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{"title"=>"An end to endless forms: Epistasis, phenotype distribution bias, and nonuniform evolution", "type"=>"journal", "authors"=>[{"first_name"=>"Elhanan", "last_name"=>"Borenstein", "scopus_author_id"=>"8985741700"}, {"first_name"=>"David C.", "last_name"=>"Krakauer", "scopus_author_id"=>"7007174357"}], "year"=>2008, "source"=>"PLoS Computational Biology", "identifiers"=>{"pmid"=>"18949026", "sgr"=>"55449093810", "doi"=>"10.1371/journal.pcbi.1000202", "scopus"=>"2-s2.0-55449093810", "pui"=>"352619806", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)", "issn"=>"1553734X"}, "id"=>"ffcbe367-1b6f-353a-859c-9587581baf41", "abstract"=>"Studies of the evolution of development characterize the way in which gene regulatory dynamics during ontogeny constructs and channels phenotypic variation. These studies have identified a number of evolutionary regularities: (1) phenotypes occupy only a small subspace of possible phenotypes, (2) the influence of mutation is not uniform and is often canalized, and (3) a great deal of morphological variation evolved early in the history of multicellular life. An important implication of these studies is that diversity is largely the outcome of the evolution of gene regulation rather than the emergence of new, structural genes. Using a simple model that considers a generic property of developmental maps-the interaction between multiple genetic elements and the nonlinearity of gene interaction in shaping phenotypic traits-we are able to recover many of these empirical regularities. We show that visible phenotypes represent only a small fraction of possibilities. Epistasis ensures that phenotypes are highly clustered in morphospace and that the most frequent phenotypes are the most similar. We perform phylogenetic analyses on an evolving, developmental model and find that species become more alike through time, whereas higher-level grades have a tendency to diverge. Ancestral phenotypes, produced by early developmental programs with a low level of gene interaction, are found to span a significantly greater volume of the total phenotypic space than derived taxa. We suggest that early and late evolution have a different character that we classify into micro- and macroevolutionary configurations. These findings complement the view of development as a key component in the production of endless forms and highlight the crucial role of development in constraining biotic diversity and evolutionary trajectories.", "link"=>"http://www.mendeley.com/research/end-endless-forms-epistasis-phenotype-distribution-bias-nonuniform-evolution", "reader_count"=>173, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>11, "Librarian"=>2, "Student > Doctoral Student"=>5, "Researcher"=>60, "Student > Ph. D. Student"=>48, "Student > Postgraduate"=>4, "Student > Master"=>13, "Other"=>9, "Student > Bachelor"=>7, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>9}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>11, "Librarian"=>2, "Student > Doctoral Student"=>5, "Researcher"=>60, "Student > Ph. D. Student"=>48, "Student > Postgraduate"=>4, "Student > Master"=>13, "Other"=>9, "Student > Bachelor"=>7, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>9}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Agricultural and Biological Sciences"=>113, "Arts and Humanities"=>1, "Philosophy"=>2, "Computer Science"=>17, "Earth and Planetary Sciences"=>9, "Engineering"=>1, "Environmental Science"=>3, "Biochemistry, Genetics and Molecular Biology"=>8, "Mathematics"=>2, "Medicine and Dentistry"=>3, "Neuroscience"=>1, "Sports and Recreations"=>1, "Physics and Astronomy"=>6, "Social Sciences"=>1, "Immunology and Microbiology"=>2, "Linguistics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Social Sciences"=>{"Social Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>6}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>3}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>1}, "Neuroscience"=>{"Neuroscience"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>9}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>113}, "Computer Science"=>{"Computer Science"=>17}, "Linguistics"=>{"Linguistics"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>8}, "Philosophy"=>{"Philosophy"=>2}}, "reader_count_by_country"=>{"Colombia"=>1, "Argentina"=>1, "United States"=>8, "United Kingdom"=>4, "Thailand"=>1, "Switzerland"=>1, "Portugal"=>1, "Spain"=>2, "New Zealand"=>2, "Netherlands"=>1, "Austria"=>1, "Turkey"=>1, "Belgium"=>1, "Norway"=>2, "Luxembourg"=>1, "Poland"=>3, "Brazil"=>6, "Denmark"=>1, "Mexico"=>1, "Israel"=>1, "Germany"=>5}, "group_count"=>3}

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• http://doi.org/10.1371/journal.pone.0070444
• http://doi.org/10.1007/s10682-009-9346-9
