAs) could alter the tumor immune microenvironment and regulate the expression of immune checkpoints (ICPs) by regulating target genes in tumors. However, only a few lncRNAs have precise functions in immunity and potential f...

Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency.

The Plant cell
Systems biology aims to uncover gene regulatory networks (GRNs) for agricultural traits, but validating them in crops is challenging. We addressed this challenge by learning and validating model-to-crop transcription factor (TF) regulons governing ni...

Identification of Hub Genes and Key Pathways Associated with Sepsis Progression Using Weighted Gene Co-Expression Network Analysis and Machine Learning.

International journal of molecular sciences
Sepsis is a life-threatening condition driven by dysregulated immune responses, resulting in organ dysfunction and high mortality rates. Identifying key genes and pathways involved in sepsis progression is crucial for improving diagnostic and therape...

GAEDGRN: reconstruction of gene regulatory networks based on gravity-inspired graph autoencoders.

Briefings in bioinformatics
Reconstructing high-resolution gene regulatory networks (GRNs) based on single-cell RNA sequencing data provides an opportunity to gain insight into disease pathogenesis. At present, there are a large number of GRN reconstruction methods based on gra...

Oxidative Phosphorylation Pathway in Ankylosing Spondylitis: Multi-Omics Analysis and Machine Learning.

International journal of rheumatic diseases
INTRODUCTION: Ankylosing spondylitis (AS) is a chronic inflammatory disease affecting the axial skeleton, characterized by immune microenvironment dysregulation and elevated cytokines like TNF-α and IL-17. Mitochondrial oxidative phosphorylation (OXP...

[Machine learning-aided design of synthetic biological parts and circuits].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Synthetic biology is an emerging interdisciplinary field at the convergence of biology, engineering, and computer science. It employs a bottom-up approach to progressively design biological parts, devices, and circuits, aiming to create artificial bi...