Dissertations / Theses on the topic 'Structural Bioinformatic'
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Roberts, Rick Lee. "Structural and bioinformatic analysis of ethylmalonyl-CoA decarboxylase." Thesis, State University of New York at Buffalo, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1600817.
Full textMany enzymes of the major metabolic pathways are categorized into superfamilies which share common folds. Current models postulate these superfamilies are the result of gene duplications coupled with mutations that result in the acquisition of new functions. Some of these new functions are considered advantageous and selected for, while others may simply be tolerated. The latter can result in metabolites being produced at low rates that are of no known use by the cell, and can become toxic when accumulated. Concurrent with the evolution of this tolerable or potentially detrimental metabolism, organisms are selected to evolve a means of correcting or “proofreading” these non-canonical metabolites to counterbalance their detrimental effects. Metabolite proofreading is a process of intermediary metabolism analogous to DNA proof reading that acts on these abnormal metabolites to prevent their accumulation and toxic effects.
Here we structurally characterize ethylmalonyl-CoA decarboxylase (EMCD), a member of the family of enoyl-CoA hydratases within the crotonase superfamily of proteins, which is coded by the ECHDC1 (enoyl-CoA hydratase domain containing 1) gene. EMCD has been shown to have a metabolic proofreading property, acting on the metabolic byproduct ethylmalonyl-CoA to prevent its accumulation which could result in oxidative damage. We use the complimentary methods of in situ crystallography, small angle X-ray scattering, and single crystal X-ray crystallography to structurally characterize EMCD, followed by homology analysis in order to propose a mechanism of action. This represents the first structure of a crotonase superfamily member thought to function as a metabolite proof reading enzyme.
Stahl, Morgan A. "The Perilipin Family of Proteins: Structural and Bioinformatic Analysis." Otterbein University Honors Theses / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=otbnhonors1620460421392971.
Full textChiara, M. "BIOINFORMATIC TOOLS FOR NEXT GENERATION GENOMICS." Doctoral thesis, Università degli Studi di Milano, 2012. http://hdl.handle.net/2434/173424.
Full textGendoo, Deena. "Bioinformatic sequence and structural analysis for Amyloidogenicity in Prions and other proteins." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=110518.
Full textLa détection de peptides ou de domaines amyloïdogéniques dans les protéines est d'une importance primordiale dans la compréhension de leur rôle dans l'amylose dans les maladies conformationnelles. Cette thèse explore différentes méthodes en vue de la détection et la prédiction des peptides amyloïdogéniques utilisant une variété de méthodes d'analyse bio-informatique. L'analyse bio-informatique des changements structurels secondaires est employé afin de déterminer si les classes des peptides structurellement ambivalentes, principalement des séquences discordantes et caméléons, sont des prédicteurs efficaces de segments amyloïdogéniques. Cette analyse élucide des relations statistiques entre la discordance, la chameleonism et l'amyloïdogénicité à travers une base de données de domaines protéiques (SCOP), un sous-ensemble de protéines formées d'amyloïdes, et de la famille prion. Les résultats présentés soulignent les limites de ces peptides en tant que prédicteurs d'amyloïdogénicité, et soulèvent des questions sur le pouvoir prédictif qui peut être récolté de méthodes de prédiction de structure secondaire. Dans une autre approche bio-informatique, la détection de segments de conformation variables dans les structures tertiaires de domaines globulaires PrP a été effectuée utilisant « Principal Component Analysis ». Cette technique a réussi à identifier cinq domaines de conformation variables au sein de la protéine PrP, et à classer ces sous-domaines par leur capacité à différencier les PrP fondés sur des réponses structurelles non-locales à la mutation pathogène et la susceptibilité aux maladies prion. Les résultats présentés sont corroborés par des observations antérieures à partir de méthodes expérimentales et de simulations de dynamique moléculaire, ce qui suggère que cette approche sert comme une méthode rapide et fiable pour la détection de segments amyloïdogéniques potentiels dans les protéines formées d'amyloïdes. Finalement, une analyse structurelle, fonctionnelle et évolutive bio-informatique est menée afin d'évaluer la prévalence du premier pli de fibrille amyloïde dans la nature vérifié expérimentalement, et si ce pli peut servir de prototype pour d'autres protéines formées d'amyloïdes. Les résultats indiquent une portée limitée de ce pli dans les protéines formées d'amyloïdes et à travers l'univers des protéines, et ont des répercussions sur l'identification future de protéines formées d'amyloïdes qui partagent ce pli. Collectivement, la thèse présentée compare ces différentes méthodes et discute leur efficacité dans la détection de segments amyloïdogéniques.
MOZZICAFREDDO, MATTEO. "Structural bioinformatic analyses of (macro)molecular interactions of biomedical relevance: an experimental validation." Doctoral thesis, Università degli Studi di Camerino, 2014. http://hdl.handle.net/11581/401775.
