{"id":2105,"date":"2022-08-28T17:34:09","date_gmt":"2022-08-28T15:34:09","guid":{"rendered":"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/"},"modified":"2022-08-28T17:34:09","modified_gmt":"2022-08-28T15:34:09","slug":"hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond","status":"publish","type":"events","link":"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/","title":{"rendered":"Hybrid Physics Seminar:Topological (big) Data Analysis: From biology to cosmology and beyond"},"content":{"rendered":"
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\nHybrid Physics SeminarCampus LimpertsbergB\u00e2timent des Sciences, BSC 0.04Webex linkWednesday, September 28, 2022 at 16:00Talk by Dr. Pratyush PranavCentre de Recherche Astrophysique de Lyon, FranceInvited by Prof. Anupam Sengupta<\/h5>\n

Topological (big) Data Analysis: From biology to cosmology and beyond<\/p><\/div><\/section>","protected":false},"excerpt":{"rendered":"

Hybrid Physics SeminarCampus LimpertsbergB\u00e2timent des Sciences, BSC 0.04Webex linkWednesday, September 28, 2022 at 16:00Talk by Dr. Pratyush PranavCentre de Recherche Astrophysique de Lyon, FranceInvited by Prof. Anupam SenguptaTopological (big) Data Analysis: From biology to cosmology and beyondModern scientific endeavors are increasingly becoming data-centric across a spectrum of scientific disciplines, including cosmology and astrophysics, biomedical sciences, material and drug discovery, and finances, to name a few. The increased focus on data has simultaneously led to a massive surge in data collection across disciplines, such that the term Big Data has entered common parlance. The advent of Big Data has simultaneously brought to front two of the central statistical challenges of our times: the detection and classification of structure in extremely large, high-dimensional, data sets, demanding increasingly more sophisticated methods to detect pattern and glean meaningful information. Among the most intriguing new approaches to this challenge is \u201cTDA,\u201d or \u201cTopological Data Analysis,\u201d one of the primary aims of which is providing non-metric, but topologically informative, pre-analyses of data which make later, more quantitative, analyses feasible. Algebraic and computational topology at the level of homology and persistent homology are the foundational pillars of TDA. These developments on the topological side are recent, and add value to the already existing computational geometric tools and methodologies employed in investigating the data in various fields, such as the Minkowski functionals. Apart from presenting tools for data analysis, topo-geometrical formalisms also provide for methods resulting in state-of-the-art visualization techniques that are based on strong mathematical foundations; see Figure 1.This talk will have two distinct parts devoted to the theoretical background and experimental applications respectively. In the first part of my talk, I will present a summary of the theoretical and computational aspects of geometry and topology from the view point of data analysis. TDA and computational geometry has been used effectively in a variety of scenarios in biomedical sciences. Consequently, in the second part of the talk, I will highlight applications by presenting examples from biological and cosmological datasets. I will begin with discussing the topological characteristics of gene replication, by examining the replication timing data from a few human cell-lines and discuss the relevance of topo-geometrical methods with respect to existing methods of analysis in the field. As a second example, I will present an analysis of the topological properties of the temperature and polarization maps of the (CMB) radiation obtained by the Planck satellite. The CMB radiation represents the earliest visible light in the Universe, and contains a treasure trove of information about the initial conditions of the Universe. The CMB also represents the largest canvas on which to test the fundamental assumptions of the cosmological principle. Within this context, I will discuss some of the anomalies that the CMB temperature and polarization maps exhibit with respect to the simulations basedon the standard cosmological model, which assumes the initial fluctuation field to be an instance of an isotropic and homogeneous Gaussian random field.Figure 1: Visualizations of structures in the CMB and galaxy distribution. Top: The surface presents the visualization of the temperature fluctuations in the CMB, along with a superposition of a visualization of topological loops. Bottom: Filamentary structures identified in an n-body cosmological simulation of large scale structure of the universe.Short bioPratyush PranavCentre de Recherche Astrophysique de Lyon, FrancePratyush Pranav is a research associate at ENS de Lyon working in the group of Thomas Buchert. You can find Pratyush\u2019s bio and activities here: