M. Weigt

发表

Direct-coupling analysis of residue coevolution captures native contacts across many protein families

C. Sander, R. Zecchina, F. Morcos, 2011, Proceedings of the National Academy of Sciences.

A ferromagnet with a glass transition

M. Mézard, S. Franz, R. Zecchina, 2001, cond-mat/0103026.

Genomics-aided structure prediction

F. Morcos, J. Onuchic, T. Hwa, 2012, Proceedings of the National Academy of Sciences.

Identification of direct residue contacts in protein–protein interaction by message passing

T. Hwa, M. Weigt, Robert A. H. White, 2009, Proceedings of the National Academy of Sciences.

Selection of sequence motifs and generative Hopfield-Potts models for protein families.

M. Weigt, Kai Shimagaki, 2019, Physical review. E.

On the properties of small-world network models

M. Weigt, A. Barrat, 1999, cond-mat/9903411.

Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1

M. Weigt, A. Schug, M. Figliuzzi, 2015, bioRxiv.

Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models.

E. Aurell, Magnus Ekeberg, M. Weigt, 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

Simultaneous identification of specifically interacting paralogs and interprotein contacts by direct coupling analysis

Carlo Baldassi, A. Pagnani, M. Weigt, 2016, Proceedings of the National Academy of Sciences.

Polynomial iterative algorithms for coloring and analyzing random graphs.

R. Zecchina, A. Pagnani, M. Weigt, 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

Sudden emergence of q-regular subgraphs in random graphs

M. Weigt, M. Pretti, 2006, cond-mat/0603819.

Phase transition and finite-size scaling in the vertex-cover problem

M. Weigt, A. Hartmann, Wolfgang Barthel, 2005, Comput. Phys. Commun..

Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners

Carlo Baldassi, Riccardo Zecchina, Andrea Pagnani, 2014, PloS one.

Structural basis of histidine kinase autophosphorylation deduced by integrating genomics, molecular dynamics, and mutagenesis

Martin Weigt, Alexander Schug, Hendrik Szurmant, 2012, Proceedings of the National Academy of Sciences.

Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis

Martin Weigt, Alexander Schug, Guido Uguzzoni, 2017, Proceedings of the National Academy of Sciences.

Global profiling of miRNAs and the hairpin precursors: insights into miRNA processing and novel miRNA discovery

Christoph Dieterich, Na Li, Andreas Gogol-Döring, 2013, Nucleic acids research.

Minimal vertex covers on finite-connectivity random graphs: a hard-sphere lattice-gas picture.

M. Weigt, A. Hartmann, 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

Approximation schemes for the dynamics of diluted spin models: the Ising ferromagnet on a Bethe lattice

M. Weigt, G. Semerjian, 2004, cond-mat/0402451.

A hard-sphere model on generalized Bethe lattices: statics

M. Weigt, H. Hansen-Goos, 2005, cond-mat/0501571.

The typical-case complexity of a vertex-covering algorithm on finite-connectivity random graphs

Alexander K. Hartmann, Martin Weigt, M. Weigt, 2000 .

Dissecting the Specificity of Protein-Protein Interaction in Bacterial Two-Component Signaling: Orphans and Crosstalks

B. Lunt, T. Hwa, M. Weigt, 2011, PloS one.

High-resolution protein complexes from integrating genomic information with molecular simulation

Terence Hwa, Martin Weigt, Alexander Schug, 2009, Proceedings of the National Academy of Sciences.

Entropy and typical properties of Nash equilibria in two-player games

Martin Weigt, M. Weigt, J. Berg, 1999 .

Inference of direct residue contacts in two-component signaling.

Terence Hwa, Martin Weigt, Bryan Lunt, 2010, Methods in enzymology.

How Pairwise Coevolutionary Models Capture the Collective Residue Variability in Proteins?

Martin Weigt, Matteo Figliuzzi, M. Weigt, 2018, Molecular biology and evolution.

Statistical mechanics of sparse generalization and graphical model selection

Andrea Pagnani, Martin Weigt, Alejandro Lage-Castellanos, 2009 .

