WALCOM: Algorithms and Computation: 14th International Conference, WALCOM 2020, Singapore, Singapore, March 31 – April 2, 2020, Proceedings

A graph is planar if it can be drawn or embedded in the plane so that no two edges intersect geometrically except at a vertex to which they are both incident. A plane graph is a planar graph with a fixed planar embedding in the plane. A drawing problem X for a plane graph G asks to determine whether G has a drawing D satisfying a set P of given properties and to find D if it exists. The corresponding problem for a planar graph G asks to determine whether G has a planar embedding Γ such that Γ has a drawing D satisfying the set P of properties and find D if it exists. If every embedding of G has a drawing D satisfying P , then the problem is trivial, i.e., the problem for plane graphs and that for planar graphs are the same. Otherwise, the problem for planar graphs becomes difficult even if an efficient solution of the problem for a plane graph exists since a planar graph may have an exponential number of planar embeddings. Various techniques are found in literature that are used to solve the drawing problems for planar graphs. In this paper we review three of the widely used techniques, namely, (i) reduction to planarity testing, (ii) incremental modification and (iii) SPQR-tree decomposition.

[1]  James Nga-Kwok Liu,et al.  Automatic extraction and identification of chart patterns towards financial forecast , 2007, Appl. Soft Comput..

[2]  Bhaskar DasGupta,et al.  A decomposition theorem and two algorithms for reticulation-visible networks , 2017, Inf. Comput..

[3]  Rudolf Fleischer,et al.  Order Preserving Matching , 2013, Theor. Comput. Sci..

[4]  Jorma Tarhio,et al.  Order-Preserving Matching with Filtration , 2014, SEA.

[5]  Mathias Weller,et al.  Linear-Time Tree Containment in Phylogenetic Networks , 2017, RECOMB-CG.

[6]  Louxin Zhang Clusters, Trees, and Phylogenetic Network Classes , 2019, Bioinformatics and Phylogenetics.

[7]  Dan Gusfield,et al.  The Fine Structure of Galls in Phylogenetic Networks , 2004, INFORMS J. Comput..

[8]  Gad M. Landau,et al.  Cartesian Tree Matching and Indexing , 2019, CPM.

[9]  Daniel H. Huson,et al.  Beyond Galled Trees - Decomposition and Computation of Galled Networks , 2007, RECOMB.

[10]  Uzi Vishkin,et al.  Optimal Doubly Logarithmic Parallel Algorithms Based on Finding All Nearest Smaller Values , 1993, J. Algorithms.

[11]  T. V. Lakshman,et al.  Variable-Stride Multi-Pattern Matching For Scalable Deep Packet Inspection , 2009, IEEE INFOCOM 2009.

[12]  Louxin Zhang,et al.  S‐Cluster++: a fast program for solving the cluster containment problem for phylogenetic networks , 2018, Bioinform..

[13]  Louxin Zhang,et al.  Compression of Phylogenetic Networks and Algorithm for the Tree Containment Problem , 2019, J. Comput. Biol..

[14]  Beate Commentz-Walter,et al.  A String Matching Algorithm Fast on the Average , 1979, ICALP.

[15]  Louxin Zhang,et al.  Solving the tree containment problem in linear time for nearly stable phylogenetic networks , 2017, Discret. Appl. Math..

[16]  Stephen J. Willson,et al.  Unique Determination of Some Homoplasies at Hybridization Events , 2007, Bulletin of mathematical biology.

[17]  Robert S. Boyer,et al.  A fast string searching algorithm , 1977, CACM.

[18]  Donald Ervin Knuth,et al.  The Art of Computer Programming, Volume II: Seminumerical Algorithms , 1970 .

[19]  Mike A. Steel,et al.  Which Phylogenetic Networks are Merely Trees with Additional Arcs? , 2015, Systematic biology.

[20]  Mihalis Yannakakis,et al.  Node-and edge-deletion NP-complete problems , 1978, STOC.

[21]  Ronald L. Rivest,et al.  Introduction to Algorithms, Second Edition , 2001 .

[22]  Andreas D. M. Gunawan Solving the Tree Containment Problem for Reticulation-Visible Networks in Linear Time , 2018, AlCoB.

[23]  Wojciech Plandowski,et al.  Fast Practical Multi-Pattern Matching , 1999, Inf. Process. Lett..

[24]  Alfred V. Aho,et al.  Efficient string matching , 1975, Commun. ACM.

[25]  Kunsoo Park,et al.  Fast Cartesian Tree Matching , 2019, SPIRE.

[26]  Jeong Seop Sim,et al.  Fast Multiple Order-Preserving Matching Algorithms , 2015, IWOCA.

[27]  Jean Vuillemin,et al.  A unifying look at data structures , 1980, CACM.

[28]  Wojciech Rytter,et al.  A linear time algorithm for consecutive permutation pattern matching , 2013, Inf. Process. Lett..

[29]  Marcin Wrochna,et al.  Reconfiguration in bounded bandwidth and tree-depth , 2014, J. Comput. Syst. Sci..

[30]  L. Orgel,et al.  Phylogenetic Classification and the Universal Tree , 1999 .

[31]  Louxin Zhang On Tree-Based Phylogenetic Networks , 2016, J. Comput. Biol..

[32]  Louxin Zhang,et al.  A program for verification of phylogenetic network models , 2016 .

[33]  Katsuto Nakajima,et al.  On rectangle intersection and overlap graphs , 1995 .

[34]  Gabriel Cardona,et al.  Comparison of Tree-Child Phylogenetic Networks , 2007, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[35]  Thierry Lecroq,et al.  A Very Fast String Matching Algorithm for Small Alphabeths and Long Patterns (Extended Abstract) , 1998, CPM.

[36]  Kaizhong Zhang,et al.  Perfect Phylogenetic Networks with Recombination , 2001, J. Comput. Biol..

[37]  Richard M. Karp,et al.  Efficient Randomized Pattern-Matching Algorithms , 1987, IBM J. Res. Dev..

[38]  Xiaohui Huang,et al.  Approximation algorithms for minimum weight connected 3-path vertex cover , 2019, Appl. Math. Comput..

[39]  Wei Zhang,et al.  A Memory Efficient Multiple Pattern Matching Architecture for Network Security , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[40]  Chun-Hung Richard Lin,et al.  Intrusion detection system: A comprehensive review , 2013, J. Netw. Comput. Appl..

[41]  Dekel Tsur Parameterized algorithm for 3-path vertex cover , 2019, Theor. Comput. Sci..

[42]  Louxin Zhang,et al.  Generating normal networks via leaf insertion and nearest neighbor interchange , 2019, BMC Bioinformatics.

[43]  Wing-Kai Hon,et al.  Space-Efficient Dictionaries for Parameterized and Order-Preserving Pattern Matching , 2016, CPM.