Project acronym 3D-REPAIR
Project Spatial organization of DNA repair within the nucleus
Researcher (PI) Evanthia Soutoglou
Host Institution (HI) CENTRE EUROPEEN DE RECHERCHE EN BIOLOGIE ET MEDECINE
Call Details Consolidator Grant (CoG), LS2, ERC-2015-CoG
Summary Faithful repair of double stranded DNA breaks (DSBs) is essential, as they are at the origin of genome instability, chromosomal translocations and cancer. Cells repair DSBs through different pathways, which can be faithful or mutagenic, and the balance between them at a given locus must be tightly regulated to preserve genome integrity. Although, much is known about DSB repair factors, how the choice between pathways is controlled within the nuclear environment is not understood. We have shown that nuclear architecture and non-random genome organization determine the frequency of chromosomal translocations and that pathway choice is dictated by the spatial organization of DNA in the nucleus. Nevertheless, what determines which pathway is activated in response to DSBs at specific genomic locations is not understood. Furthermore, the impact of 3D-genome folding on the kinetics and efficiency of DSB repair is completely unknown.
Here we aim to understand how nuclear compartmentalization, chromatin structure and genome organization impact on the efficiency of detection, signaling and repair of DSBs. We will unravel what determines the DNA repair specificity within distinct nuclear compartments using protein tethering, promiscuous biotinylation and quantitative proteomics. We will determine how DNA repair is orchestrated at different heterochromatin structures using a CRISPR/Cas9-based system that allows, for the first time robust induction of DSBs at specific heterochromatin compartments. Finally, we will investigate the role of 3D-genome folding in the kinetics of DNA repair and pathway choice using single nucleotide resolution DSB-mapping coupled to 3D-topological maps.
This proposal has significant implications for understanding the mechanisms controlling DNA repair within the nuclear environment and will reveal the regions of the genome that are susceptible to genomic instability and help us understand why certain mutations and translocations are recurrent in cancer
Summary
Faithful repair of double stranded DNA breaks (DSBs) is essential, as they are at the origin of genome instability, chromosomal translocations and cancer. Cells repair DSBs through different pathways, which can be faithful or mutagenic, and the balance between them at a given locus must be tightly regulated to preserve genome integrity. Although, much is known about DSB repair factors, how the choice between pathways is controlled within the nuclear environment is not understood. We have shown that nuclear architecture and non-random genome organization determine the frequency of chromosomal translocations and that pathway choice is dictated by the spatial organization of DNA in the nucleus. Nevertheless, what determines which pathway is activated in response to DSBs at specific genomic locations is not understood. Furthermore, the impact of 3D-genome folding on the kinetics and efficiency of DSB repair is completely unknown.
Here we aim to understand how nuclear compartmentalization, chromatin structure and genome organization impact on the efficiency of detection, signaling and repair of DSBs. We will unravel what determines the DNA repair specificity within distinct nuclear compartments using protein tethering, promiscuous biotinylation and quantitative proteomics. We will determine how DNA repair is orchestrated at different heterochromatin structures using a CRISPR/Cas9-based system that allows, for the first time robust induction of DSBs at specific heterochromatin compartments. Finally, we will investigate the role of 3D-genome folding in the kinetics of DNA repair and pathway choice using single nucleotide resolution DSB-mapping coupled to 3D-topological maps.
This proposal has significant implications for understanding the mechanisms controlling DNA repair within the nuclear environment and will reveal the regions of the genome that are susceptible to genomic instability and help us understand why certain mutations and translocations are recurrent in cancer
Max ERC Funding
1 999 750 €
Duration
Start date: 2017-03-01, End date: 2022-02-28
Project acronym 3DEpi
Project Transgenerational epigenetic inheritance of chromatin states : the role of Polycomb and 3D chromosome architecture
Researcher (PI) Giacomo CAVALLI
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Advanced Grant (AdG), LS2, ERC-2017-ADG
Summary Epigenetic inheritance entails transmission of phenotypic traits not encoded in the DNA sequence and, in the most extreme case, Transgenerational Epigenetic Inheritance (TEI) involves transmission of memory through multiple generations. Very little is known on the mechanisms governing TEI and this is the subject of the present proposal. By transiently enhancing long-range chromatin interactions, we recently established isogenic Drosophila epilines that carry stable alternative epialleles, defined by differential levels of the Polycomb-dependent H3K27me3 mark. Furthermore, we extended our paradigm to natural phenotypes. These are ideal systems to study the role of Polycomb group (PcG) proteins and other components in regulating nuclear organization and epigenetic inheritance of chromatin states. The present project conjugates genetics, epigenomics, imaging and molecular biology to reach three critical aims.
