Relevant bibliographies by topics / Algorithms- Protein / Dissertations / Theses
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Dissertations / Theses on the topic 'Algorithms- Protein'

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Published: 6 September 2023
Last updated: 31 July 2025

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1

Derevyanko, Georgy. "Structure-based algorithms for protein-protein interactions." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENY070/document.

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Les phénotypes de tous les organismes vivants connus sont déterminés par les interactions compliquées entre les protéines produites dans ces organismes. La compréhension des réponses des organismes aux stimuli externes ou internes est basée sur la compréhension des interactions des protéines individuelles et des structures de ses complexes. La prédiction d'un complexe de deux ou plus protéines est le problème du domaine du docking protéine-protéine. Les algorithmes du docking ont habituellement deux étapes majeurs: recherche 6D exhaustive suivi par le scoring. Dans ce travail, nous avons contr
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2

Lassmann, Timo. "Algorithms for building and evaluating multiple sequence alignments /." Stockholm, 2006. http://diss.kib.ki.se/2006/91-7140-887-8/.

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Hosur, Raghavendra. "Structure-based algorithms for protein-protein interaction prediction." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/75843.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2012.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student submitted PDF version of thesis.<br>Includes bibliographical references (p. 109-124).<br>Protein-protein interactions (PPIs) play a central role in all biological processes. Akin to the complete sequencing of genomes, complete descriptions of interactomes is a fundamental step towards a deeper understanding of biolog
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Bazzoli, A. "Protein structure prediction and protein design with evolutionary algorithms." Doctoral thesis, Università degli Studi di Milano, 2009. http://hdl.handle.net/2434/64478.

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5

Lappe, Michael. "Novel algorithms for protein interaction networks." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615625.

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6

Sajjadi, Sajdeh [Verfasser]. "Step by step in fast protein-protein docking algorithms / Sajdeh Sajjadi." Lübeck : Zentrale Hochschulbibliothek Lübeck, 2014. http://d-nb.info/1060276887/34.

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7

C, Dukka Bahadur K. "Clique-based algorithms for protein structure prediction." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/143887.

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8

Thomas, Dallas, and University of Lethbridge Faculty of Arts and Science. "Algorithms & experiments for the protein chain lattice fitting problem." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2006, 2006. http://hdl.handle.net/10133/535.

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This study seeks to design algorithms that may be used to determine if a given lattice is a good approximation to a given rigid protein structure. Ideal lattice models discovered using our techniques may then be used in algorithms for protein folding and inverse protein folding. In this study we develop methods based on dynamic programming and branch and bound in an effort to identify “ideal” lattice models. To further our understanding of the concepts behind the methods we have utilized a simple cubic lattice for our analysis. The algorithms may be adapted to work on any lattice. We describe
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9

Gamalielsson, Jonas. "Models for Protein Structure Prediction by Evolutionary Algorithms." Thesis, University of Skövde, Department of Computer Science, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-623.

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<p>Evolutionary algorithms (EAs) have been shown to be competent at solving complex, multimodal optimisation problems in applications where the search space is large and badly understood. EAs are therefore among the most promising classes of algorithms for solving the Protein Structure Prediction Problem (PSPP). The PSPP is how to derive the 3D-structure of a protein given only its sequence of amino acids. This dissertation defines, evaluates and shows limitations of simplified models for solving the PSPP. These simplified models are off-lattice extensions to the lattice HP model which has bee
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10

Parry-Smith, David John. "Algorithms and data structures for protein sequence analysis." Thesis, University of Leeds, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.277404.

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11

Singh, Rohit Ph D. Massachusetts Institute of Technology. "Algorithms for the analysis of protein interaction networks." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/71489.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 107-117).<br>In the decade since the human genome project, a major research trend in biology has been towards understanding the cell as a system. This interest has stemmed partly from a deeper appreciation of how important it is to understand the emergent properties of cellular systems (e.g., they seem to be the key to understanding diseases like cancer). It has also been enabled by new high-throu
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12

Djurdjević, Dušan. "Ab initio protein fold prediction using evolutionary algorithms." Thesis, University of Edinburgh, 2006. http://hdl.handle.net/1842/13660.

