scientific publication
scientific
documentation
scientific publication
Biology • Genetics • Scientific research • Data analysis • AI & Machine learning
Biology • Genetics • Scientific research
Data analysis • AI & Machine learning
05/13/2021
20 MIN READ
05/13/2021
20 MIN READ
02/27/2015
30 MIN READ
02/27/2015
30 MIN READ
03/12/2013
25 MIN READ
03/12/2013
25 MIN READ
03/25/2024
03/25/2024
25 MIN READ
25 MIN READ
Next Gen GWAS : full 2D epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction
Next Gen GWAS : full 2D epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction
This article presents NGG, a GPU-based method mapping billions of genetic interactions in Arabidopsis, revealing hidden heritability and improving phenotype prediction.
This article presents NGG, a GPU-based method mapping billions of genetic interactions in Arabidopsis, revealing hidden heritability and improving phenotype prediction.
AUTORS • Carluer JB, Chaux C, Estoup-Streiff C, Roche N, Hosy E, Mas A , Carré C, Krouk G
AUTORS • Carluer JB, Chaux C, Estoup-Streiff C, Roche N, Hosy E, Mas A , Carré C, Krouk G
Genome Biology
Genome Biology
06/21/2022
06/21/2022
25 MIN READ
25 MIN READ
PeTriBERT : Augmenting BERT with tridimensional encoding for inverse protein folding and design
PeTriBERT : Augmenting BERT with tridimensional encoding for inverse protein folding and design
The article introduces large-scale genetic analysis methods to capture complex gene interactions (epistasis) and shows they improve phenotype prediction compared to classical approaches.
The article introduces large-scale genetic analysis methods to capture complex gene interactions (epistasis) and shows they improve phenotype prediction compared to classical approaches.
AUTORS • Dumortier B, Liutkus A , Carré C, Krouk G
AUTORS • Dumortier B, Liutkus A , Carré C, Krouk G
BioRxiv
BioRxiv
06/21/2022
06/21/2022
15 MIN READ
15 MIN READ
Full epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction
Full epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction
This study introduces Next-Gen GWAS (NGG), a method capable of analyzing over 60 billion SNP interactions within hours. Applied to Arabidopsis thaliana, NGG generates 2D epistatic maps and significantly improves phenotype prediction compared to traditional GWAS models.
This study introduces Next-Gen GWAS (NGG), a method capable of analyzing over 60 billion SNP interactions within hours. Applied to Arabidopsis thaliana, NGG generates 2D epistatic maps and significantly improves phenotype prediction compared to traditional GWAS models.
AUTORS • Carré C, Carluer J-B, Chaux C, Roche N, Mas A, Krouk G
AUTORS • Carré C, Carluer J-B, Chaux C, Roche N, Mas A, Krouk G
BioRxiv
BioRxiv
Stay in touch
for more informations
Social
Copyright 2025 bionomeeX. All right reserved.
05/13/2021
05/13/2021
20 MIN READ
20 MIN READ
Prediction of Hilbertian autoregressive processes: A Recurrent Neural Network approach
Prediction of Hilbertian autoregressive processes: A Recurrent Neural Network approach
This study compares classical prediction methods for Hilbert-space autoregressive processes (ARH) with a Recurrent Neural Network (LSTM) approach, showing that LSTMs outperform for nonlinear data, while traditional statistical models remain competitive in certain cases.
This study compares classical prediction methods for Hilbert-space autoregressive processes (ARH) with a Recurrent Neural Network (LSTM) approach, showing that LSTMs outperform for nonlinear data, while traditional statistical models remain competitive in certain cases.
AUTORS • André Mas, Clément Carré
AUTORS • André Mas, Clément Carré
Hal Science
Hal Science
05/05/2019
05/05/2019
15 MIN READ
15 MIN READ
Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
The paper presents Network Walking, a method mapping transcription factor networks in Arabidopsis nitrogen signaling, linking direct and indirect gene targets to reveal large-scale regulatory dynamics.
The paper presents Network Walking, a method mapping transcription factor networks in Arabidopsis nitrogen signaling, linking direct and indirect gene targets to reveal large-scale regulatory dynamics.
AUTORS • Brooks MD, Cirrone J, Pasquino AV, Alvarez JM, Swift J, Mittal S, Juang CL, Varala K, Gutiérrez RA,Krouk G, Shasha D, Coruzzi GM.
AUTORS • Brooks MD, Cirrone J, Pasquino AV, Alvarez JM, Swift J, Mittal S, Juang CL, Varala K, Gutiérrez RA,Krouk G, Shasha D, Coruzzi GM.
Nature Communications
Nature Communications
06/22/2017
06/22/2017
25 MIN READ
25 MIN READ
Reverse engineering highlights potential principles of large gene regulatory network design and learning.
Reverse engineering highlights potential principles of large gene regulatory network design and learning.
The paper uses reverse-engineering methods on large gene regulatory networks to uncover potential organizing principles and network structures in biological systems.
