Biological Time Series Analysis Using a Context Free Language: Applicability to Pulsatile Hormone Data
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{"title"=>"Biological time series analysis using a context free language: Applicability to pulsatile hormone data", "type"=>"journal", "authors"=>[{"first_name"=>"Dennis A.", "last_name"=>"Dean", "scopus_author_id"=>"8862575600"}, {"first_name"=>"Gail K.", "last_name"=>"Adler", "scopus_author_id"=>"7201723445"}, {"first_name"=>"David P.", "last_name"=>"Nguyen", "scopus_author_id"=>"57198994886"}, {"first_name"=>"Elizabeth B.", "last_name"=>"Klerman", "scopus_author_id"=>"6701750101"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84906958497", "doi"=>"10.1371/journal.pone.0104087", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"25184442", "issn"=>"19326203", "scopus"=>"2-s2.0-84906958497", "pui"=>"600017409"}, "id"=>"9aacdfe8-d2e9-3fcd-bde5-32c23d7e8481", "abstract"=>"We present a novel approach for analyzing biological time-series data using a context-free language (CFL) representation that allows the extraction and quantification of important features from the time-series. This representation results in Hierarchically AdaPtive (HAP) analysis, a suite of multiple complementary techniques that enable rapid analysis of data and does not require the user to set parameters. HAP analysis generates hierarchically organized parameter distributions that allow multi-scale components of the time-series to be quantified and includes a data analysis pipeline that applies recursive analyses to generate hierarchically organized results that extend traditional outcome measures such as pharmacokinetics and inter-pulse interval. Pulsicons, a novel text-based time-series representation also derived from the CFL approach, are introduced as an objective qualitative comparison nomenclature. We apply HAP to the analysis of 24 hours of frequently sampled pulsatile cortisol hormone data, which has known analysis challenges, from 14 healthy women. HAP analysis generated results in seconds and produced dozens of figures for each participant. The results quantify the observed qualitative features of cortisol data as a series of pulse clusters, each consisting of one or more embedded pulses, and identify two ultradian phenotypes in this dataset. HAP analysis is designed to be robust to individual differences and to missing data and may be applied to other pulsatile hormones. Future work can extend HAP analysis to other time-series data types, including oscillatory and other periodic physiological signals.", "link"=>"http://www.mendeley.com/research/biological-time-series-analysis-using-context-free-language-applicability-pulsatile-hormone-data", "reader_count"=>22, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Librarian"=>2, "Researcher"=>4, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>3, "Other"=>2, "Student > Bachelor"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Librarian"=>2, "Researcher"=>4, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>3, "Other"=>2, "Student > Bachelor"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Nursing and Health Professions"=>2, "Medicine and Dentistry"=>3, "Agricultural and Biological Sciences"=>3, "Sports and Recreations"=>1, "Chemistry"=>1, "Social Sciences"=>2, "Computer Science"=>4, "Decision Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Chemistry"=>{"Chemistry"=>1}, "Social Sciences"=>{"Social Sciences"=>2}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>3}, "Computer Science"=>{"Computer Science"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>3}}, "reader_count_by_country"=>{"Canada"=>1, "Poland"=>1, "Italy"=>1, "Slovenia"=>1}, "group_count"=>4}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1660554"], "description"=>"<p>*Level 4 is the terminal iteration for participant ID6. Since there are only two points at the terminal iteration, only the median (defined for two points as the average) is shown.</p><p>Hierarchical Features Summary by Iteration Level for a single participant (ID6).</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160350, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.t004", "stats"=>{"downloads"=>6, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hierarchical_Features_Summary_by_Iteration_Level_for_a_single_participant_ID6_/1160350", "title"=>"Hierarchical Features Summary by Iteration Level for a single participant (ID6).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660551"], "description"=>"<p>Bolded entries were not identified by HAP Analysis.</p><p>Amplitude (A) and secretion times (T) for simulated dataset*.</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160347, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.t001", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Amplitude_A_and_secretion_times_T_for_simulated_dataset_/1160347", "title"=>"Amplitude (A) and secretion times (T) for simulated dataset*.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660550"], "description"=>"<p>(A–F) Simulated data generated from the data sets shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0104087#pone-0104087-g004\" target=\"_blank\">Fig. 4</a> panels A–F. Simulated data are identified with blue markers. Peaks identified during the nadir selection algorithm are in red. Nadirs identified at a given recursive step are joined with a line, where line color represents a different recursive step.</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160346, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.g007", "stats"=>{"downloads"=>2, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_HAP_analysis_of_simulated_cortisol_test_set_/1160346", "title"=>"HAP analysis of simulated cortisol test set.