Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Pan-genome Graph Algorithms and Data Integration (PANGAIA)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Germany,Italy,Slovakia,China,France,United States,Netherlands,Canada,Japan,United Kingdom
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2019, 2019)
Start date: 2020-01-01
End date: 2025-06-30
Duration (months): 66.0
Total project cost (EUR): 1140800.0
EU funding (EUR): 1140800.0
Participants: 13
Project status: SIGNED

Genomes are strings over the letters A,C,G,T, which represent nucleotides, the building blocks of DNA. In view of ultra-large amounts of genome sequence data emerging from ever more and technologically rapidly advancing genome sequencing devices—in the meantime, amounts of sequencing data accrued are reaching into the exabyte scale—the driving, urgent question is: how can we arrange and analyze these data masses in a formally rigorous, computationally efficient and biomedically rewarding manner? Graph based data structures have been pointed out to have disruptive benefits over traditional sequence based structures when representing pan-genomes, sufficiently large, evolutionarily coherent collections of genomes. This idea has its immediate justification in the laws of genetics: evolutionarily closely related genomes vary only in relatively little amounts of letters, while sharing the majority of their sequence content. Graph-based pan-genome representations that allow to remove redundancies without having to discard individual differences, make utmost sense. In this project, we will put this shift of paradigms—from sequence to graph based representations of genomes—into full effect. As a result, we can expect a wealth of practically relevant advantages, among which arrangement, analysis, compression, integration and exploitation of genome data are the most fundamental points. In addition, we will also open up a significant source of inspiration for computer science itself.

Keywords: algorithmic bionformatics,computational pan genomics,graph algorithms,data structures and indexing,computational comparative genomics,genome data science
Highly Reactive Low-valent Aluminium Complexes and their Application in Synthesis and Catalysis (ALLOWE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Synthetic Chemistry and Materials
Panel description: New materials and new synthetic approaches, structure-properties relations, solid state chemistry, molecular architecture, organic chemistry
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2020-COG, 2020)
Start date: 2021-06-01
End date: 2026-05-31
Duration (months): 60.0
Total project cost (EUR): 1997750.0
EU funding (EUR): 1997750.0
Participants: 1
Project status: SIGNED

This ERC-CoG 2020 proposal, ALLOWE outlines a strategy for the development of low-valent aluminium systems through their synthesis, isolation, and reactivity investigation of neutral, ambiphilic, low-valent aluminium compounds, denoted “alumylenes”. Their dimeric form “dialumenes” featuring an aluminium-aluminium double bond will also be within the scope of the project. These low-valent aluminium species are expected to provide, along with greater understanding of the fundamental behaviour of low-valent aluminium, a varied and deep reactivity profile. These highly reactive compounds will offer a cheap, sustainable and non-toxic alternative to the current transition metal-based industrial chemical processes. The proposed scheme of work begins with the synthesis of neutral alumylenes and dialumenes, respectively. This will be achieved through the use of donor ligands (i.e. N-heterocyclic carbenes) and substituents with differing electronic and steric properties. With these compounds in hand, the reactivity towards small molecules will be investigated along with development of low-valent aluminium based catalysts. Furthermore, incorporation of transition metals into these aluminium systems will be targeted as these may possess unique and interesting properties. Established methodologies such as reductive dehalogenation or reductive dehydrohalogenation will provide access to novel low-valent aluminium compounds bearing bulky substituents and donor ligands. The synthetic portion of the work will also be supported by theoretical calculations. The outcome of ALLOWE will provide (i) in-depth insight and understanding into low-valent aluminium’s bonding nature, particularly emphasis laid on ambiphilic aluminium center (ii) plethora of striking reactivity towards transition metal free stoichiometric and catalytic activation of small molecules, and (iii) various potential applications in aluminium-based material chemistry.

