Author
Carnegie Mellon UniversityORCID 0000-0002-5083-5925Unclaimed ORCID profile · follow to get notified of new preprints
9 papers
Recent·Most cited
Guillaume Marçais, C.S. Elder, Carl Kingsford
The paper investigates the impact of using canonical k-mers in sketching methods for genomic sequences and proposes solutions to address resulting issues.
Bioinformatics · Oct 17, 2024Peer-reviewedBioinformatics
Minh Hoang, Guillaume Marçais, Carl Kingsford
This paper introduces masked minimizers, a unifying framework for sequence sketching methods, and proposes a new metric to evaluate and optimize them for better genomic analysis.
bioRxiv · Oct 18, 2022 · PreprintGenomics
Hongyu Zheng, Carl Kingsford, Guillaume Marçais
The paper introduces polar sets for sequence-specific minimizer construction, showing their effectiveness on the human reference genome.
Bioinformatics · May 12, 2021Peer-reviewedBioinformatics
Trevor S. Frisby, Shawn James Baker, Guillaume Marçais, Quang Minh Hoang, Carl Kingsford, CHRISTOPHER JAMES LANGMEAD
HARVESTMAN is a framework for hierarchical feature learning and selection from whole genome sequencing data, showing improved performance over binary SNP representations in breast cancer classification.
BMC Bioinformatics · Apr 1, 2021Peer-reviewedBioinformatics
Hongyu Zheng, Carl Kingsford, Guillaume Marçais
The paper introduces a randomized algorithm called Miniception to design minimizers with optimal density guarantees for practical bioinformatics applications.
Bioinformatics · Jun 9, 2020Peer-reviewedBioinformatics
Dan DeBlasio, Fiyinfoluwa Gbosibo, Carl Kingsford, Guillaume Marçais
The paper introduces a method to create practical universal k-mer sets for minimizer schemes that can handle larger k-mer lengths, reducing false positives in sequence matching.
bioRxiv · May 30, 2019 · PreprintBioinformatics
Guillaume Marçais, Dan DeBlasio, Prashant Pandey, Carl Kingsford
The paper introduces an LSH method for edit distance that considers both k-mer content and order, improving alignment detection efficiency.
Bioinformatics · May 9, 2019Peer-reviewedBioinformatics
Guillaume Marçais, Dan DeBlasio, Carl Kingsford
The paper analyzes minimizers schemes and shows that asymptotically optimal schemes with lower density than previously thought exist, leading to more efficient bioinformatics tools.
Bioinformatics · Apr 13, 2018Peer-reviewedBioinformatics
Guillaume Marçais, David Pellow, Daniel Bork, Yaron Orenstein, Ron Shamir A, Carl Kingsford
The paper improves minimizers and winnowing schemes by analyzing k-mer ordering and introducing universal hitting sets to enhance performance.
Bioinformatics · Apr 20, 2017Peer-reviewedBioinformatics