Dissertations / Theses on the topic 'Phylogenetic'
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Jirásková, Kristýna. "Metody rekonstrukce fylogenetických superstromů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219518.
Full textKosíř, Kamil. "Metody rekonstrukce fylogenetických superstromů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220860.
Full textMecham, Jesse L. "Jumpstarting phylogenetic searches /." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1403.pdf.
Full textMcHugh, Sean W. "Phylogenetic Niche Modeling." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104893.
Full textMaster of Science
As many species face increasing pressure in a changing climate, it is crucial to understand the set of environmental conditions that shape species' ranges--known as the environmental niche--to guide conservation and land management practices. Species distribution models (SDMs) are common tools that are used to model species' environmental niche. These models treat a species' probability of occurrence as a function of environmental conditions. SDM niche estimates can predict a species' range given climate data, paleoclimate, or projections of future climate change to estimate species range shifts from the past to the future. However, SDM estimates are often biased by non-environmental factors shaping a species' range including competitive divergence or dispersal barriers. Biased SDM estimates can result in range predictions that get worse as we extrapolate beyond the observed climatic conditions. One way to overcome these biases is by leveraging the shared evolutionary history amongst related species to "fill in the gaps". Species that are more closely phylogenetically related often have more similar or "conserved" environmental niches. By estimating environmental niche over all species in a clade jointly, we can leverage niche conservatism to produce more biologically realistic estimates of niche. However, currently a methodological gap exists between SDMs estimates and macroevolutionary models, prohibiting them from being estimated jointly. We propose a novel model of evolutionary niche called PhyNE (Phylogenetic Niche Evolution), where biologically realistic environmental niches are fit across a set of species with occurrence data, while simultaneously fitting and leveraging a model of evolution across a portion of the tree of life. We evaluated model accuracy, bias, and precision through simulation analyses. Accuracy and precision increased with larger phylogeny size and effectively estimated model parameters. We then applied PhyNE to Plethodontid salamanders from Eastern North America. This ecologically-important and diverse group of lungless salamanders require cold and wet conditions and have distributions that are strongly affected by climatic conditions. Species within the family vary greatly in distribution, with some species being wide ranging generalists, while others are hyper-endemics that inhabit specific mountains in the Southern Appalachians with restricted thermal and hydric conditions. We fit PhyNE to occurrence data for these species and their associated average annual precipitation and temperature data. We identified no correlations between species environmental preference and specialization. Pattern of preference and specialization varied among Plethodontid species groups, with more aquatic species possessing a broader environmental niche, likely due to the aquatic microclimate facilitating occurrence in a wider range of conditions. We demonstrated the effectiveness of PhyNE's evolutionarily-informed estimates of environmental niche, even when species' occurrence data is limited or even absent. PhyNE establishes a proof-of-concept framework for a new class of approaches for studying niche evolution, including improved methods for estimating niche for data-deficient species, historical reconstructions, future predictions under climate change, and evaluation of niche evolutionary processes across the tree of life. Our approach establishes a framework for leveraging the rapidly growing availability of biodiversity data and molecular phylogenies to make robust eco-evolutionary predictions and assessments of species' niche and distributions in a rapidly changing world.
Mecham, Jesse Lewis. "Jumpstarting Phylogenetic Searches." BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/483.
Full textFaller, Beáta. "Combinatorial and probabilistic methods in biodiversity theory." Thesis, University of Canterbury. Mathematics and Statistics, 2010. http://hdl.handle.net/10092/3985.
Full textKrig, Kåre. "Methods for phylogenetic analysis." Thesis, Linköping University, Department of Mathematics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-56814.
Full textIn phylogenetic analysis one study the relationship between different species. By comparing DNA from two different species it is possible to get a numerical value representing the difference between the species. For a set of species, all pair-wise comparisons result in a dissimilarity matrix d.
In this thesis I present a few methods for constructing a phylogenetic tree from d. The common denominator for these methods is that they do not generate a tree, but instead give a connected graph. The resulting graph will be a tree, in areas where the data perfectly matches a tree. When d does not perfectly match a tree, the resulting graph will instead show the different possible topologies, and how strong support they have from the data.
Finally I have tested the methods both on real measured data and constructed test cases.
Pardi, Fabio. "Algorithms on phylogenetic trees." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611685.