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660562", "https://ndownloader.figshare.com/files/1660563", "https://ndownloader.figshare.com/files/1660564", "https://ndownloader.figshare.com/files/1660565", "https://ndownloader.figshare.com/files/1660566", "https://ndownloader.figshare.com/files/1660567", "https://ndownloader.figshare.com/files/1660568"], "description"=>"<div><p>We present a novel approach for analyzing biological time-series data using a context-free language (CFL) representation that allows the extraction and quantification of important features from the time-series. This representation results in Hierarchically AdaPtive (HAP) analysis, a suite of multiple complementary techniques that enable rapid analysis of data and does not require the user to set parameters. HAP analysis generates hierarchically organized parameter distributions that allow multi-scale components of the time-series to be quantified and includes a data analysis pipeline that applies recursive analyses to generate hierarchically organized results that extend traditional outcome measures such as pharmacokinetics and inter-pulse interval. Pulsicons, a novel text-based time-series representation also derived from the CFL approach, are introduced as an objective qualitative comparison nomenclature. We apply HAP to the analysis of 24 hours of frequently sampled pulsatile cortisol hormone data, which has known analysis challenges, from 14 healthy women. HAP analysis generated results in seconds and produced dozens of figures for each participant. The results quantify the observed qualitative features of cortisol data as a series of pulse clusters, each consisting of one or more embedded pulses, and identify two ultradian phenotypes in this dataset. HAP analysis is designed to be robust to individual differences and to missing data and may be applied to other pulsatile hormones. Future work can extend HAP analysis to other time-series data types, including oscillatory and other periodic physiological signals.</p></div>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160358, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0104087.s001", "https://dx.doi.org/10.1371/journal.pone.0104087.s002", "https://dx.doi.org/10.1371/journal.pone.0104087.s003", "https://dx.doi.org/10.1371/journal.pone.0104087.s004", "https://dx.doi.org/10.1371/journal.pone.0104087.s005", "https://dx.doi.org/10.1371/journal.pone.0104087.s006", "https://dx.doi.org/10.1371/journal.pone.0104087.s007"], "stats"=>{"downloads"=>15, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Biological_Time_Series_Analysis_Using_a_Context_Free_Language_Applicability_to_Pulsatile_Hormone_Data_/1160358", "title"=>"Biological Time Series Analysis Using a Context Free Language: Applicability to Pulsatile Hormone Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660544"], "description"=>"<p>Each analysis iteration for participant ID6 is shown with a different symbol: 1-circle, 2-square, 3-up triangle, 4-down triangle. The symbol color indicates the timing of the event with the color code in right-most vertical panel: the sleep episode (blue), the first 8 hours of wake (green), or second 8 hours of wake (white). The dashed lines connect median value between iterations. (<b>A</b>) Cortisol accumulation rates for nadirs identified at each iteration. Accumulation rates for the first iteration are analogous to secretory rates. (<b>B</b>) Cortisol dissipation rates for nadirs identified at each iteration. Dissipation rates for the first iteration are analogous to clearance rates. (<b>C</b>) The nadir intervals identified at each iteration are shown. The event intervals at the first iteration are analogous to the inter-pulse interval. (<b>D</b>) The relationship between an accumulation rate and the immediately following dissipation rate.</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160340, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.g005", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multi_scale_analysis_of_features_identified_with_HAP_from_a_single_participant_ID6_/1160340", "title"=>"Multi-scale analysis of features identified with HAP from a single participant (ID6).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660541"], "description"=>"<p>The figure is divided into 3 sections: Time-series (left panel), Theory – Symbolic Representation (right panel) and Computational Steps (bottom panel). Solid arrows indicate theoretical steps; dotted lines with numbers indicate computational steps listed in the bottom panel.</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160337, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.g002", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hierarchically_AdaPtive_HAP_Analysis_Schematic_/1160337", "title"=>"Hierarchically AdaPtive (HAP) Analysis Schematic.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660540"], "description"=>"<p>An example adapted from experimental data (black line) with six major cortisol pulses. For a <b>Single Pulse Rise (U<sub>1</sub>)</b> starting at time ∼3.5 hours, the single pulse peak is identified with and the starting nadir/valley is identified with a V<sub>1</sub>. The pulse rise is defined as the rise in cortisol concentration from the nadir (V<sub>1</sub>) to peak (P<sub>1</sub>). The pulse rise time (Uw<sub>1</sub>) is the time required for the cortisol concentration levels to rise from a sequence of pulses starting with the local nadir (V<sub>1</sub>) to the peak (P<sub>1</sub>). The <b>Hierarchical (multiple) Pulse Rise (U<sub>2</sub>)</b> occurs as the change in concentration from the first nadir (V<sub>2</sub>) to last nadir (P<sub>2</sub>), which is a local maximum nadir, in the rise portion of this hierarchically organized segment. The hierarchical pulse rise time (Uw<sub>2</sub>) is the elapsed time between V<sub>2</sub> and P<sub>2</sub> of the rising portion. The effect of the hierarchical pulses between V<sub>2</sub> and P<sub>2</sub> is an accumulation or increase in cortisol. Similarly, sequences of pulses associated with the dissipation or decrease in cortisol begin at time ∼4.8 hours.