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Rozprawy doktorskie na temat „Computational biology”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 25 lipca 2025

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1

Istrail, Sorin. "Computational molecular biology /." Amsterdam [u.a.] : Elsevier, 2003. http://www.loc.gov/catdir/toc/fy037/2003051360.html.

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2

Stegle, Oliver. "Probabilistic models in computational biology." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611560.

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Athanasakis, D. "Feature selection in computational biology." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1432346/.

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This thesis concerns feature selection, with a particular emphasis on the computational biology domain and the possibility of non-linear interaction between features. Towards this it establishes a two-step approach, where the first step is feature selection, followed by the learning of a kernel machine in this reduced representation. Optimization of kernel target alignment is proposed as a model selection criterion and its properties are established for a number of feature selection algorithms, including some novel variants of stability selection. The thesis further studies greedy and stochast
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4

Wu, Yichao Hurd Harry L. Ji Chuanshu. "Probability approximations with applications in computational finance and computational biology." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2006. http://dc.lib.unc.edu/u?/etd,247.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2006.<br>Title from electronic title page (viewed Oct. 10, 2007). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Statistics and Operations Research." Discipline: Statistics and Operations Research; Department/School: Statistics and Operations Research.
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5

Ranjard, Louis. "Computational biology of bird song evolution." e-Thesis University of Auckland, 2010. http://hdl.handle.net/2292/5719.

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Individuals of a given population share more behavioural traits with each other than with members of other populations. For example, in humans, traditions are specific to regions or countries. These cultural relationships can tell us about the history of the populations, their origin and the amount of exchange between them. In birds, regional dialects have been described in many species. However, the mechanisms with which dialects form in populations is not fully understood because it is difficult to analyse experimentally. Translocated populations, with their known histories, offer an opportu
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6

Lanctôt, J. Kevin. "Some string problems in computational biology." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0023/NQ51207.pdf.

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7

Miller, David J. Ghosh Avijit. "New methods in computational systems biology /." Philadelphia, Pa. : Drexel University, 2008. http://hdl.handle.net/1860/2810.

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8

Li, Limin, and 李丽敏. "Machine learning methods for computational biology." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44546749.

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9

Vialette, Stéphane. "Algorithmic Contributions to Computational Molecular Biology." Habilitation à diriger des recherches, Université Paris-Est, 2010. http://tel.archives-ouvertes.fr/tel-00862069.

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10

Selega, Alina. "Computational methods for RNA integrative biology." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/29630.

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Ribonucleic acid (RNA) is an essential molecule, which carries out a wide variety of functions within the cell, from its crucial involvement in protein synthesis to catalysing biochemical reactions and regulating gene expression. Such diverse functional repertoire is indebted to complex structures that RNA can adopt and its flexibility as an interacting molecule. It has become possible to experimentally measure these two crucial aspects of RNA regulatory role with such technological advancements as next-generation sequencing (NGS). NGS methods can rapidly obtain the nucleotide sequence of many
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11

Simoni, Giulia. "Modeling Startegies for Computational Systems Biology." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/254361.

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Mathematical models and their associated computer simulations are nowadays widely used in several research fields, such as natural sciences, engineering, as well as social sciences. In the context of systems biology, they provide a rigorous way to investigate how complex regulatory pathways are connected and how the disruption of these processes may contribute to the develop- ment of a disease, ultimately investigating the suitability of specific molecules as novel therapeutic targets. In the last decade, the launching of the precision medicine initiative has motivated the necessity to define
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12

Simoni, Giulia. "Modeling Startegies for Computational Systems Biology." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/254361.

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Mathematical models and their associated computer simulations are nowadays widely used in several research fields, such as natural sciences, engineering, as well as social sciences. In the context of systems biology, they provide a rigorous way to investigate how complex regulatory pathways are connected and how the disruption of these processes may contribute to the develop- ment of a disease, ultimately investigating the suitability of specific molecules as novel therapeutic targets. In the last decade, the launching of the precision medicine initiative has motivated the necessity to define
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13

Zagordi, Osvaldo. "Statistical physics methods in computational biology." Doctoral thesis, SISSA, 2007. http://hdl.handle.net/20.500.11767/3971.

