Single-cell tumor phylogeny inference with copy-number constrained mutation losses

Gryte Satas; Simone Zaccaria; Geoffrey Mon; Benjamin J. Raphael

doi:10.1007/978-3-030-45257-5_35

Single-cell tumor phylogeny inference with copy-number constrained mutation losses

Gryte Satas, Simone Zaccaria, Geoffrey Mon, Benjamin J. Raphael

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Motivation: Single-cell DNA sequencing enables the measurement of somatic mutations in individual tumor cells, and provides data to reconstruct the evolutionary history of the tumor.

Original language	English (US)
Title of host publication	Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings
Editors	Russell Schwartz
Publisher	Springer
Pages	273
Number of pages	1
ISBN (Print)	9783030452568
DOIs	https://doi.org/10.1007/978-3-030-45257-5_35
State	Published - 2020
Event	24th Annual Conference on Research in Computational Molecular Biology, RECOMB 2020 - Padua, Italy Duration: May 10 2020 → May 13 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12074 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	24th Annual Conference on Research in Computational Molecular Biology, RECOMB 2020
Country/Territory	Italy
City	Padua
Period	5/10/20 → 5/13/20

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-45257-5_35

Cite this

Satas, G., Zaccaria, S., Mon, G., & Raphael, B. J. (2020). Single-cell tumor phylogeny inference with copy-number constrained mutation losses. In R. Schwartz (Ed.), Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings (pp. 273). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12074 LNBI). Springer. https://doi.org/10.1007/978-3-030-45257-5_35

Satas, Gryte ; Zaccaria, Simone ; Mon, Geoffrey et al. / Single-cell tumor phylogeny inference with copy-number constrained mutation losses. Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings. editor / Russell Schwartz. Springer, 2020. pp. 273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Single-cell tumor phylogeny inference with copy-number constrained mutation losses",

abstract = "Motivation: Single-cell DNA sequencing enables the measurement of somatic mutations in individual tumor cells, and provides data to reconstruct the evolutionary history of the tumor.",

author = "Gryte Satas and Simone Zaccaria and Geoffrey Mon and Raphael, {Benjamin J.}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 24th Annual Conference on Research in Computational Molecular Biology, RECOMB 2020 ; Conference date: 10-05-2020 Through 13-05-2020",

year = "2020",

doi = "10.1007/978-3-030-45257-5_35",

language = "English (US)",

isbn = "9783030452568",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "273",

editor = "Russell Schwartz",

booktitle = "Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings",

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Satas, G, Zaccaria, S, Mon, G & Raphael, BJ 2020, Single-cell tumor phylogeny inference with copy-number constrained mutation losses. in R Schwartz (ed.), Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12074 LNBI, Springer, pp. 273, 24th Annual Conference on Research in Computational Molecular Biology, RECOMB 2020, Padua, Italy, 5/10/20. https://doi.org/10.1007/978-3-030-45257-5_35

Single-cell tumor phylogeny inference with copy-number constrained mutation losses. / Satas, Gryte; Zaccaria, Simone; Mon, Geoffrey et al.
Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings. ed. / Russell Schwartz. Springer, 2020. p. 273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12074 LNBI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Satas, Gryte

AU - Zaccaria, Simone

AU - Mon, Geoffrey

AU - Raphael, Benjamin J.

PY - 2020

Y1 - 2020

N2 - Motivation: Single-cell DNA sequencing enables the measurement of somatic mutations in individual tumor cells, and provides data to reconstruct the evolutionary history of the tumor.

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M3 - Conference contribution

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings

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Satas G, Zaccaria S, Mon G, Raphael BJ. Single-cell tumor phylogeny inference with copy-number constrained mutation losses. In Schwartz R, editor, Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings. Springer. 2020. p. 273. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-45257-5_35

Single-cell tumor phylogeny inference with copy-number constrained mutation losses

Abstract

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All Science Journal Classification (ASJC) codes

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