Genetics

Artificial intelligence in predicting EGFR mutations from whole slide images in lung Cancer: A systematic review and Meta-Analysis.

BACKGROUND: Epidermal growth factor receptor (EGFR) mutations play a pivotal role in guiding targeted therapy for lung cancer, making their accurate detection essential for personalized treatment. Recently, artificial intelligence (AI) has emerged as a promising tool for identifying EGFR mutation status from digital pathology images. This systematic review and meta-analysis evaluate the diagnostic...

Not Just $N_e$ $N_e$-more: New Applications for SMC from Ecology to Phylogenies

Genomes contain the mutational footprint of an organism's evolutionary history, shaped by diverse forces including ecological factors, selective pressures, and life history traits. The sequentially Markovian coalescent (SMC) is a versatile and tractable model for the genetic genealogy of a sample of genomes, which captures this shared history. Methods that utilize the SMC, such as PSMC and MSMC,...

DuAL-Net: A Hybrid Framework for Alzheimer's Disease Prediction from Whole-Genome Sequencing via Local SNP Windows and Global Annotations

Alzheimer's disease (AD) dementia is the most common form of dementia. With the emergence of disease-modifying therapies, predicting disease risk be...

Uncertainty-Aware Genomic Classification of Alzheimer's Disease: A Transformer-Based Ensemble Approach with Monte Carlo Dropout

INTRODUCTION: Alzheimer's disease (AD) is genetically complex, complicating robust classification from genomic data. METHODS: We developed a transfo...

Processing-in-memory for genomics workloads

Low-cost, high-throughput DNA and RNA sequencing (HTS) data is the main workforce for the life sciences. Genome sequencing is now becoming a part of...

JojoSCL: Shrinkage Contrastive Learning for single-cell RNA sequence Clustering

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular processes by enabling gene expression analysis at the indivi...

Integration of Bulk RNA and Single-Cell Analyses Reveal Distinct Expression Patterns of Anoikis-Related Genes and the Immunosuppressive Role of NQO1 Macrophages in Hepatocellular Carcinoma.

Anoikis resistance plays a crucial role in the proliferation, metastasis, and invasion of hepatocellular carcinoma (HCC). However, the key genes invol...

Artificial intelligence applications in rare and intractable diseases: Advances, challenges, and future directions.

Rare and intractable diseases affect an estimated 3.5% to 5.9% of the global population but remain largely underserved in terms of diagnosis and treat...

Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer.

Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, despite extensive research spanning several decades,...

A DNA Methylation Classification Model Predicts Organ and Disease Site

Cell-free DNA (cfDNA) analysis is a powerful, minimally invasive tool for monitoring disease progression, treatment response, and early detection. A...

PathGene: Benchmarking Driver Gene Mutations and Exon Prediction Using Multicenter Lung Cancer Histopathology Image Dataset

Accurately predicting gene mutations, mutation subtypes and their exons in lung cancer is critical for personalized treatment planning and prognosti...

Mixpert: Mitigating Multimodal Learning Conflicts with Efficient Mixture-of-Vision-Experts

Multimodal large language models (MLLMs) require a nuanced interpretation of complex image information, typically leveraging a vision encoder to per...

STAR-Net: An Interpretable Model-Aided Network for Remote Sensing Image Denoising

Remote sensing image (RSI) denoising is an important topic in the field of remote sensing. Despite the impressive denoising performance of RSI denoi...

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion

Malware detection and classification remains a topic of concern for cybersecurity, since it is becoming common for attackers to use advanced obfusca...

Biological Pathway Guided Gene Selection Through Collaborative Reinforcement Learning

Gene selection in high-dimensional genomic data is essential for understanding disease mechanisms and improving therapeutic outcomes. Traditional fe...

Methylomes Reveal Recent Evolutionary Changes in Populations of Two Plant Species.

Plant DNA methylation changes occur hundreds to thousands of times faster than DNA mutations and can be transmitted transgenerationally, making them u...

CNN-LSTM Hybrid Model for AI-Driven Prediction of COVID-19 Severity from Spike Sequences and Clinical Data

The COVID-19 pandemic, caused by SARS-CoV-2, highlighted the critical need for accurate prediction of disease severity to optimize healthcare resour...

BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model

Unlocking deep, interpretable biological reasoning from complex genomic data is a major AI challenge hindering scientific discovery. Current DNA fou...

A posteriori error estimates and adaptivity for locally conservative methods. Inexpensive implementation and evaluation, polytopal meshes, iterative linearization and algebraic solvers, and applications to complex porous media flows

A posteriori estimates give bounds on the error between the unknown solution of a partial differential equation and its numerical approximation. We ...

StarBASE-GP: Biologically-Guided Automated Machine Learning for Genotype-to-Phenotype Association Analysis

We present the Star-Based Automated Single-locus and Epistasis analysis tool - Genetic Programming (StarBASE-GP), an automated framework for discove...