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The interest of statistical physics for combinatorial optimization is not new, it suffices to think of a famous tool as simulated annealing. Recently, it has also resorted to statistical inference to address some "hard" optimization problems, developing a new class of message passing algorithms. Three applications to computational biology are presented in this thesis, namely: 1) Boolean networks, a model for gene regulatory networks; 2) haplotype inference, to study the genetic information present in a population; 3) clustering, a general machine learning tool.
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14

Pettersson, Fredrik. "A multivariate approach to computational molecular biology." Doctoral thesis, Umeå : Univ, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-609.

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15

Ziehm, Matthias Fritz. "Computational biology of longevity in model organisms." Thesis, University of Cambridge, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648888.

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16

Small, Benjamin Gavin. "The chemical and computational biology of inflammation." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/the-chemical-and-computational-biology-of-inflammation(4de5c19c-e377-4783-acfb-ad168ad35d46).html.

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Non-communicable diseases (NCD) such as cancer, heart disease and cerebrovascular injury are dependent on or aggravated by inflammation. Their prevention and treatment is arguably one of the greatest challenges to medicine in the 21st century. The pleiotropic, proinflammatory cytokine; interleukin-l beta (IL-l~) is a primary, causative messenger of inflammation. Lipopolysaccharide (LPS) induction ofIL-l~ expression via toll-like receptor 4 (TLR4) in myeloid cells is a robust experimental model of inflammation and is driven in large part via p38-MAPK and NF-KB signaling networks. The control of
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17

Futamura, Natsuhiko. "Algorithms for large-scale problems in computational biology." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2002. http://wwwlib.umi.com/cr/syr/main.

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18

Ding, Jiarui. "Computational methods for systems biology data of cancer." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/58164.

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High-throughput genome sequencing and other techniques provide a cost-effective way to study cancer biology and seek precision treatment options. In this dissertation I address three challenges in cancer systems biology research: 1) predicting somatic mutations, 2) interpreting mutation functions, and 3) stratifying patients into biologically meaningful groups. Somatic single nucleotide variants are frequent therapeutically actionable mutations in cancer, e.g., the ‘hotspot’ mutations in known cancer driver genes such as EGFR, KRAS, and BRAF. However, only a small proportion of cancer patients
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19

Uys, Lafras. "Computational systems biology of sucrose accumulation in sugarcane." Thesis, Link to the online version, 2006. http://hdl.handle.net/10019/245.

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20

Dinescu, Adriana Cundari Thomas R. "Metals in chemistry and biology computational chemistry studies /." [Denton, Tex.] : University of North Texas, 2007. http://digital.library.unt.edu/permalink/meta-dc-3678.

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21

Jones, Neil Christopher. "Computational tools for high-throughput discovery in biology." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3267820.

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Thesis (Ph. D.)--University of California, San Diego, 2007.<br>Title from first page of PDF file (viewed August 7, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 115-127).
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22

Cong, Yang, and 丛阳. "Optimization models and computational methods for systems biology." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B47752841.

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Systems biology is a comprehensive quantitative analysis of the manner in which all the components of a biological system interact functionally along with time. Mathematical modeling and computational methods are indispensable in such kind of studies, especially for interpreting and predicting the complex interactions among all the components so as to obtain some desirable system properties. System dynamics, system robustness and control method are three crucial properties in systems biology. In this thesis, the above properties are studied in four different biological systems. The ou
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23

Trybilo, Maciej. "Computational design of orthogonal microRNAs for synthetic biology." Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/8409.

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Upcoming applications of synthetic biology will require access to a wide array of robust genetic components (parts). The logic of a genetic system is encoded with regulatory elements such as pairs of transcription factors:promoters, miRNAs:target sites, or ribozymes:aptamers among others. Due to a relatively simple form and mode of operation of miRNAs, it is possible to design their synthetic variants. Out of all possible miRNA sequences the ones chosen should perform efficiently and should avoid cross-talk with both the host system circuits and within the imported synthetic ones. In this work
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24

Dinescu, Adriana. "Metals in Chemistry and Biology: Computational Chemistry Studies." Thesis, University of North Texas, 2007. https://digital.library.unt.edu/ark:/67531/metadc3678/.