Full textWang, Min-Hui. "Classification using phylogenetic trees /." The Ohio State University, 1999. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488190595939375.
Full textSundberg, Kenneth A. "Partition Based Phylogenetic Search." BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2583.
Full textHansen, Michael. "Algebra and Phylogenetic Trees." Scholarship @ Claremont, 2007. https://scholarship.claremont.edu/hmc_theses/194.
Full textPowell, Robyn Faye. "Systematics, diversification and ecology of the Conophytum-clade (Ruschieae; Aizoaceae)." University of the Western Cape, 2016. http://hdl.handle.net/11394/5453.
Full textThe Ruschieae is the most diverse and speciose tribe within the large subfamily Ruschioideae (Aizoaceae), with approximately 71 genera and a distribution centred in the arid parts of the Greater Cape Floristic Region (GCFR) of South Africa. Recent phylogenetic analyses provided the first insights into generic relationships within the tribe, with a number of novel generic relationships discovered. The tribal phylogeny recovered 12 large clades, of which the Conophytum-clade was one the most morphologically diverse based on leaf and capsule characters. The Conophytum-clade is an early-diverging lineage of the Ruschieae and includes the following 10 genera: Cheiridopsis N.E.Br., Conophytum N.E.Br., Enarganthe N.E.Br., Ihlenfeldtia H.E.K.Hartmann, Jensenobotrya A.G.J.Herre, Namaquanthus L.Bolus, Octopoma N.E.Br., Odontophorus N.E.Br., Ruschianthus L.Bolus and Schlechteranthus Schwantes. The present study presents an expanded phylogenetic analysis of the Conophytum-clade, with the sampling of the majority of species in the genera and a representative sampling (56% of species) of the speciose genus Conophytum. Phylogenetic data for up to nine plastid gene regions (atpB–rbcL, matK, psbJ–petA, rpl16, rps16, trnD– trnT, trnL–F, trnQᶷᶷᶢ–rps16, trnS–trnG) were produced for each of the sampled species. The produced plastid data was analyses using maximum parsimony, maximum likelihood and Bayesian inference. The combined plastid phylogenetic analyses were used in combination with morphological, anatomical and palynological data to assess generic and subgeneric circumscriptions within the clade. Upon assessment of generic circumscriptions in the Conophytum-clade, the number of recognised genera in the clade decreased from ten to seven. Arenifera A.G.J.Herre, which had not been sampled in any phylogeny of the Ruschieae, and Octopoma were recovered as polyphyletic, with species placed in the Conophytum-clade, while the type species was placed in the xeromorphic clade of the tribal phylogeny. The species of Arenifera and Octopoma placed in the Conophytum-clade were subsequently included in Schlechteranthus upon assessment of generic circumscriptions between the taxa. Two morphological groupings were recognised within Schlechteranthus, one including the species of Schlechteranthus and the other including species previously recognised as Arenifera and Octopoma. These two morphological groupings were treated as subgenera, with the erection of the new subgenus Microphyllus R.F.Powell. A detailed taxonomic revision of subgenus Microphyllus is presented with a key to species, descriptions of the species (including a new species: S. parvus R.F.Powell & Klak), known geographical distributions and illustrations of the species. In addition to the changes mentioned above, the expanded sampling and phylogenetic analyses of the Conophytum-clade recovered Ihlenfeldtia and Odontophorus embedded in Cheiridopsis. The species of Ihlenfeldtia were recovered with species of heiridopsis subgenus Aequifoliae H.E.K.Hartmann, while the species of Odontophorus were recovered as polyphyletic within the Cheiridopsis subgenus Odontophoroides H.E.K.Hartmann clade. Cheiridopsis was subsequently expanded to include the species of Ihlenfeldtia and Odontophorus, with these species accommodated in the subgenera of Cheiridopsis. The phylogenetic placement and relationship of these species was supported by the shared capsule morphology. The expanded sampling of the clade did not resolve the phylogenetic relationship of the monotypic genera Enarganthe, Jensenobotrya, Namaquanthus and Ruschianthus, with these genera unresolved in the Conophytum-clade. These genera however, exhibit a unique combination of morphological characters, such as a glabrous leaf epidermis and variation in pollen exine and colpi structure, in contrast to the other genera of the clade. The assessment of the generic circumscription of these genera, based on the molecular, morphological, anatomical and palynological data suggested that the generic statuses of these monotypic genera should be maintained. The expanded phylogenetic sampling of the morphologically diverse and speciose genus Conophytum recovered the genus as monophyletic. This monophyly was supported by the unique floral type in