https:\/\/www.pratyushpranav.org<\/p>\n","protected":false},"author":0,"featured_media":2106,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"featured_image_focal_point":[],"show_featured_caption":false,"ulux_newsletter_groups":"","uluxPostTitle":"","uluxPrePostTitle":"","_trash_the_other_posts":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"event_start_date":"2022-09-28 16:00:00","event_end_date":"2022-09-28 17:00:00","event_speaker_name":"Talk by Dr. Pratyush Pranav,Centre de Recherche Astrophysique de Lyon, France,Invited by Prof. Anupam Sengupta","event_speaker_link":"","event_is_online":false,"event_location":"Campus Limpertsberg : BSC 004\r\nWebex link : https:\/\/unilu.webex.com\/unilu\/j.php?MTID=m77d0998160f3054e368b851e9e79be76\r\n\r\n","event_street":"","event_location_link":"","event_zip_code":"","event_city":"","event_country":"LU"},"events-topic":[310],"events-type":[],"organisation":[75],"authorship":[],"acf":[],"yoast_head":"\nHybrid Physics Seminar:Topological (big) Data Analysis: From biology to cosmology and beyond - FSTM I Uni.lu<\/title>\n<meta name=\"description\" content=\"Hybrid Physics SeminarCampus LimpertsbergB\u00e2timent des Sciences, BSC 0.04Webex linkWednesday, September 28, 2022 at 16:00Talk by Dr. Pratyush PranavCentre de Recherche Astrophysique de Lyon, FranceInvited by Prof. Anupam SenguptaTopological (big) Data Analysis: From biology to cosmology and beyondModern scientific endeavors are increasingly becoming data-centric across a spectrum of scientific disciplines, including cosmology and astrophysics, biomedical sciences, material and drug discovery, and finances, to name a few. The increased focus on data has simultaneously led to a massive surge in data collection across disciplines, such that the term Big Data has entered common parlance. The advent of Big Data has simultaneously brought to front two of the central statistical challenges of our times: the detection and classification of structure in extremely large, high-dimensional, data sets, demanding increasingly more sophisticated methods to detect pattern and glean meaningful information. Among the most intriguing new approaches to this challenge is \u201cTDA,\u201d or \u201cTopological Data Analysis,\u201d one of the primary aims of which is providing non-metric, but topologically informative, pre-analyses of data which make later, more quantitative, analyses feasible. Algebraic and computational topology at the level of homology and persistent homology are the foundational pillars of TDA. These developments on the topological side are recent, and add value to the already existing computational geometric tools and methodologies employed in investigating the data in various fields, such as the Minkowski functionals. Apart from presenting tools for data analysis, topo-geometrical formalisms also provide for methods resulting in state-of-the-art visualization techniques that are based on strong mathematical foundations; see Figure 1.This talk will have two distinct parts devoted to the theoretical background and experimental applications respectively. In the first part of my talk, I will present a summary of the theoretical and computational aspects of geometry and topology from the view point of data analysis. TDA and computational geometry has been used effectively in a variety of scenarios in biomedical sciences. Consequently, in the second part of the talk, I will highlight applications by presenting examples from biological and cosmological datasets. I will begin with discussing the topological characteristics of gene replication, by examining the replication timing data from a few human cell-lines and discuss the relevance of topo-geometrical methods with respect to existing methods of analysis in the field. As a second example, I will present an analysis of the topological properties of the temperature and polarization maps of the (CMB) radiation obtained by the Planck satellite. The CMB radiation represents the earliest visible light in the Universe, and contains a treasure trove of information about the initial conditions of the Universe. The CMB also represents the largest canvas on which to test the fundamental assumptions of the cosmological principle. Within this context, I will discuss some of the anomalies that the CMB temperature and polarization maps exhibit with respect to the simulations basedon the standard cosmological model, which assumes the initial fluctuation field to be an instance of an isotropic and homogeneous Gaussian random field.Figure 1: Visualizations of structures in the CMB and galaxy distribution. Top: The surface presents the visualization of the temperature fluctuations in the CMB, along with a superposition of a visualization of topological loops. Bottom: Filamentary structures identified in an n-body cosmological simulation of large scale structure of the universe.Short bioPratyush PranavCentre de Recherche Astrophysique de Lyon, FrancePratyush Pranav is a research associate at ENS de Lyon working in the group of Thomas Buchert. You can find Pratyush\u2019s bio and activities here: