ERC FUNDED PROJECTS

"When I asked my seven-year-old daughter ""Who is the boy in your class who was also new in school last year, like you?"", she instantly replied ""Daniel"", using the descriptive content in my utterance to identify an entity in the real world and refer to it. The ability to use language to refer to reality is crucial for humans, and yet it is very difficult to model. AMORE breaks new ground in Computational Linguistics, Linguistics, and Artificial Intelligence by developing a model of linguistic reference to entities implemented as a computational system that can learn its own representations from data. This interdisciplinary project builds on two complementary semantic traditions: 1) Formal semantics, a symbolic approach that can delimit and track linguistic referents, but does not adequately match them with the descriptive content of linguistic expressions; 2) Distributional semantics, which can handle descriptive content but does not associate it to individuated referents. AMORE synthesizes the two approaches into a unified, scalable model of reference that operates with individuated referents and links them to referential expressions characterized by rich descriptive content. The model is a distributed (neural network) version of a formal semantic framework that is furthermore able to integrate perceptual (visual) and linguistic information about entities. We test it extensively in referential tasks that require matching noun phrases (“the Medicine student”, “the white cat”) with entity representations extracted from text and images. AMORE advances our scientific understanding of language and its computational modeling, and contributes to the far-reaching debate between symbolic and distributed approaches to cognition with an integrative proposal. I am in a privileged position to carry out this integration, since I have contributed top research in both distributional and formal semantics. "

1 499 805 €

Start date: 2017-02-01, End date: 2022-01-31

Our research interests lie in breaking new ground in studying mechanism-based functions of AP-1 (Fos/Jun) in vivo with the aim of obtaining a more global perspective on AP-1 in human physiology and disease/cancer. The unresolved issues regarding the AP-1 subunit composition will be tackled biochemically and genetically in various cell types including bone, liver and skin, the primary organs affected by altered AP-1 activity. I plan to utilize the knowledge gained on AP-1 functions in the mouse and transfer it to human disease. The opportunities here lie in exploiting the knowledge of AP-1 target genes and utilizing this information to interfere with pathways involved in normal physiology and disease/cancer. The past investigations revealed that the functions of AP-1 are an essential node at the crossroads between life and death in different cellular systems. I plan to further exploit our findings and concentrate on utilising better mouse models to define these connections. The emphasis will be on identifying molecular signatures and potential treatments in models for cancer, inflammatory and fibrotic diseases. Exploring genetically modified stem cell-based therapies in murine and human cells is an ongoing challenge I would like to meet in the forthcoming years at the CNIO. In addition, the mouse models will be used for mechanism-driven therapeutic strategies and these studies will be undertaken in collaboration with the Experimental Therapeutics Division and the service units such as the tumor bank. The project proposal is divided into 6 Goals (see also Figure 1): Some are a logical continuation based on previous work with completely new aspects (Goal 1-2), some focussing on in depth molecular analyses of disease models with innovative and unconventional concepts, such as for inflammation and cancer, psoriasis and fibrosis (Goal 3-5). A final section is devoted to mouse and human ES cells and their impact for regenerative medicine in bone diseases and cancer.

2 500 000 €

Start date: 2009-11-01, End date: 2015-10-31

The global marine ecosystem is being deeply altered by human activity. On the one hand, rising concentrations of atmospheric greenhouse gases are changing the physical and chemical state of the ocean, exerting pressure from the bottom up. Meanwhile, the global fishery has provided large economic benefits, but in so doing has restructured ecosystems by removing most of the large animal biomass, a major top-down change. Although there has been a tremendous amount of research into isolated aspects of these impacts, the development of a holistic understanding of the full interactions between physics, chemistry, ecology and economic activity might appear impossible, given the myriad complexities. This proposal lays out a strategy to assemble a team of trans-disciplinary expertise, that will develop a unified, data-constrained, grid-based modeling framework to represent the most important interactions of the global human-ocean system. Building this framework requires solving a series of fundamental problems that currently hinder the development of the full model. If these problems can be solved, the resulting model will reveal novel emergent properties and open the doors to a range of previously unexplored questions of high impact across a range of disciplines. Key questions include the ways in which animals interact with oxygen minimum zones with implications for fisheries, the impacts fish harvesting may have on nutrient recycling, spatio-temporal interactions between managed and unmanaged fisheries, and fundamental questions about the relationships between fish price, fishing cost, and multiple markets in a changing world. Just as the first coupled ocean-atmosphere models revealed a wealth of new behaviours, the coupled human-ocean model proposed here has the potential to launch multiple new fields of enquiry. It is hoped that the novel approach will contribute to a paradigm shift that treats human activity as one component within the framework of the Earth System.

1 600 000 €

Start date: 2016-07-01, End date: 2021-06-30

The use of renewable feedstocks by the chemical industry is fundamental due to both the depletion of fossil resources and the increasing pressure of environmental concerns. Biomass can act as a sustainable source of organic industrial chemicals; however, the establishment of a renewable chemical industry that is economically competitive with the present oil-based one requires the development of new processes to convert biomass-derived compounds into useful industrial materials following the principles of green chemistry. To achieve these goals, developments in several fields including heterogeneous catalysis are needed. One of the ways to accelerate the discovery of new potentially active, selective and stable catalysts is the massive use of computational chemistry. Recent advances have demonstrated that Density Functional Theory coupled to ab initio thermodynamics, transition state theory and microkinetic analysis can provide a full view of the catalytic phenomena. The aim of the present project is thus to employ these well-tested computational techniques to the development of a theoretical framework that can accelerate the identification of new catalysts for the conversion of biomass derived target compounds into useful chemicals. Since compared to petroleum-based materials-biomass derived ones are multifuncionalized, the search for new catalytic materials and processes has a strong requirement in the selectivity of the chemical transformations. The main challenges in the project are related to the high functionalization of the molecules, their liquid nature and the large number of potentially competitive reaction paths. The requirements of specificity and selectivity in the chemical transformations while keeping a reasonably flexible framework constitute a major objective. The work will be divided in three main work packages, one devoted to the properties of small molecules or fragments containing a single functional group; the second addresses competition in multiple functionalized molecules; and third is dedicated to the specific transformations of two molecules that have already been identified as potential platform generators. The goal is to identify suitable candidates that could be synthetized and tested in the Institute facilities.

1 496 200 €

Start date: 2010-10-01, End date: 2015-09-30