Relevant bibliographies by topics / Evolutionary tree

Academic literature on the topic 'Evolutionary tree'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Evolutionary tree"

1

Kao, Ming-Yang. "Tree Contractions and Evolutionary Trees." SIAM Journal on Computing 27, no. 6 (December 1998): 1592–616. http://dx.doi.org/10.1137/s0097539795283504.

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Sainudiin, Raazesh, and Amandine Véber. "A Beta-splitting model for evolutionary trees." Royal Society Open Science 3, no. 5 (May 2016): 160016. http://dx.doi.org/10.1098/rsos.160016.

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In this article, we construct a generalization of the Blum–François Beta-splitting model for evolutionary trees, which was itself inspired by Aldous' Beta-splitting model on cladograms. The novelty of our approach allows for asymmetric shares of diversification rates (or diversification ‘potential’) between two sister species in an evolutionarily interpretable manner, as well as the addition of extinction to the model in a natural way. We describe the incremental evolutionary construction of a tree with n leaves by splitting or freezing extant lineages through the generating, organizing and deleting processes. We then give the probability of any (binary rooted) tree under this model with no extinction, at several resolutions: ranked planar trees giving asymmetric roles to the first and second offspring species of a given species and keeping track of the order of the speciation events occurring during the creation of the tree, unranked planar trees , ranked non-planar trees and finally ( unranked non-planar ) trees . We also describe a continuous-time equivalent of the generating, organizing and deleting processes where tree topology and branch lengths are jointly modelled and provide code in SageMath/Python for these algorithms.
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Iannone III, Basil V., Kevin M. Potter, Qinfeng Guo, Insu Jo, Christopher M. Oswalt, and Songlin Fei. "Environmental harshness drives spatial heterogeneity in biotic resistance." NeoBiota 40 (December 4, 2018): 87–105. http://dx.doi.org/10.3897/neobiota.40.28558.

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Ecological communities often exhibit greater resistance to biological invasions when these communities consist of species that are not closely related. The effective size of this resistance, however, varies geographically. Here we investigate the drivers of this heterogeneity in the context of known contributions of native trees to the resistance of forests in the eastern United States of America to plant invasions. Using 42,626 spatially referenced forest community observations, we quantified spatial heterogeneity in relationships between evolutionary relatedness amongst native trees and both invasive plant species richness and cover. We then modelled the variability amongst the 91 ecological sections of our study area in the slopes of these relationships in response to three factors known to affect invasion and evolutionary relationships –environmental harshness (as estimated via tree height), relative tree density and environmental variability. Invasive species richness and cover declined in plots having less evolutionarily related native trees. The degree to which they did, however, varied considerably amongst ecological sections. This variability was explained by an ecological section’s mean maximum tree height and, to a lesser degree, SD in maximum tree height (R2GLMM = 0.47 to 0.63). In general, less evolutionarily related native tree communities better resisted overall plant invasions in less harsh forests and in forests where the degree of harshness was more homogenous. These findings can guide future investigations aimed at identifying the mechanisms by which evolutionary relatedness of native species affects exotic species invasions and the environmental conditions under which these effects are most pronounced.
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Kim, Jaehee, Noah A. Rosenberg, and Julia A. Palacios. "Distance metrics for ranked evolutionary trees." Proceedings of the National Academy of Sciences 117, no. 46 (November 2, 2020): 28876–86. http://dx.doi.org/10.1073/pnas.1922851117.

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Genealogical tree modeling is essential for estimating evolutionary parameters in population genetics and phylogenetics. Recent mathematical results concerning ranked genealogies without leaf labels unlock opportunities in the analysis of evolutionary trees. In particular, comparisons between ranked genealogies facilitate the study of evolutionary processes of different organisms sampled at multiple time periods. We propose metrics on ranked tree shapes and ranked genealogies for lineages isochronously and heterochronously sampled. Our proposed tree metrics make it possible to conduct statistical analyses of ranked tree shapes and timed ranked tree shapes or ranked genealogies. Such analyses allow us to assess differences in tree distributions, quantify estimation uncertainty, and summarize tree distributions. We show the utility of our metrics via simulations and an application in infectious diseases.
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Brunello, Andrea, Enrico Marzano, Angelo Montanari, and Guido Sciavicco. "Decision Tree Pruning via Multi-Objective Evolutionary Computation." International Journal of Machine Learning and Computing 7, no. 6 (December 2017): 167–75. http://dx.doi.org/10.18178/ijmlc.2017.7.6.641.

