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Researcher
Daniele Raimondi
- Disciplines:Applied mathematics in specific fields, Computer architecture and networks, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences, Control systems, robotics and automation, Modelling, Design theories and methods, Mechatronics and robotics, Biological system engineering, Computer theory, Signal processing
Affiliations
- Dynamical Systems, Signal Processing and Data Analytics (STADIUS) (Division)
Member
From1 Aug 2020 → Today - ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics (Division)
Member
From1 Jan 2018 → 31 Jul 2020 - Department of Electrical Engineering (ESAT) (Department)
Member
From25 Sep 2017 → 25 Dec 2018
Projects
1 - 4 of 4
- A novel paradigm for Precision Medicine: sparse non-linear Neural Networks for end-to-end Genome InterpretationFrom1 Oct 2022 → TodayFunding: FWO senior postdoctoral fellowship
- Identifying disease genes and mechanisms through nonlinear fusion of omics dataFrom8 Sep 2020 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Development of Clinical Blockchain Network (WP1-3).From5 Jun 2020 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Nonlinear data fusion for arbitrary entity-relation graphs with application to genome interpretation for personalized medicineFrom1 Oct 2018 → 30 Sep 2021Funding: FWO fellowships
Publications
1 - 10 of 26
- Genome interpretation in a federated learning context allows the multi-center exome-based risk prediction of Crohn's disease patients(2023)
Authors: Daniele Raimondi, Nora Verplaetse, Yves Moreau
- Large sample size and nonlinear sparse models outline epistatic effects in inflammatory bowel disease(2023)
Authors: Nora Verplaetse, Antoine Passemiers, Yves Moreau, Daniele Raimondi
- Nonlinear data fusion over Entity-Relation graphs for Drug-Target Interaction prediction(2023)
Authors: Yves Moreau, Daniele Raimondi
- Prediction of Disordered Regions in Proteins with Recurrent Neural Networks and Protein Dynamics(2022)
Authors: Daniele Raimondi
- Fast and accurate inference of gene regulatory networks through robust precision matrix estimation.(2022)
Authors: Antoine Passemiers, Yves Moreau, Daniele Raimondi
Pages: 2802 - 2809 - Fast and accurate inference of gene regulatory networks through robust precision matrix estimation(2022)
Authors: Antoine Passemiers, Yves Moreau, Daniele Raimondi
Pages: 2802 - 2809 - From genotype to phenotype in Arabidopsis thaliana: in-silico genome interpretation predicts 288 phenotypes from sequencing data(2022)
Authors: Daniele Raimondi, Yves Moreau
- PyUUL provides an interface between biological structures and deep learning algorithms(2022)
Authors: Gabriele Orlando, Daniele Raimondi, Yves Moreau, Joost Schymkowitz, Frederic Rousseau
- HPMPdb: A machine learning-ready database of protein molecular phenotypes associated to human missense variants(2022)
Authors: Daniele Raimondi, Joost Schymkowitz, Frederic Rousseau, Yves Moreau
Pages: 167 - 174 - In silico prediction of in vitro protein liquid-liquid phase separation experiments outcomes with multi-head neural attention(2021)
Authors: Daniele Raimondi, Gabriele Orlando, Emiel Michiels, Ludo Van Den Bosch, Yves Moreau, Frederic Rousseau, Joost Schymkowitz
Pages: 3473 - 3479