Spelling suggestions: "subject:"combinatorial analysis"" "subject:"ombinatorial analysis""
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Enumerative methods in combinatorial analysisAbramson, Morton January 1966 (has links)
No description available.
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Bottleneck problems in combinatorics and optimizationLeung, Pak-kin, Richard, 梁柏堅 January 1998 (has links)
published_or_final_version / Mathematics / Master / Master of Philosophy
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Counting combinatorial structures in recursively constructible graphs /Leung, Yiu-cho. January 2007 (has links)
Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 121-126). Also available in electronic version.
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Bounding the number of graphs containing very long induced paths /Butler, Steven Kay, January 2003 (has links) (PDF)
Thesis (M.S.)--Brigham Young University. Dept. of Mathematics, 2003. / Includes bibliographical references (p. 32).
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On the probability that a discrete complex random matrix is singularWood, Philip J. January 2009 (has links)
Thesis (Ph. D.)--Rutgers University, 2009. / "Graduate Program in Mathematics." Includes bibliographical references (p. 80-82).
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Phylogenetic tree reconstruction with protein linkageYu, Junjie., 于俊杰. January 2012 (has links)
Phylogenetic tree reconstruction for a set of species is an important problem for understanding the evolutionary history of the species. Existing algorithms usually represent each species as a binary string with each bit indicating whether a particular gene/protein exists in the species. Given the topology of a phylogenetic tree with each leaf representing a species (a binary string of equal length) and each internal node representing the hypothetical ancestor, the Fitch-Hartigan algorithm and the Sankoff algorithm are two polynomial-time algorithms which assign binary strings to internal nodes such that the total Hamming distance between adjacent nodes in the tree is minimized. However, these algorithms oversimplify the evolutionary process by considering only the number of protein insertions/deletions (Hamming distance) between two species and by assuming the evolutionary history of each protein is independent.
Since the function of a protein may depend on the existence of other proteins, the evolutionary history of these functionally dependent proteins should be similar, i.e. functionally dependent proteins should usually be present (or absent) in a species at the same time. Thus, in addition to the Hamming distance, the protein linkage distance for some pairs/sets of proteins: whole block linkage distance, partial block linkage distance, pairwise linkage distance is introduced. It is proved that the phylogenetic tree reconstruction problem to find the binary strings for the internal nodes of a phylogenetic tree that minimizes the sum of the Hamming distance and the linkage distance is NP-hard.
In this thesis, a general algorithm to solve the phylogenetic tree reconstruction with protein linkage problem which runs in O(4^m⋅n) time for whole/partial block linkage distance and O(4^m⋅⋅ (m+n)) time for pairwise linkage distance (compared to the straight-forward O(4^m⋅ m⋅ n) or O(4^m⋅ m^2⋅⋅ n) time algorithm) is introduced where n is the number of species and m is the length of the binary string (number of proteins). It is further shown, by experiments, that our algorithm using linkage information can construct more accurate trees (better matches with the trees constructed by biologists) than the algorithms using only Hamming distance. / published_or_final_version / Computer Science / Master / Master of Philosophy
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Minimal rank of abelian group matricesChan, Yip-cheung., 陳葉祥. January 1996 (has links)
published_or_final_version / abstract / toc / Mathematics / Master / Master of Philosophy
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Towards long-standing conjectures in combinatoricsEccles, Thomas Edward January 2013 (has links)
No description available.
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Combinatorial optimization on series-parallel graphs : algorithms and complexityRichey, Michael Bruce 08 1900 (has links)
No description available.
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k-star decomposition of lambda-fold complete multipartite graphsAnzur, Matthew Paul, January 2007 (has links) (PDF)
Thesis (Ph.D.)--Auburn University, 2007. / Abstract. Vita. Includes bibliographic references (ℓ. 39)
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