Aim 1: Analysis of the molecular mechanisms regulating Polycomb-mediated TEI. We will identify the DNA, protein and RNA components that trigger and maintain transgenerational chromatin inheritance as well as their mechanisms of action.
Aim 2: Role of 3D genome organization in the regulation of TEI. We will analyze the developmental dynamics of TEI-inducing long-range chromatin interactions, identify chromatin components mediating 3D chromatin contacts and characterize their function in the TEI process.
Aim 3: Identification of a broader role of TEI during development. TEI might reflect a normal role of PcG components in the transmission of parental chromatin onto the next embryonic generation. We will explore this possibility by establishing other TEI paradigms and by relating TEI to the normal PcG function in these systems and in normal development.
This research program will unravel the biological significance and the molecular underpinnings of TEI and lead the way towards establishing this area of research into a consolidated scientific discipline.
Summary
Epigenetic inheritance entails transmission of phenotypic traits not encoded in the DNA sequence and, in the most extreme case, Transgenerational Epigenetic Inheritance (TEI) involves transmission of memory through multiple generations. Very little is known on the mechanisms governing TEI and this is the subject of the present proposal. By transiently enhancing long-range chromatin interactions, we recently established isogenic Drosophila epilines that carry stable alternative epialleles, defined by differential levels of the Polycomb-dependent H3K27me3 mark. Furthermore, we extended our paradigm to natural phenotypes. These are ideal systems to study the role of Polycomb group (PcG) proteins and other components in regulating nuclear organization and epigenetic inheritance of chromatin states. The present project conjugates genetics, epigenomics, imaging and molecular biology to reach three critical aims.
Aim 1: Analysis of the molecular mechanisms regulating Polycomb-mediated TEI. We will identify the DNA, protein and RNA components that trigger and maintain transgenerational chromatin inheritance as well as their mechanisms of action.
Aim 2: Role of 3D genome organization in the regulation of TEI. We will analyze the developmental dynamics of TEI-inducing long-range chromatin interactions, identify chromatin components mediating 3D chromatin contacts and characterize their function in the TEI process.
Aim 3: Identification of a broader role of TEI during development. TEI might reflect a normal role of PcG components in the transmission of parental chromatin onto the next embryonic generation. We will explore this possibility by establishing other TEI paradigms and by relating TEI to the normal PcG function in these systems and in normal development.
This research program will unravel the biological significance and the molecular underpinnings of TEI and lead the way towards establishing this area of research into a consolidated scientific discipline.
Max ERC Funding
2 500 000 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym 4D-GenEx
Project Spatio-temporal Organization and Expression of the Genome
Researcher (PI) Antoine COULON
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Starting Grant (StG), LS2, ERC-2017-STG
Summary This project investigates the two-way relationship between spatio-temporal genome organization and coordinated gene regulation, through an approach at the interface between physics, computer science and biology.
In the nucleus, preferred positions are observed from chromosomes to single genes, in relation to normal and pathological cellular states. Evidence indicates a complex spatio-temporal coupling between co-regulated genes: e.g. certain genes cluster spatially when responding to similar factors and transcriptional noise patterns suggest domain-wide mechanisms. Yet, no individual experiment allows probing transcriptional coordination in 4 dimensions (FISH, live locus tracking, Hi-C...). Interpreting such data also critically requires theory (stochastic processes, statistical physics…). A lack of appropriate experimental/analytical approaches is impairing our understanding of the 4D genome.