Conophytum, with the fused petaloid staminodes forming a tube. None of the sectional classifications were recovered as monophyletic but the phylogenetic analyses did recover a few clades which more or less corresponded to the current sectional classification of the genus. A number of clades were also recovered which included species from a range of different sections. Diverse leaf and floral traits were shown to have evolved numerous times across the genus. This was particularly interesting with regards to the selected floral traits, as the phylogeny indicated a number of switches in floral morphologies across the genus. The floral diversity was assessed in complex species communities of Conophytum across the GCFR, where up to 11 species of Conophytum are found occurring sympatrically, and floral traits were shown to be different across the species within the communities. Pollination competition and adaptation were suggested as possible drivers of floral diversity in the genus, with differences in phenology, anthesis and floral morphology within the species complex communities. The unique floral type of Conophytum has enabled the species to develop a diverse range of specialised flowers, with a variety of structures, scents and colours, resulting in the diverse floral morphologies found across the genus. The complex Conophytum species communities included both closely as well as distantly related species, suggesting the soft papery capsules of Conophytum are wind dispersed. This adaptation to long distance seed dispersal resulted in a significantly higher phylogenetic diversity in Conophytum when compared to its sister genus, Cheiridopsis. A population genetics study of Conophytum also suggested that the capsules may be wind dispersed, with an indication of genetic connectivity between the geographically isolated populations of C. marginatum Lavis across the Bushmanland Inselberg Region. Although the capsules are dispersed by wind, the seeds are released from the hygrochastic capsules by runoff during rainfall events. The relationship between seed dispersal and runoff is evident from the genetic structure of populations of C. maughanii N.E.Br. and C. ratum S.A.Hammer that occur on the tops and the surrounding bases of the inselbergs, as the drainage pattern was found to directly influence population structure in these species. In addition, the AFLP analyses provided insight into the conservation of the flagship species C. ratum. The summit populations of this species were shown to sustain the populations at the base of the Gamsberg. This finding is especially important, as the distribution of the species is restricted to the Gamsberg inselberg, where mining has already commenced as of this year.
National Research Foundation (NRF)
Arvestad, Isaac, and Henrik Lagebrand. "Implementing Bayesian phylogenetic tree inference with Sequential Monte Carlo and the Phylogenetic Likelihood Library." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229429.
Full textVi undersöker om programspråksbiblioteket Phylogenetic Likelihood Library (PLL) kan användas för bayesiansk inferens av phylogenetiska träd med en sekventiell Monte Carlo-metod (SMC). Genom att implementera algoritmen med två olika delar av PLL:s programmeringsgränssnitt visar vi att det går att använda PLL för att implementera SMC-algoritmen men att det är oklart om det huvudsakliga programmeringsgränssnittet är lämpligt.
Fleissner, Roland. "Sequence alignment and phylogenetic inference." Berlin : Logos Verlag, 2004. http://diss.ub.uni-duesseldorf.de/ebib/diss/file?dissid=769.
Full textRehmsmeier, Marc. "Database searching with phylogenetic trees." [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=963977423.
Full textDeepak, Akshay. "SearchTree mining robust phylogenetic trees /." [Ames, Iowa : Iowa State University], 2010. 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:1476290.
Full textHaber, Matthew Horace. "The centrality of phylogenetic thinking /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2005. http://uclibs.org/PID/11984.
Full textSchmidt, Heiko A. "Phylogenetic trees from large datasets." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=968534945.
Full textFleissner, Roland. "Sequence alignment and phylogenetic inference." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=971844704.
Full textGottschling, Marc. "Phylogenetic analysis of selected Boraginales." [S.l. : s.n.], 2003. http://www.diss.fu-berlin.de/2003/30/index.html.
Full textHögnabba, Filip. "Phylogenetic studies of cyanobacterial lichens /." Helsinki : Yliopistopaino, 2007. http://ethesis.helsinki.fi.
Full textRoos, Marinus Cornelis. "Phylogenetic systematics of the Drynarioideae /." Amsterdam [u.a.] : North-Holland, 1985. http://www.gbv.de/dms/bs/toc/013141155.pdf.
Full textJetté, Migüel. "Reconstructing functions on phylogenetic trees." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99187.