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Numerous enzymatic reactions are controlled by the chemistry of metallic ions. This dissertation investigates the electronic properties of three transition metal (copper, chromium, and nickel) complexes and describes modeling studies performed on glutathione synthetase. (1) Copper nitrene complexes were computationally characterized, as these complexes have yet to be experimentally isolated. (2) Multireference calculations were carried out on a symmetric C2v chromium dimer derived from the crystal structure of the [(tBu3SiO)Cr(µ-OSitBu3)]2 complex. (3) The T-shaped geometry of a three-coordina
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25

Fratkin, Eugene. "Application of non-parametric algorithms to computational biology /." May be available electronically:, 2009. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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26

BARDINI, ROBERTA. "A diversity-aware computational framework for systems biology." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2752792.

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27

Codó, Tarraubella Laia. "Computational Infrastructures for biomolecular research." Doctoral thesis, Universitat de Barcelona, 2019. http://hdl.handle.net/10803/668536.

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Recently, research processes in Life sciences have evolved at a rapid pace. This evolution, mainly due to technological advances, offers more powerful equipment and generalizes the digital format of research data. In the data deluge context, we need to overcome the current tsunami of data and prepare for the future. The current model, consisting to regularly add hardware resources into centralized core facilities without global coordination, is no longer sustainable. Scientific data management and analysis should be enhanced in order to offer services and developments corresponding to the new
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28

Camacho, Diogo Mayo. "In silico cell biology and biochemistry: a systems biology approach." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/27960.

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In the post-"omic" era the analysis of high-throughput data is regarded as one of the major challenges faced by researchers. One focus of this data analysis is uncovering biological network topologies and dynamics. It is believed that this kind of research will allow the development of new mathematical models of biological systems as well as aid in the improvement of already existing ones. The work that is presented in this dissertation addresses the problem of the analysis of highly complex data sets with the aim of developing a methodology that will enable the reconstruction of a biological
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29

Weis, Michael Christian. "Computational Models of the Mammalian Cell Cycle." Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1323278159.

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30

Hallett, Michael Trevor. "An integrated complexity analysis of problems from computational biology." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq21933.pdf.

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31

Rahman, Muhammad Arifur. "Gaussian process in computational biology : covariance functions for transcriptomics." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/19460/.

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In the field of machine learning, Gaussian process models are widely used families of stochastic process for modelling data observed over time, space or both. Gaussian processes models are nonparametric, meaning that the models are developed on an infinite-dimensional parameter space. The parameter space is then typically learnt as the set of all possible solutions for a given learning problem. Gaussian process distributions are distribution over functions. The covariance function determines the properties of functions samples drawn from the process. Once the decision to model with a Gaussian
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32

Castillo, Andrea R. (Andrea Redwing). "Assessing computational methods and science policy in systems biology." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/51655.

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Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2009.<br>Includes bibliographical references (p. 109-112).<br>In this thesis, I discuss the development of systems biology and issues in the progression of this science discipline. Traditional molecular biology has been driven by reductionism with the belief that breaking down a biological system into the fundamental biomolecular components will elucidate such phenomena. We have reached limitations with this approach due to the complex and dynamical nature
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33

Haider, Syed Abbas. "Computational systems biology-based feature selection for cancer prognosis." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610378.

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34

Picart, Armada Sergio. "Statistical normalisation of network propagation methods for computational biology." Doctoral thesis, Universitat Politècnica de Catalunya, 2020. http://hdl.handle.net/10803/672381.

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The advent of high-throughput technologies and their decreasing cost have fostered the creation of a rich ecosystem of public database resources. In an era of affordable data acquisition, the core challenge has shifted to improve data interpretation, in order to understand normal and disease states. To that end, leveraging the current contextual knowledge in the form of annotations and biological networks is a powerful data amplifier to elucidate novel hypotheses. Label propagation and diffusion are the linchpin of the state of the art in network algorithms. In its simplest form, label propag
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35

McFarlane, Ross. "High-performance computing for computational biology of the heart." Thesis, University of Liverpool, 2010. http://livrepository.liverpool.ac.uk/3173/.

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This thesis describes the development of Beatbox — a simulation environment for computational biology of the heart. Beatbox aims to provide an adaptable, approachable simulation tool and an extensible framework with which High Performance Computing may be harnessed by researchers. Beatbox is built upon the QUI software package, which is studied in Chapter 2. The chapter discusses QUI’s functionality and common patterns of use, and describes its underlying software architecture, in particular its extensibility through the addition of new software modules called ‘devices’. The chapter summarises
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36

Kudahl, Ulrich Johan. "A computational biology approach to studying algae-bacterial interactions." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/276956.