Our proposal combines cutting-edge single-molecule imaging, signal-theory data analysis and physical modeling to study how genes coordinate in space and time in a single nucleus. Our objectives are to understand (a) competition/recycling of shared resources between genes within subnuclear compartments, (b) how enhancers communicate with genes domain-wide, and (c) the role of local conformational dynamics and supercoiling in gene co-regulation. Our organizing hypothesis is that, by acting on their microenvironment, genes shape their co-expression with other genes.
Building upon my expertise, we will use dual-color MS2/PP7 RNA labeling to visualize for the first time transcription and motion of pairs of hormone-responsive genes in real time. With our innovative signal analysis tools, we will extract spatio-temporal signatures of underlying processes, which we will investigate with stochastic modeling and validate through experimental perturbations. We expect to uncover how the functional organization of the linear genome relates to its physical properties and dynamics in 4D.
Summary
This project investigates the two-way relationship between spatio-temporal genome organization and coordinated gene regulation, through an approach at the interface between physics, computer science and biology.
In the nucleus, preferred positions are observed from chromosomes to single genes, in relation to normal and pathological cellular states. Evidence indicates a complex spatio-temporal coupling between co-regulated genes: e.g. certain genes cluster spatially when responding to similar factors and transcriptional noise patterns suggest domain-wide mechanisms. Yet, no individual experiment allows probing transcriptional coordination in 4 dimensions (FISH, live locus tracking, Hi-C...). Interpreting such data also critically requires theory (stochastic processes, statistical physics…). A lack of appropriate experimental/analytical approaches is impairing our understanding of the 4D genome.
Our proposal combines cutting-edge single-molecule imaging, signal-theory data analysis and physical modeling to study how genes coordinate in space and time in a single nucleus. Our objectives are to understand (a) competition/recycling of shared resources between genes within subnuclear compartments, (b) how enhancers communicate with genes domain-wide, and (c) the role of local conformational dynamics and supercoiling in gene co-regulation. Our organizing hypothesis is that, by acting on their microenvironment, genes shape their co-expression with other genes.
Building upon my expertise, we will use dual-color MS2/PP7 RNA labeling to visualize for the first time transcription and motion of pairs of hormone-responsive genes in real time. With our innovative signal analysis tools, we will extract spatio-temporal signatures of underlying processes, which we will investigate with stochastic modeling and validate through experimental perturbations. We expect to uncover how the functional organization of the linear genome relates to its physical properties and dynamics in 4D.
Max ERC Funding
1 499 750 €
Duration
Start date: 2018-04-01, End date: 2023-03-31
Project acronym ACAP
Project Acency Costs and Asset Pricing
Researcher (PI) Thomas Mariotti
Host Institution (HI) FONDATION JEAN-JACQUES LAFFONT,TOULOUSE SCIENCES ECONOMIQUES
Call Details Starting Grant (StG), SH1, ERC-2007-StG
Summary The main objective of this research project is to contribute at bridging the gap between the two main branches of financial theory, namely corporate finance and asset pricing. It is motivated by the conviction that these two aspects of financial activity should and can be analyzed within a unified framework. This research will borrow from these two approaches in order to construct theoretical models that allow one to analyze the design and issuance of financial securities, as well as the dynamics of their valuations. Unlike asset pricing, which takes as given the price of the fundamentals, the goal is to derive security price processes from a precise description of firm’s operations and internal frictions. Regarding the latter, and in line with traditional corporate finance theory, the analysis will emphasize the role of agency costs within the firm for the design of its securities. But the analysis will be pushed one step further by studying the impact of these agency costs on key financial variables such as stock and bond prices, leverage, book-to-market ratios, default risk, or the holding of liquidities by firms. One of the contributions of this research project is to show how these variables are interrelated when firms and investors agree upon optimal financial arrangements. The final objective is to derive a rich set of testable asset pricing implications that would eventually be brought to the data.