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Coelho de Souza, Fernanda, Kyle G. Dexter, Oliver L. Phillips, Roel J. W. Brienen, Jerome Chave, David R. Galbraith, Gabriela Lopez Gonzalez, et al. "Evolutionary heritage influences Amazon tree ecology." Proceedings of the Royal Society B: Biological Sciences 283, no. 1844 (December 14, 2016): 20161587. http://dx.doi.org/10.1098/rspb.2016.1587.

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Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change.
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Andrews, Peter. "Climbing the evolutionary tree." Nature 435, no. 7038 (May 2005): 24–25. http://dx.doi.org/10.1038/435024a.

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Nikkhah, Vageehe, Seyed M. Babamir, and Seyed S. Arab. "Estimating Bifurcating Consensus Phylogenetic Trees Using Evolutionary Imperialist Competitive Algorithm." Current Bioinformatics 14, no. 8 (December 13, 2019): 728–39. http://dx.doi.org/10.2174/1574893614666190225145620.

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Background:One of the important goals of phylogenetic studies is the estimation of species-level phylogeny. A phylogenetic tree is an evolutionary classification of different species of creatures. There are several methods to generate such trees, where each method may produce a number of different trees for the species. By choosing the same proteins of all species, it is possible that the topology and arrangement of trees would be different.Objective:There are methods by which biologists summarize different phylogenetic trees to a tree, called consensus tree. A consensus method deals with the combination of gene trees to estimate a species tree. As the phylogenetic trees grow and their number is increased, estimating a consensus tree based on the species-level phylogenetic trees becomes a challenge.Methods:The current study aims at using the Imperialist Competitive Algorithm (ICA) to estimate bifurcating consensus trees. Evolutionary algorithms like ICA are suitable to resolve problems with the large space of candidate solutions.Results:The obtained consensus tree has more similarity to the native phylogenetic tree than related studies.Conclusion:The proposed method enjoys mechanisms and policies that enable us more than other evolutionary algorithms in tuning the proposed algorithm. Thanks to these policies and the mechanisms, the algorithm enjoyed efficiently in obtaining the optimum consensus tree. The algorithm increased the possibility of selecting an optimum solution by imposing some changes in its parameters.
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Hellström, Nils Petter. "Darwin and the Tree of Life: the roots of the evolutionary tree." Archives of Natural History 39, no. 2 (October 2012): 234–52. http://dx.doi.org/10.3366/anh.2012.0092.

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To speak of evolutionary trees and of the Tree of Life has become routine in evolution studies, despite recurrent objections. Because it is not immediately obvious why a tree is suited to represent evolutionary history – woodland trees do not have their buds in the present and their trunks in the past, for a start – the reason why trees make sense to us is historically and culturally, not scientifically, predicated. To account for the Tree of Life, simultaneously genealogical and cosmological, we must explore the particular context in which Darwin declared the natural order to be analogous to a pedigree, and in which he communicated this vision by recourse to a tree. The name he gave his tree reveals part of the story, as before Darwin's appropriation of it, the Tree of Life grew in Paradise at the heart of God's creation.
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DiNardo, Zach, Kiran Tomlinson, Anna Ritz, and Layla Oesper. "Distance measures for tumor evolutionary trees." Bioinformatics 36, no. 7 (November 21, 2019): 2090–97. http://dx.doi.org/10.1093/bioinformatics/btz869.