Full textMartínez, Fundichely Alexander 1978. "Bioinformatic characterization and analysis of polymorphic inversions in the human genome." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/384837.
Full textDentro del estudio de las variantes estructurales en el genoma humano, las inversiones han sido las menos han consolidado sus resultados y constituye uno de los principales retos en la actualidad. Esta tesis aborda el tema a través de la implementación de "GRIAL" un nuevo algoritmo específicamente diseñado para la detección más precisa posible de las inversiones usando el mapeo de secuencias apareadas (del inglés PEM) que es el método más utilizado para estudiar la variación estructural. GRIAL se basa en reglas geométricas para agrupar los patrones de PEM que señalan un posible punto de rotura (del inglés breakpoint) de inversión, además une cada breakpoint correspondientes a inversiones independientes y refina lo más exacto posible su localización. Su uso nos permitió predecir cientos de inversiones. Un gran aporte de nuestro método es la creación de índices (del inglés score) de fiabilidad para las predicciones mediante los cuales identificamos patrones de inversión incorrectos y sus causas. Esto nos permitió filtrar nuestro resultado eliminando un gran número de predicciones posiblemente falsas. Además se creó "InvFEST", la primera base de datos especialmente dedicada a inversiones polimórficas en el genoma humano la cual representa el catálogo más fiable de inversiones, integrando además a cada inversión conocida la información asociada disponible. Actualmente InvFEST contiene (y mantiene la clasificación según el nivel de certeza) un catálogo de 1092 inversiones clasificadas, a partir de datos de 30 estudios diferentes. Finalmente el análisis de toda la información generada nos permitió describir algunos patrones de las inversiones polimórficas en el genoma humano contribuyendo de este modo a la comprensión de esta variante estructural y el estado de su información en los estudios del genoma humano.
Inversió genòmica
Moss, Tiffanie. "CHARACTERIZATION OF STRUCTURAL VARIANTS AND ASSOCIATED MICRORNAS IN FLAX FIBER AND LINSEED GENOTYPES BY BIOINFORMATIC ANALYSIS AND HIGH-THROUGHPUT SEQUENCING." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1333648149.
Full textRIZZA, FABIO. "Structural modelling of biological macromolecules: the cases of neurofibromin, bifurcating Electron Transferring Flavoprotein and Amyloid-β (1-16) peptide." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2021. http://hdl.handle.net/10281/310480.
Full textIn this thesis, three independent projects were addressed, sharing the computational approach based on molecular modeling and in particular molecular dynamics. In the first project, the Sec14-PH domain of neurofibromin (NF1) was investigated. The Sec14 domains have been identified in many different proteins, from prokaryotes to humans, serving as exchangers of lipid molecules between membranes, by means of a pocket whose opening is allowed by the motion of a specific alpha-helix (called lid helix). The crystal structure of the NF1-Sec14 domain (of both the wild type and some mutants associated with the onset of neurofibromatosis pathology) has revealed its peculiarity of being structurally coupled to a PH domain that strongly interacts with the lid helix through a long loop (called lid-lock loop). On this basis, a mechanism for the opening of the Sec14 lipid pocket was formulated which would involve a concerted movement of the lid-lock loop, but this movement has actually never been shown. Guided by available experimental data on the thermal denaturation of Sec14-PH domain of NF1, both on the wild type and some neurofibromin-related mutants, several simulations at high temperature were carried out to compare the dynamics of the wild type domain with a pathological mutant associated with the onset of neurofibromatosis. Our simulations lead us to suggest an opening mechanism for the lid helix and provide a hypothesis for the structural and dynamic basis of the onset of the disease in the case of the specific mutant. The second project addressed the study of a protein called EtfAB which catalyzes a recently discovered process known as Flavin-Based Electron Bifurcation (FBEB). This mechanism is only exploited by some anaerobic microorganisms as a third way of energy coupling. So far, four unrelated protein families are known that are able to catalyze FBEB. Among these, EtfAB, catalyzes the electron transfer between the two FAD molecules bound to it. Surprisingly, the distance between these two FADs, as observed in the crystal structure of EtfAB, is 18 Å, whereas biological electron transfer is considered more likely to occur at a maximal distance of 14 Å. To explain this, a possible mechanism has been suggested that could bring the two FAD molecules closer together. Using molecular dynamics, it was possible to test, and discard, the proposed mechanism. Furthermore, with the Density Functional Theory (DFT), it was possible to provide an interpretation to some spectroscopic data regarding the possible electron transfer between the two FAD molecules. In the third project, I collaborated with Prof. Luca Bertini on a project on the production and propagation of some reactive oxygen species (ROS) in the context of the amyloid-beta peptide involved in the pathogenesis of Alzheimer's. In the amyloid hypothesis on the onset of Alzheimer's disease, an important role has been attributed to the damage caused by ROS, produced by a metal ion coordinated to the amyloid peptide itself, in particular by the hydroxyl radical (OH.-). However, the details of how these radicals propagate and react have not yet been clarified. While Prof. Bertini's DFT calculations addressed the oxidative capacities of the hydroxyl radical and the possible reaction products in the context of the amyloid-beta peptide, my molecular dynamics simulations provided an overview on which possible targets of the hydroxyl radical, coordinated to the ion Cu of the complex, could actually react with the hydroxyl radical due to the dynamic motions of the peptide.
