Afshin Beheshti

This paper uses two-photon microscopy to detect high-grade cervical precancerous lesions with high sensitivity and specificity by analyzing metabolic and morphological features.

The paper identifies thousands of human orphan genes from RNA-Seq data, validates them with single-cell RNA-seq, and provides a compendium for future research.

The paper uses a deep learning model to identify antimicrobial resistance genes in ISS microbiome data, revealing resistance patterns in specific bacterial species.

The paper identifies a lncRNA signature associated with SARS-CoV-2 infection through transcriptomic analysis and functional correlation studies.

This study investigates how SARS-CoV-2 infection affects mitochondrial gene expression in different tissues and disease stages, finding targeted inhibition in some organs and upregulation in others.

The paper investigates differential alternative splicing in cells infected by betacoronaviruses and finds characteristic patterns linked to viral load and gene function.

The paper identifies miR-2392 as a miRNA involved in SARS-CoV-2 infection, showing its role in inflammation, glycolysis, and hypoxia, and develops a miRNA-based therapeutic targeting it.

This study analyzes over 7,000 SARS-CoV-2 datasets to reveal genomic diversity, showing iSNVs and small indels drive variation, and highlights implications for qRT-PCR and transmission tracking.

The paper describes a standardized RNA-Seq pipeline for spaceflight data, enabling reproducible analysis of gene expression changes in astronauts and organisms exposed to spaceflight.