output
20072026
most citedSingle-cell analysis of growth in budding yeast and bacteria reveals a common size regulation strategy

225 citations

Showing 2017Show all

8 papers · 1 filter

stat.ME2017

Variational Inference for Stochastic Block Models from Sampled Data

Timothée Tabouy, Pierre Barbillon, Julien Chiquet

This paper deals with non-observed dyads during the sampling of a network and consecutive issues in the inference of the Stochastic Block Model (SBM). We review sampling designs an…

q-bio.MN2017★ 8 cited

Plant responses to auxin signals: an operating principle for dynamical sensitivity yet high resilience

Silvia Grigolon, Barbara Bravi, Olivier C. Martin

Plants depend on the signaling of the phytohormone auxin for their development and for responding to environmental perturbations. The associated biomolecular signaling network invo…

q-bio.PE2017

Assessing the role of the spatial scale in the analysis of lagoon biodiversity. A case-study on the macrobenthic fauna of the Po River Delta

Giovanna Jona Lasinio, Alessio Pollice, Eric Marcon +1

The analysis of benthic assemblages is a valuable tool to describe the ecological status of transitional water ecosystems, but species are extremely sensitive and respond to both m…

math.ST2017★ 75 cited

Clustering transformed compositional data using K-means, with applications in gene expression and bicycle sharing system data

Antoine Godichon-Baggioni, Cathy Maugis-Rabusseau, Andrea Rau

Although there is no shortage of clustering algorithms proposed in the literature, the question of the most relevant strategy for clustering compositional data (i.e., data made up…

q-bio.OT2017★ 40 cited

Interest of Integrating Spaceborne LiDAR Data to Improve the Estimation of Biomass in High Biomass Forested Areas

Mohammad El Hajj, Nicolas Baghdadi, Ibrahim Fayad +3

Mapping forest AGB (Above Ground Biomass) is of crucial importance to estimate the carbon emissions associated with tropical deforestation. This study proposes a method to overcome…

stat.ME2017★ 7 cited

Online Sequential Monte Carlo smoother for partially observed stochastic differential equations

Pierre Gloaguen, Marie-Pierre Etienne, Sylvain Le Corff

This paper introduces a new algorithm to approximate smoothed additive functionals for partially observed stochastic differential equations. This method relies on a recent procedur…