Martin Weigt - researchr alias

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Viewing Publication 1 - 18 from 18

2023

Machine-learning-assisted Monte Carlo fails at sampling computationally hard problemsSimone Ciarella, Jeanne Trinquier, Martin Weigt, Francesco Zamponi. mlst, 4(1):10501, March 2023. [doi]

Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteinsCarlos A. Gandarilla-Pérez, Sergio Pinilla, Anne-Florence Bitbol, Martin Weigt. ploscb, 19(3), March 2023. [doi]

2021

On the effect of phylogenetic correlations in coevolution-based contact prediction in proteinsEdwin Rodriguez Horta, Martin Weigt. ploscb, 17(5), 2021. [doi]

adabmDCA: adaptive Boltzmann machine learning for biological sequencesAnna Paola Muntoni, Andrea Pagnani, Martin Weigt, Francesco Zamponi. bmcbi, 22(3):528, 2021. [doi]

2020

Predicting Interacting Protein Pairs by Coevolutionary Paralog MatchingThomas Gueudré, Carlo Baldassi, Andrea Pagnani, Martin Weigt. In Stefan Canzar, Francisca Rojas Ringeling, editors, Protein-Protein Interaction Networks, Methods and Protocols. Volume 2074 of Methods in Molecular Biology, pages 57-65, Springer, 2020. [doi]

FilterDCA: Interpretable supervised contact prediction using inter-domain coevolutionMaureen Muscat, Giancarlo Croce, Edoardo Sarti, Martin Weigt. ploscb, 16(10), 2020. [doi]

2019

2018

Meet-U: Educating through research immersionNika Abdollahi, Alexandre Albani, Eric Anthony, Agnes Baud, Mélissa Cardon, Robert Clerc, Dariusz Czernecki, Romain Conte, Laurent David, Agathe Delaune, Samia Djerroud, Pauline Fourgoux, Nadège Guiglielmoni, Jeanne Laurentie, Nathalie Lehmann, Camille Lochard, Rémi Montagne, Vasiliki Myrodia, Vaitea Opuu, Elise Parey, Lélia Polit, Sylvain Privé, Chloé Quignot, Maria Ruiz-Cuevas, Mariam Sissoko, Nicolas Sompairac, Audrey Vallerix, Violaine Verrecchia, Marc Delarue, Raphaël Guérois, Yann Ponty, Sophie Sacquin-Mora, Alessandra Carbone, Christine Froidevaux, Stéphane Le Crom, Olivier Lespinet, Martin Weigt, Samer Abboud, Juliana S. Bernardes, Guillaume Bouvier, Chloé Dequeker, Arnaud Ferré, Patrick Fuchs, Gaëlle Lelandais, Pierre Poulain, Hugues Richard, Hugo Schweke, Elodie Laine, Anne Lopes. ploscb, 14(3), 2018. [doi]

2013

2010

Inference of sparse combinatorial-control networks from gene-expression data: a message passing approachMarc Bailly-Bechet, Alfredo Braunstein, Andrea Pagnani, Martin Weigt, Riccardo Zecchina. bmcbi, 11:355, 2010. [doi]

2009

The importance of dilution in the inference of biological networksAlejandro Lage-Castellanos, Andrea Pagnani, Martin Weigt. allerton 2009: 531-538 [doi]

2007

Clustering by soft-constraint affinity propagation: applications to gene-expression dataMichele Leone, Sumedha, Martin Weigt. bioinformatics, 23(20):2708-2715, 2007. [doi]

2006

Constraint Satisfaction by Survey PropagationAlfredo Braunstein, Marc Mézard, Martin Weigt, Riccardo Zecchina. In Allon G. Percus, Gabriel Istrate, Cristopher Moore, editors, Computational Complexity and Statistical Physics. Studies in the sciences of complexity, pages 107-124, Oxford University Press, 2006.

2005

Phase transition and finite-size scaling in the vertex-cover problemAlexander K. Hartmann, Wolfgang Barthel, Martin Weigt. cphysics, 169(1-3):234-237, 2005. [doi]

2001

Statistical mechanics perspective on the phase transition in vertex covering of finite-connectivity random graphsAlexander K. Hartmann, Martin Weigt. TCS, 265(1-2):199-225, 2001. [doi]

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