LAURENZI, TOMMASO. "STUDY ON THE HDL::LCAT INTERACTION AND INSIGHTS INTO LCAT PHARMACOLOGICAL MODULATION." Doctoral thesis, Università degli Studi di Milano, 2021. http://hdl.handle.net/2434/835127.
Full textLiu, Xiao. "Comprehensive bioinformatic analysis of kinesin classification and prediction of structural changes from a closed to an open conformation of the motor domain." Diss., lmu, 2009. http://nbn-resolving.de/urn:nbn:de:bvb:19-108430.
Full textHvidsten, Torgeir R. "Predicting Function of Genes and Proteins from Sequence, Structure and Expression Data." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4490.
Full textBjörkholm, Patrik. "Method for recognizing local descriptors of protein structures using Hidden Markov Models." Thesis, Linköping University, The Department of Physics, Chemistry and Biology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11408.
Full textBeing able to predict the sequence-structure relationship in proteins will extend the scope of many bioinformatics tools relying on structure information. Here we use Hidden Markov models (HMM) to recognize and pinpoint the location in target sequences of local structural motifs (local descriptors of protein structure, LDPS) These substructures are composed of three or more segments of amino acid backbone structures that are in proximity with each other in space but not necessarily along the amino acid sequence. We were able to align descriptors to their proper locations in 41.1% of the cases when using models solely built from amino acid information. Using models that also incorporated secondary structure information, we were able to assign 57.8% of the local descriptors to their proper location. Further enhancements in performance was yielded when threading a profile through the Hidden Markov models together with the secondary structure, with this material we were able assign 58,5% of the descriptors to their proper locations. Hidden Markov models were shown to be able to locate LDPS in target sequences, the performance accuracy increases when secondary structure and the profile for the target sequence were used in the models.
Lysholm, Fredrik. "Structural characterization of overrepresented." Thesis, Linköping University, The Department of Physics, Chemistry and Biology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-12325.
Full textBackground: Through the last decades vast amount of sequence information have been produced by various protein sequencing projects, which enables studies of sequential patterns. One of the bestknown efforts to chart short peptide sequences is the Prosite pattern data bank. While sequential patterns like those of Prosite have proved very useful for classifying protein families, functions etc. structural analysis may provide more information and possible crucial clues linked to protein folding. Today PDB, which is the main repository for protein structure, contains more than 50’000 entries which enables structural protein studies.
Result: Strongly folded pentapeptides, defined as pentapeptides which retained a specific conformation in several significantly structurally different proteins, were studied out of PDB. Among these several groups were found. Possibly the most well defined is the “double Cys” pentapeptide group, with two amino acids in between (CXXCX|XCXXC) which were found to form backbone loops where the two Cysteine amino acids formed a possible Cys-Cys bridge. Other structural motifs were found both in helixes and in sheets like "ECSAM" and "TIKIW", respectively.
Conclusion: There is much information to be extracted by structural analysis of pentapeptides and other oligopeptides. There is no doubt that some pentapeptides are more likely to obtain a specific fold than others and that there are many strongly folded pentapeptides. By combining the usage of such patterns in a protein folding model, such as the Hydrophobic-polar-model improvements in speed and accuracy can be obtained. Comparing structural conformations for important overrepresented pentapeptides can also help identify and refine both structural information data banks such as SCOP and sequential pattern data banks such as Prosite.
Freyhult, Eva. "New techniques for analysing RNA structure /." Uppsala, 2004. http://www.math.uu.se/research/pub/Freyhult1.pdf.
Full textCapuccini, Marco. "Structure-Based Virtual Screening in Spark." Thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-257028.
Full textWallner, Björn. "Protein Structure Prediction : Model Building and Quality Assessment." Doctoral thesis, Stockholm University, Department of Biochemistry and Biophysics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-649.
Full textProteins play a crucial roll in all biological processes. The wide range of protein functions is made possible through the many different conformations that the protein chain can adopt. The structure of a protein is extremely important for its function, but to determine the structure of protein experimentally is both difficult and time consuming. In fact with the current methods it is not possible to study all the billions of proteins in the world by experiments. Hence, for the vast majority of proteins the only way to get structural information is through the use of a method that predicts the structure of a protein based on the amino acid sequence.
