Дисертації з теми "Sequence alignment algorithms"
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Starrett, Dean. "Optimal Alignment of Multiple Sequence Alignments." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/194840.
Повний текст джерелаPowell, David Richard 1973. "Algorithms for sequence alignment." Monash University, School of Computer Science and Software Engineering, 2001. http://arrow.monash.edu.au/hdl/1959.1/8051.
Повний текст джерелаArvestad, Lars. "Algorithms for biological sequence alignment." Doctoral thesis, KTH, Numerisk analys och datalogi, NADA, 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-2905.
Повний текст джерелаHo, Ngai-lam, and 何毅林. "Algorithms on constrained sequence alignment." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30201949.
Повний текст джерелаAlimehr, Leila. "The Performance of Sequence Alignment Algorithms." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-200289.
Повний текст джерелаNguyen, Ken D. "Multiple Biolgical Sequence Alignment: Scoring Functions, Algorithms, and Evaluations." Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/cs_diss/62.
Повний текст джерелаJiang, Tianwei. "Sequence alignment : algorithm development and applications /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?ECED%202009%20JIANG.
Повний текст джерелаLu, Yue. "Improving the quality of multiple sequence alignment." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-3111.
Повний текст джерелаIsa, Mohammad Nazrin. "High performance reconfigurable architectures for biological sequence alignment." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/7721.
Повний текст джерелаZhou, Rong. "Memory-efficient graph search applied to multiple sequence alignment." Diss., Mississippi State : Mississippi State University, 2005. http://library.msstate.edu/etd/show.asp?etd=etd-06282005-015428.
Повний текст джерелаLassmann, Timo. "Algorithms for building and evaluating multiple sequence alignments /." Stockholm, 2006. http://diss.kib.ki.se/2006/91-7140-887-8/.
Повний текст джерелаRumbold, A. "Multiple sequence alignment algorithms for the phylogenic analysis of chloroplast DNA." Thesis, Honours thesis, University of Tasmania, 2004. https://eprints.utas.edu.au/100/1/HonoursThesis_final.pdf.
Повний текст джерелаGharazi, Elham. "IMAP : design and implementation of an interactive and integrative programming environment for progressive multiple sequence alignment and phylogeny reconstruction." Phd thesis, Faculty of Engineering and Information Technologies, 2011. http://hdl.handle.net/2123/9328.
Повний текст джерелаNgxande, Mkhuseli. "Development of high performance computing cluster for evaluation of sequence alignment algorithms." Thesis, University of Fort Hare, 2015. http://hdl.handle.net/10353/d1020163.
Повний текст джерелаYim, Cheuk-hon Terence. "Approximate string alignment and its application to ESTs, mRNAs and genome mapping." Click to view the E-thesis via HKUTO, 2004. http://sunzi.lib.hku.hk/hkuto/record/B31455736.
Повний текст джерелаZhao, Zhiyu. "Robust and Efficient Algorithms for Protein 3-D Structure Alignment and Genome Sequence Comparison." ScholarWorks@UNO, 2008. http://scholarworks.uno.edu/td/851.
Повний текст джерелаHelal, Manal Computer Science & Engineering Faculty of Engineering UNSW. "Indexing and partitioning schemes for distributed tensor computing with application to multiple sequence alignment." Awarded by:University of New South Wales. Computer Science & Engineering, 2009. http://handle.unsw.edu.au/1959.4/44781.
Повний текст джерелаBuckingham, Lawrence. "K-mer based algorithms for biological sequence comparison and search." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/236377/1/Buckingham%2BThesis%281%29.pdf.
Повний текст джерелаYim, Cheuk-hon Terence, and 嚴卓漢. "Approximate string alignment and its application to ESTs, mRNAs and genome mapping." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31455736.
Повний текст джерелаDarbha, Sriram. "RNA Homology Searches Using Pair Seeding." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/1172.
Повний текст джерелаWe also show that pair seeds can be effectively combined with the spaced seeds approach to nucleotide homology search. The hybrid search method has theoretical specificity superior to that of the BLAST seed. We provide experimental evaluation of our hypotheses. Finally, we note that our method is easily modified to process pseudo-knotted regions in the query, something outside the scope of covariance model based methods.
Ticona, Waldo Gonzalo Cancino. "Aplicação de algoritmos genéricos multi-objetivo para alinhamento de seqüências biológicas." Universidade de São Paulo, 2003. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-09052003-215914/.
