Yunzhe Jiang

StarTrak infers cellular migration and phylogeny by integrating somatic variants, spatial data, and transcriptomics at single-pixel resolution in spatial genomics.

The paper presents a population-scale Y chromosome reference panel with 142 assemblies, revealing structural and epigenetic variation across 180,000 years of evolution.

The paper assembles and characterizes 2,110 human centromeres, revealing novel haplotypes, mobile element insertions, and mutation rate variation across chromosomes.

The paper characterizes the epigenetic features of pseudogenes across human tissues and identifies differences compared to protein-coding transcripts and lncRNAs.

The paper develops a disease-specific histone modification prediction model using a large language model and MoE architecture, achieving high AUROC scores and identifying AD-associated variants.

The paper surveys pseudogene expression in human and macaque brains compared to 29 other tissues, finding elevated and consistent brain expression and associations with neuropsychiatric disorders.

Hybrid HiFi/ultra-long ONT assemblies of 65 diverse humans yield 130 haplotypes, 1,246 complete centromeres, and a pangenome panel enabling short-read genome inference at median QV 45.

The paper expands and refines a reference catalog of human non-canonical open reading frames (ncORFs) by incorporating more datasets and introducing a translation signature score framework to prioritize high-quality ncORFs.

This study uses single-nucleus multiome sequencing to identify HIV-associated transcriptional and epigenetic changes in brain regions of individuals with HIV, revealing altered glial cell states and pro-inflammatory signaling.

The paper expands the lncRNA catalog using capture long-read RNA sequencing, significantly increasing the number of annotated transcripts in human and mouse genomes.

This paper introduces EPACT, a deep-learning framework for predicting TCR-antigen binding pairs, showing high accuracy in epitope recognition and TCR repertoire analysis.

The paper processes single-nuclei multi-omics data from 388 human brains to identify regulatory elements and build cell-type networks, revealing changes in aging and neuropsychiatric disorders.

Long-read sequencing of 81 human and mouse samples yields 200,000 full-length transcripts plus a triplet framework that separates promoter choice, splicing and 3' end use across tissues.

The paper introduces the EN-TEx resource, which provides personal epigenomes and variant-impact models across multiple tissues, revealing allele-specific loci and their associations with GWAS loci.