Evaluating Between-Pathway Models with Expression Data. - Benjamin J. Hescott; Mark D. M. Leiserson; Lenore J. Cowen; Donna K. Slonim (J. Comput. Biol., 2010)

Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut. - Mark D. M. Leiserson; Diana Tatar; Lenore J. Cowen; Benjamin J. Hescott (J. Comput. Biol., 2011)

Genecentric: a package to uncover graph-theoretic structure in high-throughput epistasis data. - Andrew Gallant; Mark D. M. Leiserson; Maxim Kachalov; Lenore J. Cowen; Benjamin J. Hescott (BMC Bioinform., 2013)

Simultaneous Identification of Multiple Driver Pathways in Cancer. - Mark D. M. Leiserson; Dima Blokh; Roded Sharan; Benjamin J. Raphael (PLoS Comput. Biol., 2013)

CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer. - Mark D. M. Leiserson; Hsin-Ta Wu; Fabio Vandin; Benjamin J. Raphael (RECOMB, 2015)

A weighted exact test for mutually exclusive mutations in cancer. - Mark D. M. Leiserson; Matthew A. Reyna; Benjamin J. Raphael (Bioinform., 2016)

Methods for Identifying Combinations of Driver Mutations in Cancer. - Mark D. M. Leiserson (2016)

Decoupled Classifiers for Group-Fair and Efficient Machine Learning. - Cynthia Dwork; Nicole Immorlica; Adam Tauman Kalai; Mark D. M. Leiserson (FAT, 2018)

A Multi-species Functional Embedding Integrating Sequence and Network Structure. - Mark D. M. Leiserson; Jason Fan; Anthony Cannistra; Inbar Fried; Tim Lim; Thomas Schaffner; Mark Crovella; Benjamin J. Hescott (RECOMB, 2018)

Hierarchical HotNet: identifying hierarchies of altered subnetworks. - Matthew A. Reyna; Mark D. M. Leiserson; Benjamin J. Raphael (Bioinform., 2018)

What are the Biases in My Word Embedding? - Nathaniel Swinger; Maria De-Arteaga; Neil Thomas Heffernan IV; Mark D. M. Leiserson; Adam Tauman Kalai (AIES, 2019)

A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer. - Itay Sason; Damian Wójtowicz; Welles Robinson; Mark D. M. Leiserson; Teresa M. Przytycka; Roded Sharan (RECOMB, 2019)

Modeling clinical and molecular covariates of mutational process activity in cancer. - Welles Robinson; Roded Sharan; Mark D. M. Leiserson (Bioinform., 2019)

PhySigs: Phylogenetic Inference of Mutational Signature Dynamics. - Sarah A. Christensen; Mark D. M. Leiserson; Mohammed El-Kebir (PSB, 2020)

Session Introduction. - Mark D. M. Leiserson; Teresa M. Przytycka; Roded Sharan (PSB, 2020)

DNA Repair Footprint Uncovers Contribution of DNA Repair Mechanism to MutationalSignatures. - Damian Wójtowicz; Mark D. M. Leiserson; Roded Sharan; Teresa M. Przytycka (PSB, 2020)

A Mixture Model for Signature Discovery from Sparse Mutation Data. - Itay Sason; Yuexi Chen; Mark D. M. Leiserson; Roded Sharan (RECOMB, 2020)

Matrix (factorization) reloaded: flexible methods for imputing genetic interactions with cross-species and side information. - Jason Fan; Xuan Cindy Li; Mark Crovella; Mark D. M. Leiserson (Bioinform., 2020)

A data-driven approach for constructing mutation categories for mutational signature analysis. - Gal Gilad; Mark D. M. Leiserson; Roded Sharan (PLoS Comput. Biol., 2021)

ScalpelSig Designs Targeted Genomic Panels from Data to Detect Activity of Mutational Signatures. - Nicholas Franzese; Jason Fan; Roded Sharan; Mark D. M. Leiserson (J. Comput. Biol., 2022)

A mutation-level covariate model for mutational signatures. - Itay Kahane; Mark D. M. Leiserson; Roded Sharan (PLoS Comput. Biol., 2023)