Summary
The main objective of this research project is to contribute at bridging the gap between the two main branches of financial theory, namely corporate finance and asset pricing. It is motivated by the conviction that these two aspects of financial activity should and can be analyzed within a unified framework. This research will borrow from these two approaches in order to construct theoretical models that allow one to analyze the design and issuance of financial securities, as well as the dynamics of their valuations. Unlike asset pricing, which takes as given the price of the fundamentals, the goal is to derive security price processes from a precise description of firm’s operations and internal frictions. Regarding the latter, and in line with traditional corporate finance theory, the analysis will emphasize the role of agency costs within the firm for the design of its securities. But the analysis will be pushed one step further by studying the impact of these agency costs on key financial variables such as stock and bond prices, leverage, book-to-market ratios, default risk, or the holding of liquidities by firms. One of the contributions of this research project is to show how these variables are interrelated when firms and investors agree upon optimal financial arrangements. The final objective is to derive a rich set of testable asset pricing implications that would eventually be brought to the data.
Max ERC Funding
1 000 000 €
Duration
Start date: 2008-11-01, End date: 2014-10-31
Project acronym ACTINIT
Project Brain-behavior forecasting: The causal determinants of spontaneous self-initiated action in the study of volition and the development of asynchronous brain-computer interfaces.
Researcher (PI) Aaron Schurger
Host Institution (HI) INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE
Call Details Starting Grant (StG), LS5, ERC-2014-STG
Summary "How are actions initiated by the human brain when there is no external sensory cue or other immediate imperative? How do subtle ongoing interactions within the brain and between the brain, body, and sensory context influence the spontaneous initiation of action? How should we approach the problem of trying to identify the neural events that cause spontaneous voluntary action? Much is understood about how the brain decides between competing alternatives, leading to different behavioral responses. But far less is known about how the brain decides "when" to perform an action, or "whether" to perform an action in the first place, especially in a context where there is no sensory cue to act such as during foraging. This project seeks to open a new chapter in the study of spontaneous voluntary action building on a novel hypothesis recently introduced by the applicant (Schurger et al, PNAS 2012) concerning the role of ongoing neural activity in action initiation. We introduce brain-behavior forecasting, the converse of movement-locked averaging, as an approach to identifying the neurodynamic states that commit the motor system to performing an action "now", and will apply it in the context of information foraging. Spontaneous action remains a profound mystery in the brain basis of behavior, in humans and other animals, and is also central to the problem of asynchronous intention-detection in brain-computer interfaces (BCIs). A BCI must not only interpret what the user intends, but also must detect "when" the user intends to act, and not respond otherwise. This remains the biggest challenge in the development of high-performance BCIs, whether invasive or non-invasive. This project will take a systematic and collaborative approach to the study of spontaneous self-initiated action, incorporating computational modeling, neuroimaging, and machine learning techniques towards a deeper understanding of voluntary behavior and the robust asynchronous detection of decisions-to-act."
Summary
"How are actions initiated by the human brain when there is no external sensory cue or other immediate imperative? How do subtle ongoing interactions within the brain and between the brain, body, and sensory context influence the spontaneous initiation of action? How should we approach the problem of trying to identify the neural events that cause spontaneous voluntary action? Much is understood about how the brain decides between competing alternatives, leading to different behavioral responses. But far less is known about how the brain decides "when" to perform an action, or "whether" to perform an action in the first place, especially in a context where there is no sensory cue to act such as during foraging. This project seeks to open a new chapter in the study of spontaneous voluntary action building on a novel hypothesis recently introduced by the applicant (Schurger et al, PNAS 2012) concerning the role of ongoing neural activity in action initiation. We introduce brain-behavior forecasting, the converse of movement-locked averaging, as an approach to identifying the neurodynamic states that commit the motor system to performing an action "now", and will apply it in the context of information foraging. Spontaneous action remains a profound mystery in the brain basis of behavior, in humans and other animals, and is also central to the problem of asynchronous intention-detection in brain-computer interfaces (BCIs). A BCI must not only interpret what the user intends, but also must detect "when" the user intends to act, and not respond otherwise. This remains the biggest challenge in the development of high-performance BCIs, whether invasive or non-invasive. This project will take a systematic and collaborative approach to the study of spontaneous self-initiated action, incorporating computational modeling, neuroimaging, and machine learning techniques towards a deeper understanding of voluntary behavior and the robust asynchronous detection of decisions-to-act."