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Abstract Motivation There has been recent increased interest in using algorithmic methods to infer the evolutionary tree underlying the developmental history of a tumor. Quantitative measures that compare such trees are vital to a number of different applications including benchmarking tree inference methods and evaluating common inheritance patterns across patients. However, few appropriate distance measures exist, and those that do have low resolution for differentiating trees or do not fully account for the complex relationship between tree topology and the inheritance of the mutations labeling that topology. Results Here, we present two novel distance measures, Common Ancestor Set distance (CASet) and Distinctly Inherited Set Comparison distance (DISC), that are specifically designed to account for the subclonal mutation inheritance patterns characteristic of tumor evolutionary trees. We apply CASet and DISC to multiple simulated datasets and two breast cancer datasets and show that our distance measures allow for more nuanced and accurate delineation between tumor evolutionary trees than existing distance measures. Availability and implementation Implementations of CASet and DISC are freely available at: https://bitbucket.org/oesperlab/stereodist. Supplementary information Supplementary data are available at Bioinformatics online.
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Dissertations / Theses on the topic "Evolutionary tree"

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Barros, Rodrigo Coelho. "Evolutionary model tree induction." Pontifícia Universidade Católica do Rio Grande do Sul, 2009. http://hdl.handle.net/10923/1687.

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Made available in DSpace on 2013-08-07T18:43:36Z (GMT). No. of bitstreams: 1 000422461-Texto+Completo-0.pdf: 1656872 bytes, checksum: 4520cf1ef2435e86327deed3e89baed9 (MD5) Previous issue date: 2009
Model trees are a particular case of decision trees employed to solve regression problems, where the variable to be predicted is continuous. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is a NPComplete problem, traditional model tree induction algorithms make use of a greedy top-down divideand- conquer strategy, which may not converge to the global optimal solution. In this work, we propose the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to global optimal solutions. We test the predictive performance of this new approach using public UCI data sets, and we compare the results with traditional greedy regression/model trees induction algorithms. Results show that our approach presents a good tradeoff between predictive performance and model comprehensibility, which may be crucial in many data mining applications.
Árvores-modelo são um caso particular de árvores de decisão aplicadas na solução de problemas de regressão, onde a variável a ser predita é contínua. Possuem a vantagem de apresentar uma saída interpretável, auxiliando o usuário do sistema a ter mais confiança na predição e proporcionando a base para o usuário ter novos insights sobre os dados, confirmando ou rejeitando hipóteses previamente formadas. Além disso, árvores-modelo apresentam um nível aceitável de desempenho preditivo quando comparadas à maioria das técnicas utilizadas na solução de problemas de regressão. Uma vez que gerar a árvore-modelo ótima é um problema NP-Completo, algoritmos tradicionais de indução de árvores-modelo fazem uso da estratégia gulosa, top-down e de divisão e conquista, que pode não convergir à solução ótima-global. Neste trabalho é proposta a utilização do paradigma de algoritmos evolutivos como uma heurística alternativa para geração de árvores-modelo. Esta nova abordagem é testada por meio de bases de dados de regressão públicas da UCI, e os resultados são comparados àqueles gerados por algoritmos gulosos tradicionais de indução de árvores-modelo. Os resultados mostram que esta nova abordagem apresenta uma boa relação custo-benefício entre desempenho preditivo e geração de modelos de fácil interpretação, proporcionando um diferencial muitas vezes crucial em diversas aplicações de mineração de dados.
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Paulden, Timothy John. "Combinatorial spanning tree representations for evolutionary algorithms." Thesis, University of Exeter, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486767.

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The research presented in this thesis lies at the interface between two distinct' fields: combinatorial mathematics and evolutionary algorithm design. We examine a number of combinatorial spanning tree representations, and develop theoretical and empirical results to quantify the intrinsic properties of each representation, focusing on properties that encapsulate the representation's suitability for evolutionary search. In Part I of the thesis, we focus on a selectIon of Cayley codes - namely, the Priifer Code, the Blob Code, and the family of Dandelion-like codes (which includes the Dandelion Code, Happy Code, MHappy Code, and Theta Code). Each of these representations is bijective, and so the efficacy of evolutionary search primarily depends on the representation's locality. We develop a number of results which demonstrate that Dandelion-like codes possess highly desirable locality properties (including bounded locality), while those of the Blob Code and Priifer. Code are inferior. We also present linear-time decoding and'encoding algorithms for the various codes, many of which have not previously appeared in the evolutionary algorithms literature. In Part II, the Theta Code is adapted to give bijective spanning tree representations on graph topologies other than the complete graph. These extended representations retain the desirable properties of the Thet'a Code, including its high locality. We then formulate general principles for developing extended representations of this kind. Finally, in Part III, we study the Edge-Window-Decoder (EWD) representation. We find that the EWD representation has several desirable properties for evolutionary search (includi.ng bounded locality), but possesses an intrinsic bi~ towards path-like trees. We also present a number of theoretical advances, including the first method for generating EWD strings uniformly at random, and a new technique for characterising representational bias using the Wiener index.
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Saka, Esin. "A Comparative Study Of Tree Encodings For Evolutionary Computing." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/3/12606317/index.pdf.