This thesis focuses on improving the current protein structure prediction methods by combining different prediction approaches together with machine-learning techniques. This work has resulted in some of the best automatic servers in world – Pcons and Pmodeller. As a part of the improvement of our automatic servers, I have also developed one of the best methods for predicting the quality of a protein model – ProQ. In addition, I have also developed methods to predict the local quality of a protein, based on the structure – ProQres and based on evolutionary information – ProQprof. Finally, I have also performed the first large-scale benchmark of publicly available homology modeling programs.
Novotny, Marian. "Applications of Structural Bioinformatics for the Structural Genomics Era." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis Acta Universitatis Upsaliensis, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7593.
Full textPeng, Zeshan. "Structure comparison in bioinformatics." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36271299.
Full textPeng, Zeshan, and 彭澤山. "Structure comparison in bioinformatics." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36271299.
Full textViklund, Håkan. "Formalizing life : Towards an improved understanding of the sequence-structure relationship in alpha-helical transmembrane proteins." Doctoral thesis, Stockholm University, Department of Biochemistry and Biophysics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-7144.
Full textGenes coding for alpha-helical transmembrane proteins constitute roughly 25% of the total number of genes in a typical organism. As these proteins are vital parts of many biological processes, an improved understanding of them is important for achieving a better understanding of the mechanisms that constitute life.
All proteins consist of an amino acid sequence that fold into a three-dimensional structure in order to perform its biological function. The work presented in this thesis is directed towards improving the understanding of the relationship between sequence and structure for alpha-helical transmembrane proteins. Specifically, five original methods for predicting the topology of alpha-helical transmembrane proteins have been developed: PRO-TMHMM, PRODIV-TMHMM, OCTOPUS, Toppred III and SCAMPI.
A general conclusion from these studies is that approaches that use multiple sequence information achive the best prediction accuracy. Further, the properties of reentrant regions have been studied, both with respect to sequence and structure. One result of this study is an improved definition of the topological grammar of transmembrane proteins, which is used in OCTOPUS and shown to further improve topology prediction. Finally, Z-coordinates, an alternative system for representation of topological information for transmembrane proteins that is based on distance to the membrane center has been introduced, and a method for predicting Z-coordinates from amino acid sequence, Z-PRED, has been developed.
Michel, Mirco. "From Sequence to Structure : Using predicted residue contacts to facilitate template-free protein structure prediction." Doctoral thesis, Stockholms universitet, Institutionen för biokemi och biofysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-141946.
Full textAt the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Submitted. Paper 4: In press.
Nordström, Rickard. "3DPOPS : From carbohydrate sequence to 3D structure." Thesis, University of Skövde, Department of Computer Science, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-713.
Full textIn this project a web-based system called 3DPOPS have been designed, developed and implemented. The system creates initial 3D structures of oligosaccharides according to user input data and is intended to be integrated with an automatized 3D prediction system for saccharides. The web interface uses a novel approach with a dynamically updated graphical representation of the input carbohydrate. The interface is embedded in a web page as a Java applet. Both expert and novice users needs are met by informative messages, a familiar concept and a dynamically updated graphical user interface in which only valid input can be created.
A set of test sequences was collected from the CarbBank database. An initial structure to each sequence could be created. All contained the information necessary to serve as starting points in a conformation search carried out by a 3D prediction system for carbohydrates.
Freyhult, Eva. "A Study in RNA Bioinformatics : Identification, Prediction and Analysis." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis Acta Universitatis Upsaliensis, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8305.
Full textVeanes, Margus. "Identification of novel loss of heterozygosity collateral lethality genes for potential applications in cancer." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-433768.
Full textBliven, 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.
Full textProtein 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 properties of protein fold space.
Circular permutation describes a relationship between two proteins where the N-terminal portion of one protein is related to the C-terminal portion of the other. Proteins that are related by a circular permutation generally share the same structure despite the rearrangement of their primary sequence. This non-sequential relationship makes them difficult for many structure alignment tools to detect. Combinatorial Extension for Circular Permutations (CE-CP) was developed to align proteins that may be related by a circular permutation. It is widely available due to its incorporation into the RCSB PDB website.
Symmetry and structural repeats are common in protein structures at many levels. The CE-Symm tool was developed in order to detect internal pseudosymmetry within individual polypeptide chains. Such internal symmetry can arise from duplication events, so aligning the individual symmetry units provides insights about conservation and evolution. In many cases, internal symmetry can be shown to be important for a number of functions, including ligand binding, allostery, folding, stability, and evolution.
