Search research articles
Contact Us
Filters
Showing results (1-10 of 17) with videos related to
Page
of 2
Sort By:
BMC Bioinformatics
|
July 5, 2022
Assessment of deep learning and transfer learning for cancer prediction based on gene expression data
Blaise Hanczar, Victoria Bourgeais, Farida Zehraoui
Plos One
|
July 18, 2024
Biobjective gradient descent for feature selection on high dimension, low sample size data
Tina Issa, Eric Angel, Farida Zehraoui
Bioinformatics (Oxford, England)
|
March 10, 2022
GraphGONet: a self-explaining neural network encapsulating the Gene Ontology graph for phenotype prediction on gene expression
Victoria Bourgeais, Farida Zehraoui, Blaise Hanczar
Plos One
|
May 25, 2023
A3SOM, abstained explainable semi-supervised neural network based on self-organizing map
Constance Creux, Farida Zehraoui, Blaise Hanczar, et al.
Bioinformatics (Oxford, England)
|
May 13, 2025
CrossAttOmics: multiomics data integration with cross-attention
Aurélien Beaude, Franck Augé, Farida Zehraoui, et al.
Bioinformatics (Oxford, England)
|
February 1, 2025
MMnc: multi-modal interpretable representation for non-coding RNA classification and class annotation
Constance Creux, Farida Zehraoui, François Radvanyi, et al.
BMC Bioinformatics
|
November 5, 2020
Biological interpretation of deep neural network for phenotype prediction based on gene expression
Blaise Hanczar, Farida Zehraoui, Tina Issa, et al.
Plos Computational Biology
|
September 12, 2024
Comparison and benchmark of deep learning methods for non-coding RNA classification
Constance Creux, Farida Zehraoui, François Radvanyi, et al.
Bioinformatics (Oxford, England)
|
November 14, 2018
IRSOM, a reliable identifier of ncRNAs based on supervised self-organizing maps with rejection
Ludovic Platon, Farida Zehraoui, Abdelhafid Bendahmane, et al.
BMC Bioinformatics
|
September 23, 2021
Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data
Victoria Bourgeais, Farida Zehraoui, Mohamed Ben Hamdoune, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 17) with videos related to
Sort By:
Page
of 2
BMC Bioinformatics
|
July 5, 2022
Assessment of deep learning and transfer learning for cancer prediction based on gene expression data
Blaise Hanczar, Victoria Bourgeais, Farida Zehraoui
Plos One
|
July 18, 2024
Biobjective gradient descent for feature selection on high dimension, low sample size data
Tina Issa, Eric Angel, Farida Zehraoui
Bioinformatics (Oxford, England)
|
March 10, 2022
GraphGONet: a self-explaining neural network encapsulating the Gene Ontology graph for phenotype prediction on gene expression
Victoria Bourgeais, Farida Zehraoui, Blaise Hanczar
Plos One
|
May 25, 2023
A3SOM, abstained explainable semi-supervised neural network based on self-organizing map
Constance Creux, Farida Zehraoui, Blaise Hanczar, et al.
Bioinformatics (Oxford, England)
|
May 13, 2025
CrossAttOmics: multiomics data integration with cross-attention
Aurélien Beaude, Franck Augé, Farida Zehraoui, et al.
Bioinformatics (Oxford, England)
|
February 1, 2025
MMnc: multi-modal interpretable representation for non-coding RNA classification and class annotation
Constance Creux, Farida Zehraoui, François Radvanyi, et al.
BMC Bioinformatics
|
November 5, 2020
Biological interpretation of deep neural network for phenotype prediction based on gene expression
Blaise Hanczar, Farida Zehraoui, Tina Issa, et al.
Plos Computational Biology
|
September 12, 2024
Comparison and benchmark of deep learning methods for non-coding RNA classification
Constance Creux, Farida Zehraoui, François Radvanyi, et al.
Bioinformatics (Oxford, England)
|
November 14, 2018
IRSOM, a reliable identifier of ncRNAs based on supervised self-organizing maps with rejection
Ludovic Platon, Farida Zehraoui, Abdelhafid Bendahmane, et al.
BMC Bioinformatics
|
September 23, 2021
Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data
Victoria Bourgeais, Farida Zehraoui, Mohamed Ben Hamdoune, et al.
Page
of 2