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Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors
Geert-Jan Huizing
,
Laura Cantini
,
Gabriel Peyré
Proceedings of the 39th International Conference on Machine Learning,, Jul 2022, Baltimore, United States
Communication dans un congrès
hal-03828733v1
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Optimal transport improves cell–cell similarity inference in single-cell omics data
Geert-Jan Huizing
,
Gabriel Peyré
,
Laura Cantini
Article dans une revue
hal-03623386v1
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Evaluating the Reproducibility of Single-Cell Gene Regulatory Network Inference Algorithms
Yoonjee Kang
,
Denis Thieffry
,
Laura Cantini
Article dans une revue
hal-03358193v1
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Classification of gene signatures for their information value and functional redundancy
Laura Cantini
,
Laurence Calzone
,
Loredana Martignetti
,
Mattias Rydenfelt
,
Nils Blüthgen
,
et al.
Article dans une revue
hal-02129604v1
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An Integrated Analysis of miRNA and Gene Expression Changes in Response to an Obesogenic Diet to Explore the Impact of Transgenerational Supplementation with Omega 3 Fatty Acids
Karla Fabiola Corral-Jara
,
Laura Cantini
,
Nathalie Poupin
,
Tao Ye
,
Jean-Paul Rigaudière
,
et al.
Article dans une revue
hal-03100700v1
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Benchmarking joint multi-omics dimensionality reduction approaches for cancer study
Laura Cantini
,
Pooya Zakeri
,
Céline Hernandez
,
Aurelien Naldi
,
Denis Thieffry
,
et al.
2020
Pré-publication, Document de travail
hal-02998156v1
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Optimal transport improves cell–cell similarity inference in single-cell omics data
Geert-Jan Huizing
,
Gabriel Peyré
,
Laura Cantini
Article dans une revue
hal-03828714v1
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Molecular Inverse Comorbidity between Alzheimer’s Disease and Lung Cancer: New Insights from Matrix Factorization
Alessandro Greco
,
Jon Sanchez Valle
,
Vera Pancaldi
,
Anaïs Baudot
,
Emmanuel Barillot
,
et al.
Article dans une revue
hal-02277045v2
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Benchmarking joint multi-omics dimensionality reduction approaches for the study of cancer
Laura Cantini
,
Pooya Zakeri
,
Céline Hernandez
,
Aurelien Naldi
,
Denis Thieffry
,
et al.
Article dans une revue
hal-03102088v1
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Paired single-cell multi-omics data integration with Mowgli
Geert-Jan Huizing
,
Ina Maria Deutschmann
,
Gabriel Peyré
,
Laura Cantini
Logiciel
hal-04186802v1
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Optimal Transport improves cell-cell similarity inference in single-cell omics data
Geert-Jan Huizing
,
Gabriel Peyré
,
Laura Cantini
Article dans une revue
hal-03365157v1
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Unsupervised Ground Metric Learning using Wasserstein Eigenvectors
Geert-Jan Huizing
,
Laura Cantini
,
Gabriel Peyré
Proceedings of the 39th International Conference on Machine Learning, Jul 2022, Baltimore, United States
Communication dans un congrès
hal-03387865v1
|
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Hope4Genes: a Hopfield-like class prediction algorithm for transcriptomic data
Laura Cantini
,
Michele Caselle
Article dans une revue
hal-02129598v1
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Identification of microRNA clusters cooperatively acting on epithelial to mesenchymal transition in triple negative breast cancer
Laura Cantini
,
Gloria Bertoli
,
Claudia Cava
,
Thierry Dubois
,
Andrei Zinovyev
,
et al.
Article dans une revue
hal-02129600v1
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Interpreting pathways to discover cancer driver genes with Moonlight
Antonio Colaprico
,
Catharina Olsen
,
Matthew Bailey
,
Gabriel Odom
,
Thilde Terkelsen
,
et al.
Article dans une revue
hal-03001026v1
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Investigating the epi-miRNome: identification of epi-miRNAs using transfection experiments
Elisa Reale
,
Daniela Taverna
,
Laura Cantini
,
Loredana Martignetti
,
Matteo Osella
,
et al.
Article dans une revue
hal-03001049v1
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Independent Component Analysis for Unraveling the Complexity of Cancer Omics Datasets
Nicolas Sompairac
,
Petr V Nazarov
,
Urszula Czerwinska
,
Laura Cantini
,
Anne Biton
,
et al.
Article dans une revue
hal-02343412v1
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Evaluating the reproducibility of single-cell gene regulatory network inference algorithms
Yoonjee Kang
,
Denis Thieffry
,
Laura Cantini
2020
Pré-publication, Document de travail
hal-03000601v1
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Assessing reproducibility of matrix factorization methods in independent transcriptomes
Laura Cantini
,
Ulykbek Kairov
,
Aurélien de Reyniès
,
Emmanuel Barillot
,
François Radvanyi
,
et al.
Article dans une revue
hal-02095317v1
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