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Mark D. M. Leiserson
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2020 – today
- 2023
- [j10]Itay Kahane
, Mark D. M. Leiserson, Roded Sharan
A mutation-level covariate model for mutational signatures. PLoS Comput. Biol. 19(6) (2023) - 2022
- [j9]Nicholas Franzese
ScalpelSig Designs Targeted Genomic Panels from Data to Detect Activity of Mutational Signatures. J. Comput. Biol. 29(1): 56-73 (2022) - 2021
- [j8]Gal Gilad
A data-driven approach for constructing mutation categories for mutational signature analysis. PLoS Comput. Biol. 17(10) (2021) - 2020
- [c12]Mark D. M. Leiserson, Teresa M. Przytycka, Roded Sharan:
Session Introduction. PSB 2020: 219-225 - [c11]Sarah A. Christensen, Mark D. M. Leiserson, Mohammed El-Kebir:
PhySigs: Phylogenetic Inference of Mutational Signature Dynamics. PSB 2020: 226-237 - [c10]Damian Wójtowicz, Mark D. M. Leiserson, Roded Sharan, Teresa M. Przytycka:
DNA Repair Footprint Uncovers Contribution of DNA Repair Mechanism to MutationalSignatures. PSB 2020: 262-273 - [c9]Itay Sason, Yuexi Chen, Mark D. M. Leiserson, Roded Sharan:
A Mixture Model for Signature Discovery from Sparse Mutation Data. RECOMB 2020: 271-272
2010 – 2019
- 2019
- [j7]Welles Robinson
Modeling clinical and molecular covariates of mutational process activity in cancer. Bioinform. 35(14): i492-i500 (2019) - [c8]Nathaniel Swinger
What are the Biases in My Word Embedding? AIES 2019: 305-311 - [c7]Itay Sason, Damian Wójtowicz
A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer. RECOMB 2019: 243-255 - 2018
- [j6]Matthew A. Reyna, Mark D. M. Leiserson, Benjamin J. Raphael:
Hierarchical HotNet: identifying hierarchies of altered subnetworks. Bioinform. 34(17): i972-i980 (2018) - [c6]Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, Mark D. M. Leiserson:
Decoupled Classifiers for Group-Fair and Efficient Machine Learning. FAT 2018: 119-133 - [c5]Mark D. M. Leiserson, Jason Fan, Anthony Cannistra, Inbar Fried, Tim Lim, Thomas Schaffner, Mark Crovella, Benjamin J. Hescott:
A Multi-species Functional Embedding Integrating Sequence and Network Structure. RECOMB 2018: 263-265 - [i1]Nathaniel Swinger, Maria De-Arteaga, Neil Thomas Heffernan IV, Mark D. M. Leiserson, Adam Tauman Kalai:
What are the biases in my word embedding? CoRR abs/1812.08769 (2018) - 2016
- [b1]Mark D. M. Leiserson:
Methods for Identifying Combinations of Driver Mutations in Cancer. Brown University, USA, 2016 - [j5]Mark D. M. Leiserson, Matthew A. Reyna, Benjamin J. Raphael:
A weighted exact test for mutually exclusive mutations in cancer. Bioinform. 32(17): 736-745 (2016) - 2015
- [c4]Mark D. M. Leiserson, Hsin-Ta Wu, Fabio Vandin, Benjamin J. Raphael:
CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer. RECOMB 2015: 202-204 - 2013
- [j4]Andrew Gallant, Mark D. M. Leiserson, Maxim Kachalov, Lenore J. Cowen, Benjamin J. Hescott:
Genecentric: a package to uncover graph-theoretic structure in high-throughput epistasis data. BMC Bioinform. 14: 23 (2013) - [j3]Mark D. M. Leiserson, Dima Blokh, Roded Sharan, Benjamin J. Raphael:
Simultaneous Identification of Multiple Driver Pathways in Cancer. PLoS Comput. Biol. 9(5) (2013) - 2012
- [c3]Andrew Gallant, Mark D. M. Leiserson, Maxim Kachalov, Lenore J. Cowen, Benjamin J. Hescott:
Genecentric: a package to uncover graph-theoretic structure in high-throughput epistasis data. BCB 2012: 576-578 - 2011
- [j2]Mark D. M. Leiserson, Diana Tatar, Lenore J. Cowen, Benjamin J. Hescott:
Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut. J. Comput. Biol. 18(11): 1399-1409 (2011) - [c2]Mark D. M. Leiserson, Diana Tatar, Lenore J. Cowen, Benjamin J. Hescott:
Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut. RECOMB 2011: 154-167 - 2010
- [j1]Benjamin J. Hescott, Mark D. M. Leiserson, Lenore J. Cowen, Donna K. Slonim
Evaluating Between-Pathway Models with Expression Data. J. Comput. Biol. 17(3): 477-487 (2010)
2000 – 2009
- 2009
- [c1]Benjamin J. Hescott, Mark D. M. Leiserson, Lenore Cowen, Donna K. Slonim:
Evaluating Between-Pathway Models with Expression Data. RECOMB 2009: 372-385
Coauthor Index
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