Keywords: synthetic molecular chemistry,inorganic molecular chemistry,main group chemistry,aluminium,low valent species
RLTProFood - Remote Lighting Technology for processing and production of food (RLTProFood)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Action type: SME instrument
Countries involved: Italy
Call: Resource-efficient eco-innovative food production and processing (H2020-SMEINST-1-2015, 2015)
Start date: 2015-10-01
End date: 2016-03-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Food processing and production industry in the market of fresh organic food are facing with the challenges, in their working facilities, of improving food safety and quality while achieving a significant reduction in energy use and waste generation. The RLTProFood project aims at a feasibility assessment for a product, the RLT (Remote Lighting technology), that exploiting the energy saver, efficient, and environmental friendly LEDs (Light Emitting Diodes) technology, together with customized optical systems, delivers a lighting system for the food working facilities addressing such challenges. The product is a compact system, realized with sustainable components and with a structure that allows to remotely deliver different kinds of light (e.g., visible, and ultraviolet) without losing performance, according customers’ needs. It is easily installed in food industry facilities (e.g., production line or cooking oven), avoiding, with its design, the direct contact with the food. Currently it has two main settings: the LED visible light RLT contributes to optimize the process of lighting food facilities, the UV LED RLT provides a sterilization and germicidal treatment. The product aims to reach the EU market of organic fresh food producers and in particular of vegetables, fruits, dairy, bakery and fresh pasta, where the beneficial effects of the RLT in its two main configurations allow for energy and waste reduction, while improving food safety and quality. The feasibility assessment in the Phase 1 includes: (i) economic viability of the RLT system with its main settings in the EU organic fresh food market with market analysis and a commercialization plan and (ii) technical feasibility of the LED UV RLT developing a pilot application for testing the product in an industry environment. Phase 2 funding could improve the economic assessment of the product in the EU market and implement the pilot application for porting the LED UV RLT in the market.

Keywords: food processing,energy saver solutions,food quality
Fuel and chemicals from lignin through enzymatic and chemical conversion (FALCON)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Biotechnology
Action type: Research and Innovation actions
Countries involved: Italy,Germany,Finland,Switzerland,Belgium,Finland,France,Netherlands,Netherlands
Call: Bioconversion of non-agricultural waste into biomolecules for industrial applications (H2020-NMBP-BIO-2016, 2016)
Start date: 2017-01-01
End date: 2020-12-31
Duration (months): 48.0
Total project cost (EUR): 6555883.75
EU funding (EUR): 6148783.75
Participants: 9
Project status: CLOSED

The transition to a biobased economy puts strong challenges on researchers and industry to develop sustainable processes. 2G biofuel plants use waste streams as substrates, but themselves generate a new waste stream of lignin-rich sludge that is left after saccharification of the carbohydrates. This waste stream is expected to exponentially increase with an increasing number of 2G bioethanol plants being built, according to a report of the International Energy Agency. FALCON aims to convert this lignin-rich industrial waste of 2G biofuel plants to higher value products, in particular shipping fuels, fuel additives and chemical building blocks. This would be the next consecutive step in turning waste to products, thus minimizing waste and simultaneously providing new alternatives for fossil resource based processes. The FALCON process is based on enzymatic and mild chemical conversion of the lignin waste stream, providing a more environmentally friendly approach to the production of fuels and chemical building blocks. FALCON takes full advantage of the lessons learned over the last 150 years in the petrochemical industry with respect to design of the processes. This implies an initial treatment at the 2G bioethanol plant, converting the waste to a lignin oil that can be more easily transported and also directly used as a low sulphur shipping fuel. It will be further converted into fuel additives and chemical building blocks in centralized facilities. To achieve this, FALCON has formed a consortium of industry (3), SME (4) and academics (2) covering the whole value chain from a 2G biofuel plant delivering the lignin waste to enzyme producers, chemists and process engineers to depolymerize the lignin to oil. End-users are a fuel and chemicals producer and a ship engine developer. This unique combination of expertise and infrastructure will ensure the development of three new value chains with a strong emphasis on the economical sustainability.
Scaffold hybridization approach targeting PPIs (SHAPPI)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-05-01
End date: 2019-04-30
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

Protein-protein interactions (PPIs) control all cellular processes relevant to health and disease, hence an outstanding challenge in chemical biology is to develop generic approaches for PPI inhibition. Such inhibitors (or chemical probes) represent unique tools to understand biological processes and starting points for drug discovery, for treatment of multiple illnesses for which effective treatments don’t currently exist e.g. cancer. SHAPPI will allow Zsofia Hegedus (the fellow) to join the laboratory of Andrew Wilson (host supervisor) at the University of Leeds (Host) and develop research expertise in the area of inhibiting protein-protein interactions. In doing so, she will (a) enhance her prospects to become an independent academic group leader and (b) address the need to train researchers in this key area of chemical biology and (c) develop cutting edge methods that advance peptidomimetic approaches for inhibition of protein-protein interactions. Scaffold hybridization will allow the combination of molecular scaffolds capable of hot spot mimicry with molecules that influence selectivity or potency. In combination with reversible chemistry this will allow generation of dynamic combinatorial libraries of rapid identification of selective and potent inhibitors. The fellowship will explore proteomimetic-peptide conjugates and peptide-small molecule dynamic combinatorial libraries to accelerate development of selective PPI inhibitors using two model interactions; HIF-1α/p300 and BID/BAX, both of which represent important targets for anticancer therapy.