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Microalgae have a profound effect on the world due to their large contribution to net carbon fixation. Although they are phototrophic, more than 50% of microalgae are thought to depend on external supply of metabolites such as B-vitamins. In oceans, algae are therefore often found together with a community of bacteria and form intricate networks where metabolites are exchanged. Currently, only a fraction of the related mechanisms and metabolite exchanges between algae and bacteria have been uncovered and many more are likely to exist. The work presented in this thesis is based on a model syste
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37

Warne, David James. "Computational inference in mathematical biology: Methodological developments and applications." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/202835/1/David_Warne_Thesis.pdf.

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Complexity in living organisms occurs on multiple spatial and temporal scales. The function of tissues depends on interactions of cells, and in turn, cell dynamics depends on intercellular and intracellular biochemical networks. A diverse range of mathematical modelling frameworks are applied in quantitative biology. Effective application of models in practice depends upon reliable statistical inference methods for experimental design, model calibration and model selection. In this thesis, new results are obtained for quantification of contact inhibition and cell motility mechanisms in prostat
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38

Subramanian, Ayshwarya. "Inferring tumor evolution using computational phylogenetics." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/275.

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Cancer research has made tremendous progress in understanding the basic biology of tumors. One of the key insights that has informed work in this area is the recognition that a tumor is an evolutionary system, in which individual cells undergo a process of rapid mutation and selection leading to a progression in phenotypes and, typically, aggressiveness of the tumor. Tumor phylogenetics is a strategy for interpreting the evolution of tumors using computer algorithms for phylogenetics, i.e., the inference of evolutionary trees. The approach takes advantage of a large body of phylogenetic theory
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39

Ballweg, Richard A. III. "Computational Analysis of Heterogeneous Cellular Responses." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin159216973756476.

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40

Karathia, Hiren Mahendrabhai. "Development and application of computational methdologies for Integrated Molecular Systems Biology." Doctoral thesis, Universitat de Lleida, 2012. http://hdl.handle.net/10803/110518.

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L'objectiu del treball presentat en aquesta tesi va ser el desenvolupament i l'aplicació de metodologies computacionals que integren l’anàlisis de informació sobre seqüències proteiques, informació funcional i genòmica per a la reconstrucció, anotació i organització de proteomes complets, de manera que els resultats es poden comparar entre qualsevol nombre d'organismes amb genomes completament seqüenciats. Metodològicament, m'he centrat en la identificació de l'organització molecular dins d'un proteoma complet d'un organisme de referència i comparació amb proteomes d'altres organismes, en esp
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41

Weirather, Jason Lee. "Computational approaches to the study of human trypanosomatid infections." Thesis, The University of Iowa, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3609102.

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<p> Trypanosomatids cause human diseases such as leishmaniasis and African trypanosomiasis. Trypanosomatids are protists from the order Trypanosomatida and include species of the genera <i>Trypanosoma</i> and <i> Leishmania</i>, which occupy a similar ecological niche. Both have digenic life-stages, alternating between an insect vector and a range of mammalian hosts. However, the strategies used to subvert the host immune system differ greatly as do the clinical outcome of infections between species. The genomes of both the host and the parasite instruct us about strategies the pathogens u
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42

Facchetti, Giuseppe. "Computational approaches to complex biological networks." Doctoral thesis, SISSA, 2013. http://hdl.handle.net/20.500.11767/4822.

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The need of understanding and modeling the biological networks is one of the raisons d'être and of the driving forces behind the emergence of Systems Biology. Because of its holistic approach and because of the widely different level of complexity of the networks, different mathematical methods have been developed during the years. Some of these computational methods are used in this thesis in order to investigate various properties of different biological systems. The first part deals with the prediction of the perturbation of cellular metabolism induced by drugs. Using Flux Balance Analysis
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43

Jones-Rhoades, Matthew W. (Matthew William). "Computational and experimental analysis of plant microRNAs." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/31191.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2005.<br>Includes bibliographical references.<br>MicroRNAs (miRNAs) are small, endogenous, non-coding RNAs that mediate gene regulation in plants and animals. We demonstrated that Arabidopsis thaliana miRNAs are highly complementary (0-3 mispairs in an ungapped alignment) to more mRNAs than would be expected by chance. These mRNAs are therefore putative regulatory targets of their complementary miRNAs. Many miRNA complementary sites are conserved to the monocot Oryza sativa (rice), implying evolutionary conservation base
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44

Kasap, Server. "High performance reconfigurable architectures for bioinformatics and computational biology applications." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/24757.