• http://doi.org/10.2527/jas.2015-9917
• http://doi.org/10.1111/ede.12313
• http://doi.org/10.1038/nrg2493
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• http://doi.org/10.1111/ede.12319
• http://doi.org/10.1016/j.biosystems.2010.08.003
• http://doi.org/10.1371/journal.pcbi.1004055
• http://doi.org/10.1534/genetics.118.300995
• http://doi.org/10.1113/jphysiol.2014.272385
• http://doi.org/10.1371/journal.pone.0086635
• http://doi.org/10.1371/journal.pone.0034285
• http://doi.org/10.1002/jez.b.22468
• http://doi.org/10.1002/jez.b.22597
• http://doi.org/10.1016/j.shpsc.2013.09.008
• http://doi.org/10.1098/rstb.2011.0214
• http://doi.org/10.1007/s13752-015-0203-5
• http://doi.org/10.1093/molbev/msw013
• http://doi.org/10.1098/rsif.2014.0249
• http://doi.org/10.1098/rsif.2017.0275
• http://doi.org/10.1086/681217
• http://doi.org/10.3389/fgene.2014.00322
• http://doi.org/10.1016/j.tcs.2011.07.004
• http://doi.org/10.1371/journal.pone.0119972
• http://doi.org/10.1098/rsfs.2015.0053
• http://doi.org/10.1016/j.physa.2011.08.050
• http://doi.org/10.1186/1742-4682-9-56
• http://doi.org/10.1016/j.pbiomolbio.2018.01.001

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• {"id"=>"840211207156060160", "text"=>"Complexity theory can explain software complexity perils: https://t.co/hRkSMqsJRc @sippy @adam_messinger @aspenjfm\nhttps://t.co/kPgcibWXr9", "created_at"=>"2017-03-10T14:42:16Z", "user"=>"C4COMPUTATION", "user_name"=>"Jessica Flack", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000310715451/a94f0748b3f09659babadb17a1aa2e8f_normal.jpeg"}
• {"id"=>"840212829923868673", "text"=>"Complexity theory can explain software complexity perils--see related work in: https://t.co/hRkSMqsJRc\n@sippy @adam_messinger @aspenjfm", "created_at"=>"2017-03-10T14:48:43Z", "user"=>"C4COMPUTATION", "user_name"=>"Jessica Flack", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000310715451/a94f0748b3f09659babadb17a1aa2e8f_normal.jpeg"}
• {"id"=>"840213610261577729", "text"=>"RT @C4COMPUTATION: Complexity theory can explain software complexity perils--see related work in: https://t.co/hRkSMqsJRc\n@sippy @adam_mess…", "created_at"=>"2017-03-10T14:51:49Z", "user"=>"JoeRaimondo", "user_name"=>"Joe Raimondo", "user_profile_image"=>"http://pbs.twimg.com/profile_images/838895764717854721/eFYGxyVq_normal.jpg"}
• {"id"=>"840248854712836096", "text"=>"RT @C4COMPUTATION: Complexity theory can explain software complexity perils--see related work in: https://t.co/hRkSMqsJRc\n@sippy @adam_mess…", "created_at"=>"2017-03-10T17:11:52Z", "user"=>"aspenjfm", "user_name"=>"jerry murdock", "user_profile_image"=>"http://pbs.twimg.com/profile_images/564159703328882688/h2nrb6mq_normal.jpeg"}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/917824"], "description"=>"<p>(A) A loglog plot of the distribution of degeneracy levels among visible\n phenotypes. Each point denotes the expected number of distinct\n phenotypes with a certain degeneracy level for a given developmental\n plan and is an average over 10,000 different plans. Note that the point\n associated with degeneracy level 0 (i.e., hidden phenotypes) is not\n included. These developmental plans frequently give rise to phenotypes\n with degeneracy levels higher than 10³, and in rare cases,\n higher than 10^3.5. Given that the total number of genotypes\n is 2¹⁴ a single phenotype can be produced by\n 6%–20% genotypes. (B) A contour plot of\n the gain function induced by a given developmental plan (all\n developmental plans produce qualitatively similar results). The gain\n function,\n <i>gain</i>(<i>d_g</i>,<i>d_p</i>),\n denotes the probability that the Hamming distance between two phenotypes\n is <i>d_p</i>, given that the distance between the\n two genotypes that produced them is <i>d_g</i>. (C)\n The distribution of pairwise phenotypic Hamming distances among randomly\n selected phenotypes (not produced by a developmental plan), distinct\n visible phenotypes (considering every visible phenotype only once,\n regardless of frequency), and visible phenotypes including all\n occurrences of each phenotype. The pairwise Hamming distances between\n randomly selected phenotypes follows a binomial distribution, with mean\n distance 7 (for phenotypes of length 14). Distinct visible phenotypes\n are closer to one another, with the mean distance 5.976. When weighting\n by the frequency of the visible phenotypes, the distance is reduced,\n with a mean distance 4.607.</p>", "links"=>[], "tags"=>["phenotypic"], "article_id"=>588286, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g003", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Localization_of_the_visible_phenotypic_subspace_/588286", "title"=>"Localization of the visible phenotypic subspace.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:18:06"}