https:\/\/www.pratyushpranav.org\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Hybrid Physics Seminar:Topological (big) Data Analysis: From biology to cosmology and beyond\" \/>\n<meta property=\"og:description\" content=\"Hybrid Physics SeminarCampus LimpertsbergB\u00e2timent des Sciences, BSC 0.04Webex linkWednesday, September 28, 2022 at 16:00Talk by Dr. Pratyush PranavCentre de Recherche Astrophysique de Lyon, FranceInvited by Prof. Anupam SenguptaTopological (big) Data Analysis: From biology to cosmology and beyondModern scientific endeavors are increasingly becoming data-centric across a spectrum of scientific disciplines, including cosmology and astrophysics, biomedical sciences, material and drug discovery, and finances, to name a few. The increased focus on data has simultaneously led to a massive surge in data collection across disciplines, such that the term Big Data has entered common parlance. The advent of Big Data has simultaneously brought to front two of the central statistical challenges of our times: the detection and classification of structure in extremely large, high-dimensional, data sets, demanding increasingly more sophisticated methods to detect pattern and glean meaningful information. Among the most intriguing new approaches to this challenge is \u201cTDA,\u201d or \u201cTopological Data Analysis,\u201d one of the primary aims of which is providing non-metric, but topologically informative, pre-analyses of data which make later, more quantitative, analyses feasible. Algebraic and computational topology at the level of homology and persistent homology are the foundational pillars of TDA. These developments on the topological side are recent, and add value to the already existing computational geometric tools and methodologies employed in investigating the data in various fields, such as the Minkowski functionals. Apart from presenting tools for data analysis, topo-geometrical formalisms also provide for methods resulting in state-of-the-art visualization techniques that are based on strong mathematical foundations; see Figure 1.This talk will have two distinct parts devoted to the theoretical background and experimental applications respectively. In the first part of my talk, I will present a summary of the theoretical and computational aspects of geometry and topology from the view point of data analysis. TDA and computational geometry has been used effectively in a variety of scenarios in biomedical sciences. Consequently, in the second part of the talk, I will highlight applications by presenting examples from biological and cosmological datasets. I will begin with discussing the topological characteristics of gene replication, by examining the replication timing data from a few human cell-lines and discuss the relevance of topo-geometrical methods with respect to existing methods of analysis in the field. As a second example, I will present an analysis of the topological properties of the temperature and polarization maps of the (CMB) radiation obtained by the Planck satellite. The CMB radiation represents the earliest visible light in the Universe, and contains a treasure trove of information about the initial conditions of the Universe. The CMB also represents the largest canvas on which to test the fundamental assumptions of the cosmological principle. Within this context, I will discuss some of the anomalies that the CMB temperature and polarization maps exhibit with respect to the simulations basedon the standard cosmological model, which assumes the initial fluctuation field to be an instance of an isotropic and homogeneous Gaussian random field.Figure 1: Visualizations of structures in the CMB and galaxy distribution. Top: The surface presents the visualization of the temperature fluctuations in the CMB, along with a superposition of a visualization of topological loops. Bottom: Filamentary structures identified in an n-body cosmological simulation of large scale structure of the universe.Short bioPratyush PranavCentre de Recherche Astrophysique de Lyon, FrancePratyush Pranav is a research associate at ENS de Lyon working in the group of Thomas Buchert. You can find Pratyush\u2019s bio and activities here: https:\/\/www.pratyushpranav.org\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/\" \/>\n<meta property=\"og:site_name\" content=\"FSTM FR\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/fstm.uni.lu\/\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/20\/2026\/03\/03111744\/FSTM_SM-Profile_1600x1600px-scaled.