Full textRyder, Robin Jeremy. "Phylogenetic models of language diversification." Thesis, University of Oxford, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.543009.
Full textStolzer, Maureen. "Phylogenetic Inference for Multidomain Proteins." Research Showcase @ CMU, 2011. http://repository.cmu.edu/dissertations/47.
Full textWelbourn, Warren Calvin. "Phylogenetic studies of trombidioid mites /." The Ohio State University, 1985. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487262825074137.
Full textKashiwada, Akemi. "Constructing Phylogenetic Trees from Subsplits." Scholarship @ Claremont, 2005. https://scholarship.claremont.edu/hmc_theses/171.
Full textBauer, Jennifer E. "A Phylogenetic and Paleobiogeographic Analysis of the Ordovician Brachiopod Eochonetes." Ohio University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1397486053.
Full textPorter, Megan L. "Crustacean phylogenetic systematics and opsin evolution." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd859.pdf.
Full textOldman, James. "Constructing phylogenetic networks based on trinets." Thesis, University of East Anglia, 2015. https://ueaeprints.uea.ac.uk/59446/.
Full textFischer, Mareike. "Novel Mathematical Aspects of Phylogenetic Estimation." Thesis, University of Canterbury. Mathematics and Statistics, 2009. http://hdl.handle.net/10092/2331.
Full textKeivany, Yazdan. "Phylogenetic relationships of Gasterosteiformes (Teleostei, Percomorpha)." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ59608.pdf.
Full textHabib, Farhat Abbas. "Genotype-phenotype correlation using phylogenetic trees." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1187297400.
Full textFuentes, Carvajal Andreina. "Phylogenetic relationships within Coleeae (Bignoniaceae juss.)." Click here to access thesis, 2007. http://www.georgiasouthern.edu/etd/archive/fall2007/carvajal_a_fuentes/carvajal_andreina_f_200708_MS.pdf.
Full text"A thesis submitted to the Graduate Faculty of Georgia Southern University in partial fulfillment of the requirements for the degree Master of Science." In Biology, under the direction of Michelle Zjhra. ETD. Electronic version approved: December 2007. Includes bibliographical references (p. 38-42)
Ababneh, Faisal. "Models and estimation for phylogenetic trees /." Connect to full text, 2006. http://hdl.handle.net/2123/927.
Full textCho, Anna. "Constructing Phylogenetic Trees Using Maximum Likelihood." Scholarship @ Claremont, 2012. http://scholarship.claremont.edu/scripps_theses/46.
Full textWu, Qiong. "Phylogenetic Networks : New Constructions and Applications." Thesis, University of East Anglia, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.514315.
Full textFujisawa, Tomochika. "Statistical analyses of genealogical-phylogenetic data." Thesis, Imperial College London, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556548.
Full textYu, Junjie, and 于俊杰. "Phylogenetic tree reconstruction with protein linkage." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B49618167.
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Computer Science
Master
Master of Philosophy
Boudko, Ekaterina. "Phylogenetic Analysis of Subtribe Alopecurinae (Poaceae)." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30696.
Full textGarcia, John. "Phylogenetic methods in Huasteca Nahuatl dialectology." Thesis, California State University, Long Beach, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1526912.
Full textThe Nahuatl language spoken by Aztec/Mexica continues to be spoken throughout Central Mexico and in the Huasteca region. Variation within the Huasteca has yet to be fully explored, and this study integrates a questionnaire published by Lastra and interviews I conducted with native speakers representing different communities. The data produced from this were used to find features that distinguish different towns and then were analyzed using cladistics, a phylogenetic method used by biologists to propose a hypothesis of the evolutionary relationships among species, and which has also been used by linguists. The output suggests there is a large split between northwest and southeast regions of the Huasteca, and that the northeast villages compose a subregion on their own. One can trace the relationships between communities on the output tree and follow a path backwards towards Central Mexico, suggesting a north-east migration.
Dissanayake, Deepthi. "Phylogenetic research of the family Chrysobalanaceae." Thesis, University of Reading, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390620.
Full textWilliams, Annette Mary. "Phylogenetic analysis of the genus Streptococcus." Thesis, University of Reading, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.333267.
Full textRadice, Rosalba. "A Bayesian approach to phylogenetic networks." Thesis, University of Bath, 2011. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538163.