• {"files"=>["https://ndownloader.figshare.com/files/917616"], "description"=>"<p>The <i>r</i> transcription factors bind to the promoters of\n <i>k</i> structural genes with affinities given by\n <i>D_ij</i>. If the net activation to a\n promoter exceeds a threshold value (illustrated as a step function) the\n gene is expressed. The phenotype is described by the distribution of\n gene expression. This regulatory architecture corresponds to the single\n layered plan - See also our analysis of a generalized, multilayered,\n model.</p>", "links"=>[], "tags"=>["computational biology/evolutionary modeling", "computational biology/transcriptional regulation", "evolutionary biology/developmental evolution"], "article_id"=>588072, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_An_illustration_of_the_developmental_model_/588072", "title"=>"An illustration of the developmental model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:14:32"}
• {"files"=>["https://ndownloader.figshare.com/files/918371"], "description"=>"<p>Each curve represents the average of 100 different plans. Due to\n computational constraints, the regulatory dimension, <i>r</i>,\n and the phenotypic dimension, <i>k</i>, are both set to\n 10.</p>", "links"=>[], "tags"=>["pairwise", "phenotypic", "hamming", "distances", "among", "randomly", "phenotypes", "produced", "and", "occurrences", "plans", "varying", "levels"], "article_id"=>588821, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g008", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_distribution_of_pairwise_phenotypic_Hamming_distances_among____randomly_selected_phenotypes_not_produced_by_a_developmental_plan_and____visible_phenotypes_including_all_occurrences_of_each_phenotype____produced_by_developmental_plans_with_varying_lev/588821", "title"=>"The distribution of pairwise phenotypic Hamming distances among\n randomly selected phenotypes (not produced by a developmental plan) and\n visible phenotypes (including all occurrences of each phenotype)\n produced by developmental plans with varying levels of density,\n <i>c</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:27:01"}
• {"files"=>["https://ndownloader.figshare.com/files/917679"], "description"=>"<p>The phenotypic dimension is set to\n <i>k</i> = 18. All curves\n represent the average of 1,000 different developmental matrices. (A) The\n number of potential phenotypes (2<i>^r</i>) and the number of distinct visible phenotypes as a function\n of the regulatory dimension. (B) The percentage of visible phenotypes\n out of the potential phenotypes, corresponding to a sigmoidal function.\n (C) The marginal contribution of each genetic element to the increase in\n the number of visible phenotypes. Formally, if\n <i>V</i>(<i>r</i>) denotes the number of visible\n phenotypes as a function of <i>r</i>, then the marginal\n contribution is defined as\n <i>V</i>(<i>r</i>)/<i>V</i>(<i>r</i>−1),\n and is evidently linear (with slope of −0.044; least squares\n regression).</p>", "links"=>[], "tags"=>["phenotypes", "regulatory"], "article_id"=>588151, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Potential_and_visible_phenotypes_as_a_function_of_the_regulatory____dimension_r_/588151", "title"=>"Potential and visible phenotypes as a function of the regulatory\n dimension, <i>r</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:15:51"}
• {"files"=>["https://ndownloader.figshare.com/files/453567", "https://ndownloader.figshare.com/files/453627", "https://ndownloader.figshare.com/files/453676", "https://ndownloader.figshare.com/files/453719"], "description"=>"<div><p>Studies of the evolution of development characterize the way in which gene regulatory dynamics during ontogeny constructs and channels phenotypic variation. These studies have identified a number of evolutionary regularities: (1) phenotypes occupy only a small subspace of possible phenotypes, (2) the influence of mutation is not uniform and is often canalized, and (3) a great deal of morphological variation evolved early in the history of multicellular life. An important implication of these studies is that diversity is largely the outcome of the evolution of gene regulation rather than the emergence of new, structural genes. Using a simple model that considers a generic property of developmental maps—the interaction between multiple genetic elements and the nonlinearity of gene interaction in shaping phenotypic traits—we are able to recover many of these empirical regularities. We show that visible phenotypes represent only a small fraction of possibilities. Epistasis ensures that phenotypes are highly clustered in morphospace and that the most frequent phenotypes are the most similar. We perform phylogenetic analyses on an evolving, developmental model and find that species become more alike through time, whereas higher-level grades have a tendency to diverge. Ancestral phenotypes, produced by early developmental programs with a low level of gene interaction, are found to span a significantly greater volume of the total phenotypic space than derived taxa. We suggest that early and late evolution have a different character that we classify into micro- and macroevolutionary configurations. These findings complement the view of development as a key component in the production of endless forms and highlight the crucial role of development in constraining biotic diversity and evolutionary trajectories.