First name
Emanuele
Last name
Ratti
Year of Study
Research Center
Thesis Title
The context of discovery of data driven biology
Thesis Abstract
My PhD dissertation aims (1) at reconstructing the structure of the context of discovery of
‘data-driven’ (big data, data intensive) biology and (2) at comparing it to traditional
molecular approaches. Within the current debate in philosophy of science, ‘traditional
approaches’ in molecular biology should be understood as the discovery and heuristics
strategies identified by mechanistic philosophers such as Carl Craver and Lindley Darden.
Therefore, key questions of my thesis are: what is the structure of discovery of datadriven
biology? Is data-driven biology methodology different from traditional molecular
approaches?
The reason for doing such an analysis comes from a recent controversy among
biologists. In particular, sides disagree on whether high throughput sequencing
technologies are stimulating the development of a new scientific method somehow
irreducible to traditional approaches. I will try to disentangle the debate by reconstructing
and comparing data-driven and traditional methodologies. The dissertation is composed
of five chapters.
The first chapter deals with methodological issues. How do I compare data-driven
and traditional molecular biology structures of discovery? Mechanistic philosophers have
extensively characterized the discovery structure of traditional molecular biology.
However, there is not such an analysis for data-driven biology. In order to do this, I will
critically revise the discovery/justification distinction. The debate on
discovery/justification has provided valuable tools on how discovery strategies might be
conceived, and it is clearly one of the main forefathers of recent philosophical discussions
on scientific methodologies in biology and physics.
In Chapter 2 I shall to try to infer a full-fledged account of discovery for datadriven
biology by means of the philosophical tools developed in Chapter 1. This analysis
will be done in parallel to the investigation of key examples of data-driven biology,
namely genome-wide association studies and cancer genomics. In Chapter 3 I analyze the
epistemic strategies enabled by biological databases in data-driven biology. In Chapter 4,
I will show how the discovery structure of ‘traditional molecular biology’ can be more
efficiently rephrased through the same theoretical framework that I use to characterize
data-driven biology.
Since data-driven and traditional molecular biology seem to adopt the same
discovery structure, one might consider the controversy motivating my research ill posed.
However, in Chapter 5 I shall argue that there is still a valuable reason of disagreement
between the sides. Actually, data-driven and traditional molecular biology endorse
different cognitive values, which provide the criteria for evaluating models and findings as
adequate or not. Here one might say that, although the structures of discovery (i.e. how reasoning and experimental strategies are structured and depend on each other) of the
two sides are the same, the contexts of discovery (i.e. the set of both
reasoning/experimental strategies and epistemic values/background assumptions that
motivate discovery) are different. Therefore, in this last chapter I shall pinpoint the
cognitive values behind traditional and data-driven biology, and how these commitments
stimulate the heated disagreement motivating my research.
‘data-driven’ (big data, data intensive) biology and (2) at comparing it to traditional
molecular approaches. Within the current debate in philosophy of science, ‘traditional
approaches’ in molecular biology should be understood as the discovery and heuristics
strategies identified by mechanistic philosophers such as Carl Craver and Lindley Darden.
Therefore, key questions of my thesis are: what is the structure of discovery of datadriven
biology? Is data-driven biology methodology different from traditional molecular
approaches?
The reason for doing such an analysis comes from a recent controversy among
biologists. In particular, sides disagree on whether high throughput sequencing
technologies are stimulating the development of a new scientific method somehow
irreducible to traditional approaches. I will try to disentangle the debate by reconstructing
and comparing data-driven and traditional methodologies. The dissertation is composed
of five chapters.
The first chapter deals with methodological issues. How do I compare data-driven
and traditional molecular biology structures of discovery? Mechanistic philosophers have
extensively characterized the discovery structure of traditional molecular biology.
However, there is not such an analysis for data-driven biology. In order to do this, I will
critically revise the discovery/justification distinction. The debate on
discovery/justification has provided valuable tools on how discovery strategies might be
conceived, and it is clearly one of the main forefathers of recent philosophical discussions
on scientific methodologies in biology and physics.
In Chapter 2 I shall to try to infer a full-fledged account of discovery for datadriven
biology by means of the philosophical tools developed in Chapter 1. This analysis
will be done in parallel to the investigation of key examples of data-driven biology,
namely genome-wide association studies and cancer genomics. In Chapter 3 I analyze the
epistemic strategies enabled by biological databases in data-driven biology. In Chapter 4,
I will show how the discovery structure of ‘traditional molecular biology’ can be more
efficiently rephrased through the same theoretical framework that I use to characterize
data-driven biology.