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A comprehensive study was undertaken for <i>ab initio </i>protein fold prediction using a fully atomistic protein model and a physicochemical potential. Twenty four EA designs where initially assessed on polyalanine, a prototypical α-helical polypeptide.  Design aspects varied include the encoding alphabet, crossover operator, replacement strategy and selection strategy. By undertaking a comprehensive parameter study, the best performing designs and associated control parameter values were identified for polyalanine. The scaling between the performance and polyalinine size was also identified
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13

Contreras-Moreira, Bruno. "Algorithms for protein comparative modelling and some evolutionary implications." Thesis, University College London (University of London), 2004. http://discovery.ucl.ac.uk/1446587/.

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Protein comparative modelling (CM) is a predictive technique to build an atomic model for a polypeptide chain, based on the experimentally determined structures of related proteins (templates). It is widely used in Structural Biology, with applications ranging from mutation analysis, protein and drug design to function prediction and analysis, particularly when there are no experimental structures of the protein of interest. Therefore, CM is an important tool to process the amount of data generated by genomic projects. Several problems affect the performance of CM and therefore solutions for t
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14

Wang, Xueyi Snoeyink Jack. "Exploring RNA and protein 3D structures by geometric algorithms." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,1905.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2008.<br>Title from electronic title page (viewed Dec. 11, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science." Discipline: Computer Science; Department/School: Computer Science.
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15

Jiménez, García Brian. "Development and optimization of high-performance computational tools for protein-protein docking." Doctoral thesis, Universitat de Barcelona, 2016. http://hdl.handle.net/10803/398790.

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Computing has pushed a paradigm shift in many disciplines, including structural biology and chemistry. This change has been mainly driven by the increase in performance of computers, the capacity of dealing with huge amounts of experimental and analysis data and the development of new algorithms. Thanks to these advances, our understanding on the chemistry that supports life has increased and it is even more sophisticated that we had never imagined before. Proteins play a major role in nature and are often described as the factories of the cell as they are involved in virtually all importan
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16

Bondugula, Rajkumar. "A novel framework for protein structure prediction." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4855.

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Thesis (Ph.D.)--University of Missouri-Columbia, 2007.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on March 23, 2009) Vita. Includes bibliographical references.
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17

Pettitt, Christopher Steven. "Refinement of protein structure models with multi-objective genetic algorithms." Thesis, University College London (University of London), 2007. http://discovery.ucl.ac.uk/1446043/.

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Here I investigate the protein structure refinement problem for homology-based protein structure models. The refinement problem has been identified as a major bottleneck in the structure prediction process and inhibits the goal of producing high-resolution experimental quality structures for target protein sequences. This thesis is composed of three investigations into aspects of template-based modelling and refinement. In the primary investigation, empirical evidence is provided to support the hypothesis that using multiple template-based structures to model a target sequence can improve the
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18

Bliven, Spencer Edward. "Structure-Preserving Rearrangements| Algorithms for Structural Comparison and Protein Analysis." Thesis, University of California, San Diego, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3716489.

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<p> Protein structure is fundamental to a deep understanding of how proteins function. Since structure is highly conserved, structural comparison can provide deep information about the evolution and function of protein families. The Protein Data Bank (PDB) continues to grow rapidly, providing copious opportunities for advancing our understanding of proteins through large-scale searches and structural comparisons. In this work I present several novel structural comparison methods for specific applications, as well as apply structure comparison tools systematically to better understand global pr
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19

Singh, Mona. "Learning algorithms with applications to robot navigation and protein folding." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/40579.

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20

Crook, James. "New algorithms and methods for protein and DNA sequence comparison." Thesis, University of Edinburgh, 1991. http://hdl.handle.net/1842/13497.

