Yutong Qiu

The paper introduces a novel algorithm to improve Hi-C contact matrices by inferring linear genomes from Hi-C data using genome graphs, resulting in more accurate structural representations.

The paper evaluates how genome graph expressiveness affects the discrepancy between genome graph distance and string set distance, introducing improvements to reduce estimation errors.

The paper introduces RLZ-Graph, a space-efficient genome graph constructed using Lempel-Ziv compression, reducing disk space by 40.7% compared to colored de Bruijn graphs.

The paper introduces a computational method to detect transcriptomic structural variants in heterogeneous samples by solving the Multiple Compatible Arrangements Problem, showing improved performance over existing tools.

This paper introduces Tulip, a toolkit for simulating ChIP-seq data to evaluate analyses like peak calling and differential binding, enabling power analysis and benchmarking.