Classification and sparse-signature extraction from gene-expression data

Andrea Pagnani, Francesca Tria, Martin Weigt, 2009, 0907.3687.

Inter-Protein Sequence Co-Evolution Predicts Known Physical Interactions in Bacterial Ribosomes and the Trp Operon

Andrea Pagnani, Martin Weigt, Christoph Feinauer, 2015, PloS one.

The importance of dilution in the inference of biological networks

Andrea Pagnani, Martin Weigt, Alejandro Lage-Castellanos, 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Structures of a dimodular nonribosomal peptide synthetase reveal conformational flexibility

M. Weigt, A. Guarné, T. Schmeing, 2019, Science.

Gene expression Clustering by soft-constraint affinity propagation : applications to gene-expression data

M. Weigt, M. Leone, 2007 .

A hard-sphere model on generalised Bethe lattices: Dynamics

M. Weigt, H. Hansen-Goos, 2005, cond-mat/0505202.

Unsupervised and semi-supervised clustering by message passing: soft-constraint affinity propagation

M. Weigt, M. Weigt, M. Leone Sumedha, 2007, 0712.1165.

Inference of Hopfield-Potts patterns from covariation in protein families: calculation and statistical error bars

R. Monasson, S. Cocco, M. Weigt, 2013 .

Context-Aware Prediction of Pathogenicity of Missense Mutations Involved in Human Disease

M. Weigt, C. Feinauer, Christoph Feinauer, 2017, bioRxiv.

Multifractal analysis of perceptron learning with errors

M. Weigt, 1997, cond-mat/9707178.

Direct coevolutionary couplings reflect biophysical residue interactions in proteins.

R. Monasson, S. Cocco, M. Weigt, 2016, The Journal of chemical physics.

Optimization problems in physics

M. Weigt, A. Hartmann, 2006 .

Dynamics of heuristic optimization algorithms on random graphs

M. Weigt, 2002, cond-mat/0203281.

Minimal vertex covers on finite-connectivity random graphs: a hard-sphere lattice-gas picture.

M. Weigt, A. Hartmann, Martin Weigt, 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

Statistical-physics approaches to RNA molecules, families and networks

S. Cocco, A. Pagnani, M. Weigt, 2022, 2207.13402.

A hard-sphere model on generalized Bethe lattices: dynamics

M. Weigt, H. Hansen-Goos, 2005, cond-mat/0505202.

A hard-sphere model on generalized Bethe lattices: statics

M. Weigt, H. Hansen-Goos, 2005, cond-mat/0501571.

Introduction to graphs

M. Weigt, A. Hartmann, 2006, cond-mat/0602129.

Phylogenetic correlations have limited effect on coevolution-based contact prediction in proteins

Edwin Rodriguez Horta, M. Weigt, 2020, bioRxiv.

Approximation schemes for the dynamics of diluted spin models: the Ising ferromagnet on a Bethe lattice

M. Weigt, G. Semerjian, 2004, cond-mat/0402451.

Statistical mechanics of the vertex-cover problem

M. Weigt, A. Hartmann, 2003, cond-mat/0307236.

On the properties of small-world network models

M. Weigt, A. Barrat, 1999, cond-mat/9903411.

Statistical mechanics of combinatorial auctions.

R. Zecchina, M. Sellitto, M. Marsili, 2006, Physical review letters.

Rbm10 facilitates heterochromatin assembly via the Clr6 HDAC complex

M. Weigt, Q. Gao, Wei Chen, 2019, bioRxiv.

A replica approach to products of random matrices

M. Weigt, 1997, cond-mat/9709009.

Structure and Function of a Dehydrating Condensation Domain in Nonribosomal Peptide Biosynthesis.