Max ERC Funding
1 338 130 €
Duration
Start date: 2015-10-01, End date: 2020-09-30
Project acronym ACTIVIA
Project Visual Recognition of Function and Intention
Researcher (PI) Ivan Laptev
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary "Computer vision is concerned with the automated interpretation of images and video streams. Today's research is (mostly) aimed at answering queries such as ""Is this a picture of a dog?"", (classification) or sometimes ""Find the dog in this photo"" (detection). While categorisation and detection are useful for many tasks, inferring correct class labels is not the final answer to visual recognition. The categories and locations of objects do not provide direct understanding of their function i.e., how things work, what they can be used for, or how they can act and react. Such an understanding, however, would be highly desirable to answer currently unsolvable queries such as ""Am I in danger?"" or ""What can happen in this scene?"". Solving such queries is the aim of this proposal.
My goal is to uncover the functional properties of objects and the purpose of actions by addressing visual recognition from a different and yet unexplored perspective. The main novelty of this proposal is to leverage observations of people, i.e., their actions and interactions to automatically learn the use, the purpose and the function of objects and scenes from visual data. The project is timely as it builds upon the two key recent technological advances: (a) the immense progress in visual recognition of objects, scenes and human actions achieved in the last ten years, as well as (b) the emergence of a massive amount of public image and video data now available to train visual models.
ACTIVIA addresses fundamental research issues in automated interpretation of dynamic visual scenes, but its results are expected to serve as a basis for ground-breaking technological advances in practical applications. The recognition of functional properties and intentions as explored in this project will directly support high-impact applications such as detection of abnormal events, which are likely to revolutionise today's approaches to crime protection, hazard prevention, elderly care, and many others."
Summary
"Computer vision is concerned with the automated interpretation of images and video streams. Today's research is (mostly) aimed at answering queries such as ""Is this a picture of a dog?"", (classification) or sometimes ""Find the dog in this photo"" (detection). While categorisation and detection are useful for many tasks, inferring correct class labels is not the final answer to visual recognition. The categories and locations of objects do not provide direct understanding of their function i.e., how things work, what they can be used for, or how they can act and react. Such an understanding, however, would be highly desirable to answer currently unsolvable queries such as ""Am I in danger?"" or ""What can happen in this scene?"". Solving such queries is the aim of this proposal.
My goal is to uncover the functional properties of objects and the purpose of actions by addressing visual recognition from a different and yet unexplored perspective. The main novelty of this proposal is to leverage observations of people, i.e., their actions and interactions to automatically learn the use, the purpose and the function of objects and scenes from visual data. The project is timely as it builds upon the two key recent technological advances: (a) the immense progress in visual recognition of objects, scenes and human actions achieved in the last ten years, as well as (b) the emergence of a massive amount of public image and video data now available to train visual models.
ACTIVIA addresses fundamental research issues in automated interpretation of dynamic visual scenes, but its results are expected to serve as a basis for ground-breaking technological advances in practical applications. The recognition of functional properties and intentions as explored in this project will directly support high-impact applications such as detection of abnormal events, which are likely to revolutionise today's approaches to crime protection, hazard prevention, elderly care, and many others."
Max ERC Funding
1 497 420 €
Duration
Start date: 2013-01-01, End date: 2018-12-31
Project acronym ADAPT
Project Theory and Algorithms for Adaptive Particle Simulation
Researcher (PI) Stephane Redon
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary "During the twentieth century, the development of macroscopic engineering has been largely stimulated by progress in digital prototyping: cars, planes, boats, etc. are nowadays designed and tested on computers. Digital prototypes have progressively replaced actual ones, and effective computer-aided engineering tools have helped cut costs and reduce production cycles of these macroscopic systems.