Повний текст джерелаThe Biological Sequence Alignment is a basic operation in Bioinformatics since it serves as a basis for other processes, i.e. determination of the protein's three-dimensional structure. Due to the large amount of data involved, mathematical and computational methods have been used to solve this problem. Traditionally, the Biological Alignment Sequence Problem is formulated as a single optimization problem. Each solution has a score that reflects the similarity between sequences. Then, the optimization process looks for the best score solution. The Multi-Objective Optimization solves problems with multiple objectives that must be reached. Frequently, there is a solution set that represents a trade-off between the objectives. Evolutionary Algorithms, which are inspired by Darwin's Evolution Theory, have been applied with success in solving this kind of problems. This work formulates the Biological Sequence Alignment as a Multi-Objective Optimization Problem in order to find a set of solutions that represent a trade-off between the extension and the quality of the solutions. Several models of Evolutionary Algorithms for Multi-Objetive Optimization have been applied and were evaluated using several performance metrics found in the literature.
Yin, Zhaoming. "Enhance the understanding of whole-genome evolution by designing, accelerating and parallelizing phylogenetic algorithms." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51875.
Повний текст джерелаFurcy, David Andre. "Speeding Up the Convergence of Online Heuristic Search and Scaling Up Offline Heuristic Search." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4855.
Повний текст джерелаLiakhovitch, Evgueni. "Genetic algorithm using restricted sequence alignments." Ohio : Ohio University, 2000. http://www.ohiolink.edu/etd/view.cgi?ohiou1172598174.
Повний текст джерелаZafalon, Geraldo Francisco Donegá. "Aplicação de estratégias híbridas em algoritmos de alinhamento múltiplo de sequências para ambientes de computação paralela e distribuída." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-28082015-120515/.
Повний текст джерелаBioinformatics has been developed in a fast way in the last years. The need for processing large sequences sets, either nucleotides or aminoacids, has stimulated the development of many algorithmic techniques, to solve this problem in a feasible way. Multiple sequence alignment algorithms have played an important role, because with the reduced computational complexity provided by them, it is possible to perform alignments with more than two sequences. However, with the fast growing of the amount and length of sequences in a set, the use of multiple alignment algorithms without new optimization strategies became almost impossible. Therefore, high performance computing has emerged as one of the features being used, through the parallelization of many strategies for execution in large computational systems. Moreover, with the continued expansion of sequences sets, other optimization strategies have been coupled with parallel multiple sequence alignments. Thus, the development of multiple sequences alignment tools based on hybrid strategies has been considered the solution with the best results. In this work, we present the development of a hybrid strategy to progressive multiple sequence alignment, where its using is widespread in Bioinformatics. In this approach, we have aggregated the parallelization and the partitioning of sequences sets in the score matrix calculation stage, and the optimization of the stages of the phylogenetic tree reconstruction and multiple alignment through ant colony and parallel simulated annealing algorithms, respectively.
Garriga, Nogales Edgar 1990. "New algorithmic contributions for large scale multiple sequence alignments of protein sequences." Doctoral thesis, TDX (Tesis Doctorals en Xarxa), 2022. http://hdl.handle.net/10803/673526.
Повний текст джерелаEn aquests dies de profunds canvis i una ràpida evolució de la tecnologia, la quantitat de dataque la ciència ha de treballar ha crescut increïblement ràpid i la grandària dels arxius ha crescutde manera quasi prohibitiva.Els alineaments múltiples de seqüència (MSA) es fan servir endiverses àrees de la biologia, i l'increment de les dades ha produït una degradació delsresultats. És per això, que es proposa una nova estratègia per realitzar els alineaments. Aquestnou paradigma permet alinear milions de seqüències i l'opcio de modularitzar el procés.'Regressive' permet la paral·lelització del procés i la combinació de diferents algoritmesd'agrupacio (guide-tree) amb el mètode de alineament que és desitgi. Dins del camp del'agrupació, s'ha de repensar l'estratègia per crear els guide-tree. Un estudi sobre l'estat actualdels mètodes i les seves virtuts i punts febles ha sigut realitzar per llençar una mica de llum enaquesta àrea. Els 'guide-tree' no poden ser el coll de botella, i haurien de servir per començarde la millor manera possible el procés d'alineament.
Cunial, Fabio. "Analysis of the subsequence composition of biosequences." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44716.