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"2560\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/\",\"url\":\"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/\",\"name\":\"Hybrid Physics Seminar:Topological (big) Data Analysis: From biology to cosmology and beyond - FSTM I Uni.lu\",\"isPartOf\":{\"@id\":\"https:\/\/www.uni.lu\/fstm-fr\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/20\/2022\/08\/default-1.jpg\",\"datePublished\":\"2022-08-28T15:34:09+00:00\",\"dateModified\":\"2022-08-28T15:34:09+00:00\",\"description\":\"Hybrid Physics SeminarCampus LimpertsbergB\u00e2timent des Sciences, BSC 0.04Webex linkWednesday, September 28, 2022 at 16:00Talk by Dr. Pratyush PranavCentre de Recherche Astrophysique de Lyon, FranceInvited by Prof. Anupam SenguptaTopological (big) Data Analysis: From biology to cosmology and beyondModern scientific endeavors are increasingly becoming data-centric across a spectrum of scientific disciplines, including cosmology and astrophysics, biomedical sciences, material and drug discovery, and finances, to name a few. The increased focus on data has simultaneously led to a massive surge in data collection across disciplines, such that the term Big Data has entered common parlance. The advent of Big Data has simultaneously brought to front two of the central statistical challenges of our times: the detection and classification of structure in extremely large, high-dimensional, data sets, demanding increasingly more sophisticated methods to detect pattern and glean meaningful information. Among the most intriguing new approaches to this challenge is \u201cTDA,\u201d or \u201cTopological Data Analysis,\u201d one of the primary aims of which is providing non-metric, but topologically informative, pre-analyses of data which make later, more quantitative, analyses feasible. Algebraic and computational topology at the level of homology and persistent homology are the foundational pillars of TDA. 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Within this context, I will discuss some of the anomalies that the CMB temperature and polarization maps exhibit with respect to the simulations basedon the standard cosmological model, which assumes the initial fluctuation field to be an instance of an isotropic and homogeneous Gaussian random field.Figure 1: Visualizations of structures in the CMB and galaxy distribution. Top: The surface presents the visualization of the temperature fluctuations in the CMB, along with a superposition of a visualization of topological loops. Bottom: Filamentary structures identified in an n-body cosmological simulation of large scale structure of the universe.Short bioPratyush PranavCentre de Recherche Astrophysique de Lyon, FrancePratyush Pranav is a research associate at ENS de Lyon working in the group of Thomas Buchert. 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The increased focus on data has simultaneously led to a massive surge in data collection across disciplines, such that the term Big Data has entered common parlance. The advent of Big Data has simultaneously brought to front two of the central statistical challenges of our times: the detection and classification of structure in extremely large, high-dimensional, data sets, demanding increasingly more sophisticated methods to detect pattern and glean meaningful information. Among the most intriguing new approaches to this challenge is \u201cTDA,\u201d or \u201cTopological Data Analysis,\u201d one of the primary aims of which is providing non-metric, but topologically informative, pre-analyses of data which make later, more quantitative, analyses feasible. Algebraic and computational topology at the level of homology and persistent homology are the foundational pillars of TDA. These developments on the topological side are recent, and add value to the already existing computational geometric tools and methodologies employed in investigating the data in various fields, such as the Minkowski functionals. Apart from presenting tools for data analysis, topo-geometrical formalisms also provide for methods resulting in state-of-the-art visualization techniques that are based on strong mathematical foundations; see Figure 1.This talk will have two distinct parts devoted to the theoretical background and experimental applications respectively. In the first part of my talk, I will present a summary of the theoretical and computational aspects of geometry and topology from the view point of data analysis. TDA and computational geometry has been used effectively in a variety of scenarios in biomedical sciences. Consequently, in the second part of the talk, I will highlight applications by presenting examples from biological and cosmological datasets. I will begin with discussing the topological characteristics of gene replication, by examining the replication timing data from a few human cell-lines and discuss the relevance of topo-geometrical methods with respect to existing methods of analysis in the field. As a second example, I will present an analysis of the topological properties of the temperature and polarization maps of the (CMB) radiation obtained by the Planck satellite. The CMB radiation represents the earliest visible light in the Universe, and contains a treasure trove of information about the initial conditions of the Universe. The CMB also represents the largest canvas on which to test the fundamental assumptions of the cosmological principle. Within this context, I will discuss some of the anomalies that the CMB temperature and polarization maps exhibit with respect