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International biological sequence databases hold information about protein and DNA molecules. The molecules are represented by sequences of characters. In analysis of this data algorithms for comparing the character sequences play a central role. Comparisons can be made using dynamic programming techniques to determine the score of optimal sequence alignments. Such methods are particularly popular with molecular biologists for they accommodate the kinds of differences which actually occur in the sequences of related molecules. Sequence alignments are normally scored using score tables based on
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Tan, Guanhong. "Study of Protein Identification Algorithms and Ammonia Metabolism in Mosquitoes." Thesis, The University of Arizona, 2006. http://hdl.handle.net/10150/193319.

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Two database search algorithms, SEQUEST and X!Tandem, were studied in detail. Research results showed that SEQUEST is relatively prone to identify single charged peptides, while X!Tandem is prone to identify highly charged peptides.Peptide fragmentation patterns associated with corresponding structure motifs are incorporated into SEQUEST Replica and X!Tandem Replica. Research results showed that selective cleavage rules for peptide fragmentation help improve peptide identification especially for selectively cleaved peptides. A tool that makes use of the peak intensity information in the experi
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22

Choudhury, Salimur Rashid, and University of Lethbridge Faculty of Arts and Science. "Approximation algorithms for a graph-cut problem with applications to a clustering problem in bioinformatics." Thesis, Lethbridge, Alta. : University of Lethbridge, Deptartment of Mathematics and Computer Science, 2008, 2008. http://hdl.handle.net/10133/774.

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Clusters in protein interaction networks can potentially help identify functional relationships among proteins. We study the clustering problem by modeling it as graph cut problems. Given an edge weighted graph, the goal is to partition the graph into a prescribed number of subsets obeying some capacity constraints, so as to maximize the total weight of the edges that are within a subset. Identification of a dense subset might shed some light on the biological function of all the proteins in the subset. We study integer programming formulations and exhibit large integrality gaps for various fo
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Palmer, Jane. "The application of genetic algorithms to problems in protein structure solution." Thesis, University of Sheffield, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286746.

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24

Otero, Fernando E. B. "New ant colony optimisation algorithms for hierarchial classification of protein functions." Thesis, University of Kent, 2010. http://www.cs.kent.ac.uk/pubs/2010/3057.

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Ant colony optimisation (ACO) is a metaheuristic to solve optimisation problems inspired by the foraging behaviour of ant colonies. It has been successfully applied to several types of optimisation problems, such as scheduling and routing, and more recently for the discovery of classification rules. The classification task in data mining aims at predicting the value of a given goal attribute for an example, based on the values of a set of predictor attributes for that example. Since real-world classification problems are generally described by nominal (categorical or discrete) and continuous (
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25

Chippington-Derrick, T. C. "Models, methods and algorithms for constraint dynamics simulations of long chain molecules." Thesis, University of Reading, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234776.

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26

Ishivatari, Luís Henrique Uchida. "Função de avaliação dinâmica em algoritmos genéticos aplicados na predição de estruturas tridimensionais de proteínas." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/95/95131/tde-27112012-185423/.

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O problema de predição de estruturas tridimensionais de proteínas pode ser visto computacionalmente como um problema de otimização, tal que dada a sequência de aminoácidos, deve-se encontrar a estrutura tridimensional da proteína dentre as muitas possíveis através da obtenção de mínimos de funções de energia. Vários pesquisadores têm proposto estratégias de Computação Evolutiva para a determinação de estruturas tridimensionais das proteínas, entretanto nem sempre resultados animadores têm sido alcançados visto que entre outros fatores, há um grande número de ótimos locais no espaço de busca. G
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Herndon, Nic. "Domain adaptation algorithms for biological sequence classification." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/35242.

