AIMC Topic: Gene Expression Profiling
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The role of mitochondrial dysfunction in the pathogenesis of atherosclerosis: A new exploration from bioinformatics analysis.
Medicine
May 30, 2025
Atherosclerosis (AS) is a complex cardiovascular disease associated with mitochondrial dysfunction (MD), which contributes to plaque formation and instability. This study explores the relationship and shared risk factors between the pathogenesis of A...
Machine learning identifies SRD5A3 as a propionate-related prognostic biomarker in triple-negative breast cancer.
Scientific reports
May 29, 2025
The increased risk of recurrence and metastasis are obstacles to treating TNBC. Propionate-related genes play an important role in tumor development and immune cell infiltration. The study was to identify the association between propionate-related ge...
scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links.
Nature communications
May 29, 2025
Recent advancements in single-cell technologies have enabled comprehensive characterization of cellular states through transcriptomic, epigenomic, and proteomic profiling at single-cell resolution. These technologies have significantly deepened our u...
Saliva-derived transcriptomic signature for gastric cancer detection using machine learning and leveraging publicly available datasets.
Scientific reports
May 27, 2025
Saliva, a non-invasive, self-collected liquid biopsy, holds promise for early gastric cancer (GC) screening. This study aims to assess the potential of saliva as a proxy for malignant gastric transformation and its diagnostic value through transcript...
Identifying shared hub genes in LIRI and MASLD through bioinformatics analysis and machine learning.
Scientific reports
May 27, 2025
Patients with metabolic dysfunction-associated steatotic liver disease (MASLD) are more susceptible to liver ischemia-reperfusion injury (LIRI), complicating liver surgery outcomes. This study aimed to uncover shared hub genes and mechanisms linking ...
Integrating bioinformatics and machine learning to identify biomarkers of branched chain amino acid related genes in osteoarthritis.
BMC musculoskeletal disorders
May 26, 2025
BACKGROUND: Branched-chain amino acids (BCAA) metabolism is significantly associated with osteoarthritis (OA), but the specific mechanism of BCAA related genes (BCAA-RGs) in OA is still unclear. Therefore, this research intended to identify potential...
Prediction of Drug-Induced Nephrotoxicity Using Chemical Information and Transcriptomics Data.
Journal of chemical information and modeling
May 26, 2025
Prediction of drug-induced nephrotoxicity is an important task in the drug discovery and development pipeline. Chemical information-based machine learning models are used in general for nephrotoxicity prediction as a part of computational modeling. C...
CorrAdjust unveils biologically relevant transcriptomic correlations by efficiently eliminating hidden confounders.
Nucleic acids research
May 22, 2025
Correcting for confounding variables is often overlooked when computing RNA-RNA correlations, even though it can profoundly affect results. We introduce CorrAdjust, a method for identifying and correcting such hidden confounders. CorrAdjust selects a...
Machine learning using scRNA-seq Combined with bulk-seq to identify lactylation-related hub genes in carotid arteriosclerosis.
Scientific reports
May 22, 2025
Atherosclerosis is a chronic inflammatory disease, this study aims to investigate the immune landscape in carotid atherosclerotic plaque formation and explore diagnostic biomarkers of lactylation-associated genes, so as to gain new insights into unde...
Machine-learning meta-analysis reveals ethylene as a central component of the molecular core in abiotic stress responses in Arabidopsis.
Nature communications
May 22, 2025
Understanding how plants adapt their physiology to overcome severe and often multifactorial stress conditions in nature is vital in light of the climate crisis. This remains a challenge given the complex nature of the underlying molecular mechanisms....
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