Ernest T. Lam

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability

This paper introduces QCML, a quantum-inspired machine learning framework, to predict chromosomal instability from CTC morphology, achieving higher accuracy than conventional methods in high-dimensional biomedical data.

Multi-platform discovery of haplotype-resolved structural variation in human genomes

This study identifies a large number of structural variants in human genomes using multiple sequencing technologies and presents them as a gold standard for future studies.

CRISPR-bind: a simple, custom CRISPR/dCas9-mediated labeling of genomic DNA for mapping in nanochannel arrays

The paper introduces CRISPR-bind, a method using dCas9 to directly label genomic DNA with fluorescent CRISPR-dCas9 complexes for improved mapping and analysis.

OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps

OMSV identifies large structural variations from optical maps with high accuracy, outperforming existing methods and detecting many missed by sequencing.

Rapid Automated Large Structural Variation Detection in a Diploid Genome by NanoChannel Based Next-Generation Mapping

The paper introduces a method to detect large structural variants in diploid genomes using Bionano Genomics next-generation mapping, achieving high resolution and throughput.