Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Machine learning identifies clinical tumor mutation landscape pathways of resistance to checkpoint inhibitor therapy in NSCLC.

BACKGROUND: Immune checkpoint inhibitors (CPIs) have revolutionized cancer therapy for several tumor...

Advanced machine learning-driven characterization of new natural cellulosic Lablab purpureus fibers through PCA and K-means clustering techniques.

The increasing demand for sustainable and eco-friendly materials has spurred significant interest in...

Integrating Artificial Intelligence and Bioinformatics Methods to Identify Disruptive STAT1 Variants Impacting Protein Stability and Function.

The Signal Transducer and Activator of Transcription 1 () gene is an essential component of the JAK...

A privacy-preserving dependable deep federated learning model for identifying new infections from genome sequences.

The traditional molecular-based identification (TMID) technique of new infections from genome sequen...

Psychiatric Genomics 2025: State of the Art and the Path Forward.

Psychiatric genetics has evolved from candidate-gene studies to whole-genome sequencing efforts. Wit...

New solutions for antibiotic discovery: Prioritizing microbial biosynthetic space using ecology and machine learning.

With the explosive increase in genome sequence data, perhaps the major challenge in natural-product-...

TransRM: Weakly supervised learning of translation-enhancing N6-methyladenosine (mA) in circular RNAs.

As our understanding of Circular RNAs (circRNAs) continues to expand, accumulating evidence has demo...

Targeting Bacterial RNA Polymerase: Harnessing Simulations and Machine Learning to Design Inhibitors for Drug-Resistant Pathogens.

The increase in antimicrobial resistance presents a major challenge in treating bacterial infections...

Machine Learning Methods for Classifying Multiple Sclerosis and Alzheimer's Disease Using Genomic Data.

Complex diseases pose challenges in prediction due to their multifactorial and polygenic nature. Thi...

A compendium of human gene functions derived from evolutionary modelling.

A comprehensive, computable representation of the functional repertoire of all macromolecules encode...

Supervised and unsupervised deep learning-based approaches for studying DNA replication spatiotemporal dynamics.

In eukaryotic cells, DNA replication is organised both spatially and temporally, as evidenced by the...

Multi-omics analyses and machine learning prediction of oviductal responses in the presence of gametes and embryos.

The oviduct is the site of fertilization and preimplantation embryo development in mammals. Evidence...

AI in Breast Cancer Imaging: An Update and Future Trends.

Breast cancer is one of the most common types of cancer affecting women worldwide. Artificial intell...

Engineering a New Generation of Gene Editors: Integrating Synthetic Biology and AI Innovations.

CRISPR-Cas technology has revolutionized biology by enabling precise DNA and RNA edits with ease. Ho...

Identifying periphery biomarkers of first-episode drug-naïve patients with schizophrenia using machine-learning-based strategies.

Schizophrenia is a complex mental disorder. Accurate diagnosis and classification of schizophrenia h...

Non-Invasive Biomarkers in the Era of Big Data and Machine Learning.

Invasive diagnostic techniques, while offering critical insights into disease pathophysiology, are o...

Pharmacogenomics and response to lithium in bipolar disorder.

AIMS: The present review explores the existing evidence on pharmacogenomic tests for prediction of l...

A novel coarsened graph learning method for scalable single-cell data analysis.

The emergence of single-cell technologies, including flow and mass cytometry, as well as single-cell...

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