On The Algorithmic Tractability Of Single Nucleotide Polymorphism Snp Analysis And Related Problems
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On the Algorithmic Tractability of Single Nucleotide Polymorphism (SNP) Analysis and Related Problems
Inhaltsangabe:Abstract: This work brings together two areas of science biology and informatics that have only recently been connected in the emerging (and vastly growing) research field of Bioinformatics. In order to achieve a common basis for Parts 2 and 3 of this work, Part 1 intends to introduce the computer scientist to the relevant biological background and terminology (Chapter 2), and to familiarize the biologist with the relevant topics from theoretical computer science (Chapter 3). Chapter 2 first introduces some terminology from the field of genetics, thereby defining SNPs. We then motivate the analysis of SNPs by two applications, i.e. the analysis of evolutionary development and the field of pharmacogenetics. Especially the field of pharmacogenetics is capable of having an enormous impact on medicine and the pharmaceutical industry in the near future by using SNP data to predict the efficacy of medication. Chapter 3 gives a brief introduction to the field of computational complexity. We will see and motivate how algorithms are analyzed in theoretical computer science. This will lead to the definition of complexity classes , introducing the class NP which includes computationally hard problems. Some of the hard problems in the class NP can be solved efficiently using the tool of fixed-parameter tractability, introduced at the end of this chapter. An important application of SNP data is in the analysis of the evolutionary history of species development (phylogenetic analysis part two chapters 4 and 5). As will be made plausible in Chapter 5 using SNP data is in many ways superior to previous approaches of phylogenetic analysis. In order to analyze the development of species using SNP data, an underlying model of evolution must be specified. A popular model is the so-called perfect phylogeny, but the construction of this phylogeny is a computationally hard problem when there are inconsistencies (such as read-errors or an imperfect .t to the model of perfect phylogeny) in the underlying data. Chapter 4 analyzes the problem of forbidden submatrix removal which is closely connected to constructing perfect phylogenies we will see in Chapter 5 that its computational complexity is directly related to that of constructing a perfect phylogeny from data which is partially erroneous. In this chapter, we analyze the algorithmic tractability of forbidden submatrix removal , characterizing cases where this problem is NP-complete (being [...]
Experimental and Efficient Algorithms
Author: Sotiris Nikoletseas
language: en
Publisher: Springer Science & Business Media
Release Date: 2005-04-28
This book constitutes the refereed proceedings of the 4th International Workshop on Experimental and Efficient Algorithms, WEA 2005, held in Santorini Island, Greece in May 2005. The 47 revised full papers and 7 revised short papers presented together with extended abstracts of 3 invited talks were carefully reviewed and selected from 176 submissions. The book is devoted to the design, analysis, implementation, experimental evaluation, and engineering of efficient algorithms. Among the application areas addressed are most fields applying advanced algorithmic techniques, such as combinatorial optimization, approximation, graph theory, discrete mathematics, scheduling, searching, sorting, string matching, coding, networking, data mining, data analysis, etc.
Parameterized and Exact Computation
This book constitutes the thoroughly refereed post-conference proceedings of the 6th International Symposium on Parameterized and Exact Computation, IPEC 2011, in Saarbrücken, Germany, in September 2011. The 21 revised full papers presented were carefully reviewed and selected from 40 submissions. The topics addressed cover research in all aspects of parameterized and exact computation and complexity, including but not limited to new techniques for the design and analysis of parameterized and exact algorithms, fixed-parameter tractability results, parameterized complexity theory, relationship between parameterized complexity and traditional complexity classifications, applications of parameterized and exact computation, and implementation issues of parameterized and exact algorithms.