AIMC Topic: Gene Regulatory Networks

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GeneRAIN: multifaceted representation of genes via deep learning of gene expression networks.

Genome biology
We develop GeneRAIN, a suite of Transformer-based models that learn gene expression relationships from 410 K human bulk RNA-seq samples. Featuring a novel Binning-By-Gene normalization technique, our models capture diverse biological information beyo...

Integrative analysis identifies FERMT3 as a key regulator of metabolic reprogramming in keloid scarring and metabolic syndrome.

Functional & integrative genomics
 Keloid scarring and Metabolic Syndrome (MS) are distinct conditions marked by chronic inflammation and tissue dysregulation, suggesting shared pathogenic mechanisms. Identifying common regulatory genes could unveil novel therapeutic targets. Methods...

HLX and SLC25A20: Immunologic regulators bridging ankylosing spondylitis and uveitis via multi-omics integration and machine learning.

PloS one
BACKGROUND: Ankylosing spondylitis (AS), a chronic inflammatory disorder affecting axial joints, is frequently complicated by uveitis. However, the molecular mechanisms linking AS to secondary uveitis remain poorly understood.

Comprehensive analysis of disulfidptosis-related genes in pulmonary hypertension through machine learning and immune infiltration: Spotlight on USP32 and ZNF655 as key regulators.

PloS one
BACKGROUND: Disulfidptosis, a novel cellular death manner, has yet to be fully explored within the context of pulmonary arterial hypertension (PAH). This study aims to identify genes implicated in PAH that are involved in disulfidptosis.

CELLM: Bridging Natural Language Processing and Synthetic Genetic Circuit Design with AI.

ACS synthetic biology
The complexity of the genetic circuit design limits accessibility and efficiency in synthetic biology. This study presents an integrated system that combines Cello software with large language models (DeepSeek-R1, Phi-4) and the LangChain framework i...

Uncovering key biomarkers, potential therapeutic targets and development of deep learning model in heart failure.

PloS one
Heart failure (HF) represents a significant public health concern, characterized by elevated rates of mortality and morbidity. Recent advancements in gene sequencing technologies have led to the identification of numerous genes associated with heart ...

Diagnostic PANoptosis-related genes in acute kidney injury: bioinformatics, machine learning, and validation.

Annals of medicine
BACKGROUND: Acute kidney injury (AKI) is a prevalent and life-threatening condition characterized by abrupt renal function decline and subsequent inflammatory cascades. PANoptosis has emerged as a significant contributor to the pathophysiology of AKI...

ACO1 OGDH axis drives mitochondrial immune crosstalk in preeclampsia through systems biology enabling dual target therapy.

Scientific reports
Preeclampsia (PE), a devastating pregnancy complication affecting 5% of gravidas worldwide, exhibits poorly characterized connections between mitochondrial dysfunction and immune dysregulation. This study aims to identify integrated mitochondrial-imm...

Identification and experimental validation of biomarkers related to mitochondrial and programmed cell death in obsessive-compulsive disorder.

Scientific reports
Background Mitochondrial-related genes (MRGs) and programmed cell death-related genes (PCD-RGs) have been proven to play important roles in obsessive-compulsive disorder (OCD), and identifying their shared biomarkers is conducive to the diagnosis and...

Exploring potential associations and biomarkers linked polycystic ovarian syndrome with atherosclerosis via comprehensive bioinformatics analysis, machine learning, and animal experiments.

Functional & integrative genomics
Polycystic ovary syndrome (PCOS), a common endocrine condition affecting multiple systems, is tied to atherosclerosis (AS) progression among reproductive-aged women. The present study aimed to explore the underlying associations and uncover potential...