to the simulations basedon the standard cosmological model, which assumes the initial fluctuation field to be an instance of an isotropic and homogeneous Gaussian random field.Figure 1: Visualizations of structures in the CMB and galaxy distribution. Top: The surface presents the visualization of the temperature fluctuations in the CMB, along with a superposition of a visualization of topological loops. Bottom: Filamentary structures identified in an n-body cosmological simulation of large scale structure of the universe.Short bioPratyush PranavCentre de Recherche Astrophysique de Lyon, FrancePratyush Pranav is a research associate at ENS de Lyon working in the group of Thomas Buchert. You can find Pratyush\u2019s bio and activities here: https:\/\/www.pratyushpranav.org","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/","og_locale":"fr_FR","og_type":"article","og_title":"Hybrid Physics Seminar:Topological (big) Data Analysis: From biology to cosmology and beyond","og_description":"Hybrid Physics SeminarCampus LimpertsbergB\u00e2timent des Sciences, BSC 0.04Webex linkWednesday, September 28, 2022 at 16:00Talk by Dr. Pratyush PranavCentre de Recherche Astrophysique de Lyon, FranceInvited by Prof. Anupam SenguptaTopological (big) Data Analysis: From biology to cosmology and beyondModern scientific endeavors are increasingly becoming data-centric across a spectrum of scientific disciplines, including cosmology and astrophysics, biomedical sciences, material and drug discovery, and finances, to name a few. The increased focus on data has simultaneously led to a massive surge in data collection across disciplines, such that the term Big Data has entered common parlance. The advent of Big Data has simultaneously brought to front two of the central statistical challenges of our times: the detection and classification of structure in extremely large, high-dimensional, data sets, demanding increasingly more sophisticated methods to detect pattern and glean meaningful information. Among the most intriguing new approaches to this challenge is \u201cTDA,\u201d or \u201cTopological Data Analysis,\u201d one of the primary aims of which is providing non-metric, but topologically informative, pre-analyses of data which make later, more quantitative, analyses feasible. Algebraic and computational topology at the level of homology and persistent homology are the foundational pillars of TDA. These developments on the topological side are recent, and add value to the already existing computational geometric tools and methodologies employed in investigating the data in various fields, such as the Minkowski functionals. Apart from presenting tools for data analysis, topo-geometrical formalisms also provide for methods resulting in state-of-the-art visualization techniques that are based on strong mathematical foundations; see Figure 1.This talk will have two distinct parts devoted to the theoretical background and experimental applications respectively. In the first part of my talk, I will present a summary of the theoretical and computational aspects of geometry and topology from the view point of data analysis. TDA and computational geometry has been used effectively in a variety of scenarios in biomedical sciences. Consequently, in the second part of the talk, I will highlight applications by presenting examples from biological and cosmological datasets. I will begin with discussing the topological characteristics of gene replication, by examining the replication timing data from a few human cell-lines and discuss the relevance of topo-geometrical methods with respect to existing methods of analysis in the field. As a second example, I will present an analysis of the topological properties of the temperature and polarization maps of the (CMB) radiation obtained by the Planck satellite. The CMB radiation represents the earliest visible light in the Universe, and contains a treasure trove of information about the initial conditions of the Universe. The CMB also represents the largest canvas on which to test the fundamental assumptions of the cosmological principle. Within this context, I will discuss some of the anomalies that the CMB temperature and polarization maps exhibit with respect to the simulations basedon the standard cosmological model, which assumes the initial fluctuation field to be an instance of an isotropic and homogeneous Gaussian random field.Figure 1: Visualizations of structures in the CMB and galaxy distribution. Top: The surface presents the visualization of the temperature fluctuations in the CMB, along with a superposition of a visualization of topological loops. Bottom: Filamentary structures identified in an n-body cosmological simulation of large scale structure of the universe.Short bioPratyush PranavCentre de Recherche Astrophysique de Lyon, FrancePratyush Pranav is a research associate at ENS de Lyon working in the group of Thomas Buchert. You can find Pratyush\u2019s bio and activities here: https:\/\/www.pratyushpranav.org","og_url":"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/","og_site_name":"FSTM