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One of the most important factors on the success of evolutionary algorithms (EAs) about trees is the representation of them. The representation should exhibit efficiency, locality and heritability to enable effective evolutionary computing. Neville proposed three different methods for encoding labeled trees. The first one is similar with Prü
fer'
s encoding. In 2001, it is reported that, the use of Prü
fer numbers is a poor representation of spanning trees for evolutionary search, since it has low locality for random trees. In the thesis Neville'
s other two encodings, namely Neville branch numbers and Neville leaf numbers, are studied. For their performance in EA their properties and algorithms for encoding and decoding them are also examined. Optimal algorithms with time and space complexities of O(n) , where n is the number of nodes, for encoding and decoding Neville branch numbers are given. The localities of Neville'
s encodings are investigated. It is shown that, although the localities of Neville branch and leaf numbers are perfect for star type trees, they are low for random trees. Neville branch and Neville leaf numbers are compared with other codings in EAs and SA for four problems: '
onemax tree problem'
, '
degree-constrained minimum spanning tree problem'
, '
all spanning trees problem'
and '
all degree constrained spanning trees problem'
. It is shown that, neither Neville nor Prü
fer encodings are suitable for EAs. These encodings are suitable for only tree enumeration and degree computation. Algorithms which are timewise and spacewise optimal for '
all spanning trees problem'
(ASTP) for complete graphs, are given by using Neville branch encoding. Computed time and space complexities for solving ASTP of complete graphs are O(nn-2) and O(n) if trees are only enumerated and O(nn-1) and O(n) if all spanning trees are printed , respectively, where n is the number of nodes. Similarly, '
all degree constrained spanning trees problem'
of a complete graph is solvable in O(nn-1) time and O(n) space.
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vanCort, Tracy. "Computational Evolutionary Linguistics." Scholarship @ Claremont, 2001. https://scholarship.claremont.edu/hmc_theses/137.

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Languages and species both evolve by a process of repeated divergences, which can be described with the branching of a phylogenetic tree or phylogeny. Taking advantage of this fact, it is possible to study language change using computational tree building techniques developed for evolutionary biology. Mathematical approaches to the construction of phylogenies fall into two major categories: character based and distance based methods. Character based methods were used in prior work in the application of phylogenetic methods to the Indo-European family of languages by researchers at the University of Pennsylvania. Discussion of the limitations of character-based models leads to a similar presentation of distance based models. We present an adaptation of these methods to linguistic data, and the phylogenies generated by applying these methods to several modern Germanic languages and Spanish. We conclude that distance based for phylogenies are useful for historical linguistic reconstruction, and that it would be useful to extend existing tree drawing methods to better model the evolutionary effects of language contact.
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Lind, Brandon M. "NATURAL AND ANTHROPOGENIC DRIVERS OF TREE EVOLUTIONARY DYNAMICS." VCU Scholars Compass, 2018. https://scholarscompass.vcu.edu/etd/5359.

