Wang Liu-Wei

WarpDemuX-tRNA: barcode multiplexing for nanopore tRNA sequencing

WarpDemuX-tRNA improves barcode multiplexing for nanopore tRNA sequencing with higher precision and efficiency.

MoDorado: Enhanced detection of tRNA modifications in nanopore sequencing by off-label use of modification callers

The paper introduces MoDorado, an algorithm that detects tRNA modifications beyond those trained in existing models, identifying seven new modifications in S. pombe.

Demultiplexing and barcode-specific adaptive sampling for nanopore direct RNA sequencing

WarpDemuX improves multiplexing accuracy and speed for nanopore dRNA-seq, enabling efficient phenotyping of SARS-CoV-2 variants and real-time RNA enrichment.

Sequencing accuracy and systematic errors of nanopore direct RNA sequencing

This study evaluates sequencing accuracy and systematic errors in direct RNA sequencing across species and synthetic RNA, identifying error patterns and their implications for downstream applications.

FrameRate: learning the coding potential of unassembled metagenomic reads

FrameRate predicts coding frames from unassembled metagenomic reads using machine learning, bypassing assembly and capturing functional profiles efficiently.

DeepViral: infectious disease phenotypes improve prediction of novel virus-host interactions

DeepViral improves prediction of virus-host protein interactions by incorporating disease phenotypes and protein sequences.

D4: Deep Drug-drug interaction Discovery and Demystification

D4 identifies potential drug-drug interactions and their mechanisms using deep learning from drug phenotypic and functional data, achieving high accuracy on known interactions and discovering novel ones.

Taxonomic propagation of phenotypic features predict host pathogen interactions

The paper predicts host-pathogen interactions by integrating phenotypic, functional, and taxonomic knowledge using an ontology-based machine learning method.