Since data-driven and traditional molecular biology seem to adopt the same
discovery structure, one might consider the controversy motivating my research ill posed.
However, in Chapter 5 I shall argue that there is still a valuable reason of disagreement
between the sides. Actually, data-driven and traditional molecular biology endorse
different cognitive values, which provide the criteria for evaluating models and findings as
adequate or not. Here one might say that, although the structures of discovery (i.e. how reasoning and experimental strategies are structured and depend on each other) of the
two sides are the same, the contexts of discovery (i.e. the set of both
reasoning/experimental strategies and epistemic values/background assumptions that
motivate discovery) are different. Therefore, in this last chapter I shall pinpoint the
cognitive values behind traditional and data-driven biology, and how these commitments
stimulate the heated disagreement motivating my research.
Email
emanuele.ratti@ieo.eu
Additional Info
Areas of specialization: Philosophy of biology, philosophy of science
Research interests: Sociology of science, philosophy of information, bioinformatics
Education
2011 MA in Research University of Hertfordshire, UK
Supervisor: professor Luciano Floridi
Present position
PhD Student (2012-2016) in the program Foundations of the Life Sciences and Their Ethical Consequences, European School of Molecular Medicine, Ifom-Ieo Campus, Milan (Italy). This program is affiliated with the European Institute of Oncology (IEO) and the faculty of Health Sciences of the University of Milan.
Thesis Committee: dr Marco Nathan (Denver University), professor Giovanni Boniolo (University of Milan), professor Michael Weisberg (University of Pennsylvania), dr Francesca Ciccarelli (King's College)
Lab experience
January-May 2012. Diego Pasini's Lab: Epigenetic Mechanisms and Stem Cell Differentiation and Oncogenesis. Training in basic lab procedures: DNA extraction, PCR, transfection.
May 2012 - October 2012. Marina Mapelli's Lab: Molecular Basis of Asymmetric Cell Division. Training in basic procedures: DNA extraction, PCR, transfection, protein expression test
October 2012 - September 2013. Francesca Ciccarelli's Lab: Bioinformatics and Evolutionary Genomics of Cancer. Analysis of data from whole-genome and whole-exome screenings for the project Network of Cancer Genes 4.0
Other experiences
Visiting Student (09-2013/06-2014) at the department of philosophy of the University of Pennsylvania under the supervision of professor Michael Weisberg
Selected publications
"Diverse Perspectives on Ontology" (with Emilio Sanfilippo, Francesca Quattri, Aleksandra Sojic, Federico Boem, Gaoussou Camara and Erik Chuck). Applied Ontology 2013, 8(8), 59-71, doi:10.3233/AO-13012
"NCG4.0: the Network of Cancer Genes in the Era of Massive Mutational Screenings of Cancer Genomes" (with Omer An, Vera Pendino, Matteo D'Antonio, Marco Gentilini and Francesca Ciccarelli). Database: The Journal of Biological Databases and Curation. 2014, Vol. 2014, doi:10.1093/database/bau015
"Junk or Functional DNA? ENCODE and the Function Controversy" (with Pierre-Luc Germain and Federico Boem). Biology & Philosophy. Forthcoming
"Levels of Abstraction, Emergentism and Artificial Life". Journal of Theoretical and Experimental Artificial Intelligence (special issue "Inforgs and Infosphere: Themes from Luciano Floridi's Philosophy of Artificial Intelligence). Forthcoming
Selected presentations, conferences, seminars
Conferences:
(with Federico Boem) "The Gene after ENCODE: a Wittgensteinian Approach", 9th July 2013, ISHPSSB 2013 Meeting, Montpellier
"What is Integration in Bioinformatics Modeling of Big Data? A Proposal Based on Idealization", August 28-31 2013, Fourth conference of the European Philosophy of Science Association (EPSA), Helsinki
Organized Symposia:
"Ontology for and from Science: the Ontological Analysis of Biology", 11th March 2013, first international conference of the German Society for Philosophy of Science/Gesellschaft für Wissenschaftsphilosophie (GWP), University of Hannover
"Models in Bioinformatics", August 28-31 2013, fourth conference of the European Philosophy of Science Association (EPSA), Helsink
Seminars:
Seminar on Next-generation Digital Information Storage in DNA (Church et al.), Francesca Ciccarelli's Lab (25th February 2013), IFOM-IEO Campus, Milan
(invited seminar) "The ENCODE Controversy", 28th May 2013, lgBIG-meeting, University of Geneva
References
Professor Giovanni Boniolo, University of Milan, giovanni.boniolo@ieo.eu
Dr Marco Nathan, University of Denver, marco.nathan@du.edu
Professor Michael Weisberg, University of Pennsylvania, weisberg@phil.upenn.edu
Research interests: Sociology of science, philosophy of information, bioinformatics
Education
2011 MA in Research University of Hertfordshire, UK
Supervisor: professor Luciano Floridi
Present position
PhD Student (2012-2016) in the program Foundations of the Life Sciences and Their Ethical Consequences, European School of Molecular Medicine, Ifom-Ieo Campus, Milan (Italy). This program is affiliated with the European Institute of Oncology (IEO) and the faculty of Health Sciences of the University of Milan.
