J. Tubiana

发表

Statistical physics and representations in real and artificial neural networks

Simona Cocco, Lorenzo Posani, J'erome Tubiana, 2017, Physica A: Statistical Mechanics and its Applications.

Emergence of Compositional Representations in Restricted Boltzmann Machines

Rémi Monasson, Jérôme Tubiana, R. Monasson, 2016, Physical review letters.

ScanNet: An interpretable geometric deep learning model for structure-based protein binding site prediction

H. Wolfson, J. Tubiana, D. Schneidman-Duhovny, 2021, bioRxiv.

Blind deconvolution for spike inference from fluorescence recordings

Thomas Panier, G. Debrégeas, J. Tubiana, 2020, Journal of Neuroscience Methods.

RBM-MHC: A Semi-Supervised Machine-Learning Method for Sample-Specific Prediction of Antigen Presentation by HLA-I Alleles

R. Monasson, T. Mora, S. Cocco, 2020, Cell systems.

Flexible machine learning prediction of antigen presentation for rare and common HLA-I alleles

R. Monasson, T. Mora, S. Cocco, 2020, bioRxiv.

Superimmunity by pan-sarbecovirus nanobodies

J. Tubiana, D. Schneidman-Duhovny, Derek J. Taylor, 2022, Cell Reports.

Computational protein design with evolutionary-based and physics-inspired modeling: current and future synergies.

R. Monasson, S. Cocco, J. Tubiana, 2022 .

Reduced B cell antigenicity of Omicron lowers host serologic response

H. Wolfson, J. Tubiana, D. Schneidman-Duhovny, 2022, Cell Reports.

Neural assemblies uncovered by generative modeling explain whole-brain activity statistics and reflect structural connectivity

H. Baier, G. Debrégeas, J. Tubiana, 2021, bioRxiv.

ScanNet: A Web Server for Structure-based Prediction of Protein Binding Sites with Geometric Deep Learning.

H. Wolfson, J. Tubiana, D. Schneidman-Duhovny, 2022, Journal of molecular biology.

Bringing the tracker-guards back in: Arms-carrying markets and quests for status in conservation at war

J. Tubiana, L. Lombard, 2020 .

Translations and Commentary

J. Tubiana, R. S. O'fahey, M. I. Salīm, 1983 .

A state of disunity: conflict dynamics in unity state, South Sudan, 2013-15

J. Tubiana, Claudio Gramizzi, Joshua Craze, 2016 .

Machine learning for evolutionary-based and physics-inspired protein design: Current and future synergies.

R. Monasson, S. Cocco, J. Tubiana, 2022, Current opinion in structural biology.

ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction

H. Wolfson, J. Tubiana, D. Schneidman-Duhovny, 2021, Nature Methods.

ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction

H. Wolfson, J. Tubiana, D. Schneidman-Duhovny, 2022, Nature Methods.

Reduced antigenicity of Omicron lowers host serologic response

H. Wolfson, J. Tubiana, D. Schneidman-Duhovny, 2022, bioRxiv.

Super-immunity by broadly protective nanobodies to sarbecoviruses

J. Tubiana, D. Schneidman-Duhovny, Wei Huang, 2021 .

Funneling modulatory peptide design with generative models: Discovery and characterization of disruptors of calcineurin protein-protein interactions

H. Wolfson, J. Tubiana, Inbal Sher, 2023, PLoS Comput. Biol..

The Zaghawa from an ecological perspective

J. Tubiana, M. Chadwick, M. Tubiana, 1977 .

Machine learning for evolutionary-based and physics-inspired protein design: Current and future synergies.

R. Monasson, S. Cocco, J. Tubiana, 2023, Current opinion in structural biology.

Inference of compressed Potts graphical models.

Simona Cocco, Rémi Monasson, Alice Coucke, 2019, Physical review. E.

Blind sparse deconvolution for inferring spike trains from fluorescence recordings

Jérôme Tubiana, Sébastien Wolf, Georges Debrégeas, 2017, bioRxiv.

The Zaghawa from an Ecological Perspective: Foodgathering, the Pastoral System, Tradition and Development of the Zaghawa of the Sudan and the Chad

J. Tubiana, M. Tubiana, 2004 .

Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins

Simona Cocco, Rémi Monasson, Jérôme Tubiana, 2019, Neural Computation.

Learning protein constitutive motifs from sequence data

Simona Cocco, Rémi Monasson, Jérôme Tubiana, 2018, eLife.

Discriminating physiological from non‐physiological interfaces in structures of protein complexes: A community‐wide study

Charles W Christoffer, H. Wolfson, O. Schueler‐Furman, 2023, Proteomics.

‘Place-cell’ emergence and learning of invariant data with restricted Boltzmann machines: breaking and dynamical restoration of continuous symmetries in the weight space pdf

Simona Cocco, Moshir Harsh, J'erome Tubiana, 2019, Journal of Physics A: Mathematical and Theoretical.

Restricted Boltzmann machines : from compositional representations to protein sequence analysis

Jérôme Tubiana, J. Tubiana, 2018 .

EvoRator2: Predicting Site-specific Amino Acid Substitutions Based on Protein Structural Information Using Deep Learning.

H. Wolfson, J. Tubiana, T. Pupko, 2023, Journal of molecular biology.

Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies

H. Baier, G. Debrégeas, J. Tubiana, 2021 .

Inference of compressed Potts graphical models.

R. Monasson, S. Cocco, J. Tubiana, 2019, Physical Review E.

‘Place-cell’ emergence and learning of invariant data with restricted Boltzmann machines: breaking and dynamical restoration of continuous symmetries in the weight space

R. Monasson, S. Cocco, J. Tubiana, 2019, Journal of Physics A: Mathematical and Theoretical.