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Christopher L. Barrett, Executive Director, Virginia Bioinformatics Institute/Professor of Computer Science, Virginia Tech. Dr. Barrett’s talk entitled “Massively Interactive Systems: Thinking and Deciding in the Age of Big Data"
Abstract: This talk discusses advanced computationally assisted reasoning about large interaction-dominated systems. Current questions in science, from the biochemical foundations of life to the scale of the world economy, involve details of huge numbers and levels of intricate interactions. Subtle indirect causal connections and vastly extended definitions of system boundaries dominate the immediate future of scientific research. Beyond sheer numbers of details and interactions, the systems are variously layered and structured in ways perhaps best described as networks. Interactions include, and often co-create, these morphological and dynamical features, which can interact in their own right. Such “massively interacting” systems are characterized by, among other things, large amounts of data and branching behaviors. Although the amount of associated data is large, the systems do not even begin to explore their entire phase spaces. Their study is characterized by advanced computational methods. Major methodological revisions seem to be indicated.
Heretofore unavailable and rapidly growing basic source data and increasingly powerful computing resources drive complex system science toward unprecedented detail and scale. There is no obvious reason for this direction in science to change. The cost of acquiring data has historically dominated scientific costs and shaped the research environment in terms of approaches and even questions. In the several years, as the costs of social data, biological data and physical data have plummeted on a per-unit basis and as the volume of data is growing exponentially, the cost drivers for scientific research have clearly shifted from data generation to storage and analytical computation-based methods. The research environment is rapidly being reshaped by this change and, in particular, the social and bio–sciences are revolutionized by it. Moreover, the study of socially– and biologically–coupled systems (e.g., societal infrastructures and infectious disease public health policy analysis) is in flux as computation-based methods begin to greatly expand the scope of traditional problems in revolutionary ways.
How does this situation serve to guide the development of “information portal technology” for complex system science and for decision support? An example of an approach to detailed computational analysis of social and behavioral interaction with physical and infrastructure effects in the immediate aftermath of a devastating disaster will be described in this context.
CRI Workshop Learning Series
Bioinformatics Workshop 2014
Harper Court, Chicago
Photo by David Christopher
Global Biomedical Informatics: Innovation, Governance, Societal Engagement
Rising Powers Policy Workshop
Wednesday 18 February 2015
University of Sussex, Building Arts C, Room Number 333
Invitation only
The heralded revolutions in global medicine and healthcare fuelled by the life sciences and genomics require the harnessing of the ever-increasing waves of data that are being generated, through development and deployment of informatics tools, databases and data interpretation. There is a need to better understand the governance and steering of bioinformatics by national governments’ and other governance actors’ on the global stage. Social and scientific trends such as open access and consumerisation underpin developments in the field. This workshop addresses this challenge by bringing together a range of stakeholders from national and international bioinformatics initiatives, private sector bioinformatics services, genomic scientists and social scientists studying the field. Key topics for discussion include: Issues of disciplinary work and skills in bioinformatics and computational biology; Role of global centres of bioinformatics innovation; Educational and investment policies; Role of citizen and academic engagement; Data privacy; Open innovation, IP and data ownership; Outsourcing patterns; Genomic-clinical data linkage.
Organised by members of the ESRC Rising Powers ‘State strategies of governance in global medical biotech innovation: the impact of China and India’, KCL and University of Sussex.
Form more information, please see our website: www.sussex.ac.uk/globalhealthpolicy/events/workshops/glob....
Howest Proclamatie Advanced Bachelor of Bioinformatics en
Bachelor Biomedische Laboratoriumtechnologie
Christopher L. Barrett, Executive Director, Virginia Bioinformatics Institute/Professor of Computer Science, Virginia Tech. Dr. Barrett’s talk entitled “Massively Interactive Systems: Thinking and Deciding in the Age of Big Data"
Abstract: This talk discusses advanced computationally assisted reasoning about large interaction-dominated systems. Current questions in science, from the biochemical foundations of life to the scale of the world economy, involve details of huge numbers and levels of intricate interactions. Subtle indirect causal connections and vastly extended definitions of system boundaries dominate the immediate future of scientific research. Beyond sheer numbers of details and interactions, the systems are variously layered and structured in ways perhaps best described as networks. Interactions include, and often co-create, these morphological and dynamical features, which can interact in their own right. Such “massively interacting” systems are characterized by, among other things, large amounts of data and branching behaviors. Although the amount of associated data is large, the systems do not even begin to explore their entire phase spaces. Their study is characterized by advanced computational methods. Major methodological revisions seem to be indicated.
