Constructing a tree from homeomorphic subtrees, with applications to computational evolutionary biology
Henzinger, Monika H
King, V.
Warnow, T.
Algorithms
Data structures
Evolutionary biology
Theory of databases
We are given a set T = {T 1 ,T 2 , . . .,T k } of rooted binary trees, each T i leaf-labeled by a subset L(Ti)⊂{1,2,...,n} . If T is a tree on {1,2, . . .,n }, we let T|L denote the minimal subtree of T induced by the nodes of L and all their ancestors. The consensus tree problem asks whether there exists a tree T * such that, for every i , T∗|L(Ti) is homeomorphic to T i .
We present algorithms which test if a given set of trees has a consensus tree and if so, construct one. The deterministic algorithm takes time min{O(N n 1/2 ), O(N+ n 2 log n )}, where N=∑i|Ti| , and uses linear space. The randomized algorithm takes time O(N log3 n) and uses linear space. The previous best for this problem was a 1981 O(Nn) algorithm by Aho et al. Our faster deterministic algorithm uses a new efficient algorithm for the following interesting dynamic graph problem: Given a graph G with n nodes and m edges and a sequence of b batches of one or more edge deletions, then, after each batch, either find a new component that has just been created or determine that there is no such component. For this problem, we have a simple algorithm with running time O(n 2 log n + b 0 min{n 2 , m log n }), where b 0 is the number of batches which do not result in a new component. For our particular application, b0≤1 . If all edges are deleted, then the best previously known deterministic algorithm requires time O(mn−−√) to solve this problem. We also present two applications of these consensus tree algorithms which solve other problems in computational evolutionary biology.
Springer Nature
1999
info:eu-repo/semantics/article
doc-type:article
text
http://purl.org/coar/resource_type/c_6501
https://research-explorer.ista.ac.at/record/11679
Henzinger M, King V, Warnow T. Constructing a tree from homeomorphic subtrees, with applications to computational evolutionary biology. <i>Algorithmica</i>. 1999;24:1-13. doi:<a href="https://doi.org/10.1007/pl00009268">10.1007/pl00009268</a>
eng
info:eu-repo/semantics/altIdentifier/doi/10.1007/pl00009268
info:eu-repo/semantics/altIdentifier/issn/0178-4617
info:eu-repo/semantics/altIdentifier/issn/1432-0541
info:eu-repo/semantics/closedAccess