Yousong Peng

Improved prediction of virus-human protein-protein interactions by incorporating network topology and viral molecular mimicry

This paper introduces vhPPIpred, a machine learning method for predicting virus-human PPIs that outperforms existing methods and provides a benchmark dataset.

Flu Virus Infection in Juvenile Mice Leads to Lifelong Multi-Organ Damage and Parkinsonian Pathological Changes in Aging

This study shows that influenza infection in juvenile mice causes lifelong multi-organ damage and Parkinsonian changes in aging, with persistent inflammation and secreted proteins mediating systemic effects.

Systematic identification and characterization of virus lncRNAs suggests extensive structural mimicry of host lncRNAs

This study identifies 5,053 novel virus long non-coding RNAs (vlncRNAs) across 25 viral species and finds that many structurally mimic host lncRNAs, potentially acting as miRNA sponges.

LRP8 is a Receptor for Yellow Fever Virus

This study identifies LRP8 as a receptor for Yellow Fever Virus, showing it facilitates infection and presents a potential therapeutic target.

Risk evaluation of newly emerging flu viruses based on genomic sequences and AI

This paper introduces FluRisk, a computational framework using genomic data and AI to assess the risk of emerging influenza viruses, showing improved performance over traditional methods.

Virome analysis provides new insights into the pathogenesis mechanism and treatment of SLE disease

This study analyzes the virome in SLE patients and controls, finding higher viral positivity in patients and suggesting viral infections may worsen disease severity.

Modeling the antigenic evolution of seasonal influenza viruses with PREDAC for vaccine strain selection in the season of 2025

This study models the antigenic evolution of seasonal influenza viruses using PREDAC and finds no need to update vaccine strains for the 2025 season.

Comprehensive characterization of the integrin family across 32 cancer types

This study characterizes integrin family alterations across 32 cancer types, identifies integrinScore as a prognostic marker, and proposes potential therapeutic targets.

VIGA: an one-stop tool for eukaryotic Virus Identification and Genome Assembly from next-generation-sequencing data

VIGA is a tool for eukaryotic virus identification and genome assembly from NGS data, showing improved performance in assembling complete genomes and revealing virome differences in disease states.

vsRNAfinder: a novel method for identifying high-confidence viral small RNAs from small RNA-Seq data

vsRNAfinder identifies high-confidence viral small RNAs from sRNA-Seq data, outperforming existing methods in sensitivity.

Prediction of coronavirus 3C-like protease cleavage sites using machine-learning algorithms

This study develops a random forest model to predict coronavirus 3CL protease cleavage sites, achieving high accuracy on both viral and host protein datasets.

Prokaryotic virus Host Predictor: a Gaussian model for host prediction of prokaryotic viruses in metagenomics

This paper introduces PHP, a Gaussian model for predicting hosts of prokaryotic viruses in metagenomics, achieving higher accuracy than existing methods.

Prediction of the receptorome for the human-infecting virome

The paper predicts the receptorome for the human-infecting virome using a random-forest model and protein-protein interaction data, identifying 1380 human cell membrane proteins and 693 virus-specific receptors.

Prediction of antiviral drugs against African Swine Fever Viruses based on protein-protein interaction analysis

The paper predicts antiviral drugs against African Swine Fever Viruses by analyzing protein-protein interactions and identifying key host proteins as potential drug targets.

Classification of multigene families of African swine fever viruses

This study classifies MGF proteins of ASFV into 35 groups based on sequence homology and provides a web server for classification.

Identification of viruses with the potential to infect human

This study develops machine learning models to identify human-infecting viruses using k-mer frequency in viral genomic sequences, achieving over 90% accuracy.

Influenza incidence prediction for the United States: an update for the 2018-2019 season

The paper updates an epidemiological model to predict influenza incidence for the 2018-2019 season and evaluates its accuracy for the 2017-2018 season.