Scalable Steady State Analysis of Boolean Biological Regulatory Networks
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{"title"=>"Scalable steady state analysis of boolean biological regulatory networks", "type"=>"journal", "authors"=>[{"first_name"=>"Ferhat", "last_name"=>"Ay", "scopus_author_id"=>"26647990500"}, {"first_name"=>"Fei", "last_name"=>"Xu", "scopus_author_id"=>"55161782500"}, {"first_name"=>"Tamer", "last_name"=>"Kahveci", "scopus_author_id"=>"6602549479"}], "year"=>2009, "source"=>"PLoS ONE", "identifiers"=>{"isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pui"=>"359079912", "issn"=>"19326203", "pmid"=>"19956604", "doi"=>"10.1371/journal.pone.0007992", "sgr"=>"77949511910", "scopus"=>"2-s2.0-77949511910"}, "id"=>"c9266b5f-291d-33e8-a999-5c0a1d368eef", "abstract"=>"BACKGROUND: Computing the long term behavior of regulatory and signaling networks is critical in understanding how biological functions take place in organisms. Steady states of these networks determine the activity levels of individual entities in the long run. Identifying all the steady states of these networks is difficult due to the state space explosion problem.\n\nMETHODOLOGY: In this paper, we propose a method for identifying all the steady states of Boolean regulatory and signaling networks accurately and efficiently. We build a mathematical model that allows pruning a large portion of the state space quickly without causing any false dismissals. For the remaining state space, which is typically very small compared to the whole state space, we develop a randomized traversal method that extracts the steady states. We estimate the number of steady states, and the expected behavior of individual genes and gene pairs in steady states in an online fashion. Also, we formulate a stopping criterion that terminates the traversal as soon as user supplied percentage of the results are returned with high confidence.\n\nCONCLUSIONS: This method identifies the observed steady states of boolean biological networks computationally. Our algorithm successfully reported the G1 phases of both budding and fission yeast cell cycles. Besides, the experiments suggest that this method is useful in identifying co-expressed genes as well. By analyzing the steady state profile of Hedgehog network, we were able to find the highly co-expressed gene pair GL1-SMO together with other such pairs.\n\nAVAILABILITY: Source code of this work is available at http://bioinformatics.cise.ufl.edu/palSteady.html twocolumnfalse].", "link"=>"http://www.mendeley.com/research/scalable-steady-state-analysis-boolean-biological-regulatory-networks", "reader_count"=>60, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>5, "Researcher"=>18, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>3, "Student > Master"=>4, "Other"=>2, "Student > Bachelor"=>4, "Lecturer > Senior Lecturer"=>1, "Professor"=>6}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>5, "Researcher"=>18, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>3, "Student > Master"=>4, "Other"=>2, "Student > Bachelor"=>4, "Lecturer > Senior Lecturer"=>1, "Professor"=>6}, "reader_count_by_subject_area"=>{"Engineering"=>4, "Environmental Science"=>3, "Biochemistry, Genetics and Molecular Biology"=>4, "Mathematics"=>4, "Agricultural and Biological Sciences"=>29, "Medicine and Dentistry"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>2, "Psychology"=>1, "Computer Science"=>10, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Psychology"=>{"Psychology"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>29}, "Computer Science"=>{"Computer Science"=>10}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}, "Mathematics"=>{"Mathematics"=>4}, "Environmental Science"=>{"Environmental Science"=>3}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "reader_count_by_country"=>{"United States"=>1, "China"=>1, "Brazil"=>1, "Italy"=>1, "France"=>1, "Portugal"=>2, "Germany"=>4, "India"=>1}, "group_count"=>2}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/873302"], "description"=>"<p>The binary values correspond to activation levels of these genes. (a) The three states on the left are transient and of Type 1. The state with self loop is steady and Type 0. (b) The four states in simple loop are cyclic steady states and they are of Type 1. (c) The leftmost state is transient and Type 1. Even though only is of Type 2 (others are Type 1), the remaining five states create a complex loop, and thus they are transient.</p>", "links"=>[], "tags"=>["hypothetical"], "article_id"=>543763, "categories"=>["Infectious Diseases", "Medicine", "Molecular Biology"], "users"=>["Ferhat Ay", "Fei Xu", "Tamer Kahveci"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0007992.g001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_States_of_a_hypothetical_network_with_three_genes_/543763", "title"=>"States of a hypothetical network with three genes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 03:37:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/873930"], "description"=>"1<p>We used a cut-off time of 24-hours and “-” indicates that the method could not find all steady states within this time. denotes seconds and denotes minutes.</p>2<p>Running time of our algorithm when 90% of the steady states are found with 90% confidence.</p>3<p>Running time of our algorithm when 80% of the steady states are found with 80% confidence.</p>", "links"=>[], "tags"=>["algorithm", "genysis"], "article_id"=>544388, "categories"=>["Infectious Diseases", "Medicine", "Molecular Biology"], "users"=>["Ferhat Ay", "Fei Xu", "Tamer Kahveci"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0007992.t001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_comparison_of_our_algorithm_with_an_existing_method_Genysis_18_19_on_real_and_random_networks_/544388", "title"=>"The comparison of our algorithm with an existing method, Genysis [18], [19],on real and random networks.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 03:40:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/873675"], "description"=>"<p>These genes are a selected subset of the genes of <i>p53 network</i> of <i>Homo Sapiens </i><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0007992#pone.0007992-Ogata1\" target=\"_blank\">[46]</a>. Y-axis shows for each gene the fraction of steady states that the gene is in active state.</p>", "links"=>[], "tags"=>["estimators", "profiles"], "article_id"=>544136, "categories"=>["Infectious Diseases", "Medicine", "Molecular Biology"], "users"=>["Ferhat Ay", "Fei Xu", "Tamer Kahveci"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0007992.g004", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Convergence_of_the_estimators_for_the_steady_state_profiles_of_the_genes_/544136", "title"=>"Convergence of the estimators for the steady state profiles of the genes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 03:39:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/873576"], "description"=>"<p>Red arrows with pointed heads represent activation, black arrows with bar heads represent inhibition and yellow arrows indicate self-degradation.</p>", "links"=>[], "tags"=>["fission"], "article_id"=>544043, "categories"=>["Infectious Diseases", "Medicine", "Molecular Biology"], "users"=>["Ferhat Ay", "Fei Xu", "Tamer Kahveci"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0007992.g003", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Regulatory_network_of_the_cell_cycle_of_fission_yeast_/544043", "title"=>"Regulatory network of the cell cycle of fission yeast.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 03:38:33"}
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Relative Metric

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