2024
Zero-shot animal behavior classification with image-text foundation models, G Dussert, V Miele, C. Van Reeth, A. Delestrade, S Dray, S Chamaille-Jammes, BioRxiv
Being confident in confidence scores: calibration in deep learning models for camera trap image sequences, G Dussert, S Chamaille-Jammes, S Dray, V Miele, Remote Sening for Ecology and Evolution
2023
Mobbing calls of seven species of Parids under the paradigm of the FME-D combination, A Salis, T Lengagne, V Miele, K Sieving, H Henry, JP Léna, ResearchSquare
DeepFaune : vers un traitement automatisé des images de pièges photographiques, S Chamaillé-Jammes, V Miele, N Rigoudy, G Dussert, B Spataro, Biodiversité, des clés pour agir 4
Nine tips for ecologists using machine learning, M Desprez, V Miele, O Gimenez, arXiv:2305.10472
The DeepFaune initiative: a collaborative effort towards the automatic identification of the European fauna in camera-trap images, N Rigoudy, G Dussert, the DeepFaune consortium, B Spataro, V Miele, S Chamaillé Jammes, European Journal of Wildlife Research
Quantifying the overall effect of biotic interactions on species communities along environmental gradients, M Ohlmann, G Poggiato, S Dray, W Thuiller, C Matias, V Miele, Ecological Modelling
2022
Using latent block models to detect structure in ecological networks, J Aubert, P Barbillon, S Donnet, V Miele, ISTE Editions
2021
An appraisal of graph embeddings for comparing trophic network architectures, C Botella, S Dray, C Matias, V Miele, W Thuiller, Methods in Ecology and Evolution
Revisiting animal photo‐identification using deep metric learning and network analysis, V Miele, G Dussert, B Spataro, S Chamaillé-Jammes, D Allainé, C. Bonenfant, Methods in Ecology and Evolution
Images, écologie et deep learning, V Miele, S Dray, O Gimenez, Regards sur la biodiversité - Société Française d’Écologie et d’Évolution
2020
Core-periphery structure in mutualistic networks: an epitaph for nestedness?, AM Martín González, DP Vázquez, R Ramos-Jiliberto, SH Lee, V Miele, bioRxiv, 2020.04. 02.021691
Deep learning for species identification of modern and fossil rodent molars, V Miele, G Dussert, T Cucchi, S Renaud, bioRxiv
Core–periphery dynamics in a plant–pollinator network V Miele, R Ramos‐Jiliberto, DP Vázquez, Journal of Animal Ecology
2019
Nine quick tips for analyzing network data, V Miele, C Matias, S Robin, S Dray PLOS Computational Biology 15 (12), e1007434
Non-trophic interactions strengthen the diversity—functioning relationship in an ecological bioenergetic network model, V Miele, C Guill, R Ramos-Jiliberto, S Kéfi PLoS Computational Biology 15 (8), e1007269
Global survey of mobile DNA horizontal transfer in arthropods reveals Lepidoptera as a prime hotspot, D Reiss, G Mialdea, V Miele, DM de Vienne, J Peccoud, C Gilbert, L Duret, ... PLoS genetics 15 (2), e1007965
Diversity indices for ecological networks: a unifying framework using Hill numbers, M Ohlmann, V Miele, S Dray, L Chalmandrier, L O’Connor, W Thuiller, Ecology Letters
2018
Playing hide and seek with repeats in local and global de novo transcriptome assembly of short RNA-seq reads, L Lima, B Sinaimeri, G Sacomoto, H Lopez-Maestre, C Marchet, V Miele..., Algorithms for molecular biology 12 (1), 1-19
2017
Revealing the hidden structure of dynamic ecological networks, V Miele, C Matias Royal Society open science 4 (6), 170251
Inferring the timing of territoriality and rut in male roe deer from movements? Some preliminary results-and new perspectives, N Morellet, V Miele, C Bonenfant, EURODEER meeting