Structural comparison tools were applied comprehensively across all PDB structures for systematic analysis. Pairwise structural comparisons of all proteins in the PDB have been computed using the Open Science Grid computing infrastructure, and are kept continually up-to-date with the release of new structures. These provide a network-based view of protein fold space. CE-Symm was also applied to systematically survey the PDB for internally symmetric proteins. It is able to detect symmetry in ~20% of all protein families. Such PDB-wide analyses give insights into the complex evolution of protein folds.
Brown, Peter G. "Structural Alignments for Similarity Detection in Bioinformatics." Thesis, Griffith University, 2019. http://hdl.handle.net/10072/390033.
Full textThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Info & Comm Tech
Science, Environment, Engineering and Technology
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Stamatelou, Ismini Christina. "Clustering approaches for extracting structural determinants of enzyme active sites." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-426221.
Full textJakobsson, Jenny. "Structural variation identification in non-reference cattle breed genomes." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-448593.
Full textSontheimer, Jana. "Functional characterization of proteins involved in cell cycle by structure-based computational methods." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-86778.
Full textPeterson, Mark Erik. "Evolutionary constraints on the structural similarity of proteins and applications to comparative protein structure modeling." Diss., Search in ProQuest Dissertations & Theses. UC Only, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3339202.
Full textBottoms, Christopher A. "Bioinformatics of protein bound water." Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/4188.
Full textThe 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 (July 17, 2006) Vita. Includes bibliographical references.
Leonardi, Emanuela. "Bioinformatic Analysis of Protein Mutations." Doctoral thesis, Università degli studi di Padova, 2012. http://hdl.handle.net/11577/3426280.
Full textAlterazioni genetiche sono state identificate per molte malattie di natura genetica, ma in molti casi i meccanismi molecolari che contribuiscono all’insorgere della malattia non sono ancora chiari. Lo studio degli effetti delle mutazioni a livello della proteina permette di chiarire i processi biologici coinvolti nella malattia e il ruolo della proteina in essa. La bioinformatica può aiutare a affrontare questo problema rappresentando il punto di connessione tra diverse discipline quali la clinica, la genetica, la biologia strutturale e la biochimica. In questa tesi ho impiegato un approccio computazionale per affrontare l’analisi di alcuni esempi di proteine di interesse biomedico, integrando diverse risorse di dati e indirizzando la ricerca sperimentale e clinica. Strutture proteiche determinate sperimentalmente o mediante il modelling molecolare sono state utilizzate come base per determinare la relazione tra struttura e funzione, essenziale per ottenere informazioni sulla correlazione genotipo-fenotipo. Le proteine prese in esame sono state inoltre analizzate nel loro contesto, considerando le interazioni che avvengono con altre proteine o ligandi nei diversi compartimenti cellulari. I risultati dell’analisi bioinformatica sono stati poi utilizzati per formulare ipotesi funzionali che in alcuni casi sono state verificate e confermate sperimentalmente da altri gruppi di ricerca. Le mutazioni identificate nei geni codificanti per le proteine in esame sono state valutate per il loro impatto sulla struttura e funzione della proteina utilizzando numerosi metodi di predizione disponibili online. Le diverse applicazioni descritte in questa tesi hanno fornito l’idea per lo sviluppo di nuovi approcci computazionali per lo caratterizzazione strutturale e funzionale di proteine e dei loro mutanti. Si è visto che la predizione migliora utilizzando un ensemble dei diversi metodi di predizione disponibili. Inoltre, per la predizione degli effetti di mutazioni è stato ideato un nuovo approccio computazionale che utilizza le reti di interazione tra residui per rappresentare la struttura proteica. Questi metodi sono stati utilizzati anche nell’analisi di dati genomici originati da nuove tecnologie di sequenziamento. Questo ambito necessita di nuove strategie di indagine per l’individuazione di poche varianti causative in un’enorme quantità di varianti identificate di dubbio significato. A questo scopo viene proposta una strategia di analisi che utilizza informazioni derivanti dalle reti di interazioni proteiche. I nuovi approcci formulati in questa tesi sono stati applicati e valutati ad un nuovo esperimento internazionale, chiamato Critical Assessment of Genome Interpretation (CAGI), fornendo in alcuni casi ottimi risultati
Baez, William David. "RNA Secondary Structures: from Biophysics to Bioinformatics." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1525714439675315.
Full textBrown, David K. "Bioinformatics tool development with a focus on structural bioinformatics and the analysis of genetic variation in humans." Thesis, Rhodes University, 2018. http://hdl.handle.net/10962/60708.
Full textJohansson, Joakim. "Modifying a Protein-Protein Interaction Identifier with a Topology and Sequence-Order Independent Structural Comparison Method." Thesis, Linköpings universitet, Bioinformatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-147777.
