Mark D. M. Leiserson

Orcid: 0000-0002-1034-4363

According to our database1, Mark D. M. Leiserson authored at least 20 papers between 2010 and 2023.

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Bibliography

2023
A mutation-level covariate model for mutational signatures.
PLoS Comput. Biol., 2023

2022
ScalpelSig Designs Targeted Genomic Panels from Data to Detect Activity of Mutational Signatures.
J. Comput. Biol., 2022

2021
A data-driven approach for constructing mutation categories for mutational signature analysis.
PLoS Comput. Biol., 2021

2020
A Mixture Model for Signature Discovery from Sparse Mutation Data.
Proceedings of the Research in Computational Molecular Biology, 2020

DNA Repair Footprint Uncovers Contribution of DNA Repair Mechanism to MutationalSignatures.
Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

Session Introduction.
Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

PhySigs: Phylogenetic Inference of Mutational Signature Dynamics.
Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

2019
Modeling clinical and molecular covariates of mutational process activity in cancer.
Bioinform., 2019

A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer.
Proceedings of the Research in Computational Molecular Biology, 2019

What are the Biases in My Word Embedding?
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018
Hierarchical HotNet: identifying hierarchies of altered subnetworks.
Bioinform., 2018

A Multi-species Functional Embedding Integrating Sequence and Network Structure.
Proceedings of the Research in Computational Molecular Biology, 2018

Decoupled Classifiers for Group-Fair and Efficient Machine Learning.
Proceedings of the Conference on Fairness, Accountability and Transparency, 2018

2016
Methods for Identifying Combinations of Driver Mutations in Cancer.
PhD thesis, 2016

A weighted exact test for mutually exclusive mutations in cancer.
Bioinform., 2016

2015
CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer.
Proceedings of the Research in Computational Molecular Biology, 2015

2013
Simultaneous Identification of Multiple Driver Pathways in Cancer.
PLoS Comput. Biol., 2013

Genecentric: a package to uncover graph-theoretic structure in high-throughput epistasis data.
BMC Bioinform., 2013

2011
Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut.
J. Comput. Biol., 2011

2010
Evaluating Between-Pathway Models with Expression Data.
J. Comput. Biol., 2010


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