Повний текст джерелаRinaudo, Philippe. "Algorithmique de l'alignement structure-séquence d'ARN : une approche générale et paramétrée." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00847745.
Повний текст джерелаZhang, Xiaodong. "A Local Improvement Algorithm for Multiple Sequence Alignment." Ohio University / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1049485762.
Повний текст джерелаZhang, Ching. "Genetic algorithm approaches for efficient multiple molecular sequence alignment." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0013/NQ30660.pdf.
Повний текст джерелаAhmed, Nova. "Parallel Algorithm for Memory Efficient Pairwise and Multiple Genome Alignment in Distributed Environment." Digital Archive @ GSU, 2004. http://digitalarchive.gsu.edu/cs_theses/2.
Повний текст джерелаKim, Eagu. "Inverse Parametric Alignment for Accurate Biological Sequence Comparison." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/193664.
Повний текст джерелаURGESE, GIANVITO. "Computational Methods for Bioinformatics Analysis and Neuromorphic Computing." Doctoral thesis, Politecnico di Torino, 2016. http://hdl.handle.net/11583/2646486.
Повний текст джерелаHameed, A. "Parallelization of the AAE algorithm." Thesis, Honours thesis, University of Tasmania, 2007. https://eprints.utas.edu.au/3270/1/ahThesis.pdf.
Повний текст джерелаBell, Lachlan Hamilton. "Sequence analysis of enzymes of the shikimate pathway : development of a novel multiple sequence alignment algorithm." Thesis, University of Glasgow, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307193.
Повний текст джерелаIoste, Aline Rodrigheri. "Sequências de DNA: uma nova abordagem para o alinhamento ótimo." Pontifícia Universidade Católica de São Paulo, 2016. https://tede2.pucsp.br/handle/handle/18207.
Повний текст джерелаThe objective of this study is to deeply understand the techniques currently used in optimal alignment of DNA sequences, focused on the strengths and limitations of these methods. Analyzing the feasibility of creating a new logical approach able to ensure optimal results , taking into account existing problems in optimal alignment as: (i ) the numerous alignment possibilities of two sequences , ( ii ) the great need for space and memory the machines, ( ii ) processing time to compute the optimal data and (iv ) exponential growth. This study allowed the beginning of the creation of a new logical approach to the global optimum alignment, showing promising results in higher scores with less need for calculations where the mastery of these new techniques can lead to use search of excellent results in the global alignment optimal in large data bases
O objetivo deste estudo é entender profundamente as técnicas utilizadas atualmente no alinhamento ótimo de sequências de DNA e analisar a viabilidade da criação de uma nova abordagem lógica capaz de garantir o resultado ótimo, levando em consideração os problemas existentes no alinhamento ótimo como: (i) as inúmeras possibilidades de alinhamento de duas sequências, (ii) a grande necessidade de espaço e memória das máquinas, (ii) o tempo de processamento para computar os dados ótimos e (iv) seu crescimento exponencial. O presente estudo permitiu o início da criação de uma nova abordagem lógica para o alinhamento ótimo global, demonstrando resultados promissores de maiores pontuações com menos necessidades de cálculos, onde o domínio destas novas técnicas pode conduzir à utilização da busca de resultados ótimos no alinhamento global de sequências biológicas em grandes bases de dados
Pappas, Nicholas Peter. "Searching Biological Sequence Databases Using Distributed Adaptive Computing." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/31074.
Повний текст джерелаMaster of Science
Hu, Hanqing. "USING PROGRAM SLICING AND SEQUENCE ALIGNMENT TO ANALYZE ORGANISMS OF AVIDA, A DIGITAL EVOLUTION PLATFORM." Miami University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=miami1331015337.
Повний текст джерелаCuevas, Tristan Lee. "A PAIRWISE COMPARISON OF DNA SEQUENCE ALIGNMENT USING AN OPENMP IMPLEMENTATION OF THE SWAMP PARALLEL SMITH-WATERMAN ALGORITHM." Kent State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=kent1429528937.
Повний текст джерелаTrněný, Ondřej. "Metody vícenásobného zarovnávání nukleotidových sekvencí." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220010.
Повний текст джерелаDing, Guoxiang. "DERIVING ACTIVITY PATTERNS FROM INDIVIDUAL TRAVEL DIARY DATA: A SPATIOTEMPORAL DATA MINING APPROACH." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1236777859.