Thesis Committee: dr Marco Nathan (Denver University), professor Giovanni Boniolo (University of Milan), professor Michael Weisberg (University of Pennsylvania), dr Francesca Ciccarelli (King's College)
Lab experience
January-May 2012. Diego Pasini's Lab: Epigenetic Mechanisms and Stem Cell Differentiation and Oncogenesis. Training in basic lab procedures: DNA extraction, PCR, transfection.
May 2012 - October 2012. Marina Mapelli's Lab: Molecular Basis of Asymmetric Cell Division. Training in basic procedures: DNA extraction, PCR, transfection, protein expression test
October 2012 - September 2013. Francesca Ciccarelli's Lab: Bioinformatics and Evolutionary Genomics of Cancer. Analysis of data from whole-genome and whole-exome screenings for the project Network of Cancer Genes 4.0
Other experiences
Visiting Student (09-2013/06-2014) at the department of philosophy of the University of Pennsylvania under the supervision of professor Michael Weisberg
Selected publications
"Diverse Perspectives on Ontology" (with Emilio Sanfilippo, Francesca Quattri, Aleksandra Sojic, Federico Boem, Gaoussou Camara and Erik Chuck). Applied Ontology 2013, 8(8), 59-71, doi:10.3233/AO-13012
"NCG4.0: the Network of Cancer Genes in the Era of Massive Mutational Screenings of Cancer Genomes" (with Omer An, Vera Pendino, Matteo D'Antonio, Marco Gentilini and Francesca Ciccarelli). Database: The Journal of Biological Databases and Curation. 2014, Vol. 2014, doi:10.1093/database/bau015
"Junk or Functional DNA? ENCODE and the Function Controversy" (with Pierre-Luc Germain and Federico Boem). Biology & Philosophy. Forthcoming
"Levels of Abstraction, Emergentism and Artificial Life". Journal of Theoretical and Experimental Artificial Intelligence (special issue "Inforgs and Infosphere: Themes from Luciano Floridi's Philosophy of Artificial Intelligence). Forthcoming
Selected presentations, conferences, seminars
Conferences:
(with Federico Boem) "The Gene after ENCODE: a Wittgensteinian Approach", 9th July 2013, ISHPSSB 2013 Meeting, Montpellier
"What is Integration in Bioinformatics Modeling of Big Data? A Proposal Based on Idealization", August 28-31 2013, Fourth conference of the European Philosophy of Science Association (EPSA), Helsinki
Organized Symposia:
"Ontology for and from Science: the Ontological Analysis of Biology", 11th March 2013, first international conference of the German Society for Philosophy of Science/Gesellschaft für Wissenschaftsphilosophie (GWP), University of Hannover
"Models in Bioinformatics", August 28-31 2013, fourth conference of the European Philosophy of Science Association (EPSA), Helsink
Seminars:
Seminar on Next-generation Digital Information Storage in DNA (Church et al.), Francesca Ciccarelli's Lab (25th February 2013), IFOM-IEO Campus, Milan
(invited seminar) "The ENCODE Controversy", 28th May 2013, lgBIG-meeting, University of Geneva
References
Professor Giovanni Boniolo, University of Milan, giovanni.boniolo@ieo.eu
Dr Marco Nathan, University of Denver, marco.nathan@du.edu
Professor Michael Weisberg, University of Pennsylvania, weisberg@phil.upenn.edu
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