Ecological networks to unravel the routes to horizontal transposon transfers, S Venner, V Miele, C Terzian, C Biémont, V Daubin, C Feschotte, ... PLoS biology 15 (2), e2001536
Réseaux et connectivité EE Cossart, C Fontaine, G Marchand, M Balasse, S Bréhard, C Manen, ...V Miele,... Prospectives de l’Institut Écologie et environnement du CNRS, 187-193
Statistical clustering of temporal networks through a dynamic stochastic block model, C Matias, V Miele Journal of the Royal Statistical Society: Series B (Statistical Methodology)
2016
Colib’read on galaxy: a tools suite dedicated to biological information extraction from raw NGS reads, Y Le Bras, O Collin, C Monjeaud, V Lacroix, É Rivals, C Lemaitre, V Miele, ... GigaScience 5 (1), s13742-015-0105-2
How structured is the entangled bank? The surprisingly simple organization of multiplex ecological networks leads to increased persistence and resilience, S Kéfi, V Miele, EA Wieters, SA Navarrete, EL Berlow, PLoS biology 14 (8), e1002527
Fruiting strategies of perennial plants: a resource budget model to couple mast seeding to pollination efficiency and resource allocation strategies, S Venner, A Siberchicot, PF Pélisson, E Schermer, MC Bel-Venner, ...V Miele..., The American Naturalist 188 (1), 66-75
Calcul parallèle avec R, V Miele, V Louvet, EDP Sciences
2015
DNA physical properties and nucleosome positions are major determinants of HIV-1 integrase selectivity, M Naughtin, Z Haftek-Terreau, J Xavier, S Meyer, M Silvain, ...V Miele..., PloS one 10 (6), e0129427
2014
Navigating in a sea of repeats in rna-seq without drowning, G Sacomoto, B Sinaimeri, C Marchet, V Miele, MF Sagot, V Lacroix, International Workshop on Algorithms in Bioinformatics, 82-96
Spatially constrained clustering of ecological networks, V Miele, F Picard, S Dray, Methods in Ecology and Evolution 5 (8), 771-779
Fast and parallel algorithm for population-based segmentation of copy-number profiles, G Rigaill, V Miele, F Picard, Computational Intelligence Methods for Bioinformatics and Biostatistics
2013
New developments in KisSplice: Combining local and global transcriptome assemblers to decipher splicing in RNA-seq data, A Julien-Laferriere, G Sacomoto, R Chikhi, E Scaon, D Parsons, MF Sagot, ...V Miele..., Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM)
2012
High-quality sequence clustering guided by network topology and multiple alignment likelihood, V Miele, S Penel, V Daubin, F Picard, D Kahn, L Duret, Bioinformatics 28 (8), 1078-1085
2011
Ultra-fast sequence clustering from similarity networks with SiLiX, V Miele, S Penel, L Duret, BMC bioinformatics 12, 1-9
2010
Strategies for online inference of model-based clustering in large and growing networks, H Zanghi, F Picard, V Miele, C Ambroise, The Annals of Applied Statistics
2009
Deciphering the connectivity structure of biological networks using MixNet, F Picard, V Miele, JJ Daudin, L Cottret, S Robin, BMC bioinformatics 10 (6), 1-11
2008
Fast online graph clustering via Erdős–Rényi mixture, H Zanghi, C Ambroise, V Miele, Pattern recognition 41 (12), 3592-3599
DNA physical properties determine nucleosome occupancy from yeast to fly, V Miele, C Vaillant, Y d'Aubenton-Carafa, C Thermes, T Grange, Nucleic acids research 36 (11), 3746-3756
2006
A reversible jump Markov chain Monte Carlo algorithm for bacterial promoter motifs discovery, P Nicolas, AS Tocquet, V Miele, F Muri, Journal of Computational Biology 13 (3), 651-667
2005
seq++: analyzing biological sequences with a range of Markov-related models, V Miele, PY Bourguignon, D Robelin, G Nuel, H Richard, Bioinformatics 21 (11), 2783-2784