New algorithms for inference and optimization from large-scale biological data

Risultati finali

New inference techniques. Maximum inter-alignment matching

[Month 24] Development of novel inference techniques including prior knowledge as input to T2.1b. Study of the maximum inter-alignment matching of families with paralogs.. Message-passing method for sampling high-dimensional polytopes including prior knowledge.

RepSeq database

[Month 24] Publication of the curated datasets (T3.1) on the project-portal.

Functional modules

Month 58 Results for longrange effects and predictions on functional modules in the human posttranscriptional regulatory and signaling network Integrated regulatory networks for specific cell types

Gold Standard Database. Deployment of algorithmic pipeline

[Month 24]. “Gold-Standard”: a list of multi-domain interacting proteins of known structure. Contact maps at different cutoffs will be available, together with the list of sequences in Pfam and Uniprot, and proposed seeds for the MSAs. Deployment of the algorithmic pipeline for maximizing the inter-alignment information developed as D1.2

Reconstruction of regulatory and signaling networks

[Month 24]: Algorithm for the efficient reconstruction/inference of regulatory networks integrating transcriptional and post-transcriptional data bases, expression data bases, sigalling networks and data bases for validated interactions.

Prediction highly neutralizing antibodies. Experimental validation

Month 40 Rational prediction o biomolecules from model inference Wetlab validation of the biomolecule phenotypes

Integrative analysis of gene expression and cancer metabolism

[Month 24]: Algorithm for the efficient analysis of metabolism and gene expression at genome scale and in tissue.

Bacterial core interactome based on proximity. Full bacterial interactome

Month 40 First predictions of the coevolutionary inferred Bacterial Core interactome based on operon based proximity Integration of T23 for predicting the whole bacterial interactome

Improved inference for graphical models

Month 36 Improved inference strategies for analyzing graphical models

Predictors of cell responses. Protocol of experimental design in-tissue experiments

Month 58 Analysis of different predictors of cellular responses to changes in the levels of key enzymes andor uptake systems relevant for proliferative regimes specifically for bacteria or cancer cells

Progress report 1

[month 12] Progress Report 1

International Workshop - Habana

[month 24] International Workshop – Habana

International Workshop - Buenos Aires

[month 36] International Workshop – Buenos Aires.

Data management Plan (DMP)

[month 6 - revised version months 24, 48] Data Management Plan (DMP).

INFERNET website

[month 3] INFERNET website

International School - Paris

[month 16] International School – Paris.

Progress report 2

[month 36] Progress Report 2.

Final Conference - Turin

[month 28] Final conference – Turin.

Pubblicazioni

A density consistency approach to the inverse Ising problem

Autori: Alfredo Braunstein; Giovanni Catania; Luca Dall'Asta; Luca Dall'Asta; Anna Paola Muntoni
Pubblicato in: Journal of Statistical Mechanics: Theory and Experiment, Numero 26, 2021, ISSN 1742-5468
Editore: Institute of Physics
DOI: 10.48550/arxiv.2010.13746

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

Autori: Juan Rodriguez-Rivas, Giancarlo Croce, Maureen Muscat, Martin Weigt
Pubblicato in: PNAS, 2022, ISSN 0027-8424
Editore: National Academy of Sciences
DOI: 10.1073/pnas.2113118119

Inference of metabolic fluxes in nutrient-limited continuous cultures: A Maximum Entropy approach with the minimum information

Autori: Jose A. Pereiro-Morejón; Jorge Fernández-de-Cossio-Díaz; R. Mulet;
Pubblicato in: iScience, 2022, ISSN 2589-0042
Editore: CellPress
DOI: 10.1016/j.isci.2022.105450

Contamination source detection in water distribution networks using belief propagation

Autori: Ernesto Ortega; Alfredo Braunstein; Alfredo Braunstein; Alejandro Lage-Castellanos
Pubblicato in: Stochastic Environmental Research and Risk Assessment, Numero 29, 2020, ISSN 1436-3240
Editore: Springer Verlag
DOI: 10.48550/arxiv.1809.10626

Stochastic and parameter analysis for an integrative cancer model

Autori: Marcela V. Reale; David Hipólito Margarit; Ariel F. Scagliotti; Lilia M. Romanelli
Pubblicato in: Physica Scripta, Numero 10, 2022, ISSN 0031-8949
Editore: Royal Swedish Academy of Sciences
DOI: 10.1088/1402-4896/aca566

Statistical mechanics of interacting metabolic networks.

