Zhang Zhang

MIA is a tensor-based framework for multi-omics data integration that improves clustering and feature discovery, showing effectiveness in cancer subtype identification.

The paper analyzes the evolutionary history of RNA editing factors across Archaeplastida genomes, identifying gene expansions and horizontal transfers.

The paper introduces the GSA Family, a platform for sharing multi-omics and multimodal data, with expanded databases and improved features.

The ChickenGTEx project provides a multi-tissue reference of regulatory variants in chicken, analyzing their functional impacts and utility in genetics, genomics, and evolutionary studies.

The paper identifies human divergently-paired genes (DPGs) and analyzes their conservation, regulatory features, and evolutionary patterns across vertebrate lineages.

The paper identifies non-mutational p53 functional deficiency in TP53 wild-type tumors using SVM models, revealing significant functional impairment and clinical implications.

The paper proposes and validates three mathematical laws of genome nucleotide composition across three domains of life.

This study characterizes RNA editing profiles in rice endosperm development across five stages, identifying CDS-recoding sites and their impact on mitochondrial proteins and evolutionary conservation.

This paper develops a machine learning model using LightGBM to predict high-risk SARS-CoV-2 variants based on haplotype network features, achieving high accuracy in identifying variants of concern and interest.

SoyOmics integrates soybean multi-omics data to support functional studies and molecular breeding by providing a centralized database with analysis tools.

McAN constructs haplotype networks using a minimum-cost arborescence approach, achieving speeds two orders of magnitude faster than existing methods.

inClust is a clustering framework that integrates multi-source data using variational autoencoder and vector arithmetic, performing well in various clustering tasks.

KaKs_Calculator 3.0 calculates selective pressure on coding and non-coding sequences using a normalized substitution rate ratio, enabling genome-wide scans for natural selection and functional elements.

The paper introduces the GSA family of repositories to manage explosive growth and diverse data types in genomic data archiving.

The Genome Warehouse (GWH) is a public repository for genome-scale data that provides storage, submission, and visualization tools for genome assemblies across species.

The paper describes the 2019nCoVR resource, which curates and analyzes SARS-CoV-2 genomes, variants, and haplotypes globally, providing daily updates and integration with literature and databases.

scCapsNet is a deep learning model for single-cell RNA data analysis that provides interpretable feature extraction and accurate cell type classification.

The paper characterizes bumblebee genomes across 17 species to identify genetic variation linked to ecological and behavioral traits, revealing insights into genome structure, evolution, and adaptation.

This study identifies PRKCG as a glioma biomarker through multi-omics integration, showing its association with glioma progression and survival outcomes when combined with MGMT.

SR4R provides a processed SNP database for rice, offering four reference SNP panels for population genetics and genomic breeding.

This paper introduces a deep learning model called NGNC to reconstruct gene regulatory networks and infer gene dynamics from time series scRNA-seq data, achieving state-of-the-art results.

This study characterizes long non-coding RNAs (lncRNAs) by analyzing feature relationships and introduces LGC, an algorithm that accurately identifies lncRNAs across species without prior knowledge.