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Species of trees inhabit diverse and heterogeneous environments, and often play important ecological roles in such communities. As a result of their vast ecological breadth, trees have become adapted to various environmental pressures. In this dissertation I examine various environmental factors that drive evolutionary dynamics in threePinusspecies in California and Nevada, USA. In chapter two, I assess the role of management influence of thinning, fire, and their interaction on fine-scale gene flow within fire-suppressed populations of Pinus lambertiana, a historically dominant and ecologically important member of mixed-conifer forests of the Sierra Nevada, California. Here, I find evidence that treatment prescription differentially affects fine-scale genetic structure and effective gene flow in this species. In my third chapter, I describe the development of a dense linkage map for Pinus balfouriana which I use in chapter four to assess the quantitative trait locus (QTL) landscape of water-use efficiency across two isolated ranges of the species. I find evidence that precipitation-related variables structure the geographical range of P. balfouriana, that traits related to water-use efficiency are heritable and differentiated across populations, and associated QTLs underlying this phenotypic variation explain large proportions of total variation. In chapter five, I assess evidence for local adaptation to the eastern Sierra Nevada rain shadow within P. albicaulisacross fine spatial scales of the Lake Tahoe Basin, USA. Here, genetic variation of traits related to water availability were structured more so across populations than neutral variation, and loci identified by genome-wide association methods show elevated signals of local adaptation that track soil water availability. In chapter six, I review theory related to polygenic local adaptation and literature of genotype-phenotype associations in trees. I find that evidence suggests a polygenic basis for many traits important to conservation and industry, and I suggest paths forward to best describing such genetic bases in tree species. Overall, my results show that spatial and genetic structure of trees are often driven by their environment, and that ongoing selective pressures driven by environmental change will continue to be important in these systems.
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Wang, Qiang. "Maximum likelihood estimation of phylogenetic tree with evolutionary parameters." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1083177084.

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Thesis (Ph. D.)--Ohio State University, 2004.
Title from first page of PDF file. Document formatted into pages; contains xi, 167 p.; also includes graphics Includes bibliographical references (p. 157-167). Available online via OhioLINK's ETD Center
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Chen, Lei. "Construction of Evolutionary Tree Models for Oncogenesis of Endometrial Adenocarcinoma." Thesis, University of Skövde, School of Humanities and Informatics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-25.

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Endometrial adenocarcinoma (EAC) is the fourth leading cause of carcinoma in woman worldwide, but not much is known about genetic factors involved in this complex disease. During the EAC process, it is well known that losses and gains of chromosomal regions do not occur completely at random, but partly through some flow of causality. In this work, we used three different algorithms based on frequency of genomic alterations to construct 27 tree models of oncogenesis. So far, no study about applying pathway models to microsatellite marker data had been reported. Data from genome–wide scans with microsatellite markers were classified into 9 data sets, according to two biological approaches (solid tumor cell and corresponding tissue culture) and three different genetic backgrounds provided by intercrossing the susceptible rat BDII strain and two normal rat strains. Compared to previous study, similar conclusions were drawn from tree models that three main important regions (I, II and III) and two subordinate regions (IV and V) are likely to be involved in EAC development. Further information about these regions such as their likely order and relationships was produced by the tree models. A high consistency in tree models and the relationship among p19, Tp53 and Tp53 inducible

protein genes provided supportive evidence for the reliability of results.

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Mork, Amy Lovejoy. "EVOLUTIONARY MORPHOLOGY OF THE MASTICATORY APPARATUS IN TREE GOUGING MARMOSETS." Kent State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=kent1342796212.

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Thompson, Evan Benjamin. "The application of genetic and evolutionary algorithms to spanning tree problems." Thesis, University of Exeter, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288698.

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Kummer, Tyler A. "Assessing and Improving Student Understanding of Tree-Thinking." BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/6276.

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Evolution is the unifying theory of biology. The importance of understanding evolution by those who study the origins, diversification and diversity life cannot be overstated. Because of its importance, in addition to a scientific study of evolution, many researchers have spent time studying the acceptance and the teaching of evolution. Phylogenetic Systematics is the field of study developed to understand the evolutionary history of organisms, traits, and genes. Tree-thinking is the term by which we identify concepts related to the evolutionary history of organisms. It is vital that those who undertake a study of biology be able to understand and interpret what information these phylogenies are meant to convey. In this project, we evaluated the current impact a traditional study of biology has on the misconceptions students hold by assessing tree-thinking in freshman biology students to those nearing the end of their studies. We found that the impact of studying biology was varied with some misconceptions changing significantly while others persisted. Despite the importance of tree-thinking no appropriately developed concept inventory exists to measure student understanding of these important concepts. We developed a concept inventory capable of filling this important need and provide evidence to support its use among undergraduate students. Finally, we developed and modified activities as well as courses based on best practices to improve teaching and learning of tree-thinking and organismal diversity. We accomplished this by focusing on two key questions. First, how do we best introduce students to tree-thinking and second does tree-thinking as a course theme enhance student understanding of not only tree-thinking but also organismal diversity. We found important evidence suggesting that introducing students to tree-thinking via building evolutionary trees was less successful than introducing the concept via tree interpretation and may have in fact introduced or strengthened a misconception. We also found evidence that infusing tree-thinking into an organismal diversity course not only enhances student understanding of tree-thinking but also helps them better learn organismal diversity.
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Books on the topic "Evolutionary tree"