Повний текст джерелаNosek, Ondřej. "Hardwarová akcelerace algoritmu pro hledání podobnosti dvou DNA řetězců." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2007. http://www.nusl.cz/ntk/nusl-236882.
Повний текст джерелаZhao, Mengyao. "Genomic variation detection using dynamic programming methods." Thesis, Boston College, 2014. http://hdl.handle.net/2345/bc-ir:104357.
Повний текст джерелаBackground: Due to the rapid development and application of next generation sequencing (NGS) techniques, large amounts of NGS data have become available for genome-related biological research, such as population genetics, evolutionary research, and genome wide association studies. A crucial step of these genome-related studies is the detection of genomic variation between different species and individuals. Current approaches for the detection of genomic variation can be classified into alignment-based variation detection and assembly-based variation detection. Due to the limitation of current NGS read length, alignment-based variation detection remains the mainstream approach. The Smith-Waterman algorithm, which produces the optimal pairwise alignment between two sequences, is frequently used as a key component of fast heuristic read mapping and variation detection tools for next-generation sequencing data. Though various fast Smith-Waterman implementations are developed, they are either designed as monolithic protein database searching tools, which do not return detailed alignment, or they are embedded into other tools. These issues make reusing these efficient Smith-Waterman implementations impractical. After the alignment step in the traditional variation detection pipeline, the afterward variation detection using pileup data and the Bayesian model is also facing great challenges especially from low-complexity genomic regions. Sequencing errors and misalignment problems still influence variation detection (especially INDEL detection) a lot. The accuracy of genomic variation detection still needs to be improved, especially when we work on low- complexity genomic regions and low-quality sequencing data. Results: To facilitate easy integration of the fast Single-Instruction-Multiple-Data Smith-Waterman algorithm into third-party software, we wrote a C/C++ library, which extends Farrar's Striped Smith-Waterman (SSW) to return alignment information in addition to the optimal Smith-Waterman score. In this library we developed a new method to generate the full optimal alignment results and a suboptimal score in linear space at little cost of efficiency. This improvement makes the fast Single-Instruction-Multiple-Data Smith-Waterman become really useful in genomic applications. SSW is available both as a C/C++ software library, as well as a stand-alone alignment tool at: https://github.com/mengyao/Complete- Striped-Smith-Waterman-Library. The SSW library has been used in the primary read mapping tool MOSAIK, the split-read mapping program SCISSORS, the MEI detector TAN- GRAM, and the read-overlap graph generation program RZMBLR. The speeds of the mentioned software are improved significantly by replacing their ordinary Smith-Waterman or banded Smith-Waterman module with the SSW Library. To improve the accuracy of genomic variation detection, especially in low-complexity genomic regions and on low-quality sequencing data, we developed PHV, a genomic variation detection tool based on the profile hidden Markov model. PHV also demonstrates a novel PHMM application in the genomic research field. The banded PHMM algorithms used in PHV make it a very fast whole-genome variation detection tool based on the HMM method. The comparison of PHV to GATK, Samtools and Freebayes for detecting variation from both simulated data and real data shows PHV has good potential for dealing with sequencing errors and misalignments. PHV also successfully detects a 49 bp long deletion that is totally misaligned by the mapping tool, and neglected by GATK and Samtools. Conclusion: The efforts made in this thesis are very meaningful for methodology development in studies of genomic variation detection. The two novel algorithms stated here will also inspire future work in NGS data analysis
Thesis (PhD) — Boston College, 2014
Submitted to: Boston College. Graduate School of Arts and Sciences
Discipline: Biology
Belghiti, Moulay Tayeb. "Modélisation et techniques d'optimisation en bio-informatique et fouille de données." Thesis, Rouen, INSA, 2008. http://www.theses.fr/2008ISAM0002.