Full textHayward, Peter. "Parallel likelihood calculations for phylogenetic trees." Thesis, Stellenbosch : Stellenbosch University, 2011. http://hdl.handle.net/10019.1/17919.
Full textENGLISH ABSTRACT: Phylogenetic analysis is the study of evolutionary relationships among organisms. To this end, phylogenetic trees, or evolutionary trees, are used to depict the evolutionary relationships between organisms as reconstructed from DNA sequence data. The likelihood of a given tree is commonly calculated for many purposes including inferring phylogenies, sampling from the space of likely trees and inferring other parameters governing the evolutionary process. This is done using Felsenstein’s algorithm, a widely implemented dynamic programming approach that reduces the computational complexity from exponential to linear in the number of taxa. However, with the advent of efficient modern sequencing techniques the size of data sets are rapidly increasing beyond current computational capability. Parallel computing has been used successfully to address many similar problems and is currently receiving attention in the realm of phylogenetic analysis. Work has been done using data decomposition, where the likelihood calculation is parallelised over DNA sequence sites. We propose an alternative way of parallelising the likelihood calculation, which we call segmentation, where the tree is broken down into subtrees and the likelihood of each subtree is calculated concurrently over multiple processes. We introduce our proposed system, which aims to drastically increase the size of trees that can be practically used in phylogenetic analysis. Then, we evaluate the system on large phylogenies which are constructed from both real and synthetic data, to show that a larger decrease of run times are obtained when the system is used.
AFRIKAANSE OPSOMMING:Filogenetiese analise is die studie van evolusionêre verwantskappe tussen organismes. Filogenetiese of evolusionêre bome word aangewend om die evolusionêre verwantskappe, soos herwin vanuit DNS-kettings data, tussen organismes uit te beeld. Die aanneemlikheid van ’n gegewe filogenie word oor die algemeen bereken en aangewend vir menigte doeleindes, insluitende die afleiding van filogenetiese bome, om te monster vanuit ’n versameling van sulke moontlike bome en vir die afleiding van ander belangrike parameters in die evolusionêre proses. Dit word vermag met behulp van Felsenstein se algoritme, ’n alombekende benaderingwyse wat gebruik maak van dinamiese programmering om die berekeningskompleksiteit van eksponensieel na lineêr in die aantal taxa, te herlei. Desnieteenstaande, het die koms van moderne, doeltreffender orderingsmetodes groter datastelle tot gevolg wat vinnig besig is om bestaande berekeningsvermoë te oorskry. Parallelle berekeningsmetodes is reeds suksesvol toegepas om vele soortgelyke probleme op te los, met groot belangstelling tans in die sfeer van filogenetiese analise. Werk is al gedoen wat gebruik maak van data dekomposisie, waar die aanneemlikheidsberekening oor die DNS basisse geparallelliseer word. Ons stel ’n alternatiewe metode voor, wat ons segmentasie noem, om die aanneemlikheidsberekening te parallelliseer, deur die filogenetiese boom op te breek in sub-bome, en die aanneemlikheid van elke sub-boom gelyklopend te bereken oor verskeie verwerkingseenhede. Ons stel ’n stelsel voor wat dit ten doel het om ’n drastiese toename in die grootte van die bome wat gebruik kan word in filogenetiese analise, teweeg te bring. Dan, word ons voorgestelde stelsel op groot filogenetiese bome, wat vanaf werklike en sintetiese data gekonstrueer is, evalueer. Dit toon aan dat ’n groter afname in looptyd verkry word wanneer die stelsel in gebruik is.
Figueroa, Alex. "Phylogenetic Relationships and Evolution of Snakes." ScholarWorks@UNO, 2016. http://scholarworks.uno.edu/td/2222.
Full textBhattacharya, Deblina Patra, Sebastian Canzler, Stephanie Kehr, Jana Hertel, Ivo Grosse, and Peter F. Stadler. "Phylogenetic distribution of plant snoRNA families." Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-215736.
Full textViana, Gerardo ValdÃso Rodrigues. "Techniques for construction of phylogenetic trees." Universidade Federal do CearÃ, 2007. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=1353.