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Cheeseman, Peter. Evolutionary tree reconstruction. [Moffett Field, Calif.?]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1990.

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Lizards in an evolutionary tree: The ecology of adaptive radiation in anoles. Berkeley: University of California Press, 2009.

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The evolutionary relevance of vegetative long-shoot/short-shoot differentiation in gymnospermous tree species. Stuttgart: Schweizerbart Science, 2012.

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International Colloquium on the Ecology of Tree Squirrels (1994 Powdermill Biological Station). Ecology and evolutionary biology of tree squirrels: Proceedings of the International Colloquium on the Ecology of Tree Squirrels, Powdermill Biological Station, Carnegie Museum of Natural History, 22-28 April 1994. Martinsville, Va: Virginia Museum of Natural History, 1998.

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Hendy, M. D. Discrete fourier analysis for evolutionary trees. Palmerston North, N.Z: School of Mathematical and Information Sciences, Massey University, 1992.

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Groover, Andrew, and Quentin Cronk, eds. Comparative and Evolutionary Genomics of Angiosperm Trees. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-49329-9.

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Kretowski, Marek. Evolutionary Decision Trees in Large-Scale Data Mining. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21851-5.

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Cryan, Mary Elizabeth. Learning and approximation algorithms for problems motivated by evolutionary trees. [s.l.]: typescript, 1999.

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Gill, Jonna. The k-assignment polytope and the space of evolutionary trees. Linköping: Matematiska institutionen, Linköpings universitet, 2004.

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Schwikowski, Benno. A New algorithmic approach to the construction of multiple alignments and evolutionary trees. Sankt Augustin, Germany: GMD-Forschungszentrum Informationstechnik, 1998.

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Book chapters on the topic "Evolutionary tree"

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Kao, Ming-Yang. "Tree contractions and evolutionary trees." In Lecture Notes in Computer Science, 299–310. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-62592-5_81.

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Xu, Xiaohua, Zheng Liao, Ping He, Baichuan Fan, and Tianyu Jing. "Evolutionary Tree Spectral Clustering." In Advances in Intelligent Systems and Computing, 259–67. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0344-9_22.

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Auger, David. "Multiple Tree for Partially Observable Monte-Carlo Tree Search." In Applications of Evolutionary Computation, 53–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20525-5_6.

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Saitou, Naruya. "Tree and Network Building." In Introduction to Evolutionary Genomics, 367–415. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5304-7_16.

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Fineschi, Silvia, Francesco Loreto, Michael Staudt, and Josep Peñuelas. "Diversification of Volatile Isoprenoid Emissions from Trees: Evolutionary and Ecological Perspectives." In Tree Physiology, 1–20. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6606-8_1.

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Pal, Aruna. "Molecular Evolutionary Study: Phylogenetic Tree." In Springer Protocols Handbooks, 159–80. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1818-9_8.

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Silva, Sara, and Jonas Almeida. "Dynamic Maximum Tree Depth." In Genetic and Evolutionary Computation — GECCO 2003, 1776–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45110-2_69.

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Rothlauf, Franz. "Analysis of Tree Representations." In Representations for Genetic and Evolutionary Algorithms, 119–76. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-642-88094-0_6.

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Rothlauf, Franz. "Design of Tree Representations." In Representations for Genetic and Evolutionary Algorithms, 177–97. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-642-88094-0_7.

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Mäkelä, Annikki, and Harry T. Valentine. "Tree Structure Revisited: Eco-Evolutionary Models." In Models of Tree and Stand Dynamics, 161–98. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35761-0_7.

