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Network-Guided Biomarker Discovery

Chloé-Agathe Azencott
Machine Learning for Health Informatics, 9605, , 2016, Lecture Notes in Computer Science, ⟨10.1007/978-3-319-50478-0_16⟩
Chapitre d'ouvrage hal-01427118v1

A systematic analysis of gene-gene interaction in multiple sclerosis

Lotfi Slim , Clément Chatelain , Hélène de Foucauld , Chloé-Agathe Azencott
BMC Medical Genomics, 2022, 15 (1), pp.100. ⟨10.1186/s12920-022-01247-3⟩
Article dans une revue hal-03122122v1

Nonlinear post-selection inference for genome-wide association studies

Lotfi Slim , Clément Chatelain , Chloé-Agathe Azencott
Pacific Symposium on Biocomputing, Jan 2022, Kohala Coast, Hawaii, United States. ⟨10.1101/2020.09.30.320515⟩
Communication dans un congrès hal-03122125v1

Where Do We Stand in Regularization for Life Science Studies?

Veronica Tozzo , Chloé-Agathe Azencott , Samuele Fiorini , Emanuele Fava , Andrea Trucco , et al.
Journal of Computational Biology, 2021, ⟨10.1089/cmb.2019.0371⟩
Article dans une revue hal-03367708v1

Multitask group Lasso for Genome Wide association Studies in diverse populations

Chloé-Agathe Azencott , Asma Nouira
Pacific Symposium on Biocomputing, Jan 2022, Kohala Coast, Hawaii, United States. pp.163-174
Communication dans un congrès hal-03510963v1

Drug Target Identification with Machine Learning: How to Choose Negative Examples

Matthieu Najm , Chloé-Agathe Azencott , Benoit Playe , Véronique Stoven
International Journal of Molecular Sciences, 2021, 22 (10), pp.5118. ⟨10.3390/ijms22105118⟩
Article dans une revue hal-03359024v1

Advancing Drug-Target Interactions Prediction: Leveraging a Large-Scale Dataset with a Rapid and Robust Chemogenomic Algorithm.

Gwenn Guichaoua , Philippe Pinel , Brice Hoffmann , Chloé-Agathe Azencott , Veronique Stoven
2024
Pré-publication, Document de travail hal-04495209v1
Image document

kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection

Lotfi Slim , Clement Chatelain , Chloé-Agathe Azencott , Jean-Philippe Vert
36th International Conference on Machine Learning (ICML 2019), Jun 2019, Long Beach, CA, United States
Communication dans un congrès hal-02441304v1

Efficient multi-task chemogenomics for drug specificity prediction

Benoit Playe , Chloé-Agathe Azencott , Véronique Stoven
PLoS ONE, 2018, 13 (10), pp.e0204999. ⟨10.1371/journal.pone.0204999⟩
Article dans une revue hal-01984828v1
Image document

A new hybrid record linkage process to make epidemiological databases interoperable: application to the GEMO and GENEPSO studies involving BRCA1 and BRCA2 mutation carriers

Yue Jiao , Fabienne Lesueur , Chloé-Agathe Azencott , Maïté Laurent , Noura Mebirouk , et al.
BMC Medical Research Methodology, 2021, 21 (1), pp.155. ⟨10.1186/s12874-021-01299-6⟩
Article dans une revue inserm-03313811v1

A network-guided protocol to discover susceptibility genes in genome-wide association studies using stability selection

Héctor Climente-González , Chloé-Agathe Azencott , Makoto Yamada
STAR Protocols, 2023, 4 (1), pp.101998. ⟨10.1016/j.xpro.2022.101998⟩
Article dans une revue hal-04019421v1

Machine learning and genomics: precision medicine versus patient privacy

Chloé-Agathe Azencott
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2018, 376 (2128), pp.20170350
Article dans une revue hal-01984830v1

Dynamic Risk Prediction of 30-Day Mortality in Patients With Advanced Lung Cancer: Comparing Five Machine Learning Approaches

Charles Vesteghem , Weronika Szejniuk , Rasmus Brøndum , Ursula Falkmer , Chloé-Agathe Azencott , et al.
JCO Clinical Cancer Informatics, 2022, 6, ⟨10.1200/CCI.22.00054⟩
Article dans une revue hal-03901659v1
Image document

Machine learning tools for biomarker discovery

Chloé-Agathe Azencott
Machine Learning [stat.ML]. Sorbonne Université UPMC, 2020
HDR tel-02354924v2