Full textPhylogenetic tree structures express similarities, ancestrality, and relationships between species or group of species, and are also known as evolutionary trees or phylogenies. Phylogenetic trees have leaves that represent species (taxons), and internal nodes that correspond to hypothetical ancestors of the species. In this thesis we rst present elements necessary to the comprehension of phylogenetic trees systematics, then efcient algorithms to build them will be described. Molecular biology concepts, life evolution, and biological classication are important to the understanding of phylogenies. Phylogenetic information may provide important knowledge to biological research work, such as, organ transplantation from animals, and drug toxicologic tests performed in other species as a precise prediction to its application in human beings. To solve a phylogeny problem implies that a phylogenetic tree must be built from known data about a group of species, according to an optimization criterion. The approach to this problem involves two main steps: the rst refers to the discovery of perfect phylogenies, in the second step, information extracted from perfect phylogenies are used to infer more general ones. The techniques that are used in the second step take advantage of evolutionary hypothesis. The problem becomes NP-hard for a number of interesting hypothesis, what justify the use of inference methods based on heuristics, metaheuristics, and approximative algorithms. The description of an innovative technique based on local search with multiple start over a diversied neighborhood summarizes our contribution to solve the problem. Moreover, we used parallel programming in order to speed up the intensication stage of the search for the optimal solution. More precisely, we developed an efcient algorithm to obtain approximate solutions for a phylogeny problem which infers an optimal phylogenetic tree from characteristics matrices of various species. The designed data structures and the binary data manipulation in some routines accelerate simulation and illustration of the experimentation tests. Well known instances have been used to compare the proposed algorithm results with those previously published. We hope that this work may arise researchers' interest to the topic and contribute to the Bioinformatics area.
Ãrvores filogenÃticas sÃo estruturas que expressam a similaridade, ancestralidade e relacionamentos entre as espÃcies ou grupo de espÃcies. Conhecidas como Ãrvores evolucionÃrias ou simplesmente filogenias, as Ãrvores filogenÃticas possuem folhas que representam as espÃcies (tÃxons) e nÃs internos que correspondem aos seus ancestrais hipotÃticos. Neste trabalho, alÃm das informaÃÃes necessÃrias para o entendimento de toda a sistemÃtica filogenÃtica, sÃo apresentadas tÃcnicas algorÃtmicas para construÃÃo destas Ãrvores. Os conceitos bÃsicos de biologia molecular, evoluÃÃo da vida e classificaÃÃo biolÃgica, aqui descritos, permitem compreender o que à uma Filogenia e qual sua importÃncia para a Biologia. As informaÃÃes filogenÃticas fornecem,por exemplo, subsÃdios importantes para decisÃes relativas aos transplantes de ÃrgÃos ou tecidos de outras espÃcies para o homem e para que testes de reaÃÃo imunolÃgica ou de toxicidade sejam feitos antes em outros sistemas biolÃgicos similares ao ser humano. Resolver um Problema de Filogenia corresponde à construÃÃo de uma Ãrvore filogenÃtica a partir de dados conhecidos sobre as espÃcies em estudo, obedecendo a algum critÃrio de otimizaÃÃo. A abordagem dada a esse problema envolve duas etapas, a primeira, referente aos casos em que as filogenias sÃo perfeitas cujos procedimentos desenvolvidos serÃo utilizados na segunda etapa, quando deve ser criada uma tÃcnica de inferÃncia para a filogenia num caso geral. Essas tÃcnicas consideram de forma peculiar as hipÃteses sobre o processo de evoluÃÃo. Para muitas hipÃteses de interesse o problema se torna NP-DifÃcil, justificando-se o uso de mÃtodos de inferÃncia atravÃs de heurÃsticas, meta-heurÃsticas e algoritmos aproximativos. Nossa contribuiÃÃo neste trabalho consiste em apresentar uma tÃcnica de resoluÃÃo desse problema baseada em buscas locais com partidas mÃltiplas em vizinhanÃas diversificadas. Foi utilizada a programaÃÃo paralela para minimizar o tempo de execuÃÃo no processo de intensificaÃÃo da busca pela soluÃÃo Ãtima do problema. Desta forma, desenvolvemos um algoritmo para obter soluÃÃes aproximadas para um Problema da Filogenia, no caso, para inferir, a partir de matrizes de caracterÃsticas de vÃrias espÃcies, uma Ãrvore filogenÃtica que mais se aproxima da histÃria de sua evoluÃÃo. Uma estrutura de dados escolhida adequadamente aliada à manipulaÃÃo de dados em binÃrio em algumas rotinas facilitaram a simulaÃÃo e ilustraÃÃo dos testes realizados. InstÃncias com resultados conhecidos na literatura foram utilizadas para comprovar a performance do algoritmo. Esperamos com este trabalho despertar o interesse dos pesquisadores da Ãrea de ComputaÃÃo, consolidando, assim, o crescimento da BioinformÃtica.