M. Weigt, Bo Li, T. Schmeing, 2022, Journal of the American Chemical Society.

Entropy and typical properties of Nash equilibria in two-player games

M. Weigt, J. Berg, 1999, cond-mat/9905076.

Where the really hard sampling problems are

M. Weigt, F. Zamponi, S. Ciarella, 2022, 2210.11145.

MULTIFRACTALITY AND PERCOLATION IN THE COUPLING SPACE OF PERCEPTRONS

A. Engel, M. Weigt, 1996, cond-mat/9608092.

Finitely coordinated models for low-temperature phases of amorphous systems

M. Weigt, R. Kuehn, A. Zippelius, 2007, cond-mat/0703534.

Context-Aware Generative Models for Multi-Domain Proteins using Transformers

A. Pagnani, M. Weigt, Barthélémy Meynard-Piganeau, 2022 .

Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins

M. Weigt, C. A. Gandarilla-Pérez, S. Pinilla, 2022, bioRxiv.

A ferromagnet with a glass transition

M. Mézard, S. Franz, R. Zecchina, 2001, cond-mat/0103026.

Machine-learning-assisted Monte Carlo fails at sampling computationally hard problems

M. Weigt, F. Zamponi, S. Ciarella, 2022, 2210.11145.

A ferromagnet with a glass transition

M. Mézard, S. Franz, R. Zecchina, 2001, cond-mat/0103026.

Sudden emergence of q-regular subgraphs in random graphs

M. Weigt, M. Pretti, 2006, cond-mat/0603819.

Cavity approach to the random solid state.

M. Mézard, M. Weigt, P. Goldbart, 2005, Physical review letters.

Direct coevolutionary couplings reflect biophysical residue interactions in proteins

R. Monasson, S. Cocco, M. Weigt, 2016, bioRxiv.

Supplementary text: Direct-coupling analysis of residue co-evolution captures native contacts across many protein families

C. Sander, R. Zecchina, F. Morcos, 2011 .

Glassy behavior induced by geometrical frustration in a hard-core lattice-gas model

M. Weigt, A. Hartmann, 2002, cond-mat/0210054.

Propagation of external regulation and asynchronous dynamics in random Boolean networks.

A Pagnani, M Weigt, R Zecchina, 2007, Chaos.

The computational core and fixed point organization in Boolean networks

M. Leone, R. Zecchina, A. Pagnani, 2005, cond-mat/0512089.

Core percolation and onset of complexity in boolean networks.

L Correale, M Leone, A Pagnani, 2004, Physical review letters.

Coloring random graphs

Riccardo Zecchina, Andrea Pagnani, Martin Weigt, 2002, Physical review letters.

Threshold values, stability analysis and high-q asymptotics for the coloring problem on random graphs

Florent Krzakala, Andrea Pagnani, Martin Weigt, 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

Hiding solutions in random satisfiability problems: A statistical mechanics approach

Riccardo Zecchina, Alexander K. Hartmann, Federico Ricci-Tersenghi, 2001, Physical review letters.

A thermodynamic model for the agglomeration of DNA-looping proteins

Martin Weigt, Sumedha, M. Weigt, 2008, 0801.1480.

1 Splicing factor Rbm 10 facilitates heterochromatin assembly in fission yeast

M. Weigt, Wei Chen, S. Kempa, 2019 .

Towards finite-dimensional gelation

M. Weigt, A. Zippelius, K. Broderix, 2002, cond-mat/0204494.

Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria

Dominique Schneider, Martin Weigt, Christoph Feinauer, 2017, Proceedings of the National Academy of Sciences.

Perturbation Biology: Inferring Signaling Networks in Cellular Systems

Weiqing Wang, Chris Sander, Riccardo Zecchina, 2013, PLoS Comput. Biol..

Epistatic models predict mutable sites in SARS-CoV-2 proteins and epitopes

M. Weigt, Giancarlo Croce, Juan Rodriguez-Rivas, 2021, Proceedings of the National Academy of Sciences.

Efficient generative modeling of protein sequences using simple autoregressive models

A. Pagnani, M. Weigt, F. Zamponi, 2021, Nature Communications.

Deciphering polymorphism in 61,157 Escherichia coli genomes via epistatic sequence landscapes

M. Weigt, O. Tenaillon, E. Ruppé, 2022, Nature Communications.

Meet-U: Educating through research immersion

Alessandra Carbone, Yann Ponty, Guillaume Bouvier, 2018, PLoS Comput. Biol..

A multi-scale coevolutionary approach to predict interactions between protein domains

Giancarlo Croce, Thomas Gueudre, Martin Weigt, 2019, bioRxiv.