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Doctor of Philosophy<br>Department of Computing and Information Sciences<br>Doina Caragea<br>The large volume of data generated in the recent years has created opportunities for discoveries in various fields. In biology, next generation sequencing technologies determine faster and cheaper the exact order of nucleotides present within a DNA or RNA fragment. This large volume of data requires the use of automated tools to extract information and generate knowledge. Machine learning classification algorithms provide an automated means to annotate data but require some of these data to be manuall
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Chi, Pin-Hao. "Efficient protein tertiary structure retrievals and classifications using content based comparison algorithms." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4817.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2007.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on September 19, 2007) Vita. Includes bibliographical references.
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29

Park, Daniel K. (Daniel Kyu). "Web servers, databases, and algorithms for the analysis of protein interaction networks." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/79146.

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Thesis (S.M.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2013.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (p. 41-44).<br>Understanding the cell as a system has become one of the foremost challenges in the post-genomic era. As a result of advances in high-throughput (HTP) methodologies, we have seen a rapid growth in new types of data at the whole-genome
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Li, Wenzhou. "Protein Identification Algorithms Developed from Statistical Analysis of MS/MS Fragmentation Patterns." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/242432.

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Tandem mass spectrometry is widely used in proteomic studies because of its ability to identify large numbers of peptides from complex mixtures. In a typical LC-MS/MS experiment, thousands of tandem mass spectra will be collected and peptide identification algorithms are of great importance to translate them into peptide sequences. Though these spectra contain both m/z and intensity values, most popular protein identification algorithms primarily use predicted fragment m/z values to assign peptide sequences to fragmentation spectra. The intensity information is often undervalued, because it is
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Karimpour-Fard, Anis. "Prediction of protein-protein interactions and function in bacteria /." Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2008.

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Thesis (Ph.D. in Bioinformatics) -- University of Colorado Denver, 2008.<br>Typescript. Includes bibliographical references (leaves 141-150). Free to UCD Anschutz Medical Campus. Online version available via ProQuest Digital Dissertations;
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Akkaladevi, Somasheker. "Decision Fusion for Protein Secondary Structure Prediction." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_diss/9.

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Prediction of protein secondary structure from primary sequence of amino acids is a very challenging task, and the problem has been approached from several angles. Proteins have many different biological functions; they may act as enzymes or as building blocks (muscle fibers) or may have transport function (e.g., transport of oxygen). The three-dimensional protein structure determines the functional properties of the protein. A lot of interesting work has been done on this problem, and over the last 10 to 20 years the methods have gradually improved in accuracy. In this dissertation we investi
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Planas, Iglesias Joan 1980. "On the study of 3D structure of proteins for developing new algorithms to complete the interactome and cell signalling networks." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/104152.

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Proteins are indispensable players in virtually all biological events. The functions of proteins are determined by their three dimensional (3D) structure and coordinated through intricate networks of protein-protein interactions (PPIs). Hence, a deep comprehension of such networks turns out to be crucial for understanding the cellular biology. Computational approaches have become critical tools for analysing PPI networks. In silico methods take advantage of the existing PPI knowledge to both predict new interactions and predict the function of proteins. Regarding the task of predicting PPIs, s
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34

Kim, Wooyoung. "Innovative Algorithms and Evaluation Methods for Biological Motif Finding." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/cs_diss/63.

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Biological motifs are defined as overly recurring sub-patterns in biological systems. Sequence motifs and network motifs are the examples of biological motifs. Due to the wide range of applications, many algorithms and computational tools have been developed for efficient search for biological motifs. Therefore, there are more computationally derived motifs than experimentally validated motifs, and how to validate the biological significance of the ‘candidate motifs’ becomes an important question. Some of sequence motifs are verified by their structural similarities or their functional roles i
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Zhao, Zhiyu. "Robust and Efficient Algorithms for Protein 3-D Structure Alignment and Genome Sequence Comparison." ScholarWorks@UNO, 2008. http://scholarworks.uno.edu/td/851.