Full textBittencourt, Valnaide Gomes. "Aplica??o de t?cnicas de aprendizado de m?quina no reconhecimento de classes estruturais de prote?nas." Universidade Federal do Rio Grande do Norte, 2005. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15423.
Full textCoordena??o de Aperfei?oamento de Pessoal de N?vel Superior
Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated
Atualmente, a classifica??o estrutural de prote?nas, que diz respeito ? infer?ncia de padr?es em sua conforma??o 3D, ? um dos principais problemas em aberto da Biologia Molecular. Esse problema vem recebendo a aten??o de muitos pesquisadores na ?rea de Bioinform?tica pelo fato de as fun??es das prote?nas estarem intrinsecamente relacionadas ?s suas diferentes conforma??es espaciais, que s?o de dif?cil obten??o experimental em laborat?rio. Considerando a grande diferen?a entre o n?mero de seq??ncias de prote?nas conhecidas e o n?mero de estruturas tridimensionais determinadas experimentalmente, ? alta a demanda por t?cnicas automatizadas de classifica??o estrutural de prote?nas. Nesse contexto, as ferramentas computacionais, principalmente as t?cnicas de Aprendizado de M?quina (AM), tornaram-se alternativas essenciais para tratar esse problema. Neste trabalho, t?cnicas de AM s?o empregadas no reconhecimento de classes estruturais de prote?nas: ?rvore de Decis?o, k-Vizinhos Mais Pr?ximos, Na?ve Bayes, M?quinas de Vetores Suporte e Redes Neurais Artificiais. Esses m?todos foram escolhidos por representarem diferentes paradigmas de aprendizado e serem bastante citados na literatura. Visando conseguir uma melhoria de desempenho na solu??o do problema abordado, sistemas de multiclassifica??o homog?nea (Bagging e Boosting) e heterog?nea (Voting, Stacking e StackingC) s?o aplicados nesta pesquisa, usando como base as t?cnicas de AM anteriormente mencionadas. Al?m disso, pelo fato de a base de dados de prote?nas considerada neste trabalho apresentar o problema de classes desbalanceadas, t?cnicas artificiais de balanceamento de classes (Under-sampling Aleat?rio, Tomek Links, CNN, NCL e OSS) s?o utilizadas a fim de minimizar esse problema e melhorar o desempenho dos classificadores. Para a avalia??o dos m?todos de AM, um procedimento de valida??o cruzada ? empregado, em que a acur?cia dos classificadores ? medida atrav?s das m?dias da taxa de classifica??o incorreta nos conjuntos de testes independentes. Essas m?dias s?o comparadas duas a duas pelo teste de hip?tese a fim de avaliar se h? diferen?a estatisticamente significativa entre elas. Com os resultados obtidos, pode-se observar, entre os classificadores base, o desempenho superior do m?todo M?quinas de Vetores Suporte. Os sistemas de multiclassifica??o (homog?nea e heterog?nea), por sua vez, apresentaram, em geral, uma acur?cia superior ou similar a dos classificadores usados como base, destacando-se o Boosting que usou ?rvore de Decis?o em sua forma??o e o StackingC tendo como meta classificador a Regress?o Linear. O m?todo Voting, apesar de sua simplicidade, tamb?m mostrou-se adequado para a solu??o do problema considerado nesta disserta??o. Em rela??o ?s t?cnicas de balanceamento de classes, n?o foram alcan?ados melhores resultados de classifica??o global com as bases de dados obtidas com a aplica??o de tais t?cnicas. No entanto, foi poss?vel uma melhor classifica??o espec?fica da classe minorit?ria, de dif?cil aprendizado. A t?cnica NCL foi a que se mostrou mais apropriada ao balanceamento de classes da base de dados de prote?nas
Wu, Man-kit Edward, and 胡文傑. "Improved indexes for next generation bioinformatics applications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43224222.
Full textWu, Man-kit Edward. "Improved indexes for next generation bioinformatics applications." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43224222.
Full textGrimbs, Sergio. "Towards structure and dynamics of metabolic networks." Phd thesis, Universität Potsdam, 2009. http://opus.kobv.de/ubp/volltexte/2009/3239/.