The paper uses reverse-engineering methods on large gene regulatory networks to uncover potential organizing principles and network structures in biological systems.
AUTORS • André Mas, Clément Carré, Gabriel Krouk.
AUTORS • André Mas, Clément Carré, Gabriel Krouk.
Nature Communications. PMID: 30952851.
Nature Communications. PMID: 30952851.
04/25/2016
04/25/2016
25 MIN READ
25 MIN READ
Non-asymptotic Adaptive Prediction in Functional Linear Models
Non-asymptotic Adaptive Prediction in Functional Linear Models
The article analyzes patterns in biological networks (e.g. food webs, ecological networks) to identify general organizing principles and structural rules that govern their architecture.
The article analyzes patterns in biological networks (e.g. food webs, ecological networks) to identify general organizing principles and structural rules that govern their architecture.
AUTORS • Brunel, E., Mas. A. and Roche, A.
AUTORS • Brunel, E., Mas. A. and Roche, A.
Journal of Multivariate Analysis, 143, pp. 208-232.
Journal of Multivariate Analysis, 143, pp. 208-232.
09/26/2016
09/26/2016
25 MIN READ
25 MIN READ
Combinatorial interaction network of transcriptomic and phenotypic responses to nitrogen and hormones in the Arabidopsis thaliana root.
Combinatorial interaction network of transcriptomic and phenotypic responses to nitrogen and hormones in the Arabidopsis thaliana root.
The study shows how Arabidopsis thaliana roots integrate nutrient and hormone signals, revealing complex cross-talk and key genes controlling root growth.
The study shows how Arabidopsis thaliana roots integrate nutrient and hormone signals, revealing complex cross-talk and key genes controlling root growth.
AUTORS • Ristova D, Carré C, Pervent M, Medici A, Kim GJ, Scalia D, Ruffel S, Birnbaum KD, Lacombe B, Busch W, Coruzzi GM, Krouk G
AUTORS • Ristova D, Carré C, Pervent M, Medici A, Kim GJ, Scalia D, Ruffel S, Birnbaum KD, Lacombe B, Busch W, Coruzzi GM, Krouk G
Science Signaling
Science Signaling
06/08/2015
06/08/2015
25 MIN READ
25 MIN READ
GeneCloud Reveals Semantic Enrichment in Lists of Gene Descriptions.
GeneCloud Reveals Semantic Enrichment in Lists of Gene Descriptions.
introduces Gene Cloud a tool designed to analyze gene lists by identifying semantic enrichment in gene descriptions. This method aids in uncovering underlying biological themes and relationships within gene sets.
introduces Gene Cloud a tool designed to analyze gene lists by identifying semantic enrichment in gene descriptions. This method aids in uncovering underlying biological themes and relationships within gene sets.
AUTORS • Krouk G, Carré C, Fizames C, Gojon A, Ruffel S, Lacombe B.
AUTORS • Krouk G, Carré C, Fizames C, Gojon A, Ruffel S, Lacombe B.
Molecular Plant (Cell Press).
Molecular Plant (Cell Press).
2015
2015
25 MIN READ
25 MIN READ
High Dimensional Principal Projections
High Dimensional Principal Projections
PCA is used for dimension reduction in functional or high-dimensional data. The study provides non-asymptotic bounds on the risk of empirical eigenprojectors, improving nonparametric functional estimation.
PCA is used for dimension reduction in functional or high-dimensional data. The study provides non-asymptotic bounds on the risk of empirical eigenprojectors, improving nonparametric functional estimation.
AUTORS • Mas A., Ruymgaart F.
AUTORS • Mas A., Ruymgaart F.
Complex Analysis and Operator Theory, 9, 35-63.
Complex Analysis and Operator Theory, 9, 35-63.
02/27/2015
02/27/2015
30 MIN READ
30 MIN READ
AtNIGT1/HRS1 integrates nitrate and phosphate signals at the Arabidopsis root tip
AtNIGT1/HRS1 integrates nitrate and phosphate signals at the Arabidopsis root tip
AtNIGT1/HRS1 in Arabidopsis integrates nitrate and phosphate signals to control root growth, acting as a molecular logic gate that coordinates nutrient responses.
AtNIGT1/HRS1 in Arabidopsis integrates nitrate and phosphate signals to control root growth, acting as a molecular logic gate that coordinates nutrient responses.
AUTORS • Medici A, Marshall-Colon A, Ronzier E, Szponarski W, Wang R, Gojon A, Crawford NM, Ruffel S, Coruzzi GM, Krouk G.
AUTORS • Medici A, Marshall-Colon A, Ronzier E, Szponarski W, Wang R, Gojon A, Crawford NM, Ruffel S, Coruzzi GM, Krouk G.
Nature Communications. PMID: 25723764.
Nature Communications. PMID: 25723764.
03/12/2013
03/12/2013
25 MIN READ
25 MIN READ
Process for identifying rare events
Process for identifying rare events
A method to identify rare specific cells within a large population by exposing them to reagents, detecting responses, clustering the cells, and removing non-rare cells.
