activity
20132026
most citedState-of-the-Art Methods for Exposure-Health Studies: results from the Exposome Data Challenge Event

90 citations · 128 across the 6 of their papers we have counts for

collaborators

6 papers

stat.AP2026

Data Shared Neighbourhood Selection for multi-condition network inference

Blanche Francheterre, Ruben Colindres Zuehlke, Vivian Viallon +2

External stresses may affect both the circulating levels of specific biomarkers and disturb the correlation structures across molecular entities. The contribution of both types of…

cs.LG2025★ 1 cited

An AI-driven framework for the prediction of personalised health response to air pollution

Nazanin Zounemat-Kermani, Sadjad Naderi, Claire H. Dilliway +10

Air pollution is a growing global health threat, exacerbated by climate change and linked to cardiovascular and respiratory diseases. While personal sensing devices enable real-tim…

stat.ME2023★ 4 cited

Automated calibration of consensus weighted distance-based clustering approaches using sharp

Barbara Bodinier, Dragana Vuckovic, Sabrina Rodrigues +3

In consensus clustering, a clustering algorithm is used in combination with a subsampling procedure to detect stable clusters. Previous studies on both simulated and real data sugg…

stat.AP2022★ 90 cited

State-of-the-Art Methods for Exposure-Health Studies: results from the Exposome Data Challenge Event

Léa Maitre, Jean-Baptiste Guimbaud, Charline Warembourg +7

The exposome recognizes that individuals are exposed simultaneously to a multitude of different environmental factors and takes a holistic approach to the discovery of etiological…

stat.ME2021★ 33 cited

Automated calibration for stability selection in penalised regression and graphical models

Barbara Bodinier, Sarah Filippi, Therese Haugdahl Nost +2

Stability selection represents an attractive approach to identify sparse sets of features jointly associated with an outcome in high-dimensional contexts. We introduce an automated…

stat.CO2013

The TimeMachine for Inference on Stochastic Trees

Gianluca Campanella, Maria De Iorio, Ajay Jasra +1

The simulation of genealogical trees backwards in time, from observations up to the most recent common ancestor (MRCA), is hindered by the fact that, while approaching the root of…