Full textIn dieser Arbeit werden mathematische und informatische Ansätze zur Behandlung diverser Probleme im Zusammenhang mit der Modellierung metabolischer Netzwerke vorgestellt, insbesondere unter Berücksichtigung der eingeschränkten Verfügbarkeit detaillierter Enzymkinetiken. Es wird gezeigt, dass präzise mathematische Formulierungen der Probleme notwendig sind, um erstens angemessene und, falls möglich, effiziente Algorithmen zur Lösung zu entwickeln. Und zweitens, um die Güte der so gefundenen Lösungen zu bewerten. Des weiteren werden Methoden zur Analyse dynamischer Eigenschaften metabolischer Netzwerke eingeführt, welche entweder nur auf der Struktur der Netzwerke basieren oder zusätzlich noch Informationen über stationäre Zustände mit berücksichtigen. Außerdem wird eine Strategie zur Bestimmung von Schlüsselreaktionen eines Netzwerkes vorgestellt, welche die Entwicklung kinetischer Modelle vereinfacht. Der Erfolg neuer Technologien ermöglicht eine immer billigere und schnellere Sequenzierung des Genoms. Dies wird in naher Zukunft die Analyse biologischer Netzwerke nicht nur für Spezies, sondern auch für einzelne Individuen ermöglichen. Die automatische Rekonstruktion metabolischer Netzwerke ist bestens dafür geeignet, diese großen Datenmengen auszuwerten. Eine mathematische Formulierung der Rekonstruktion als Optimierungsproblem wird vorgestellt, die sowohl bereits vorhandenes Wissen als auch theoretische Vorhersagen verschiedenster bioinformatischer Methoden berücksichtigt. Die rekonstruierten Netzwerke sind hinsichtlich möglichst großer und plausibler Zusammenhangskomponenten hin optimiert, um fragmentierte und isolierte Teilnetzwerke zu vermeiden. Als Beispiel dient die Rekonstruktion der Saccharosesynthese in Chlamydomonas reinhardtii. Es wird gezeigt, dass das Problem sehr rechenintensiv ist und somit Approximationsalgorithmen erforderlich macht. Das 'inverse scope' Problem hat als Optimierungsziel, für ein gegebenes metabolisches Netzwerk die minimale Menge notwendiger Metabolite zu bestimmen, um eine ebenfalls gegebene Menge von gewünschten Zielmetaboliten zu produzieren. Diese Zielmetabolite können entweder durch experimentellen Messungen festgelegt werden, oder sie sind die gewünschten Endprodukte einer biotechnologischen Anwendung. Es wird gezeigt, dass das 'inverse scope' Problem rechenintensiv ist. Allerdings wird angenommen, dass die Berechnungskomplexität stark von der Anzahl gerichteter Zyklen innerhalb des metabolischen Netzwerkes abhängt. Dies könnte die Entwicklung effizienter Approximationsalgorithmen ermöglichen. Unter der Annahme von Massenwirkungskinetiken erlaubt es die 'chemical reaction network theory' (CRNT), anhand der Struktur metabolischer Netzwerke Rückschlüsse auf Multistabilität zu ziehen. Auch weitere Kinetiken können durch Modellierung von Enzymmechanismen mit berücksichtigt werden. CRNT wird zum Vergleich von mehreren Modellen des Calvinzyklus, welche sich in Größe und Abstraktionsniveau unterscheiden, verwendet. Obwohl für kleinere Modelle Ergebnisse erzielt werden, erlauben es die verfügbaren Theoreme und Algorithmen der CRNT nicht, Aussagen für größere Modelle zu machen, da die gegenwärtigen Implementierungen der Algorithmen an ihre Berechnungsgrenzen stoßen. Sind sowohl die Stoichiometrie eines metabolischen Netzwerkes, als auch die Metabolitkonzentrationen und Flüsse im stationären Zustand bekannt, so kann 'structural kinetic modelling' angewandt werden, um das dynamische Verhalten des Netzwerkes zu analysieren, selbst wenn die expliziten Ratengleichung unbekannt sind. Dieser Ansatz wird verwendet, um den stabilisierenden Einfluss allosterischer Regulation in menschlichen Erythrozyten zu untersuchen. Des weiteren werden die Reaktionen anhand ihrer Bedeutung hinsichtlich Stabilität im stationären Zustand angeordnet. Die wichtigsten Reaktionen bezüglich dieser Ordnung sind Hexokinase, Phosphofructokinase und Pyruvatkinase, welche bekanntermaßen stark reguliert und irreversibel sind. Kinetische Modelle, die auf generischen Ratengleichung beruhen, werden mit detaillierten Referenzmodellen für Erythrozyten und Hepatozyten verglichen. Die generischen Modelle simulieren das Verhalten nur in der Nähe eines gegebenen stationären Zustandes recht gut. Der zuvor erwähnte Ansatz, wichtige Reaktionen bezüglich Stabilität zu identifizieren, wird zur Bestimmung von Schlüsselreaktionen genutzt. Diese Schlüsselreaktionen werden im Detail modelliert, während für alle anderen Reaktionen weiterhin generische Ratengleichung verwendet werden. Die so entstandenen Hybridmodelle können das Verhalten des Referenzmodells signifikant besser beschreiben. Die Hybridmodelle können als Ausgangspunkt zur Erstellung genomweiter kinetischer Modelle dienen.
Cuthbertson, Jonathan M. "Structural bioinformatics and simulation studies of α-helical membrane proteins." Thesis, University of Oxford, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420449.