Garrote, López Marina. "Algebraic and semi-algebraic phylogenetic reconstruction." Doctoral thesis, Universitat Politècnica de Catalunya, 2021. http://hdl.handle.net/10803/672316.
Full textLa filogenètica és l'estudi de la història evolutiva entre grups d'entitats biològiques (anomenades tàxons). Aquests processos evolutius estan modelitzats per arbres filogenètics els nodes dels quals representen diferents tàxons i les branques corresponen als processos evolutius entre ells. Les fulles normalment representen tàxons actuals i l'arrel és el seu avantpassat comú. Actualment, la reconstrucció filogenètica pretén estimar l'arbre filogenètic que millor explica les relacions evolutives de tàxons actuals utilitzant únicament informació del seu genoma organitzada en un alineament. En aquesta tesi ens centrem en la reconstrucció de la topologia dels arbres filogenètics, és a dir, reconstruir la forma de l'arbre tenint en compte els noms associats a les fulles. Amb aquesta finalitat, assumim que les seqüències d'ADN evolucionen segons un procés de Markov d'acord amb un model de substitució de nucleòtids. Aquests models de substitució assignem matrius de transició a les arestes d’un arbre i una distribució de nucleòtids a l'arrel. Donat un arbre i un model, es pot calcular la distribució de les possibles observacions de nucleòtids a les fulles en termes dels paràmetres del model. Aquesta distribució conjunta s’expressa en forma de vector, les entrades del qual es poden escriure com polinomis en funció dels paràmetres del model i satisfan certes relacions algebraiques. L'estudi d'aquestes relacions i de la geometria de les varietats algebraiques que defineixen (anomenades varietats filogenètiques) han servit per entendre millor el problema de la reconstrucció filogenètica. No obstant això, des d'una perspectiva biològica no estem interessats en tota la varietat, sinó només en la regió de punts que resulten de paràmetres estocàstics (l'anomenada regió estocàstica). La descripció d'aquestes regions condueix a restriccions semi-algebraiques que tenen un paper important ja que caracteritzen les distribucions amb significat biològic. Una de les principals motivacions d'aquesta tesi és la següent: Podria l'ús d'eines semi-algebraiques millorar les eines algebraiques ja existents per a la reconstrucció filogenètica? Per poder respondre, calculem la distància euclidiana entre punts de dades obtinguts a partir d’un alineament i varietats filogenètiques i les seves regions estocàstiques en escenaris d'especial interès en la filogenètica. En alguns casos, podem calcular aquestes distàncies de forma analítica i això ens permet demostrar que, fins i tot si un punt de dades fos proper a la varietat filogenètica d'un arbre donat, podria estar més a prop de la regió estocàstica d'un altre arbre. En particular, considerar la regió estocàstica sembla ser fonamental per fer front al problema de la reconstrucció filogenètica quan tractem amb del fenomen d'atracció de branques llargues. Tot i això, incorporar d'eines semi-algebraiques en els mètodes de reconstrucció filogenètica pot ser extremadament difícil i el procediment per fer-ho no és gens evident. En aquesta tesi, presentem dos mètodes de reconstrucció filogenètica que combinen condicions algebraiques i semi-algebraiques per al model general de Markov. El primer mètode que presentem és el SAQ, que rep el nom de Semi-Algebraic Quartet reconstruction method. A continuació, introduïm un mètode més versàtil, l'ASAQ (Algebraic and Semi-Algebraic Quartet reconstruction method), que combina el SAQ amb el mètode Erik+2 (basat en certes restriccions algebraiques). Tots dos són mètodes de reconstrucció filogenètica per a alineaments d'ADN per quatre tàxons i hem demostrat que tots dos són estadísticament consistents. Finalment, testem els mètodes proposats amb dades simulades i dades reals per comprovar el seu rendiment en diversos escenaris. Les nostres simulacions mostren que ambdós mètodes SAQ i ASAQ obtenen
Matemàtica aplicada
Habib, Farhat. "Genotype-phenotype correlation using phylogenetic trees." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1187297400.
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