Zhenyu Jia

RNASeek is a generative foundation model for RNA sequence design and functional prediction, using reinforcement learning to optimize RNA properties like stability and cleavage activity.

The paper presents a haplotype-resolved genome assembly of the pomegranate cultivar 'Wonderful' using DNA from haploid pollen grains and long-read sequencing technologies.

The paper assembles the genome of Pavon 76, a Green Revolution wheat cultivar, providing a chromosome-scale reference for CIMMYT-derived wheat and highlighting structural divergence from the standard reference genome.

This paper develops PRECIS, a method combining prime editing and a synthetic intron reporter to efficiently generate SF3B1 mutant cell lines that recapitulate cancer-related splicing and CNV events.

IIIandMe improves haplotype phasing accuracy using three gametes, validated through simulation and citrus data.

This study evaluates 15 machine learning algorithms and 30 gene expression signatures for prostate cancer prognosis using 1,558 patients, finding survival analysis models outperform binary classifiers and identifying top signatures comparable to commercial panels.

CancerMIRNome provides an interactive database for analyzing and visualizing miRNA expression data from cancer studies to identify dysregulated miRNAs and develop biomarkers.

PCaDB provides a database for analyzing transcriptomes from prostate cancer cohorts and includes scRNA-seq data and prognostic signatures to aid in diagnosis and prognosis.

The paper applies genomic selection methods to multi-omics data to develop prognostic signatures for prostate cancer, showing improved predictability and computational efficiency.

Hapi infers chromosome-length haplotypes from 3-5 gametes, outperforming existing methods in accuracy, reliability, and cost efficiency.

This study maps seed coat pattern traits in cowpea to three loci using genomic resources and identifies candidate genes involved in flavonoid biosynthesis.

GDCRNATools provides an R/Bioconductor package for analyzing lncRNA, miRNA, and mRNA data from the GDC to study ceRNA regulatory networks in cancers.

The paper evaluates prediction strategies for hybrid rice traits using various omic datasets and methods, finding genomic-metabolomic combinations and BLUP as most effective.