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Documents authored by van Iersel, Leo

Document
DOI: 10.4230/LIPIcs.WABI.2023.7
Making a Network Orchard by Adding Leaves

Authors: Leo van Iersel, Mark Jones, Esther Julien, and Yukihiro Murakami

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Phylogenetic networks are used to represent the evolutionary history of species. Recently, the new class of orchard networks was introduced, which were later shown to be interpretable as trees with additional horizontal arcs. This makes the network class ideal for capturing evolutionary histories that involve horizontal gene transfers. Here, we study the minimum number of additional leaves needed to make a network orchard. We demonstrate that computing this proximity measure for a given network is NP-hard and describe a tight upper bound. We also give an equivalent measure based on vertex labellings to construct a mixed integer linear programming formulation. Our experimental results, which include both real-world and synthetic data, illustrate the efficiency of our implementation.
Cite as

Leo van Iersel, Mark Jones, Esther Julien, and Yukihiro Murakami. Making a Network Orchard by Adding Leaves. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 7:1-7:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{vaniersel_et_al:LIPIcs.WABI.2023.7,
  author =	{van Iersel, Leo and Jones, Mark and Julien, Esther and Murakami, Yukihiro},
  title =	{{Making a Network Orchard by Adding Leaves}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{7:1--7:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.7},
  URN =		{urn:nbn:de:0030-drops-186333},
  doi =		{10.4230/LIPIcs.WABI.2023.7},
  annote =	{Keywords: Phylogenetics, Network, Orchard Networks, Proximity Measures, NP-hardness}
}
Document
DOI: 10.4230/LIPIcs.ESA.2022.69
Embedding Phylogenetic Trees in Networks of Low Treewidth

Authors: Leo van Iersel, Mark Jones, and Mathias Weller

Published in: LIPIcs, Volume 244, 30th Annual European Symposium on Algorithms (ESA 2022)

Abstract
Given a rooted, binary phylogenetic network and a rooted, binary phylogenetic tree, can the tree be embedded into the network? This problem, called Tree Containment, arises when validating networks constructed by phylogenetic inference methods. We present the first algorithm for (rooted) Tree Containment using the treewidth t of the input network N as parameter, showing that the problem can be solved in 2^O(t²)⋅|N| time and space.
Cite as

Leo van Iersel, Mark Jones, and Mathias Weller. Embedding Phylogenetic Trees in Networks of Low Treewidth. In 30th Annual European Symposium on Algorithms (ESA 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 244, pp. 69:1-69:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{vaniersel_et_al:LIPIcs.ESA.2022.69,
  author =	{van Iersel, Leo and Jones, Mark and Weller, Mathias},
  title =	{{Embedding Phylogenetic Trees in Networks of Low Treewidth}},
  booktitle =	{30th Annual European Symposium on Algorithms (ESA 2022)},
  pages =	{69:1--69:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-247-1},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{244},
  editor =	{Chechik, Shiri and Navarro, Gonzalo and Rotenberg, Eva and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2022.69},
  URN =		{urn:nbn:de:0030-drops-170070},
  doi =		{10.4230/LIPIcs.ESA.2022.69},
  annote =	{Keywords: fixed-parameter tractability, treewidth, phylogenetic tree, phylogenetic network, display graph, tree containment, embedding}
}
Document
DOI: 10.4230/LIPIcs.WABI.2022.16
Reconstructing Phylogenetic Networks via Cherry Picking and Machine Learning

Authors: Giulia Bernardini, Leo van Iersel, Esther Julien, and Leen Stougie

Published in: LIPIcs, Volume 242, 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)

Abstract
Combining a set of phylogenetic trees into a single phylogenetic network that explains all of them is a fundamental challenge in evolutionary studies. In this paper, we apply the recently-introduced theoretical framework of cherry picking to design a class of heuristics that are guaranteed to produce a network containing each of the input trees, for practical-size datasets. The main contribution of this paper is the design and training of a machine learning model that captures essential information on the structure of the input trees and guides the algorithms towards better solutions. This is one of the first applications of machine learning to phylogenetic studies, and we show its promise with a proof-of-concept experimental study conducted on both simulated and real data consisting of binary trees with no missing taxa.
Cite as

Giulia Bernardini, Leo van Iersel, Esther Julien, and Leen Stougie. Reconstructing Phylogenetic Networks via Cherry Picking and Machine Learning. In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 16:1-16:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{bernardini_et_al:LIPIcs.WABI.2022.16,
  author =	{Bernardini, Giulia and van Iersel, Leo and Julien, Esther and Stougie, Leen},
  title =	{{Reconstructing Phylogenetic Networks via Cherry Picking and Machine Learning}},
  booktitle =	{22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)},
  pages =	{16:1--16:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-243-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{242},
  editor =	{Boucher, Christina and Rahmann, Sven},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2022.16},
  URN =		{urn:nbn:de:0030-drops-170507},
  doi =		{10.4230/LIPIcs.WABI.2022.16},
  annote =	{Keywords: Phylogenetics, Hybridization, Cherry Picking, Machine Learning, Heuristic}
}
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