The twenty-first century is most likely to see a similar development at the atomic scale. Indeed, the recent years have seen tremendous progress in nanotechnology - in particular in the ability to control matter at the atomic scale. Similar to what has happened with macroscopic engineering, powerful and generic computational tools will be needed to engineer complex nanosystems, through modeling and simulation. As a result, a major challenge is to develop efficient simulation methods and algorithms.
NANO-D, the INRIA research group I started in January 2008 in Grenoble, France, aims at developing
efficient computational methods for modeling and simulating complex nanosystems, both natural and artificial. In particular, NANO-D develops SAMSON, a software application which gathers all algorithms designed by the group and its collaborators (SAMSON: Software for Adaptive Modeling and Simulation Of Nanosystems).
In this project, I propose to develop a unified theory, and associated algorithms, for adaptive particle simulation. The proposed theory will avoid problems that plague current popular multi-scale or hybrid simulation approaches by simulating a single potential throughout the system, while allowing users to finely trade precision for computational speed.
I believe the full development of the adaptive particle simulation theory will have an important impact on current modeling and simulation practices, and will enable practical design of complex nanosystems on desktop computers, which should significantly boost the emergence of generic nano-engineering."
Summary
"During the twentieth century, the development of macroscopic engineering has been largely stimulated by progress in digital prototyping: cars, planes, boats, etc. are nowadays designed and tested on computers. Digital prototypes have progressively replaced actual ones, and effective computer-aided engineering tools have helped cut costs and reduce production cycles of these macroscopic systems.
The twenty-first century is most likely to see a similar development at the atomic scale. Indeed, the recent years have seen tremendous progress in nanotechnology - in particular in the ability to control matter at the atomic scale. Similar to what has happened with macroscopic engineering, powerful and generic computational tools will be needed to engineer complex nanosystems, through modeling and simulation. As a result, a major challenge is to develop efficient simulation methods and algorithms.
NANO-D, the INRIA research group I started in January 2008 in Grenoble, France, aims at developing
efficient computational methods for modeling and simulating complex nanosystems, both natural and artificial. In particular, NANO-D develops SAMSON, a software application which gathers all algorithms designed by the group and its collaborators (SAMSON: Software for Adaptive Modeling and Simulation Of Nanosystems).
In this project, I propose to develop a unified theory, and associated algorithms, for adaptive particle simulation. The proposed theory will avoid problems that plague current popular multi-scale or hybrid simulation approaches by simulating a single potential throughout the system, while allowing users to finely trade precision for computational speed.
I believe the full development of the adaptive particle simulation theory will have an important impact on current modeling and simulation practices, and will enable practical design of complex nanosystems on desktop computers, which should significantly boost the emergence of generic nano-engineering."
Max ERC Funding
1 476 882 €
Duration
Start date: 2012-09-01, End date: 2017-08-31
Project acronym ADOS
Project AMPA Receptor Dynamic Organization and Synaptic transmission in health and disease
Researcher (PI) Daniel Georges Gustave Choquet
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Advanced Grant (AdG), LS5, ERC-2013-ADG
Summary AMPA glutamate receptors (AMPAR) play key roles in information processing by the brain as they mediate nearly all fast excitatory synaptic transmission. Their spatio-temporal organization in the post synapse with respect to presynaptic glutamate release sites is a key determinant in synaptic transmission. The activity-dependent regulation of AMPAR organization is at the heart of synaptic plasticity processes underlying learning and memory. Dysfunction of synaptic transmission - hence AMPAR organization - is likely at the origin of a number of brain diseases.
Building on discoveries made during my past ERC grant, our new ground-breaking objective is to uncover the mechanisms that link synaptic transmission with the dynamic organization of AMPAR and associated proteins. For this aim, we have assembled a team of neurobiologists, computer scientists and chemists with a track record of collaboration. We will combine physiology, cellular and molecular neurobiology with development of novel quantitative imaging and biomolecular tools to probe the molecular dynamics that regulate synaptic transmission.
