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ELECTION SERIES #3
The traditional pencil-and-paper method to mark your vote in the polling booth has been gradually replaced by electronic voting machines in many countries, in Europe and beyond. Ensuring the security of electronic voting machines and quelling fears of vote-rigging have become ever more important. One ERC-funded researcher has been working tirelessly to develop such an e-voting system through two projects, SEEVS and its follow-up SEEVCA.
The increasing development of wearable technology sparks the need for new, innovative ways to interact with our shiny gadgets. Deviating from the conventional approach based on touch-sensitive devices, Prof. Jürgen Steimle aims at producing body-worn user interfaces that can be applied directly on the skin. Highly personalised, biocompatible and ultrathin, these devices will seamlessly blend with the human skin to create a technological extension of our body.
The amount of currently available biomedical data is overwhelming. Large databases exist at different scales, from genes, to proteins, to patients' histories. But what do scientists do with all this information? Serbian-born Professor Nataša Pržulj, from University College London, works with Big Data to establish patterns and gain knowledge that could revolutionise how we treat diseases.
Colorectal cancer (CRC) is the second most common cause of cancer-related deaths. European researchers developed novel ex vivo three-dimensional organoid cultures that replicate genetic events in CRC, as tools to test novel therapeutics.
Travellers already benefit from applications harnessing data from sensor networks and smartphone users. They calculate alternative routes, help plan carpooling routes, or support the optimisation of public transport. With her ERC grant, Prof. Vana Kalogeraki works on a comprehensive software framework that will simplify the development of such mobile human-centred systems and make them more predictable and reliable.
Maria Brandão de Vasconcelos, together with her colleague Filipa Matos Baptista, Henrique Veiga-Fernandes (ERC grantee), Diogo Fonseca Pereira and Sílvia Arroz Madeira, founded StemCell2MAX in 2015. The company is a biotechnology start-up, specialised in cell based therapies, including novel solutions to multiply the scarcely available blood stem cells, addressing an enormous demand for research and cancer treatment. StemCell2MAX technology is based on Prof. Veiga-Fernandes's ground-breaking discoveries in hematopoietic stem cell biology.
Originally published in March 2017 as part of the multimedia campaign "ERC - 10 years – 10 portraits."
An ERC-funded project has significantly increased understanding of the crucial role that microorganisms in the gut play in maintaining health. The findings have since led to a patent, as well as a follow-on project that could one day steer the way to new targeted treatments for diseases, including cancer.
Through her work with the fruit fly Drosophila santomea, Dr Virginie Orgogozo aims to answer one of the most challenging questions of modern evolutionary biology: how do observable characteristics change between species and yet remain stable in a given species?
Haematopoietic Stem Cells (HSCs) are blood cells located in the bone marrow. These cells are extensively used in research to develop treatments for many severe diseases, including HIV and multiple sclerosis, and their transplant is a key therapy for certain types of cancer like leukemia and multiple myeloma. However, the use of HSCs is seriously constrained by their limited availability since growing them in the lab does not produce very large quantities. There is therefore an urgent need for methods allowing scientists to multiply HSCs, without losing any of their properties.
Is a precise answer always better than a slightly less detailed one? Not necessarily. Some problems could take forever to compute and tie up vast IT capacity. Where solutions are needed urgently, e.g. in business or manufacturing, near-enough can be more than enough. ERC-funded research has produced a library of fast, powerful approximation algorithms.