Lina Ma

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

RCoV19 integrates SARS-CoV-2 genome data, monitors variants, and provides risk pre-warning tools for COVID-19 response.

The paper introduces Coronavirus GenBrowser (CGB), a tool for analyzing and visualizing SARS-CoV-2 genomic sequences to study transmission and evolution.

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.

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.

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.