Publications / Statistical Genomics and Biological Physics

Generating interacting protein sequences using domain-to-domain translation

Meynard-Piganeau B., Fabbri C., Weigt M., Pagnani A., Feinauer C. Bioinformatics (2023)

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1 July 2023

Publications / Statistical Genomics and Biological Physics

adabmDCA: adaptive Boltzmann machine learning for biological sequences

Muntoni A., Pagnani A., Weigt M., Zamponi F. BMC Bioinformatics (2021)

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1 December 2021

Publications / Statistical Genomics and Biological Physics

Efficient generative modeling of protein sequences using simple autoregressive models

Trinquier J., Uguzzoni G., Pagnani A., Zamponi F., Weigt M. Nature Communications (2021)

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4 October 2021

Publications / Statistical Genomics and Biological Physics

Aligning biological sequences by exploiting residue conservation and coevolution

Muntoni A., Pagnani A., Weigt M., Zamponi F. Physical Review E (2020)

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7 December 2020

Publications / Statistical Genomics and Biological Physics

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

Feinauer C., Szurmant H., Weigt M., Pagnani A. PLOS ONE (2016)

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16 February 2016

Publications / Statistical Genomics and Biological Physics

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

Baldassi C., Zamparo M., Feinauer C., Procaccini A., Zecchina R., Weigt M., Pagnani A. PLoS ONE (2014)

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24 March 2014

Publications / Statistical Genomics and Biological Physics

Perturbation biology: inferring signaling networks in cellular systems.

Molinelli E., Korkut A., Wang W., Miller M., Gauthier N., Jing X., Kaushik P., He Q., Mills G., Solit D., Pratilas C., Weigt M., Braunstein A., Pagnani A., Zecchina R., Sander C. PLoS Computational Biology (2013)

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19 December 2013