Повний текст джерелаThis Ph.D. thesis is particularly intended to treat two types of problems : clustering and the multiple alignment of sequence. Our objective is to solve efficiently these global problems and to test DC Programming approach and DCA on real datasets. The thesis is divided into three parts : the first part is devoted to the new approaches of nonconvex optimization-global optimization. We present it a study in depth of the algorithm which is used in this thesis, namely the programming DC and the algorithm DC ( DCA). In the second part, we will model the problem clustering in three nonconvex subproblems. The first two subproblems are distinguished compared to the choice from the norm used, (clustering via norm 1 and 2). The third subproblem uses the method of the kernel, (clustering via the method of the kernel). The third part will be devoted to bioinformatics, one goes this focused on the modeling and the resolution of two subproblems : the multiple alignment of sequence and the alignment of sequence of RNA. All the chapters except the first end in numerical tests
Thibord, Florian. "Variation génétique et plasmatique des microARNs : impact sur les paramètres biologiques de l’hémostase OPTIMIR, a novel algorithm for integrating available genome-wide genotype data into miRNA sequence alignment analysis A Genome Wide Association Study on plasma FV levels identified PLXDC2 as a new modifier of the coagulation process." Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS379.
Повний текст джерелаMicroRNAs (miRNA) are small non coding RNAs with an average size of 22 nucleotides, mainly known to regulate gene expression in the cytoplasm. These small RNAs are estimated to regulate the majority of human genes, and are potentially involved in several diseases. MiRNA sequences might contain genetic variants and can undergo post-transcriptional variations, which generate miRNA isoforms called isomiRs. In order to accurately detect and quantify miRNA expression, isomiRs as well as paralogous miRNAs must be accounted for. The optimiR pipeline developed during this project overcome these challenges by integrating genetic information and by implementing an original strategy based on local alignement. Sequencing data were obtained from the MARTHA cohort, which is composed of french unrelated patients who experienced venous thrombosis (VTE). Normalized expression of 162 miRNAs from 334 patients were used to analyze: 1) the genetic determinants of miRNA expression; 2) the association of miRNA expression levels with VTE recurence; 3) the correlations between miRNA expression levels and hemostatic traits. As a whole, these analyses allowed me to identify miRNAs of interest for the study of VTE and hemostasis
Yu, Daniel C. T., and 游景達. "Efficient Algorithms for Constrained Sequence Alignment Problems." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/v2a9sc.
Повний текст джерела靜宜大學
資訊管理學系研究所
91
Sequence alignment is one of the most important primitive tools in computational biology. By using this methodology, we can identify a homologous relationship effectively with a biological sequence about which more is known. Though the sequence alignment tool is useful, the alignment results generated by this tool may not always meet the user-specified constraints, which are the datasets biologists believed that should be aligned together. Therefore, the development of a new sequence alignment tool that meets the user-specified constraints becomes a necessity. In this thesis, two efficient constrained sequence alignment algorithms for different application is being proposed. 1.Constrained sequence alignment using consecutive subsequence constraints - an extended version of C2SA(Constrained Pairwise Sequence Alignment, C2SA), which is proposed by Chuan-Yi Tang et al., with reduced time complexity of O(rn^2). 2.Constrained structural RNA sequence alignment - a constrained sequence alignment method with basepairing which takes O(rn^4), where n is the maximum of the lengths of sequences being aligned and r is the number of constraints.
Abbasi, Maryam. "Multiobjective Sequence Alignment Formulation, Algorithms and Application." Doctoral thesis, 2019. http://hdl.handle.net/10316/87604.
Повний текст джерелаSequence alignment is a standard technique in bioinformatics to measure the relationship between evolutionary or structurally related DNA/proteins sequences. Most modern programs for sequence alignment optimize a given objective function that is a convex combination of how many gaps need to be inserted into the sequences and how many characters become aligned. Clearly, depending on the weights given to each of the two components, different optimal alignments can be obtained. Therefore, choosing only one weight setting may provide an undesirable bias in further steps of the analysis, such as phylogenetic tree construction, and provide too simplistic interpretations. In this thesis, we take a different point of view on the mathematical formulation of the sequence alignment problem. Rather than considering the optimization of a scalar score function, resulting from a weighted sum of components, we consider a vector score function with the goal of optimizing, simultaneously, the different score components. This brings us to the topic of multiobjective optimization, which deals with the mathematical formulation of optimization problems with several conflicting objectives as well as with algorithms to solve them. Under this new formulation, these algorithms return a set of non-dominated alignments, each of which representing a trade-off between the several components. This set gives further information about the similarity of the sequences, from which a practitioner could analyze and choose the most plausible alignment. We consider the biobjective pairwise sequence alignment problem and propose extensions of efficient dynamic programming algorithms for several variants of this problem. We propose a novel pruning technique that substantially reduces the computation time and memory usage. Moreover, we consider a biobjective variant of this problem with more than two sequences, which is computationally intractable. We introduce local search techniques for this problem and conduct an in-depth experimental analysis on a wide range of benchmark instances. Based on the hypervolume indicator and empirical attainment function methodology, we establish functional relationships between algorithm performance and instance features. Finally, we present a method that uses multiobjective concepts for the construction of phylogenetic trees. We test this method on two real-life cases and show that the number of distinct phylogenetic tree topologies obtained is very small. This work shows that multiobjective concepts can successfully be applied to the sequence alignment problem and identifies which approaches can be used for the several variants of this problem. We believe that the methods proposed in this thesis, by providing more information about the relationship between biological sequences than the current known procedures, can be of great value to a broad range of research communities as well as to practitioners in the field.