</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160336, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.g001", "stats"=>{"downloads"=>4, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hierarchically_embedded_cortisol_pulses_/1160336", "title"=>"Hierarchically embedded cortisol pulses.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660553"], "description"=>"<p>Accumulation and dissipation rates computed from the Level 1 iteration for all participants.</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160349, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.t003", "stats"=>{"downloads"=>6, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Accumulation_and_dissipation_rates_computed_from_the_Level_1_iteration_for_all_participants_/1160349", "title"=>"Accumulation and dissipation rates computed from the Level 1 iteration for all participants.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660552"], "description"=>"<p>The table is organized by number of iterations: 3 for 9 participants and 4 for 5 participants. As iteration level increases, the representation appears simpler.</p><p>Pulsicons for All Participants.</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160348, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.t002", "stats"=>{"downloads"=>1, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pulsicons_for_All_Participants_/1160348", "title"=>"Pulsicons for All Participants.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660546"], "description"=>"<p>Within each panel, the left figure plots the time and amplitudes of each pulse and the right figure plots the resulting simulated dataset. The gamma value affects the clearance rate. (A) Gamma = 0.25 (B) Gamma = 0.75 (C) Gamma = 1.0 (D) Gamma = 1.5 (E) Gamma = 2.5, (F) Gamma = 5.0.</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160342, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.g006", "stats"=>{"downloads"=>3, "page_views"=>70, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulated_24_hour_cortisol_concentration_time_series_profiles_with_gamma_values_from_Table_1_/1160342", "title"=>"Simulated 24-hour cortisol concentration time-series profiles with gamma values from Table 1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660543"], "description"=>"<p>(<b>A</b>) Amplitude as a function of the rise or fall duration extracted from the first iteration of the HAP algorithm for participant ID6. Concentration rises (changes between local nadirs and subsequent local peaks) are shown with blue circles. Concentration falls (changes between local peaks and subsequent local nadirs) are shown with green triangles. Regression lines are shown separately for the rises (blue circles) and falls (green triangles). (<b>B</b>) A histogram of the instantaneous accumulation rates ( = rise amplitude/rise duration) from Panel A. (<b>C</b>) A histogram of the instantaneous dissipation rates ( = fall amplitude/fall duration) from Panel A.</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160339, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.g004", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Accumulation_and_dissipation_rates_for_a_single_participant_ID6_/1160339", "title"=>"Accumulation and dissipation rates for a single participant (ID6).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-09-03 03:51:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1660542"], "description"=>"<p>The dotted vertical lines with lower case Roman numerals represent the same time points in the Time-Series, the Pulsicon, and the Production Graph for participant ID6. Shaded rectangles labeled with uppercase roman numerals represent the same temporal interval in the Time-Series, the Pulsicon, and the Production Graph. <b>Time-Series:</b> The 24-hour cortisol time-series. Nadirs identified in each of the four HAP iterations are connected with lines. The terminal HAP nadirs are identified with black circles. <b>Pulsicon:</b> The pulsicon for the time-series. <b>Production Graph:</b> Each rectangle represents productions: the application of rules defined in the CFL The five rectangular boxes represent the key features of the time-series. The first two rectangles (Labeled 1 and 2) show that there is a decreasing portion prior to the main portion of the cortisol time-series with the “>” in rectangle 2 (e.g., before left black circle). The main portion of the cortisol time-series is represented by the center rectangle (Labeled 3) with the production symbol (S). The production symbol (S) is a variable that can be replaced with any of the rules defined in the context free language. This section contains a hierarchy of embedded pulses. The last two rectangles (Labeled 4 and 5) from the production graph show that the cortisol time-series is rising after the main portion (rectangle labeled 3) of the cortisol time-series (e.g., after right black circle).</p>", "links"=>[], "tags"=>["Context Free Language", "Biological Time Series Analysis", "Pulsatile Hormone Data", "data analysis pipeline", "pulsatile cortisol hormone data", "HAP analysis", "cfl"], "article_id"=>1160338, "categories"=>["Uncategorised"], "users"=>["Dennis A. Dean II", "Gail K. Adler", "David P. Nguyen", "Elizabeth B. Klerman"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104087.g003", "stats"=>{"downloads"=>2, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Qualitative_time_series_representations_for_a_single_participant_ID6_/1160338", "title"=>"Qualitative time-series representations for a single participant (ID6).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-09-03 03:51:12"}

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Relative Metric

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