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Sequence analysis and structure analysis are two of the fundamental areas of bioinformatics research. This dissertation discusses, specifically, protein structure related problems including protein structure alignment and query, and genome sequence related problems including haplotype reconstruction and genome rearrangement. It first presents an algorithm for pairwise protein structure alignment that is tested with structures from the Protein Data Bank (PDB). In many cases it outperforms two other well-known algorithms, DaliLite and CE. The preliminary algorithm is a graph-theory based a
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Reyaz-Ahmed, Anjum B. "Protein Secondary Structure Prediction Using Support Vector Machines, Nueral Networks and Genetic Algorithms." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/cs_theses/43.

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Bioinformatics techniques to protein secondary structure prediction mostly depend on the information available in amino acid sequence. Support vector machines (SVM) have shown strong generalization ability in a number of application areas, including protein structure prediction. In this study, a new sliding window scheme is introduced with multiple windows to form the protein data for training and testing SVM. Orthogonal encoding scheme coupled with BLOSUM62 matrix is used to make the prediction. First the prediction of binary classifiers using multiple windows is compared with single window
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Yerardi, Jason T. "The Implementation and Evaluation of Bioinformatics Algorithms for the Classification of Arabinogalactan-Proteins in Arabidopsis thaliana." Ohio University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1301069861.

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38

North, Benjamin H. "A Comparison of Clustering Algorithms for the Study of Antibody Loop Structures." Master's thesis, Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/464867.

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Computer and Information Science<br>M.S.<br>Antibodies are the fundamental agents of the immune system. The CDRs, or Complementarity Determining Regions act as the functional surfaces in binding antibodies to their targets. These CDR structures, which are peptide loops, are diverse in both amino acid sequence and structure. In 2011, we surveyed a database of CDR loop structures using the affinity propagation clustering algorithm of Frey and Dueck. With the growth of the number of structures deposited in the Protein Data Bank, the number of antibody CDRs has approximately tripled. In addition,
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Parkinson, Scott. "Rational Design Inspired Application of Natural Language Processing Algorithms to Red Shift mNeptune684." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/41928.

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Recent innovations and progress in machine learning algorithms from the Natural Language Processing (NLP) community have motivated efforts to apply these models and concepts to proteins. The representations generated by trained NLP models have been shown to capture important semantic and structural understanding of proteins encompassing biochemical and biophysical properties, among other key concepts. In turn, these representations have demonstrated application to protein engineering tasks including mutation analysis and design of novel proteins. Here we use this NLP paradigm in a protein engi
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Yaveroglu, Omer Nebil. "Identification Of Functionally Orthologous Protein Groups In Different Species Based On Protein Network Alignment." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612395/index.pdf.

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In this study, an algorithm named ClustOrth is proposed for determining and matching functionally orthologous protein clusters in different species. The algorithm requires protein interaction networks of the organisms to be compared and GO terms of the proteins in these interaction networks as prior information. After determining the functionally related protein groups using the Repeated Random Walks algorithm, the method maps the identified protein groups according to the similarity metric defined. In order to evaluate the similarities of protein groups, graph theoretical information is used
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Shah, Anuj R. "Improving protein remote homology detection using supervised and semi-supervised support vector machines." Online access for everyone, 2008. http://www.dissertations.wsu.edu/Dissertations/Spring2008/A_Shah_042408.pdf.

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Klaib, Ahmad. "Exact string matching algorithms for searching DNA and protein sequences and searching chemical databases." Thesis, University of Huddersfield, 2014. http://eprints.hud.ac.uk/id/eprint/24266/.

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The enormous quantities of biological and chemical files and databases are likely to grow year on year, consequently giving rise to the need to develop string-matching algorithms capable of minimizing the searching response time. Being aware of this need, this thesis aims to develop string matching algorithms to search biological sequences and chemical structures by studying exact string matching algorithms in detail. As a result, this research developed a new classification of string matching algorithms containing eight categories according to the pre-processing function of algorithms and pro
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Olandersson, Sandra. "Evaluation of Machine Learning Algorithms for Classification of Short-Chain Dehydrogenase/Reductase Protein Sequences." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3828.

