The Imperfect Ancestral Recombination Graph Reconstruction Problem: Upper Bounds for Recombination and Homoplasy

2010 ◽  
Vol 17 (6) ◽  
pp. 767-781
Author(s):  
Fumei Lam ◽  
Ryan Tarpine ◽  
Sorin Istrail
Author(s):  
Dániel Garamvölgyi ◽  
Tibor Jordán

AbstractA d-dimensional framework is a pair (G, p), where $$G=(V,E)$$ G = ( V , E ) is a graph and p is a map from V to $$\mathbb {R}^d$$ R d . The length of an edge $$uv\in E$$ u v ∈ E in (G, p) is the distance between p(u) and p(v). The framework is said to be globally rigid in $$\mathbb {R}^d$$ R d if every other d-dimensional framework (G, q), in which the corresponding edge lengths are the same, is congruent to (G, p). In a recent paper Gortler, Theran, and Thurston proved that if every generic framework (G, p) in $$\mathbb {R}^d$$ R d is globally rigid for some graph G on $$n\ge d+2$$ n ≥ d + 2 vertices (where $$d\ge 2$$ d ≥ 2 ), then already the set of (unlabeled) edge lengths of a generic framework (G, p), together with n, determine the framework up to congruence. In this paper we investigate the corresponding unlabeled reconstruction problem in the case when the above generic global rigidity property does not hold for the graph. We provide families of graphs G for which the set of (unlabeled) edge lengths of any generic framework (G, p) in d-space, along with the number of vertices, uniquely determine the graph, up to isomorphism. We call these graphs weakly reconstructible. We also introduce the concept of strong reconstructibility; in this case the labeling of the edges is also determined by the set of edge lengths of any generic framework. For $$d=1,2$$ d = 1 , 2 we give a partial characterization of weak reconstructibility as well as a complete characterization of strong reconstructibility of graphs. In particular, in the low-dimensional cases we describe the family of weakly reconstructible graphs that are rigid but not redundantly rigid.


Author(s):  
Paul Balister ◽  
Béla Bollobás ◽  
Bhargav Narayanan

The chapter “Reconstructing Random Jigsaws” examines the reconstruction problem for a family of discrete structures, asking whether it is possible to uniquely reconstruct a structure in this family from the “deck” of all its substructures of some fixed size. Reconstruction problems involving combinatorics and randomness have a very rich history. The oldest such problem is perhaps the graph reconstruction conjecture of Kelly and Ulam; analogous questions include reconstructing finite sets satisfying symmetry conditions, reconstructing finite abelian groups, and reconstructing finite subsets of the plane. A natural line of enquiry is to ask how the answer to the reconstruction problem changes when it is necessary to reconstruct a typical (as opposed to an arbitrary) structure in a family of discrete structures. This chapter presents a theoretical case study of interest for all the complex architectures of networks: a reconstruction problem connected with DNA sequencing via the shotgun-sequencing technique.


Author(s):  
Pamela Fleischmann ◽  
Marie Lejeune ◽  
Florin Manea ◽  
Dirk Nowotka ◽  
Michel Rigo

A reconstruction problem of words from scattered factors asks for the minimal information, like multisets of scattered factors of a given length or the number of occurrences of scattered factors from a given set, necessary to uniquely determine a word. We show that a word [Formula: see text] can be reconstructed from the number of occurrences of at most [Formula: see text] scattered factors of the form [Formula: see text], where [Formula: see text] is the number of occurrences of the letter [Formula: see text] in [Formula: see text]. Moreover, we generalise the result to alphabets of the form [Formula: see text] by showing that at most [Formula: see text] scattered factors suffices to reconstruct [Formula: see text]. Both results improve on the upper bounds known so far. Complexity time bounds on reconstruction algorithms are also considered here.


1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.


Author(s):  
S. Yahya Mohamed ◽  
A. Mohamed Ali

In this paper, the notion of energy extended to spherical fuzzy graph. The adjacency matrix of a spherical fuzzy graph is defined and we compute the energy of a spherical fuzzy graph as the sum of absolute values of eigenvalues of the adjacency matrix of the spherical fuzzy graph. Also, the lower and upper bounds for the energy of spherical fuzzy graphs are obtained.


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