An evolution-based model for designing chorismate mutase enzymes

Simona Cocco, Rama Ranganathan, Martin Weigt, 2020, Science.

Inferring protein-protein interaction networks from inter-protein sequence co-evolution

A. Pagnani, M. Weigt, H. Szurmant, 2015, bioRxiv.

Inverse statistical physics of protein sequences: a key issues review

Simona Cocco, Rémi Monasson, Martin Weigt, 2017, Reports on progress in physics. Physical Society.

Simplest random K-satisfiability problem

Riccardo Zecchina, Federico Ricci-Tersenghi, Martin Weigt, 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

Phylogenetic correlations can suffice to infer protein partners from sequences

Martin Weigt, Anne-Florence Bitbol, Guillaume Marmier, 2019, bioRxiv.

The evolution of the temporal program of genome replication

M. Weigt, G. Fischer, C. Thermes, 2017, bioRxiv.

Aligning biological sequences by exploiting residue conservation and coevolution.

A. Pagnani, M. Weigt, F. Zamponi, 2020, Physical review. E.

Aligning biological sequences by exploiting residue conservation and coevolution

Andrea Pagnani, Anna Paola Muntoni, Martin Weigt, 2020, bioRxiv.

Inference of sparse combinatorial-control networks from gene-expression data: a message passing approach

Riccardo Zecchina, Alfredo Braunstein, Andrea Pagnani, 2010, BMC Bioinformatics.

Gene-network inference by message passing

M. Weigt, A. Braunstein, R. Zecchina, 2008, 0812.0936.

Inference algorithms for gene networks: a statistical mechanics analysis

M. Weigt, A. Braunstein, R. Zecchina, 2008, 0812.0940.

Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction

Simona Cocco, Rémi Monasson, Martin Weigt, 2015, Nucleic acids research.

Direct coupling analysis for protein contact prediction.

Terence Hwa, Martin Weigt, Faruck Morcos, 2014, Methods in molecular biology.

Clustering by Soft-constraint Affinity Propagation: Applications to Gene-expression Data

Michele Leone, Martin Weigt, Sumedha, 2022 .

Derivations of τ-measurable Operators

M. Weigt, 2009 .

DERIVATIONS OF FRÉCHET NUCLEAR GB$^{\ast }$-ALGEBRAS

M. Weigt, I. ZARAKAS, 2015, Bulletin of the Australian Mathematical Society.

Tensor products of generalized B⁎-algebras

M. Weigt, M. Fragoulopoulou, A. Inoue, 2014 .

Tensor products of unbounded operator algebras

M. Weigt, M. Fragoulopoulou, A. Inoue, 2014 .

Applications of Generalized B∗-Algebras to Quantum Mechanics

M. Weigt, 2021, Trends in Mathematics.

Derivations of generalized B*-algebras

M. Weigt, I. Zarakas, 2013 .

Derivations of Locally Convex -Algebras

M. Weigt, M. Fragoulopoulou, I. Zarakas, 2011 .

On formal power series over topological algebras

M. Weigt, I. Zarakas, 2022, Extracta Mathematicae.

Sparse generative modeling via parameter reduction of Boltzmann machines: Application to protein-sequence families.

Anna Paola Muntoni, Francesco Zamponi, Martin Weigt, 2020, Physical review. E.

Evolution-based design of chorismate mutase enzymes

Simona Cocco, Donald Hilvert, Rama Ranganathan, 2020, bioRxiv.

Statistical physics of interacting proteins: Impact of dataset size and quality assessed in synthetic sequences.

M. Weigt, Pierre Mergny, A. Bitbol, 2019, Physical review. E.

Statistical physics of interacting proteins: impact of dataset size and quality assessed in synthetic sequences

Martin Weigt, Anne-Florence Bitbol, Carlos A. Gandarilla-P'erez, 2019, bioRxiv.

The number of guards needed by a museum: A phase transition in vertex covering of random graphs

Alexander K. Hartmann, Martin Weigt, M. Weigt, 2000, Physical review letters.

Computational modeling of phosphotransfer complexes in two-component signaling.

Terence Hwa, Martin Weigt, Alexander Schug, 2010, Methods in enzymology.