Keywords: dynamic covalent chemistry,peptidomimetics,protein protein interaction inhibitors
Enhancing the scientific capacity of the Faculty of Chemistry and Pharmacy at Sofia University as leading regional research and innovation centre in the area of advanced functional materials (Materials Networking)

Framework: Horizon 2020 — Spreading excellence and widening participation
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Action type: Coordination and support actions
Countries involved: Spain,Germany,Bulgaria,United Kingdom
Call: Twinning (H2020-TWINN-2015, 2015)
Start date: 2016-09-01
End date: 2019-08-31
Duration (months): 36.0
Total project cost (EUR): 1000000.0
EU funding (EUR): 1000000.0
Participants: 4
Project status: CLOSED

The main objective of the TWINNING project is enhancement the scientific and technological capacity of the Faculty of Chemistry and Pharmacy at Sofia University (FCP-SU) and raising the research profile of the Faculty and its staff in the field of advanced functional materials via networking with three World-wide leading institutions – Department of Materials Science & Metallurgy, University of Cambridge, Max-Plank Institute of Polymer Research and Faculty of Chemistry, University of Barcelona. Faculty of Chemistry and Pharmacy at SU is a leading research centre in functional materials in Bulgaria and its networking and collaboration with global leaders in this research field will help in developing its potential to become European-wide known centre with increasing research and innovation contributions and achievements. Such achievements will increase the participation of the teams from FCP-SU in European and international projects and will promote higher performance of other research institutions in Bulgaria. The partners from research intensive institutions have high international reputation and expertise in the various aspects of synthesis, modification, characterization, testing and modelling of functional materials. Additional advantage for the FCP-SU is that the leading research partners have complementary competences ranging from various fields of Chemistry to broad area of Materials Science. Based on the expertise and achievements of the research groups in FCP-SU, the present project will contribute to two of the priority areas of the Bulgaria’s Smart Specialization Strategy with relevant thematic priorities “Materials for clean energy and environment protection” and “Materials with pharmaceutical and medical applications”. The work program of the project is distributed in 5 work packages including the main activities, envisaged in the work programme of the Call.

Keywords: material science,scientific excellence,networking,advanced materials,bulgarian smart specialization strategy,chemistry
Neural-based solution to boost drug preclinical research success (MolPredict)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-06-01
End date: 2018-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The competitiveness of the R&D process in this industry has been steadily declining during the past two decades. Whereas in 2000 the average cost for developing a new drug was close to €1 billion, in 2015 the estimated cost was €2.58 billion, a 150% increase. Consequently, the different actors of the pharmaceutical R&D industry have an urgent need to improve their effectiveness to develop new drugs. In this sense, the early stage of the R&D process shows the greatest potential to increase the success rate of new drug candidates, as it is in this phase where candidate molecules are selected for further testing in humans. Computer Aided Drug Design (CADD) is the most cost-effective tool for drug discovery. These technologies allow researchers to screen large databases of molecules and simulate its interaction in vivo. However, they are extremely intensive in computational resources. As a result, existing solutions have to implement simplifications in the simulations in order to incur acceptable computational times. These simplifications come at the cost of accuracy, finding a low rate of bioactive molecules that, in addition, usually fail during clinical trials. Pharmacelera aims at creating a new computing standard for Computer-Aided Drug Design (CADD) through an open machine learning platform that enables accurate prediction of molecular properties of candidate molecules based on quantum-mechanics (QM) calculations during drug development. By providing early stage ADME-Tox analysis, thus dramatically reducing the failure rate of the drug design process. In addition, by combining HPC, new disruptive molecular modelling techniques (computational chemistry) and machine learning, PharmAgile will be 20x faster and 10x more precise than any existing solution. Consequently, PharmAgile will be able to reduce the overall costs of drug development by up to 19% and the drug development time up to 8%. This translates into $335 million and 2 years saved per new approved drug.