</p> </div>", "links"=>[], "tags"=>["phenotype", "and", "nonuniform"], "article_id"=>149341, "categories"=>["Cancer", "Evolutionary Biology", "Biological Sciences"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000202.s001", "https://dx.doi.org/10.1371/journal.pcbi.1000202.s002", "https://dx.doi.org/10.1371/journal.pcbi.1000202.s003", "https://dx.doi.org/10.1371/journal.pcbi.1000202.s004"], "stats"=>{"downloads"=>16, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/An_End_to_Endless_Forms_Epistasis_Phenotype_Distribution_Bias_and___Nonuniform_Evolution/149341", "title"=>"An End to Endless Forms: Epistasis, Phenotype Distribution Bias, and\n Nonuniform Evolution", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2008-10-24 02:35:41"}
• {"files"=>["https://ndownloader.figshare.com/files/918106"], "description"=>"<p>(A) The percentage of visible phenotypes out of the potential phenotypes\n as a function of the number of regulatory layers. The regulatory\n dimension, <i>r</i>, and the phenotypic dimension,\n <i>k</i>, are both set to 14. For a single regulatory layer,\n the visible phenotypes already constitute only 8.2% of the\n 2¹⁴ potential phenotypes, in accordance with our results\n for the basic model. Introducing additional recurrent layers\n dramatically decreases the number of visible phenotypes (note the\n logarithmic scale), reaching 0.06% (approximately 10\n phenotypes) with 50 layers. Furthermore, if each regulatory layer\n incorporates a different developmental plan, the reduction in the number\n of visible phenotypes as a function of the number of layers is even more\n extreme. (B) The distribution of the number of unique phenotypes that\n remain visible when the systems reaches steady state.</p>", "links"=>[], "tags"=>["multilayered"], "article_id"=>588572, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g006", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_effect_of_multilayered_developmental_plans_/588572", "title"=>"The effect of multilayered developmental plans.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:22:52"}
• {"files"=>["https://ndownloader.figshare.com/files/918497"], "description"=>"<p>Similar colors denote shared regulatory wiring.</p>", "links"=>[], "tags"=>["evolutionary"], "article_id"=>588970, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g009", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulating_the_evolutionary_process_forward_through_time_/588970", "title"=>"Simulating the evolutionary process forward through time.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:29:30"}
• {"files"=>["https://ndownloader.figshare.com/files/918196"], "description"=>"<p>(A) The percentage of visible phenotypes out of the potential phenotypes\n as a function of the developmental plan density, <i>c</i>. The\n regulatory dimension, <i>r</i>, and the phenotypic dimension,\n <i>k</i>, are both set to 14. Each point represent the\n average of 1,000 different plans. For a given density value,\n <i>c</i>, each entry in the matrix is attributed with a\n nonzero value (either +1 or −1) with probability\n <i>c</i>. (B) The number of variable traits,\n <i>ν</i> (i.e., phenotypic elements that are\n active in at least one phenotype) as a function of the developmental\n plan density, <i>c</i>. The experimental settings are\n identical to those described in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000202#pcbi-1000202-g007\" target=\"_blank\">Figure 7A</a>. (C) The percentage of\n visible phenotypes out of the 2<i>^ν</i> achievable phenotypes as a function of the developmental plan\n density, <i>c</i>.</p>", "links"=>[], "tags"=>["phenotype"], "article_id"=>588663, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g007", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_effect_of_developmental_plan_density_on_phenotype_distribution_/588663", "title"=>"The effect of developmental plan density on phenotype distribution.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:24:23"}
