AI Medical Compendium Journal:
Frontiers in genetics

Showing 1 to 10 of 44 articles

Identifying health risk determinants and molecular targets in patients with idiopathic pulmonary fibrosis via combined differential and weighted gene co-expression analysis.

Frontiers in genetics
INTRODUCTION: Idiopathic pulmonary fibrosis (IPF) is a rare but debilitating lung disease characterized by excessive fibrotic tissue accumulation, primarily affecting individuals over 50 years of age. Early diagnosis is challenging, and without inter...

Quadratic descriptors and reduction methods in a two-layered model for compound inference.

Frontiers in genetics
Compound inference models are crucial for discovering novel drugs in bioinformatics and chemo-informatics. These models rely heavily on useful descriptors of chemical compounds that effectively capture important information about the underlying compo...

Machine learning potential predictor of idiopathic pulmonary fibrosis.

Frontiers in genetics
INTRODUCTION: Idiopathic pulmonary fibrosis (IPF) is a severe chronic respiratory disease characterized by treatment challenges and poor prognosis. Identifying relevant biomarkers for effective early-stage risk prediction is therefore of critical imp...

Classical and machine learning tools for identifying yellow-seeded by fusion of hyperspectral features.

Frontiers in genetics
INTRODUCTION: Due to its favorable traits-such as lower lignin content, higher oil concentration, and increased protein levels-the genetic improvement of yellow-seeded rapeseed has attracted more attention than other rapeseed color variations. Tradit...

Exploring prognosis and therapeutic strategies for HBV-HCC patients based on disulfidptosis-related genes.

Frontiers in genetics
BACKGROUND: Hepatocellular carcinoma (HCC) accounts for over 80% of primary liver cancers and is the third leading cause of cancer-related deaths worldwide. Hepatitis B virus (HBV) infection is the primary etiological factor. Disulfidptosis is a newl...

Depression-related innate immune genes and pan-cancer gene analysis and validation.

Frontiers in genetics
BACKGROUND: Depression, a prevalent chronic mental disorder, presents complexities and treatment challenges that drive researchers to seek new, precise therapeutic targets. Additionally, the potential connection between depression and cancer has garn...

Integration of single-cell transcriptomics and bulk transcriptomics to explore prognostic and immunotherapeutic characteristics of nucleotide metabolism in lung adenocarcinoma.

Frontiers in genetics
BACKGROUND: Lung adenocarcinoma (LUAD) is a highly aggressive tumor with one of the highest morbidity and mortality rates in the world. Nucleotide metabolic processes are critical for cancer development, progression, and alteration of the tumor micro...

DLBWE-Cys: a deep-learning-based tool for identifying cysteine S-carboxyethylation sites using binary-weight encoding.

Frontiers in genetics
Cysteine S-carboxyethylation, a novel post-translational modification (PTM), plays a critical role in the pathogenesis of autoimmune diseases, particularly ankylosing spondylitis. Accurate identification of S-carboxyethylation modification sites is e...

Understanding the impacts of drought on peanuts L.): exploring physio-genetic mechanisms to develop drought-resilient peanut cultivars.

Frontiers in genetics
Peanut is a vital source of protein, particularly in the tropical regions of Asian and African countries. About three-quarters of peanut production occurs worldwide in arid and semi-arid regions, making drought an important concern in peanut producti...

Recent advances in deep learning and language models for studying the microbiome.

Frontiers in genetics
Recent advancements in deep learning, particularly large language models (LLMs), made a significant impact on how researchers study microbiome and metagenomics data. Microbial protein and genomic sequences, like natural languages, form a , enabling t...