Keywords: drug development,adme tox prediction,advanced mollecular modelling,quantum computing,predictive models,one shot learning
Zero Defect Manufacturing Platform (ZDMP)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Germany,Spain,Germany,Spain,Spain,Italy,Italy,Austria,Germany,Italy,Italy,Finland,Romania,Romania,Bulgaria,France,Czechia,United Kingdom,Portugal,United Kingdom,United Kingdom,Portugal,Portugal,Portugal,Portugal
Call: Digital Manufacturing Platforms for Connected Smart Factories (H2020-DT-2018-1, 2018)
Start date: 2019-01-01
End date: 2023-06-30
Duration (months): 54.0
Total project cost (EUR): 19482804.32
EU funding (EUR): 16204368.66
Participants: 38
Project status: SIGNED

Smart, SME Friendly, open, Zero-Defect Manufacturing Reference Platform, Apps, SDK, and Marketplace for Product and Process Quality in any factory for achieving excellence in European and Global Manufacturing The ZDMP project combines state of the art technological approaches based on commercial grade standard or open-source or previous-project software with an innovative integration concept based on proven and integrating technologies. It provides Process and Product Quality support on top of a platform layer. These all can utilise ZDMP core services which can also be used to build ZD Apps which are placed on the ZD Marketplace. The ultimate aim is to establish a sustainable business and technological approach at the end of the project and launch “ZDMP Limited” assisted by the possibility of a crowdsourcing approach and ZDMP ambassadors. ZDMPs pan-European consortium entails ICT Technology SMEs (ICE, ASC, SOFT), Manufacturing/ZD Technology SMEs (PROF, CET, VSYS), Technology Corporates (SAG, Scale Focus), 4 Sector and Cross-Domain Use cases (14 Partners SME/Large from Automotive, Machine Tools, Construction, Electronics), Researchers/Associations (IKERLAN, ITI, UNINOVA, TUT, and UPV), specialists (DIN – German Standards, Rooter – Regulation, UOS-ITI – Call Management). ZDMP also is supported by the Coordinating partners of FOF projects CREMA, vf-OS, and C2NET.

Keywords: zero defects,industry 4 0
Magnetoelectric Ultra-low-power Spin-wave Transducers (MUST)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Belgium
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-04-01
End date: 2020-03-31
Duration (months): 24.0
Total project cost (EUR): 160800.0
EU funding (EUR): 160800.0
Participants: 1
Project status: CLOSED

The ability to control the magnetisation of magnetic materials by electric fields is highly desirable from both scientific and technological viewpoints. Magnetoelectric materials are materials that link electric fields to magnetic properties via mechanical degrees of freedom. Using such materials, we propose to control ultrafast magnetisation dynamics by GHz electric fields and develop novel hybrid electro-magneto-mechanical devices at the nanoscale. More specifically, we propose magnetoelectric devices that act as transducers between electrical and magnetic domains. MUST will use magnetoelectric composites, consisting of piezoelectric and magnetostrictive bilayers, to generate spin waves or excite ferromagnetic resonance using electric signals via mechanical strain. MUST will investigate geometries exerting in-plane or out-of-plane stress to achieve the highest magnetoelectric coupling and enable the most energy efficient spin wave generation and detection. Moreover, MUST intends to study magnetoelectric composites at the magnetoacoustic resonance, with the promise of a strongly enhanced magnetoelectric coupling. The targeted small lateral scale (500 nm) and high operation frequency (bandwidth above 20 GHz) bring such transducers to the frontier of ultrasound devices. Furthermore, MUST will experimentally demonstrate a novel approach for spin wave excitation by the vibration of a magnetic domain wall induced by mechanical actuation in a magnetoelectric transducer. By an interdisciplinary approach combining magnonics and ultrasound devices, as well as nanofabrication, MUST intends to enhance the understanding of the almost unexplored territory of magnetoelectric phenomena at the nanoscale and at GHz frequencies and establish a versatile magnetoelectric transducer platform that can be used in various magnonic (logic) applications.

Keywords: magnetoelectrics,magnetostriction,magnonics,spin waves,magnetic domain walls