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The classification of protein sequences is a subfield in the area of Bioinformatics that attracts a substantial interest today. Machine Learning algorithms are here believed to be able to improve the performance of the classification phase. This thesis considers the application of different Machine Learning algorithms to the classification problem of a data set of short-chain dehydrogenases/reductases (SDR) proteins. The classification concerns both the division of the proteins into the two main families, Classic and Extended, and into their different subfamilies. The results of the different
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Denarie, Laurent. "Robotics-inspired methods to enhance protein design." Phd thesis, Toulouse, INPT, 2017. http://oatao.univ-toulouse.fr/18677/1/Denarie.pdf.

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The ability to design proteins with specific properties would yield great progress in pharmacology and bio-technologies. Methods to design proteins have been developed since a few decades and some relevant achievements have been made including de novo protein design. Yet, current approaches suffer some serious limitations. By not taking protein’s backbone motions into account, they fail at capturing some of the properties of the candidate design and cannot guarantee that the solution will in fact be stable for the goal conformation. Besides, although multi-states design methods have been propo
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Wistrand, Markus. "Hidden Markov models for remote protein homology detection /." Stockholm, 2005. http://diss.kib.ki.se/2006/91-7140-598-4/.

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Hom, Geoffrey Deshaies Raymond Joseph. "Advances in computational protein design : development of more efficient search algorithms and their application to the full-sequence design of larger proteins /." Diss., Pasadena, Calif. : California Institute of Technology, 2005. http://resolver.caltech.edu/CaltechETD:etd-05302005-223153.

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Bakare, Olalekan Olanrewaju. "Identification and Molecular validation of Biomarkers for the accurate and sensitive diagnosis of bacterial and viral Pneumonia." University of Western Cape, 2019. http://hdl.handle.net/11394/7421.

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Philosophiae Doctor - PhD<br>Pneumonia remains the major cause of death in children and the elderly and several efforts have been intensified to reduce the rate of pneumonia infection. The major breakthrough has been the discovery of certain biomarkers for the diagnosis of pneumonia through immunogenic techniques.
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Kolar, Michal. "Statistical Physics and Message Passing Algorithms. Two Case Studies: MAX-K-SAT Problem and Protein Flexibility." Doctoral thesis, SISSA, 2006. http://hdl.handle.net/20.500.11767/4659.

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In the last decades the tl1eory of spin glasses has been developed within the framework of statistical physics. The obtained results showed to be novel not only from the physical point of vie\l\'1 but they have brought also new mathematical techniques and algorithmic approaches. Indeed, the problem of finding ground state of a spin glass is (in general) NP-complete. The methods that were found brought new ideas to the field of Combinatorial Optimization, and on the other side, the similar methods of Combinatorial Optimization, were applied in physical systems. As it happened with the M
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Mathuriya, Amrita. "Prediction of secondary structures for large RNA molecules." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28195.

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Thesis (M. S.)--Computing, Georgia Institute of Technology, 2009.<br>Committee Chair: Bader, David; Committee Co-Chair: Heitsch, Christine; Committee Member: Harvey, Stephen; Committee Member: Vuduc, Richard.
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Lan, Liang. "Data Mining Algorithms for Classification of Complex Biomedical Data." Diss., Temple University Libraries, 2012. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/214773.

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Abstract:
Computer and Information Science<br>Ph.D.<br>In my dissertation, I will present my research which contributes to solve the following three open problems from biomedical informatics: (1) Multi-task approaches for microarray classification; (2) Multi-label classification of gene and protein prediction from multi-source biological data; (3) Spatial scan for movement data. In microarray classification, samples belong to several predefined categories (e.g., cancer vs. control tissues) and the goal is to build a predictor that classifies a new tissue sample based on its microarray measurements. When
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