Live high content 3D SuperResolution Light Imaging (SRLI) combined with electron microscopy will allow unprecedented visualization of AMPAR organization in synapses at the scale of individual subunits up to the level of intact tissue. Simultaneous SRLI and electrophysiology will elucidate the intricate relations between dynamic AMPAR organization, trafficking and synaptic transmission. Novel peptide- and small protein-based probes used as protein-protein interaction reporters and modulators will be developed to image and directly interfere with synapse organization.
We will identify new processes that are fundamental to activity dependent modifications of synaptic transmission. We will apply the above findings to understand the causes of early cognitive deficits in models of neurodegenerative disorders and open new avenues of research for innovative therapies.
Summary
AMPA glutamate receptors (AMPAR) play key roles in information processing by the brain as they mediate nearly all fast excitatory synaptic transmission. Their spatio-temporal organization in the post synapse with respect to presynaptic glutamate release sites is a key determinant in synaptic transmission. The activity-dependent regulation of AMPAR organization is at the heart of synaptic plasticity processes underlying learning and memory. Dysfunction of synaptic transmission - hence AMPAR organization - is likely at the origin of a number of brain diseases.
Building on discoveries made during my past ERC grant, our new ground-breaking objective is to uncover the mechanisms that link synaptic transmission with the dynamic organization of AMPAR and associated proteins. For this aim, we have assembled a team of neurobiologists, computer scientists and chemists with a track record of collaboration. We will combine physiology, cellular and molecular neurobiology with development of novel quantitative imaging and biomolecular tools to probe the molecular dynamics that regulate synaptic transmission.
Live high content 3D SuperResolution Light Imaging (SRLI) combined with electron microscopy will allow unprecedented visualization of AMPAR organization in synapses at the scale of individual subunits up to the level of intact tissue. Simultaneous SRLI and electrophysiology will elucidate the intricate relations between dynamic AMPAR organization, trafficking and synaptic transmission. Novel peptide- and small protein-based probes used as protein-protein interaction reporters and modulators will be developed to image and directly interfere with synapse organization.
We will identify new processes that are fundamental to activity dependent modifications of synaptic transmission. We will apply the above findings to understand the causes of early cognitive deficits in models of neurodegenerative disorders and open new avenues of research for innovative therapies.
Max ERC Funding
2 491 157 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym ALLEGRO
Project Active large-scale learning for visual recognition
Researcher (PI) Cordelia Schmid
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Call Details Advanced Grant (AdG), PE6, ERC-2012-ADG_20120216
Summary A massive and ever growing amount of digital image and video content
is available today, on sites such as
Flickr and YouTube, in audiovisual archives such as those of BBC and
INA, and in personal collections. In most cases, it comes with
additional information, such as text, audio or other metadata, that forms a
rather sparse and noisy, yet rich and diverse source of annotation,
ideally suited to emerging weakly supervised and active machine
learning technology. The ALLEGRO project will take visual recognition
to the next level by using this largely untapped source of data to
automatically learn visual models. The main research objective of
our project is the development of new algorithms and computer software
capable of autonomously exploring evolving data collections, selecting
the relevant information, and determining the visual models most
appropriate for different object, scene, and activity categories. An
emphasis will be put on learning visual models from video, a
particularly rich source of information, and on the representation of
human activities, one of today's most challenging problems in computer
vision. Although this project addresses fundamental research
issues, it is expected to result in significant advances in
high-impact applications that range from visual mining of the Web and
automated annotation and organization of family photo and video albums
to large-scale information retrieval in television archives.
