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Content archived on 2024-06-18

Statistical Network-based Inference for Proteomics Experiment Reasoning

Objective

Experimental proteomics is a promising and growing domain, as state-of-the-art equipment allows for accurate, fast and environment-friendly research and diagnostics. However, current high performance experimental equipment is often complex, making setting up experiments and interpreting the results non-trivial.
Currently available models often are inaccurate, consider a single experimental step in isolation, and don't adapt to the specific characteristics of the equipment used.
This PoC project aims at offering software, support and training for experimental proteomics based on data mining techniques developed in the ErcStG project MiGraNT. This technology allows for accurately modeling the characteristics of the experimental steps and provides advanced global inference techniques which can be applied for designing experiments, interpreting results and other forms of support useful for scientific discovery and quality control.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

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Call for proposal

ERC-2013-PoC
See other projects for this call

Host institution

KATHOLIEKE UNIVERSITEIT LEUVEN
EU contribution
€ 149 800,00
Address
OUDE MARKT 13
3000 Leuven
Belgium

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Region
Vlaams Gewest Prov. Vlaams-Brabant Arr. Leuven
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Beneficiaries (1)