One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties. - Chloé-Agathe Azencott; Alexandre Ksikes; S. Joshua Swamidass; Jonathan H. Chen; Liva Ralaivola; Pierre Baldi (J. Chem. Inf. Model., 2007)

Influence Relevance Voting: An Accurate And Interpretable Virtual High Throughput Screening Method. - S. Joshua Swamidass; Chloé-Agathe Azencott; Ting-Wan Lin; Hugo Gramajo; Shiou-Chuan Tsai; Pierre Baldi (J. Chem. Inf. Model., 2009)

Bridging the Gap Between Neural Network and Kernel Methods: Applications to Drug Discovery. - Pierre Baldi; Chloé-Agathe Azencott; Sanjay Joshua Swamidass (WIRN, 2010)

A CROC stronger than ROC: measuring, visualizing and optimizing early retrieval. - Sanjay Joshua Swamidass; Chloé-Agathe Azencott; Kenny Daily; Pierre Baldi (Bioinform., 2010)

Learning to Predict Chemical Reactions. - Matthew A. Kayala; Chloé-Agathe Azencott; Jonathan H. Chen; Pierre Baldi (J. Chem. Inf. Model., 2011)

Efficient network-guided multi-locus association mapping with graph cuts. - Chloé-Agathe Azencott; Dominik G. Grimm; Mahito Sugiyama; Yoshinobu Kawahara; Karsten M. Borgwardt (Bioinform., 2013)

Multi-Task Feature Selection on Multiple Networks via Maximum Flows. - Mahito Sugiyama; Chloé-Agathe Azencott; Dominik G. Grimm; Yoshinobu Kawahara; Karsten M. Borgwardt (SDM, 2014)

Multitask Feature Selection with Task Descriptors. - Victor Bellon; Véronique Stoven; Chloé-Agathe Azencott (PSB, 2016)

Network-Guided Biomarker Discovery. - Chloé-Agathe Azencott (CoRR, 2016)

Network-Guided Biomarker Discovery. - Chloé-Agathe Azencott (Machine Learning for Health Informatics, 2016)

Machine learning and genomics: precision medicine vs. patient privacy. - Chloé-Agathe Azencott (CoRR, 2018)

kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection. - Lotfi Slim; Clément Chatelain 002; Chloé-Agathe Azencott; Jean-Philippe Vert (ICML, 2019)

Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data. - Héctor Climente-González; Chloé-Agathe Azencott; Samuel Kaski; Makoto Yamada (Bioinform., 2019)

Machine learning tools for biomarker discovery. (Outils d'apprentissage statistique pour la découverte de biomarqueurs). - Chloé-Agathe Azencott (2020)

Boosting GWAS using biological networks: A study on susceptibility to familial breast cancer. - Héctor Climente-González; Christine Lonjou; Fabienne Lesueur; GENESIS study group; Dominique Stoppa-Lyonnet; Nadine Andrieu; Chloé-Agathe Azencott (PLoS Comput. Biol., 2021)

EDEN : An Event DEtection Network for the annotation of Breast Cancer recurrences in administrative claims data. - Elise Dumas; Anne-Sophie Hamy; Sophie Houzard; Eva Hernandez; Aullène Toussaint; Julien Guerin; Laetitia Chanas; Victoire de Castelbajac; Mathilde Saint-Ghislain; Beatriz Grandal; Eric Daoud; Fabien Reyal; et al. (CoRR, 2022)

Where Do We Stand in Regularization for Life Science Studies? - Veronica Tozzo; Chloé-Agathe Azencott; Samuele Fiorini; Emanuele Fava; Andrea Trucco; Annalisa Barla (J. Comput. Biol., 2022)

Detection of genes with differential expression dispersion unravels the role of autophagy in cancer progression. - Christophe Le Priol; Chloé-Agathe Azencott; Xavier Gidrol (PLoS Comput. Biol., 2023)

pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods. - Abdelkader Behdenna; Maximilien Colange; Julien Haziza; Aryo Gema; Guillaume Appé; Chloé-Agathe Azencott; Akpéli Nordor (BMC Bioinform., 2023)

Drug-Target Interactions Prediction at Scale: The Komet Algorithm with the LCIdb Dataset. - Gwenn Guichaoua; Philippe Pinel; Brice Hoffmann; Chloé-Agathe Azencott; Véronique Stoven (J. Chem. Inf. Model., 2024)

Assessing Random Forest self-reproducibility for optimal short biomarker signature discovery. - Ahmed Debit; Christophe Poulet; Claire Josse; Guy Jerusalem; Chloé-Agathe Azencott; Vincent Bours; Kristel Van Steen (Briefings Bioinform., 2025)