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Exploring the Solution Space of Cancer Evolution Inference Frameworks for Single-Cell Sequencing Data.

, , , , , и . WIVACE, том 1780 из Communications in Computer and Information Science, стр. 70-81. Springer, (2022)

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Daniele Suzzi

Daniele Pillitteri

Daniele Capriotti

Daniele Gaggero

Daniele Martini

 

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Learning mutational graphs of individual tumor evolution from multi-sample sequencing data., , , , и . CoRR, (2017)Control-FREEC viewer: a tool for the visualization and exploration of copy number variation data., , , и . BMC Bioinform., 25 (1): 72 (декабря 2024)Assessment of network module identification across complex diseases, , , , , , , , , и 168 other автор(ы). Nature Methods, 16 (9): 843--852 (2019)Exploring the Solution Space of Cancer Evolution Inference Frameworks for Single-Cell Sequencing Data., , , , , и . WIVACE, том 1780 из Communications in Computer and Information Science, стр. 70-81. Springer, (2022)cyTRON and cyTRON/JS: Two Cytoscape-Based Applications for the Inference of Cancer Evolution Models., , , , , , и . CIBB, том 12313 из Lecture Notes in Computer Science, стр. 13-18. Springer, (2019)Exposing the Probabilistic Causal Structure of Discrimination., , , и . CoRR, (2015)Inference of Cancer Progression Models with Biological Noise., , , и . CoRR, (2014)Structural Learning of Probabilistic Graphical Models of Cumulative Phenomena., , , и . ICCS (1), том 10860 из Lecture Notes in Computer Science, стр. 678-693. Springer, (2018)Efficient Simulation of Financial Stress Testing Scenarios with Suppes-Bayes Causal Networks., , и . ICCS, том 108 из Procedia Computer Science, стр. 272-284. Elsevier, (2017)De novo mutational signature discovery in tumor genomes using SparseSignatures., , , , и . PLoS Comput. Biol., (2021)