• {"files"=>["https://ndownloader.figshare.com/files/918026"], "description"=>"<p>The total number of elements in ,\n <i>r</i> = 18.</p>", "links"=>[], "tags"=>["of", "elements"], "article_id"=>588485, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g005", "stats"=>{"downloads"=>3, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pr_p_j__1____as_a_function_of_s_j_the_number_of____1_elements_in_/588485", "title"=>"<i>Pr</i>(<i>p_j</i> = 1),\n as a function of <i>s_j</i>, the number of\n +1 elements in .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:21:25"}
• {"files"=>["https://ndownloader.figshare.com/files/918591"], "description"=>"<p>(A) The average pairwise Hamming distance between visible phenotypes\n within and between phyla. Each phylum corresponds to a developmental\n plan, and the set of the most frequent visible phenotypes produced by\n this plan represent species. The ancestral phyla is employing a\n developmental plan with\n <i>r</i> = 4 and\n <i>k</i> = 14. In each\n branching event, each of the two descendant phyla add an additional\n regulatory element with random connectivities preserving the ancestral\n component of the developmental plan (<a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000202#pcbi-1000202-g009\" target=\"_blank\">Figure 9</a>). This branching process\n continues until we get the 1024 most recent phyla, each employing a\n developmental plan with\n <i>r</i> = 14 and\n <i>k</i> = 14. (B) A\n phylogenetic tree including phenotypes from derived and ancestral phyla.\n The tree is reconstructed by computing the pairwise Hamming distance\n matrix between all phenotypes and applying a neighbor-joining\n algorithms. Rectangular, triangular, and circular nodes represent\n phenotypes from the ancestral phylum, intermediate phyla, and derived\n phyla respectively. Phyla within each phylogenetic level are illustrated\n with different colors. The small tree on the bottom left corner\n illustrates the phylogenetic tree of different developmental plans\n (using the same color coding as that used in the main tree). Phenotypes\n (or ‘species’) of different phyla differ only in the\n developmental plan and not in genotype, but the resulting tree\n successfully clusters the members of each phyla. Furthermore, the\n members of intermediate phyla are correctly clustered, spanning the same\n phylogenetic space as their descendants. Members of the ancestral phylum\n (represented by black rectangles) span similar regions to those covered\n by all derived phenotypes. (C) Representation of ancestral,\n intermediate, and derived phenotypes according to the first two\n principle components. Ellipses illustrate the mean and variance for each\n phylum. The color coding is identical to that used in the phylogenetic\n tree.</p>", "links"=>[], "tags"=>["ontogenetic-phylogenetic"], "article_id"=>589060, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g010", "stats"=>{"downloads"=>3, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Phenotype_distribution_in_an_ontogenetic_phylogenetic_model_/589060", "title"=>"Phenotype distribution in an ontogenetic-phylogenetic model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:31:00"}
• {"files"=>["https://ndownloader.figshare.com/files/917956"], "description"=>"<p>(A) The average Hamming distance among visible phenotypes as a function\n of their frequency (dots). Visible phenotypes are ranked according to\n their frequency level. For each rank, we calculate the average Hamming\n distance between all visible phenotypes with this or higher rank. The\n most abundant phenotypes are very similar. This similarity decreases as\n less frequent phenotypes are included in the analysis. We also calculate\n which fraction of all visible phenotypes are included in these\n phenotypes (solid line). The inset shows a zoom of the same plot,\n focusing only on the top 5% most frequent phenotypes. The\n phenotypes that are included in this small fraction of the distinct\n visible phenotypes, are, on average, only 4 bits different, and still\n cover 50% of the phenotypes. (B) The one mutant neighbor\n network of the visible phenotypes. The size of the node is proportional\n to the logarithm of its frequency. In this plot,\n <i>r</i> = <i>k</i> = 12.</p>", "links"=>[], "tags"=>["phenotypes", "the", "patchiness", "phenotypic"], "article_id"=>588415, "categories"=>["Infectious Diseases", "Evolutionary Biology", "Computational Biology"], "users"=>["Elhanan Borenstein", "David C. Krakauer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000202.g004", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_average_distance_between_the_the_most_frequent_phenotypes_and_the____patchiness_of_the_visible_phenotypic_subspace_/588415", "title"=>"The average distance between the the most frequent phenotypes and the\n patchiness of the visible phenotypic subspace.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-10-24 02:20:15"}

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Relative Metric

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F1000Prime