* means equal contribution, shared co-first authorship. Papers ordered chronologically.

Journal Papers

1. Tournebize, R., Chu, G. and Moorjani, P., 2022. Reconstructing the history of founder events using genome-wide patterns of allele sharing across individuals. PLoS Genetics, 18(6), p.e1010243.
2. Lalani, Z.*, Chu, G.*, Hsu, S., Kagawa, S., Xiang, M., Zaccaria, S. and El-Kebir, M., 2022. CNAViz: An interactive webtool for user-guided segmentation of tumor DNA sequencing data. PLOS Computational Biology, 18(10), p.e1010614.
3. Park, Minhyuk, Ivanovic, S., Chu, G., Shen, C., and Warnow, T. “UPP2: fast and accurate alignment of datasets with fragmentary sequences.” Bioinformatics 39, no. 1 (2023): btad007.
4. Chu, G., and Warnow, T. “SCAMPP+ FastTree: improving scalability for likelihood-based phylogenetic placement.” Bioinformatics Advances 3, no. 1 (2023): vbad008.

Conference Papers

1. Lalani, Z.*, Chu, G.*, Hsu, S., Zaccaria, S. and El-Kebir, M., 2022. User-guided local and global copy-number segmentation for tumor sequencing data. RECOMB-CCB.
2. Mai, U.*, Chu, G.*, and Raphael, B. J., 2024. “Maximum Likelihood Inference of Time-scaled Cell Lineage Trees with Mixed-type Missing Data.” bioRxiv (2024) doi: 10.1101/2024.03.05.583638. RECOMB 2024.

Workshop Papers

1. Wang, Y., Sun, J., Wang, X., Wei, Y., Wu, H., Yu, Z. and Chu, G., 2020, July. Sperax: An Approach To Defeat Long Range Attacks In Blockchains. In IEEE INFOCOM 2020-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 574-579). IEEE.

Presentations

1. Poster Presentation Exploring Trade-offs in Scalable Phylogenetic Placement Methods. ISCB-LA 2022.
2. Contributed Talk “User-guided local and global copy-number segmentation for tumor sequencing data.” Research in Computational Molecular Biology (RECOMB) – Computational Cancer Biology (CCB), May 2022.
3. Poster Presentation “LAML: Lineage Analysis via Maximum Likelihood.” National Cancer Institute (NCI): Spring School on Algorithmic Cancer Biology (SSACB), Apr 2024.
4. Contributed Talk “LAML: Lineage Analysis via Maximum Likelihood.” Cold Spring Harbor Laboratory (CSHL): Biological Data Science, Machine Learning Session, Nov 2024.