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The field of Bioinformatics and Computational Biology (BCB), a relatively new discipline which spans the boundaries of Biology, Computer Science and Engineering, aims to develop systems that help organise, store, retrieve and analyse genomic and other biological information in a convenient and speedy way. This new discipline emerged mainly as a result of the Human Genome project which succeeded in transcribing the complete DNA sequence of the human genome, hence making it possible to address many problems which were impossible to even contemplate before, with a plethora of applications includi
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45

Misirli, Goksel. "Data integration strategies for informing computational design in synthetic biology." Thesis, University of Newcastle upon Tyne, 2013. http://hdl.handle.net/10443/1873.

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The potential design space for biological systems is complex, vast and multidimensional. Therefore, effective large-scale synthetic biology requires computational design and simulation. By constraining this design space, the time- and cost-efficient design of biological systems can be facilitated. One way in which a tractable design space can be achieved is to use the extensive and growing amount of biological data available to inform the design process. By using existing knowledge design efforts can be focused on biologically plausible areas of design space. However, biological data is large,
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46

Fu, Yan. "Computational Systems Biology Analysis of Cell Reprogramming and Activation Dynamics." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/28414.

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In the past two decades, molecular cell biology has transitioned from a traditional descriptive science into a quantitative science that systematically measures cellular dynamics on different levels of genome, transcriptome and proteome. Along with this transition emerges the interdisciplinary field of systems biology, which aims to unravel complex interactions in biological systems through integrating experimental data into qualitative or quantitative models and computer simulations. In this dissertation, we applied various systems biology tools to investigate two important problems with re
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47

Donaldson, Eric F. Baric Ralph S. "Computational and molecular biology approaches to viral replication and pathogenesis." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,1731.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2008.<br>Title from electronic title page (viewed Sep. 16, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Microbiology and Immunology Virology." Discipline: Microbiology and Immunology; Department/School: Medicine.
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48

Yang, Pengyi. "Ensemble methods and hybrid algorithms for computational and systems biology." Thesis, The University of Sydney, 2012. https://hdl.handle.net/2123/28979.

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Modern molecular biology increasingly relies on the application of high-throughput technologies for studying the function, interaction, and integration of genes, proteins, and a variety of other molecules on a large scale. The application of those high throughput technologies has led to the exponential growth of biological data, making modern molecular biology a data-intensive science. Huge effort has been directed to the development of robust and efficient computational algorithms in order to make sense of these extremely large and complex biological data, giving rise to several interdiscipli
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49

Khan, Maria Mohammad. "Computational Biology in the Analysis of Epigenetic Nuclear Self-Organization." Thesis, The University of Arizona, 2010. http://hdl.handle.net/10150/146042.

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The function of the nucleus is central to the survival of cells and thus life as a whole. Among other processes, it is the site of gene expression, DNA repair, and genome stability. These functions are carried in the context of a complex nuclear architecture. The nucleus is compartmentalized both spatially and functionally. These compartments are proteinaceous nuclear bodies or chromatin domains, both of which are not segregated from other compartments by membranes-as are the organelles of cells. Specifically, proteinaceous nuclear bodies are characterized as regions within the nucleus with di
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Ghaffarizadeh, Ahmadreza. "COMPUTATIONAL MODELS OF INTRACELLULAR AND INTERCELLULAR PROCESSES IN DEVELOPMENTAL BIOLOGY." DigitalCommons@USU, 2014. https://digitalcommons.usu.edu/etd/3103.

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Systems biology takes a holistic approach to biological questions as it applies mathematical modeling to link and understand the interaction of components in complex biological systems. Multiscale modeling is the only method that can fully accomplish this aim. Mutliscale models consider processes at different levels that are coupled within the modeling framework. A first requirement in creating such models is a clear understanding of processes that operate at each level. This research focuses on modeling aspects of biological development as a complex process that occurs at many scales. Two of
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