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Conference papers on the topic "Evolutionary tree"

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Antolík, Ján, and William H. Hsu. "Evolutionary tree genetic programming." In the 2005 conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1068009.1068312.

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Barros, Rodrigo C., Márcio P. Basgalupp, Duncan D. Ruiz, André C. P. L. F. de Carvalho, and Alex A. Freitas. "Evolutionary model tree induction." In the 2010 ACM Symposium. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1774088.1774327.

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Friedrich, Markus, Pierre-Alain Fayolle, Thomas Gabor, and Claudia Linnhoff-Popien. "Optimizing evolutionary CSG tree extraction." In GECCO '19: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3321707.3321771.

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Oliveira, Andrey, Danilo Sanches, and Bruna Osti. "Hybrid greedy genetic algorithm for the Euclidean Steiner tree problem." In Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/eniac.2019.9350.

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This paper presents a genetic algorithm for the Euclidean Steiner tree problem. This is an optimization problem whose objective is to obtain a minimum length tree to interconnect a set of fixed points, and for this purpose to be achieved, new auxiliary points, called Steiner points, can be added. The proposed heuristic uses a genetic algorithm to manipulate spanning trees, which are then transformed into Steiner trees by inserting and repositioning the Steiner points. Greedy genetic operators and evolutionary strategies are tested. Results of numerical experiments for benchmark library problem (OR-Library) are presented and discussed.This paper presents a genetic algorithm for the Euclidean Steiner tree problem. This is an optimization problem whose objective is to obtain a minimum length tree to interconnect a set of fixed points, and for this purpose to be achieved, new auxiliary points, called Steiner points, can be added. The proposed heuristic uses a genetic algorithm to manipulate spanning trees, which are then transformed into Steiner trees by inserting and repositioning the Steiner points. Greedy genetic operators and evolutionary strategies are tested. Results of numerical experiments for benchmark library problem (OR-Library) are presented and discussed.
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Jiang, Tao, Eugene L. Lawler, and Lusheng Wang. "Aligning sequences via an evolutionary tree." In the twenty-sixth annual ACM symposium. New York, New York, USA: ACM Press, 1994. http://dx.doi.org/10.1145/195058.195454.

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Murphy, Eoin, Michael O'Neill, Edgar Galvan-Lopez, and Anthony Brabazon. "Tree-adjunct grammatical evolution." In 2010 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2010. http://dx.doi.org/10.1109/cec.2010.5586497.

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"PARSING TREE ADJOINING GRAMMARS USING EVOLUTIONARY ALGORITHMS." In Special Session on Bio-Inspired Multi-Agent Systems. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0001811506320639.

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"Process Mining through Tree Automata." In International Conference on Evolutionary Computation Theory and Applications. SCITEPRESS - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004555201520159.

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Johansson, Ulf, Cecilia Sonstrod, and Tuve Lofstrom. "One tree to explain them all." In 2011 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2011. http://dx.doi.org/10.1109/cec.2011.5949785.

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McGuinness, Cameron. "Multiple pass Monte Carlo tree search." In 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2016. http://dx.doi.org/10.1109/cec.2016.7743974.

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Reports on the topic "Evolutionary tree"

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Qi, Fei, Zhaohui Xia, Gaoyang Tang, Hang Yang, Yu Song, Guangrui Qian, Xiong An, Chunhuan Lin, and Guangming Shi. A Graph-based Evolutionary Algorithm for Automated Machine Learning. Web of Open Science, December 2020. http://dx.doi.org/10.37686/ser.v1i2.77.

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As an emerging field, Automated Machine Learning (AutoML) aims to reduce or eliminate manual operations that require expertise in machine learning. In this paper, a graph-based architecture is employed to represent flexible combinations of ML models, which provides a large searching space compared to tree-based and stacking-based architectures. Based on this, an evolutionary algorithm is proposed to search for the best architecture, where the mutation and heredity operators are the key for architecture evolution. With Bayesian hyper-parameter optimization, the proposed approach can automate the workflow of machine learning. On the PMLB dataset, the proposed approach shows the state-of-the-art performance compared with TPOT, Autostacker, and auto-sklearn. Some of the optimized models are with complex structures which are difficult to obtain in manual design.
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