O alinhamento de sequências é um procedimento utilizado na Bioinformática que tem por objetivo medir a semelhança entre sequências de DNA ou proteínas relacionadas entre si de uma forma evolutiva ou estrutural. As aplicações atuais para alinhamento de sequências otimizam uma determinada função objetivo que resulta da combinação convexa da quantidade de espaços a inserir nas sequências e da quantidade de caracteres que ficam alinhados. Dependendo das ponderações atribuídas a cada um destes dois componentes, diferentes alinhamentos podem ser obtidos. Desta forma, a escolha de uma só ponderação pode enviesar, indesejadamente, os passos seguintes da análise, por exemplo, na construção de árvores filogenéticas, e fornecer interpretações demasiado simples. Esta tese aborda o problema de alinhamento de sequências de uma forma diferente na perspetiva de formulação matemática. Em vez da otimização de uma função escalar que resulta de uma soma ponderada das componentes, considera-se uma função vetorial em que se pretende otimizar, simultaneamente, as suas componentes. O estudo destes problemas é abordado em otimização multi-objetivo, que lida com as formulações matemáticas de problemas de otimização com vários objetivos conflituosos entre si e com algoritmos para a sua resolução. Com esta nova formulação, os algoritmos retornam um conjunto de alinhamentos não-dominados, cada um representando um compromisso entre as várias componentes da função objetivo. Este conjunto, ao fornecer mais informação acerca da semelhança entre as sequências em análise, permite, ao profissional, escolher o alinhamento mais plausível. Neste estudo, considera-se o problema bi-objetivo de alinhamento emparelhado de sequências e variantes deste problema, para os quais propõem-se extensões de algoritmos eficientes baseados em programação dinâmica. Propõe-se iguamente uma variante bi-objetivo deste problema para mais do que duas sequências, que é considerado um problema computacionalmente intratável. Por esta razão, apresentam-se técnicas de procura local para este problema. Estes algoritmos são analisados experimentalmente num conjunto de instâncias de referência. Com base no indicador de hipervolume e na metodologia das funções de aproveitamento, estabelecem-se relações funcionais entre o desempenho dos algoritmos e características destas instâncias. Finalmente, apresenta-se um método que utiliza conceitos de otimização multi-objetivo para a construção de árvores filogenéticas. Este método é testado em dois casos reais. Os resultados obtidos indicam que o número de topologias distintas de árvores filogenéticas é bastante pequeno. Este estudo mostra que os conceitos multi-objetivo podem ser utilizados com sucesso no problema de alinhamento de sequências e permite identificar quais as abordagens que podem ser utilizadas para cada uma das variantes apresentadas. Ao fornecer mais informação acerca da relação entre as sequências biológicas do que os métodos atuais, espera-se que as contribuições desta tese possam de grande valor tanto para a comunidade académica como para os profissionais de Bioinformática.
Wang, Shu 1973. "On multiple sequence alignment." Thesis, 2007. http://hdl.handle.net/2152/3715.
Повний текст джерелаWang, Xuting. "Multiple sequence alignment using traveling salesman problem algorithms." 2002. http://purl.galileo.usg.edu/uga%5Fetd/wang%5Fxuting%5F200205%5Fms.
Повний текст джерелаMa, Fangrui. "Biological sequence analyses theory, algorithms, and applications /." 2009. http://proquest.umi.com/pqdweb?did=1821098721&sid=1&Fmt=2&clientId=14215&RQT=309&VName=PQD.
Повний текст джерелаTitle from title screen (site viewed October 13, 2009). PDF text: xv, 233 p. : ill. ; 4 Mb. UMI publication number: AAT 3360173. Includes bibliographical references. Also available in microfilm and microfiche formats.