FR","article_publisher":"https:\/\/www.facebook.com\/fstm.uni.lu\/","og_image":[{"width":2560,"height":2560,"url":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/20\/2026\/03\/03111744\/FSTM_SM-Profile_1600x1600px-scaled.jpg","type":"image\/jpeg"}],"twitter_card":"summary_large_image","schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/","url":"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/","name":"Hybrid Physics Seminar:Topological (big) Data Analysis: From biology to cosmology and beyond - FSTM I Uni.lu","isPartOf":{"@id":"https:\/\/www.uni.lu\/fstm-fr\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/#primaryimage"},"image":{"@id":"https:\/\/www.uni.lu\/fstm-fr\/events\/hybrid-physics-seminartopological-big-data-analysis-from-biology-to-cosmology-and-beyond\/#primaryimage"},"thumbnailUrl":"https:\/\/www.uni.lu\/wp-content\/uploads\/sites\/20\/2022\/08\/default-1.jpg","datePublished":"2022-08-28T15:34:09+00:00","dateModified":"2022-08-28T15:34:09+00:00","description":"Hybrid Physics SeminarCampus LimpertsbergB\u00e2timent des Sciences, BSC 0.04Webex linkWednesday, September 28, 2022 at 16:00Talk by Dr. Pratyush PranavCentre de Recherche Astrophysique de Lyon, FranceInvited by Prof. Anupam SenguptaTopological (big) Data Analysis: From biology to cosmology and beyondModern scientific endeavors are increasingly becoming data-centric across a spectrum of scientific disciplines, including cosmology and astrophysics, biomedical sciences, material and drug discovery, and finances, to name a few. The increased focus on data has simultaneously led to a massive surge in data collection across disciplines, such that the term Big Data has entered common parlance. The advent of Big Data has simultaneously brought to front two of the central statistical challenges of our times: the detection and classification of structure in extremely large, high-dimensional, data sets, demanding increasingly more sophisticated methods to detect pattern and glean meaningful information. Among the most intriguing new approaches to this challenge is \u201cTDA,\u201d or \u201cTopological Data Analysis,\u201d one of the primary aims of which is providing non-metric, but topologically informative, pre-analyses of data which make later, more quantitative, analyses feasible. Algebraic and computational topology at the level of homology and persistent homology are the foundational pillars of TDA. These developments on the topological side are recent, and add value to the already existing computational geometric tools and methodologies employed in investigating the data in various fields, such as the Minkowski functionals. Apart from presenting tools for data analysis, topo-geometrical formalisms also provide for methods resulting in state-of-the-art visualization techniques that are based on strong mathematical foundations; see Figure 1.This talk will have two distinct parts devoted to the theoretical background and experimental applications respectively. In the first part of my talk, I will present a summary of the theoretical and computational aspects of geometry and topology from the view point of data analysis. TDA and computational geometry has been used effectively in a variety of scenarios in biomedical sciences. Consequently, in the second part of the talk, I will highlight applications by presenting examples from biological and cosmological datasets. I will begin with discussing the topological characteristics of gene replication, by examining the replication timing data from a few human cell-lines and discuss the relevance of topo-geometrical methods with respect to existing methods of analysis in the field. As a second example, I will present an analysis of the topological properties of the temperature and polarization maps of the (CMB) radiation obtained by the Planck satellite. The CMB radiation represents the earliest visible light in the Universe, and contains a treasure trove of information about the initial conditions of the Universe. The CMB also represents the largest canvas on which to test the fundamental assumptions of the cosmological principle. Within this context, I will discuss some of the anomalies that the CMB temperature and polarization maps exhibit with respect to the simulations basedon the standard cosmological model, which assumes the initial fluctuation field to be an instance of an isotropic and homogeneous Gaussian random field.Figure 1: Visualizations of structures in the CMB and galaxy distribution. Top: The surface presents the visualization of the temperature fluctuations in the CMB, along with a superposition of a visualization of topological loops. Bottom: Filamentary structures identified in an n-body cosmological simulation of large scale structure of the universe.Short bioPratyush PranavCentre de Recherche Astrophysique de Lyon, FrancePratyush Pranav is a research associate at ENS de Lyon working in the group of Thomas Buchert. 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