Genetics

Multimodality, interaction modeling, and multimodule architectures in genomic prediction: A unified conceptual framework.

The rapid expansion of genomic, environmental, phenomic, and other high-dimensional data sources has transformed genomic prediction in plant breeding. However, the terms multimodal, interaction modeling, and multimodule architecture are often used inconsistently, generating ambiguity regarding whether they refer to biological assumptions, data integration strategies, or computational design. These...

Integrative genomics and zero-shot deep learning-based phenotyping reveal the genetic architecture of seed traits in mungbean (Vigna radiata L.).

Improving seed size and weight is a major breeding goal in mungbean (Vigna radiata (L.) R. Wilczek). Improved genomic resources and precision phenotyping may enable more efficient selection for seed trait improvement. In this study, we integrated a deep learning-based segment anything model phenotyping pipeline with genome-wide association studies (GWAS), comparative mapping, and genomic predictio...

Genomic prediction in quinoa across contrasting environments using statistical and machine learning models.

Quinoa (Chenopodium quinoa Willd.) is gaining global importance for its nutritional value and adaptability; however, breeding progress remains limited...

Multi-level Transcriptomic and Machine-learning Analyses Identify MZT1 as a Proliferation-associated Prognostic Marker in Lung Adenocarcinoma.

BACKGROUND/AIM: Lung adenocarcinoma (LUAD) exhibits substantial molecular heterogeneity and variable clinical outcomes, highlighting the need for biom...

Artificial intelligence-assisted design of MAGE-A4 ×CD16 T-cell receptor-like natural killer cell engagers.

The cancer-testis antigen MAGE-A4 is an attractive immunotherapy target due to its high expression in various malignancies and restricted expression i...

From rules to foundation models: a comprehensive review of machine learning approaches for siRNA design.

Small interfering RNAs (siRNAs) are a clinically validated therapeutic modality with eight FDA-approved drugs, yet designing effective siRNAs remains ...

Kidney stones composition prediction using artificial intelligence (KiSCAI) study.

OBJECTIVES: To develop and validate explainable machine learning (ML) models predicting urinary stone composition from routinely available clinical va...

Multi-Technique Integration Identifies O-GlcNAc Transferase in Fibroblast-Like Synoviocytes as a Therapeutic Target for Rheumatoid Arthritis.

Rheumatoid arthritis (RA) progression is driven by the pathogenic transformation of stromal fibroblast-like synoviocytes (FLSs). Using artificial inte...

Compensation-Balanced Recurrent Neural Architecture Based on Nonlinear Spiking Neural Membrane Systems.

Nonlinear spiking neural P (NSNP) systems offer a biologically inspired framework for modeling nonlinear temporal dynamics via spike consumption and g...

Mapping Allele-specific RBP Binding by a Machine Learning Coupled RNA Editing Strategy in Human Embryonic Stem Cells.

RNA-binding proteins (RBPs) play critical roles in regulating the maintenance and differentiation of embryonic stem cells. A critical step in understa...

Developability-by-design for bispecific antibodies in discovery: combining computational prediction and early screening for candidate selection.

INTRODUCTION: The molecular and architectural complexity of bispecific antibodies can introduce developability risks beyond those encountered with con...

Integrated pan-cancer analysis reveals a cancer-associated fibroblast oxidative stress response signature predicting immunotherapy response and prognosis.

Oxidative stress plays a significant regulatory role in tumor immune responses and can influence the efficacy of immunotherapy. Accordingly, therapeut...

An integrative multi-project transcriptomic and structural prediction framework identifies candidate cold-responsive transcription factors in Medicago sativa.

Cold stress limits alfalfa (Medicago sativa) growth and persistence, but public transcriptomic datasets differ widely in genotype, tissue, treatment d...

Cancer-associated fusion transcripts: mechanisms, functional roles, and clinical implications.

Fusion transcripts are hybrid RNA molecules generated through genomic rearrangements or RNA-level fusion mechanisms. They represent important molecula...

A novel convolution-transformer model for differentiating hypertrophic cardiomyopathy from Phenocopies using cardiac MRI.

BACKGROUND AND OBJECTIVES: Hypertrophic Cardiomyopathy (HCM) is the most prevalent inherited cardiomyopathy. Its left ventricular hypertrophy (LVH) ph...

A genomic catalog of Earth's bacterial and archaeal symbionts.

Microbial symbiosis drives the functional and phylogenomic diversification of life on Earth yet remains underexplored because of culturing challenges....

Organoid intelligence: a promising paradigm for autism spectrum disorder research.

Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition marked by heterogeneity in its clinical presentations, which complicat...

Artificial intelligence for translational personalized neoantigen cancer vaccine development.

Personalized neoantigen cancer vaccine is a promising strategy for precision immunotherapy by targeting patient-specific and mutation-derived tumor an...

Integration of Bulk RNA Sequencing and Single-Cell Sequencing to Identify Prognostic Genes Associated With MCDRGs in Neuroblastoma.

Neuroblastoma (NB) is a common pediatric tumor that exhibits significant clinical heterogeneity and substantial prognostic variability. However, there...

Identification of Epigenetic Regulator-Associated Genes in Keloid Disease Through Integrated Bulk and Single-Cell Transcriptomics With RT-qPCR Validation.

There exists a close correlation between epigenetic factors and the progression of keloid disease (KD). The research aims to identify the key genes li...