Heretofore unavailable and rapidly growing basic source data and increasingly powerful computing resources drive complex system science toward unprecedented detail and scale. There is no obvious reason for this direction in science to change. The cost of acquiring data has historically dominated scientific costs and shaped the research environment in terms of approaches and even questions. In the several years, as the costs of social data, biological data and physical data have plummeted on a per-unit basis and as the volume of data is growing exponentially, the cost drivers for scientific research have clearly shifted from data generation to storage and analytical computation-based methods. The research environment is rapidly being reshaped by this change and, in particular, the social and bio–sciences are revolutionized by it. Moreover, the study of socially– and biologically–coupled systems (e.g., societal infrastructures and infectious disease public health policy analysis) is in flux as computation-based methods begin to greatly expand the scope of traditional problems in revolutionary ways.
How does this situation serve to guide the development of “information portal technology” for complex system science and for decision support? An example of an approach to detailed computational analysis of social and behavioral interaction with physical and infrastructure effects in the immediate aftermath of a devastating disaster will be described in this context.
Bioinformatic Analysis and dBase Capture of Human RNA. Extracted of Information from Raw Data. Correlation engine hunts for and reports (logs) repeat 100BaseWindow signatures over previous 10kBases
Howest plechtige Proclamatie Brugge - Bachelor Verpleegkunde, Brugopleiding Verpleegkunde, Bachelor Biomedische Laboratorium-technologie en Advanced Bachelor of Bioinformatics - 7 november 2024
Christopher L. Barrett, Executive Director, Virginia Bioinformatics Institute/Professor of Computer Science, Virginia Tech. Dr. Barrett’s talk entitled “Massively Interactive Systems: Thinking and Deciding in the Age of Big Data"
Abstract: This talk discusses advanced computationally assisted reasoning about large interaction-dominated systems. Current questions in science, from the biochemical foundations of life to the scale of the world economy, involve details of huge numbers and levels of intricate interactions. Subtle indirect causal connections and vastly extended definitions of system boundaries dominate the immediate future of scientific research. Beyond sheer numbers of details and interactions, the systems are variously layered and structured in ways perhaps best described as networks. Interactions include, and often co-create, these morphological and dynamical features, which can interact in their own right. Such “massively interacting” systems are characterized by, among other things, large amounts of data and branching behaviors. Although the amount of associated data is large, the systems do not even begin to explore their entire phase spaces. Their study is characterized by advanced computational methods. Major methodological revisions seem to be indicated.
Heretofore unavailable and rapidly growing basic source data and increasingly powerful computing resources drive complex system science toward unprecedented detail and scale. There is no obvious reason for this direction in science to change. The cost of acquiring data has historically dominated scientific costs and shaped the research environment in terms of approaches and even questions. In the several years, as the costs of social data, biological data and physical data have plummeted on a per-unit basis and as the volume of data is growing exponentially, the cost drivers for scientific research have clearly shifted from data generation to storage and analytical computation-based methods. The research environment is rapidly being reshaped by this change and, in particular, the social and bio–sciences are revolutionized by it. Moreover, the study of socially– and biologically–coupled systems (e.g., societal infrastructures and infectious disease public health policy analysis) is in flux as computation-based methods begin to greatly expand the scope of traditional problems in revolutionary ways.
How does this situation serve to guide the development of “information portal technology” for complex system science and for decision support? An example of an approach to detailed computational analysis of social and behavioral interaction with physical and infrastructure effects in the immediate aftermath of a devastating disaster will be described in this context.