Selection of sequence motifs and generative Hopfield-Potts models for protein families

Martin Weigt, Kai Shimagaki, M. Weigt, 2019, bioRxiv.

Modeling Sequence-Space Exploration and Emergence of Epistatic Signals in Protein Evolution

M. Weigt, F. Zamponi, Juan Rodriguez-Rivas, 2021, bioRxiv.

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

Simona Cocco, Rémi Monasson, Martin Weigt, 2012, PLoS Comput. Biol..

adabmDCA: adaptive Boltzmann machine learning for biological sequences

Andrea Pagnani, Anna Paola Muntoni, Francesco Zamponi, 2021, BMC Bioinform..

On the effect of phylogenetic correlations in coevolution-based contact prediction in proteins

Edwin Rodriguez Horta, M. Weigt, 2020, PLoS Comput. Biol..

Sparse generative modeling of protein-sequence families pdf

Anna Paola Muntoni, Martin Weigt, Pierre Barrat-Charlaix, 2020, ArXiv.

Generating interacting protein sequences using domain-to-domain translation

A. Pagnani, M. Weigt, Barthélémy Meynard-Piganeau, 2022, bioRxiv.

Machine-learning-assisted Monte Carlo fails at sampling computationally hard problems

M. Weigt, F. Zamponi, Simone Ciarella, 2022, Mach. Learn. Sci. Technol..

Clustering by soft-constraint affinity propagation: applications to gene-expression data

Sumedha, M. Weigt, M. Leone, 2007, Bioinform..

Statistical mechanics perspective on the phase transition in vertex covering of finite-connectivity random graphs

Alexander K. Hartmann, Martin Weigt, M. Weigt, 2000, Theor. Comput. Sci..

Improving landscape inference by integrating heterogeneous data in the inverse Ising problem

Martin Weigt, Matteo Figliuzzi, Pierre Barrat-Charlaix, 2016, Scientific Reports.

Spectrum preserving linear mappings between Banach algebras

M. Weigt, 2003 .

Solving satisfiability problems by fluctuations: The dynamics of stochastic local search algorithms

Alexander K. Hartmann, Wolfgang Barthel, Martin Weigt, 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

Inter-residue, inter-protein and inter-family coevolution: bridging the scales.

Martin Weigt, Hendrik Szurmant, M. Weigt, 2018, Current opinion in structural biology.

Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-

R. Zecchina, Carlo Baldassi, A. Pagnani, 2022 .

Inverse statistical physics of protein sequences: a key issues review

R. Monasson, S. Cocco, M. Weigt, 2017, Reports on progress in physics. Physical Society.

Replica structure of one-dimensional disordered Ising models

R. Monasson, M. Weigt, 1996, cond-mat/9608149.

Computational complexity arising from degree correlations in networks

Alexei Vazquez, Martin Weigt, M. Weigt, 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

The satisfiability problem

Alexander K. Hartmann, Martin Weigt, M. Weigt, 2006 .

TULIP — a Transformer based Unsupervised Language model for Interacting Peptides and T-cell receptors that generalizes to unseen epitopes

T. Mora, M. Weigt, A. Walczak, 2024, bioRxiv.

Statistical mechanics perspective on the phase transition in vertex covering of finite-connectivity random graphs

M. Weigt, A. Hartmann, 2000, Theor. Comput. Sci..

Selection of sequence motifs and generative Hopfield-Potts models for protein families

M. Weigt, Kai Shimagaki, 2019, bioRxiv.

Constraint Satisfaction by Survey Propagation

Riccardo Zecchina, Marc Mézard, Alfredo Braunstein, 2002, Computational Complexity and Statistical Physics.

High-resolution protein complexes from integrating genomic information with molecular simulation

J. Onuchic, T. Hwa, M. Weigt, 2009, Proceedings of the National Academy of Sciences.

Rbm10 facilitates heterochromatin assembly via the Clr6 HDAC complex

M. Weigt, Wei Chen, S. Kempa, 2019, Epigenetics & Chromatin.

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

R. Monasson, S. Cocco, M. Weigt, 2012, PLoS Comput. Biol..