Full textHatherley, Rowan. "Structural bioinformatics studies and tool development related to drug discovery." Thesis, Rhodes University, 2016. http://hdl.handle.net/10962/d1020021.
Full textRepo, Susanna. "Structural bioinformatics in the study of protein function and evolution /." Turku, Finland : Dept. of Biochemistry and Pharmacy, Abo Akademi University, 2008. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=017048818&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
Full textShu, Nanjiang. "Protein structure prediction zinc-binding sites, one-dimensional structure and remote homology /." Doctoral thesis, Stockholm : Department of Materials and Environmental Chemistry (MMK), Stockholm University, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-34094.
Full textAt the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript. Härtill 4 uppsatser.
Tamura, Takeyuki. "Graph Algorithmic Approaches for Structure Inferences in Bioinformatics." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/68893.
Full textCarlsson, Jonas. "Mutational effects on protein structure and function." Doctoral thesis, Linköpings universitet, Bioinformatik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-50491.
Full textGarma, L. D. (Leonardo D. ). "Structural bioinformatics tools for the comparison and classification of protein interactions." Doctoral thesis, Oulun yliopisto, 2017. http://urn.fi/urn:isbn:9789526216065.
Full textTiivistelmä Suurin osa proteiinien toiminnasta tapahtuu vuorovaikutuksessa muiden molekyylien kanssa. Proteiinit, jotka osallistuvat samanlaisiin vuorovaikutuksiin todennäköisesti toimivat samalla tavalla. Kahden proteiinin todennäköisyys esiintyä samanlaisissa vuorovaikutustilanteissa voidaan määrittää tutkimalla niiden rakenteellista samankaltaisuutta. Tämä väitöskirjatyö käsittelee proteiini-proteiini- ja proteiini-ligandi -vuorovaikutusten vertailuun käytettyjen menetelmien kehitystä, ja niiden soveltamista rakenteeseen perustuvissa luokittelujärjestelmissä. Tunnettuja dimeerisiä proteiinikomplekseja tutkittiin uudella MultiMer-align-ohjelmaan (MM-align) perustuvalla menetelmällä. Vertailun tulokset osoittavat, että uusi menetelmä suoriutui MM-alignia paremmin merkittävässä osassa tapauksista. Tuloksia käytettiin myös kompleksien luokitteluun, jonka tuloksena oli 1761 erilaista proteiinien välistä vuorovaikutustyyppiä. Luonnossa esiintyvien proteiinien välisten vuorovaikutusten määrän arvioitiin tilastollisen mallin avulla olevan noin 4000. Tilastollisen mallin avulla saatiin vertailtua sekä sekvenssin (”quaternary families”) sekä rakenteen (”quaternary folds”) mukaan ryhmiteltyjen proteiinikompleksien määriä. Proteiinien ja pienien orgaanisten ligandien välisiä vuorovaikutuksia tutkittiin sekvenssistä riippumattomilla menetelmillä. Uudella menetelmällä testattiin kolmea eri samankaltaisuutta mittaavaa metriikkaa. Näistä parasta käytettiin viiden muun tunnetun menetelmän kanssa vertailemaan kaikkia tunnettuja proteiini-FAD (Flavin-Adenine-Dinucleotide, flaviiniadeniinidinukleotidi) -komplekseja. Proteiini-ligandikontaktien osalta uusi menetelmä kuvasi kompleksien samankaltaisuutta muita menetelmiä paremmin. Vertailun tuloksia hyödyntäen proteiini-FAD-kompleksit luokiteltiin edelleen 237 ryhmään. Suurimmassa osassa tapauksista luokittelujärjestelmä oli onnistunut jakamaan kompleksit ryhmiin niiden toiminnallisuuden mukaisesti. Ryhmät voitiin määritellä yksikäsitteisesti kuvaamalla FAD:n sitoutumispaikka graafisesti. Väitöskirjatyö osoittaa, että siinä kehitetyt menetelmät ovat parempia kuin aikaisemmin käytetyt menetelmät. Tulokset osoittavat, että sekä proteiinien väliset että proteiini-FAD -vuorovaikutukset voidaan luokitella rajattuun määrään vuorovaikutustyyppejä ja yleisesti luokittelu on yhtenevä proteiinien toiminnan suhteen
Mengiste, Simachew Abebe. "Computational Approaches to the Degeneration of Brain Networks and Other Complex Networks." Doctoral thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-213729.
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Cury, Jean. "Evolutionary genomics of conjugative elements and integrons." Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCB062/document.
Full textLiu, Tsunglin. "Physics and bioinformatics of RNA." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1141407392.
Full textBahena, Silvia. "Computational Methods for the structural and dynamical understanding of GPCR-RAMP interactions." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-416790.
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