Christopher L. Barrett, Executive Director, Virginia Bioinformatics Institute/Professor of Computer Science, Virginia Tech. Dr. Barrett’s talk entitled “Massively Interactive Systems: Thinking and Deciding in the Age of Big Data"
Abstract: This talk discusses advanced computationally assisted reasoning about large interaction-dominated systems. Current questions in science, from the biochemical foundations of life to the scale of the world economy, involve details of huge numbers and levels of intricate interactions. Subtle indirect causal connections and vastly extended definitions of system boundaries dominate the immediate future of scientific research. Beyond sheer numbers of details and interactions, the systems are variously layered and structured in ways perhaps best described as networks. Interactions include, and often co-create, these morphological and dynamical features, which can interact in their own right. Such “massively interacting” systems are characterized by, among other things, large amounts of data and branching behaviors. Although the amount of associated data is large, the systems do not even begin to explore their entire phase spaces. Their study is characterized by advanced computational methods. Major methodological revisions seem to be indicated.
Heretofore unavailable and rapidly growing basic source data and increasingly powerful computing resources drive complex system science toward unprecedented detail and scale. There is no obvious reason for this direction in science to change. The cost of acquiring data has historically dominated scientific costs and shaped the research environment in terms of approaches and even questions. In the several years, as the costs of social data, biological data and physical data have plummeted on a per-unit basis and as the volume of data is growing exponentially, the cost drivers for scientific research have clearly shifted from data generation to storage and analytical computation-based methods. The research environment is rapidly being reshaped by this change and, in particular, the social and bio–sciences are revolutionized by it. Moreover, the study of socially– and biologically–coupled systems (e.g., societal infrastructures and infectious disease public health policy analysis) is in flux as computation-based methods begin to greatly expand the scope of traditional problems in revolutionary ways.
How does this situation serve to guide the development of “information portal technology” for complex system science and for decision support? An example of an approach to detailed computational analysis of social and behavioral interaction with physical and infrastructure effects in the immediate aftermath of a devastating disaster will be described in this context.
CRI Workshop Learning Series
Bioinformatics Workshop 2014
University of Chicago
Photo by David Christopher
Howest Proclamatie Advanced Bachelor of Bioinformatics en
Bachelor Biomedische Laboratoriumtechnologie
Howest Proclamatie Advanced Bachelor of Bioinformatics en
Bachelor Biomedische Laboratoriumtechnologie
Christopher L. Barrett, Executive Director, Virginia Bioinformatics Institute/Professor of Computer Science, Virginia Tech. Dr. Barrett’s talk entitled “Massively Interactive Systems: Thinking and Deciding in the Age of Big Data"
Abstract: This talk discusses advanced computationally assisted reasoning about large interaction-dominated systems. Current questions in science, from the biochemical foundations of life to the scale of the world economy, involve details of huge numbers and levels of intricate interactions. Subtle indirect causal connections and vastly extended definitions of system boundaries dominate the immediate future of scientific research. Beyond sheer numbers of details and interactions, the systems are variously layered and structured in ways perhaps best described as networks. Interactions include, and often co-create, these morphological and dynamical features, which can interact in their own right. Such “massively interacting” systems are characterized by, among other things, large amounts of data and branching behaviors. Although the amount of associated data is large, the systems do not even begin to explore their entire phase spaces. Their study is characterized by advanced computational methods. Major methodological revisions seem to be indicated.
Heretofore unavailable and rapidly growing basic source data and increasingly powerful computing resources drive complex system science toward unprecedented detail and scale. There is no obvious reason for this direction in science to change. The cost of acquiring data has historically dominated scientific costs and shaped the research environment in terms of approaches and even questions. In the several years, as the costs of social data, biological data and physical data have plummeted on a per-unit basis and as the volume of data is growing exponentially, the cost drivers for scientific research have clearly shifted from data generation to storage and analytical computation-based methods. The research environment is rapidly being reshaped by this change and, in particular, the social and bio–sciences are revolutionized by it. Moreover, the study of socially– and biologically–coupled systems (e.g., societal infrastructures and infectious disease public health policy analysis) is in flux as computation-based methods begin to greatly expand the scope of traditional problems in revolutionary ways.
How does this situation serve to guide the development of “information portal technology” for complex system science and for decision support? An example of an approach to detailed computational analysis of social and behavioral interaction with physical and infrastructure effects in the immediate aftermath of a devastating disaster will be described in this context.