A method to identify rare specific cells within a large population by exposing them to reagents, detecting responses, clustering the cells, and removing non-rare cells.
AUTORS • Cezar R., Ienco D., Mas A., Masseglia F., Poncelet P., Pudlo P., Székely E, Teisseire M., Vendrell J.-P.,
AUTORS • Cezar R., Ienco D., Mas A., Masseglia F., Poncelet P., Pudlo P., Székely E, Teisseire M., Vendrell J.-P.,
Inria Hal Science
Inria Hal Science
04/2013
04/2013
25 MIN READ
25 MIN READ
Minimax adaptive tests for the functional linear model
Minimax adaptive tests for the functional linear model
Two new data-driven methods are proposed to test the slope in functional linear models, using functional PCA and multiple testing. They adapt to unknown smoothness, are minimax optimal, and their performance is supported by theory and simulations.
Two new data-driven methods are proposed to test the slope in functional linear models, using functional PCA and multiple testing. They adapt to unknown smoothness, are minimax optimal, and their performance is supported by theory and simulations.
AUTORS • Hilgert N., Mas A., Verzelen N.
AUTORS • Hilgert N., Mas A., Verzelen N.
Annals of Statistics.
Annals of Statistics.
06/27/2013
06/27/2013
20 MIN READ
20 MIN READ
Gene regulatory networks: learning causalityfrom time and perturbation
Gene regulatory networks: learning causalityfrom time and perturbation
The study focuses on mapping causal gene interactions in plants using time-series and perturbation data to improve gene regulatory network models.
The study focuses on mapping causal gene interactions in plants using time-series and perturbation data to improve gene regulatory network models.
AUTORS • Krouk G, Lingeman J, Colon AM, Coruzzi G, Shasha D.
AUTORS • Krouk G, Lingeman J, Colon AM, Coruzzi G, Shasha D.
Genome Biology. PMCID: PMC3707030.
Genome Biology. PMCID: PMC3707030.
03/12/2013
03/12/2013
25 MIN READ
25 MIN READ
Asymptotics of prediction in functional linear regression with functional outputs
Asymptotics of prediction in functional linear regression with functional outputs
A method to identify rare specific cells within a large population by exposing them to reagents, detecting responses, clustering the cells, and removing non-rare cells.
A method to identify rare specific cells within a large population by exposing them to reagents, detecting responses, clustering the cells, and removing non-rare cells.
AUTORS • Crambes C., Mas A.
AUTORS • Crambes C., Mas A.
Bernoulli, 19, No. 5B, 2627-2651.
Bernoulli, 19, No. 5B, 2627-2651.
03/2012
03/2012
25 MIN READ
25 MIN READ
Representation of small ball probabilities in Hilbert space and lower bound in regression for functional data
Representation of small ball probabilities in Hilbert space and lower bound in regression for functional data
The paper introduces small ball probability, extreme value theory, and functional data regression, highlighting challenges in bounding quadratic risk. These concepts are later connected to present the main results, with proofs in the final section.
The paper introduces small ball probability, extreme value theory, and functional data regression, highlighting challenges in bounding quadratic risk. These concepts are later connected to present the main results, with proofs in the final section.
AUTORS • Mas A.
AUTORS • Mas A.
Electronic Journal of Statistics, 6, 1745-1778.
Electronic Journal of Statistics, 6, 1745-1778.
2012
2012
20 MIN READ
20 MIN READ
PCA-kernel estimation
PCA-kernel estimation
The paper studies dimension reduction via PCA for high-dimensional or functional data, analyzing how projecting onto empirical eigenvectors affects nonparametric methods like kernel regression, and proving asymptotic equivalences between empirical and theoretical projections.
The paper studies dimension reduction via PCA for high-dimensional or functional data, analyzing how projecting onto empirical eigenvectors affects nonparametric methods like kernel regression, and proving asymptotic equivalences between empirical and theoretical projections.
AUTORS • Biau G., Mas A.
AUTORS • Biau G., Mas A.
Statistics & Risk Modeling, 29, 19–46.
Statistics & Risk Modeling, 29, 19–46.
2010
2010
25 MIN READ
25 MIN READ
Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate
Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate
The study analyzes rapid gene expression in Arabidopsis thaliana roots responding to nitrate, identifying key early regulatory events and validating a predictive state-space model.
The study analyzes rapid gene expression in Arabidopsis thaliana roots responding to nitrate, identifying key early regulatory events and validating a predictive state-space model.
AUTORS • Krouk G, Mirowski P, LeCun Y, Shasha DE, Coruzzi GM.
AUTORS • Krouk G, Mirowski P, LeCun Y, Shasha DE, Coruzzi GM.
Genome Biology. PMID: 21182762.
Genome Biology. PMID: 21182762.
Stay in touch
for more informations
Social
Copyright 2025 bionomeeX. All right reserved.
Stay in touch
for more informations
Social
Copyright 2025 bionomeeX. All right reserved.