Ph.D
Group : Bioinformatics

Conception, modélisation et simulation in silico d’un nanosystème biologique artificiel pour le diagnostic médical

Starts on 01/10/2013
Advisor : AMAR, Patrick

Funding : Contrat doctoral uniquement recherche
Affiliation : Université Paris-Saclay
Laboratory : LRI BIOINFO

Defended on 29/09/2016, committee :

Research activities :

Abstract :
The medical diagnosis is traditionally done by examining the clinical symptoms
and by searching in samples (blood, urine, biopsies, etc.) for the simultaneous presence (or
absence) of biomarkers of the various pathologies considered by the doctor. The search for
biomarkers is conducted using large equipments in a specialised laboratory; The results being
communicated to the doctor, who will then interpret them by applying a medical diagnosis
algorithm.
We wanted to combine in a single device, for a given disease, the detection of its biomarkers
and an implementation of the appropriate diagnosis algorithm. The presence or absence of a
biomarker can be represented by a boolean variable, and the diagnosis algorithm by a complex
boolean function whose value indicates the presence of the targeted disease.
Our diagnosis device is an articial biochemical nano-computer where logical information is
represented by metabolites and the computations are performed by a synthetic enzymatic network.
To build this computer, it has been necessary to establish a theoretical basis of enzymatic
logical networks. We then used this theory to dene what an enzymatic logic network is, and
how it computes correctly the associated boolean function.
For modularity and reusability reasons, we decided to design libraries of enzymatic logic gates
that implement basic boolean operators, and then to assemble these building blocks to get
the complete logic enzymatic network. So, I have designed and developed two software tools,
NetGate and NetBuild, which will automatically perform these operations.
NetGate creates libraries containing hundreds of enzymatic logic gates obtained from the metabolic
networks of living organisms. Before that, it was necessary to manually analyse these
metabolic networks in order to extract each logic gate.
NetBuild uses a library of logic gates (for example created using NetGate) and assembles them
to build circuits that compute a given boolean function. These circuits use specic metabolites
for its inputs (for example the biomarkers of a pathology) and produce a readily detectable
molecular species (using colorimetry for example).

CAUSAL LEARNING FOR DIAGNOSTIC SUPPORT


CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.