Interpretable network-guided epistasis detection

Diane Duroux , Héctor Climente-González , Chloé-Agathe Azencott , Kristel van Steen
GigaScience, 2022, 11, ⟨10.1093/gigascience/giab093⟩
Article dans une revue hal-03114245v1

Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data

Héctor Climente-González , Chloé-Agathe Azencott , Samuel Kaski , Makoto Yamada
Bioinformatics, 2019, 35 (14), ⟨10.1093/bioinformatics/btz333⟩
Article dans une revue hal-02072349v1

Multitask feature selection with task descriptors

Victor Bellon , Véronique Stoven , Chloé-Agathe Azencott
Pacific Symposium on Biocomputing, Jan 2016, Hawai, United States. pp.261-272
Communication dans un congrès hal-01246697v1
Image document

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.

S Sieberts , Fan Zhu , Javier García-García , Eli Stahl , Abhishek Pratap , et al.
Nature Communications, 2016, 7, pp.12460. ⟨10.1038/ncomms12460⟩
Article dans une revue hal-01420921v1

The Evaluation of Tools Used to Predict the Impact of Missense Variants Is Hindered by Two Types of Circularity

Dominik G. Grimm , Chloé-Agathe Azencott , Fabian Aicheler , Udo Gieraths , Daniel G. Macarthur , et al.
Human Mutation, 2015, 36 (5), pp.513-523. ⟨10.1002/humu.22768⟩
Article dans une revue hal-01246688v1

Assessing Random Forest self-reproducibility for optimal short biomarker signature discovery

Christophe Poulet , Ahmed Debit , Claire Josse , Guy Jerusalem , Chloé-Agathe Azencott , et al.
2023
Pré-publication, Document de travail hal-04188150v1

Disparities in accessibility to oncology care centers in France

Eric Daoud , Anne-Sophie Hamy-Petit , Elise Dumas , Lidia Delrieu , Beatriz Grandal Rejo , et al.
2022
Pré-publication, Document de travail hal-03511050v1

Non-invasive multi-cancer diagnosis using DNA hypomethylation of LINE-1 retrotransposons

Marc Michel , Maryam Heidary , Anissa Mechri , Kévin Da Silva , Marine Gorse , et al.
2024
Pré-publication, Document de travail hal-04453898v1

Detection of genes with differential expression dispersion unravels the role of autophagy in cancer progression

Christophe Le Priol , Chloé-Agathe Azencott , Xavier Gidrol
PLoS Computational Biology, 2023, 19 (3), pp.e1010342. ⟨10.1371/journal.pcbi.1010342⟩
Article dans une revue hal-03901624v1

Prediction of human population responses to toxic compounds by a collaborative competition.

Federica Eduati , Lara M Mangravite , Tao Wang , Hao Tang , J Christopher Bare , et al.
Nature Biotechnology, 2015, 33 (9), pp.933-40. ⟨10.1038/nbt.3299⟩
Article dans une revue hal-01428019v1
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The French Early Breast Cancer Cohort (FRESH): A Resource for Breast Cancer Research and Evaluations of Oncology Practices Based on the French National Healthcare System Database (SNDS)

Elise Dumas , Lucie Laot , Florence Coussy , Beatriz Grandal Rejo , Eric Daoud , et al.
Cancers, 2022, 14 (11), pp.2671. ⟨10.3390/cancers14112671⟩
Article dans une revue hal-03901737v1

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 , et al.
2022
Pré-publication, Document de travail hal-03903457v1
Image document

Biological networks and GWAS: comparing and combining network methods to understand the genetics of familial breast cancer susceptibility in the GENESIS study

Héctor Climente-González , Christine Lonjou , Fabienne Lesueur , Dominique Stoppa-Lyonnet , Nadine Andrieu , et al.
PLoS Computational Biology, 2021, ⟨10.1101/2020.05.04.076661⟩
Article dans une revue hal-03114234v1

martini: an R package for genome-wide association studies using SNP networks

Chloé-Agathe Azencott , Héctor Climente-González
2021
Pré-publication, Document de travail hal-03122108v1

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 , et al.
BMC Bioinformatics, 2023, 24 (1), ⟨10.1186/s12859-023-05578-5⟩
Article dans une revue hal-03114226v1

The inconvenience of data of convenience: computational research beyond post-mortem analyses

Chloé-Agathe Azencott , Tero Aittokallio , Sushmita Roy , Ankit Agrawal , Emmanuel Barillot , et al.
Nature Methods, 2017, 14 (10), pp.937 - 938. ⟨10.1038/nmeth.4457⟩
Article dans une revue hal-01679028v1