AIMC Topic: Genomics

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Whole-genome sequencing and comparative genomics reveal antimicrobial potential and adaptive traits of Bacillus velezensis AM12.

Functional & integrative genomics
The global rise of antimicrobial resistance has intensified the demand for novel antimicrobial agents with broad-spectrum efficacy and unique mechanisms of action. Herein, a marine-derived strain, Bacillus velezensis (B. velezensis) AM12, exhibiting ...

Precision breeding in a changing climate: unlocking resilience through omics and gene editing.

Functional & integrative genomics
Climate change, rising global food demand, and shrinking resources require transformative innovations in crop breeding. This review outlines recent advances in new breeding technologies (NBTs), including molecular markers, genome-wide association stu...

ReaGP: integrating residual units and attention mechanisms in convolution neural network for genomic prediction.

Genetics, selection, evolution : GSE
BACKGROUND: Various methods have been widely utilized to estimate the genomic breeding values (GEBVs) for genomic prediction. Traditional approaches often relied on the assumption of linear regression models, which struggle to effectively capture the...

Bayesian neural networks for genomic prediction: uncertainty quantification and SNP interpretation with SHAP and GWAS.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
This study presents a Bayesian neural networks framework with LASSO regularization and the GSMeSP interpretability tool, enabling accurate, uncertainty-aware, and biologically interpretable genomic prediction. Deep learning offers significant potenti...

Multi-omics study of molecular and genetic bases of orthostatic hypotension.

Clinical epigenetics
Orthostatic hypotension is a sharp decrease in blood pressure when an individual transitions from a supine to an upright position. OH affects at least 30% of older adults. It is attributed to the dysfunction of the autonomic innervation and decreased...

Multi-omics driven computational framework for cancer molecular subtype classification.

Scientific reports
Cancer molecular subtype classification is an essential component of precision oncology which provides insights into cancer prognosis and guides targeted therapy. Despite the growing applications of AI for cancer molecular subtype classification, cha...

A novel prognostic model for lung squamous cell carcinoma based on multi-omics analysis and machine learning.

PloS one
Lung squamous-cell carcinoma (LUSC) is a highly aggressive malignancy with a poor prognosis. Tertiary lymphoid structures (TLS) play a crucial role in the immune response and significantly influence the efficacy of immunotherapy. However, the prognos...

Predicting the influence of homologous recombination repair deficiency genes on glioma heterogeneity and patient prognosis using multi-omics analysis and machine learning.

PloS one
BACKGROUND: Glioma is the most common malignant tumor of the central nervous system, and homologous recombination deficiency (HRD) may play a crucial role in its progression. Our study aimed to predict the impact of HRD on glioma heterogeneity and pa...

Omics approaches to understand cardiovascular disease.

BMC cardiovascular disorders
Omics approaches have emerged as indispensable tools in unravelling the intricate molecular landscape of cardiovascular disease (CVD) by providing comprehensive insights into the underlying mechanisms driving CVD pathogenesis, progression, and respon...

Spatial omics: applications and utility in profiling the tumor microenvironment.

Cancer metastasis reviews
Spatial transcriptomics has emerged as a transformative technology in biomedical research, offering unprecedented insights into gene and protein expression within their native tissue context. Unlike conventional bulk or single-cell sequencing approac...