Summary
A massive and ever growing amount of digital image and video content
is available today, on sites such as
Flickr and YouTube, in audiovisual archives such as those of BBC and
INA, and in personal collections. In most cases, it comes with
additional information, such as text, audio or other metadata, that forms a
rather sparse and noisy, yet rich and diverse source of annotation,
ideally suited to emerging weakly supervised and active machine
learning technology. The ALLEGRO project will take visual recognition
to the next level by using this largely untapped source of data to
automatically learn visual models. The main research objective of
our project is the development of new algorithms and computer software
capable of autonomously exploring evolving data collections, selecting
the relevant information, and determining the visual models most
appropriate for different object, scene, and activity categories. An
emphasis will be put on learning visual models from video, a
particularly rich source of information, and on the representation of
human activities, one of today's most challenging problems in computer
vision. Although this project addresses fundamental research
issues, it is expected to result in significant advances in
high-impact applications that range from visual mining of the Web and
automated annotation and organization of family photo and video albums
to large-scale information retrieval in television archives.
Max ERC Funding
2 493 322 €
Duration
Start date: 2013-04-01, End date: 2019-03-31
Project acronym AlmaCrypt
Project Algorithmic and Mathematical Cryptology
Researcher (PI) Antoine Joux
Host Institution (HI) SORBONNE UNIVERSITE
Call Details Advanced Grant (AdG), PE6, ERC-2014-ADG
Summary Cryptology is a foundation of information security in the digital world. Today's internet is protected by a form of cryptography based on complexity theoretic hardness assumptions. Ideally, they should be strong to ensure security and versatile to offer a wide range of functionalities and allow efficient implementations. However, these assumptions are largely untested and internet security could be built on sand.
The main ambition of Almacrypt is to remedy this issue by challenging the assumptions through an advanced algorithmic analysis.
In particular, this proposal questions the two pillars of public-key encryption: factoring and discrete logarithms. Recently, the PI contributed to show that in some cases, the discrete logarithm problem is considerably weaker than previously assumed. A main objective is to ponder the security of other cases of the discrete logarithm problem, including elliptic curves, and of factoring. We will study the generalization of the recent techniques and search for new algorithmic options with comparable or better efficiency.
We will also study hardness assumptions based on codes and subset-sum, two candidates for post-quantum cryptography. We will consider the applicability of recent algorithmic and mathematical techniques to the resolution of the corresponding putative hard problems, refine the analysis of the algorithms and design new algorithm tools.
Cryptology is not limited to the above assumptions: other hard problems have been proposed to aim at post-quantum security and/or to offer extra functionalities. Should the security of these other assumptions become critical, they would be added to Almacrypt's scope. They could also serve to demonstrate other applications of our algorithmic progress.
In addition to its scientific goal, Almacrypt also aims at seeding a strengthened research community dedicated to algorithmic and mathematical cryptology.
--
Summary
Cryptology is a foundation of information security in the digital world. Today's internet is protected by a form of cryptography based on complexity theoretic hardness assumptions. Ideally, they should be strong to ensure security and versatile to offer a wide range of functionalities and allow efficient implementations. However, these assumptions are largely untested and internet security could be built on sand.
The main ambition of Almacrypt is to remedy this issue by challenging the assumptions through an advanced algorithmic analysis.
In particular, this proposal questions the two pillars of public-key encryption: factoring and discrete logarithms. Recently, the PI contributed to show that in some cases, the discrete logarithm problem is considerably weaker than previously assumed. A main objective is to ponder the security of other cases of the discrete logarithm problem, including elliptic curves, and of factoring. We will study the generalization of the recent techniques and search for new algorithmic options with comparable or better efficiency.
We will also study hardness assumptions based on codes and subset-sum, two candidates for post-quantum cryptography. We will consider the applicability of recent algorithmic and mathematical techniques to the resolution of the corresponding putative hard problems, refine the analysis of the algorithms and design new algorithm tools.
Cryptology is not limited to the above assumptions: other hard problems have been proposed to aim at post-quantum security and/or to offer extra functionalities. Should the security of these other assumptions become critical, they would be added to Almacrypt's scope. They could also serve to demonstrate other applications of our algorithmic progress.
In addition to its scientific goal, Almacrypt also aims at seeding a strengthened research community dedicated to algorithmic and mathematical cryptology.
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Max ERC Funding
2 403 125 €
Duration
Start date: 2016-01-01, End date: 2021-12-31