Autori: Jorge Fernandez-de-Cossio-Diaz; Jorge Fernandez-de-Cossio-Diaz; Roberto Mulet
Pubblicato in: Physical Review E, Numero 21, 2020, ISSN 1539-3755
Editore: American Physical Society
DOI: 10.1103/physreve.101.042401

Expectation propagation on the diluted Bayesian classifier.

Autori: Alfredo Braunstein; Alfredo Braunstein; Thomas Gueudré; Andrea Pagnani; Andrea Pagnani; Mirko Pieropan
Pubblicato in: Physical Review E, Numero 39, 2021, ISSN 1539-3755
Editore: American Physical Society
DOI: 10.1103/physreve.103.043301

Path-integral solution of MacArthur’s resource-competition model for large ecosystems with random species-resources couplings

Autori: A. R. Batista-Tomás; Andrea De Martino; Roberto Mulet
Pubblicato in: Chaos, 2021, ISSN 1054-1500
Editore: American Institute of Physics
DOI: 10.1063/5.0046972

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

Autori: Pierre Barrat-Charlaix; Anna Paola Muntoni; Kai Shimagaki; Martin Weigt; Francesco Zamponi
Pubblicato in: Physical Review E, Numero 5, 2021, ISSN 1539-3755
Editore: American Physical Society
DOI: 10.48550/arxiv.2011.11259

Efficient generative modeling of protein sequences using simple autoregressive models

Autori: Jeanne Trinquier; Jeanne Trinquier; Guido Uguzzoni; Andrea Pagnani; Francesco Zamponi; Martin Weigt
Pubblicato in: Nature Communications, Numero 11, 2022, Pagina/e 2021, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.48550/arxiv.2103.03292

Global multivariate model learning from hierarchically correlated data

Autori: Edwin Rodriguez Horta; Alejandro Lage-Castellanos; Martin Weigt; Pierre Barrat-Charlaix
Pubblicato in: Journal of Statistical Mechanics: Theory and Experiment, Numero 29, 2021, ISSN 1742-5468
Editore: Institute of Physics
DOI: 10.1088/1742-5468/ac06c2

The cavity master equation: average and fixed point of the ferromagnetic model in random graphs

Autori: Eduardo Domínguez; David Machado; Roberto Mulet
Pubblicato in: Journal of Statistical Mechanics: Theory and Experiment, Numero 6, 2020, ISSN 1742-5468
Editore: Institute of Physics
DOI: 10.48550/arxiv.2004.03674

FilterDCA: Interpretable supervised contact prediction using inter-domain coevolution

Autori: Maureen Muscat, Giancarlo Croce, Edoardo Sarti, Martin Weigt
Pubblicato in: Plos Computational Biology, 2020, ISSN 1553-734X
Editore: Public Library of Science
DOI: 10.1371/journal.pcbi.1007621

Loop Corrections in Spin Models through Density Consistency.

Autori: Alfredo Braunstein; Alfredo Braunstein; Giovanni Catania; Luca Dall'Asta; Luca Dall'Asta
Pubblicato in: Physical Review Letters, Numero 15, 2019, ISSN 0031-9007
Editore: American Physical Society
DOI: 10.48550/arxiv.1810.10602

Evolution-based design of chorismate mutase enzymes

Autori: William P. Russ; Matteo Figliuzzi; Christian Stocker; Pierre Barrat-Charlaix; Michael Socolich; Pater Kast; Donald Hilvert; Rémi Monasson; Simona Cocco; Martin Weigt; Rama Ranganathan
Pubblicato in: Science, Numero 20, 2020, ISSN 0036-8075
Editore: American Association for the Advancement of Science
DOI: 10.1101/2020.04.01.020487

Analysis of cell proliferation and tissue remodelling uncovers a KLF4 activity score associated with poor prognosis in colorectal cancer

Autori: Silvia Halim; Elke Markert; Alexei Vazquez
Pubblicato in: British Journal of Cancer, Numero 5, 2018, ISSN 0007-0920
Editore: Nature Publishing Group
DOI: 10.1038/s41416-018-0253-0

An integrative model of cancer cell differentiation with immunotherapy*

Autori: David H Margarit; Nadia S González; Lilia M Romanelli; Alejandro J Fendrik; Ariel F Scagliotti; Marcela V Reale
Pubblicato in: Biophysical Journal, 2021, ISSN 1478-3967
Editore: Institute of Physics Publishing
DOI: 10.1088/1478-3975/ac2e72

Ancestral Sequence Reconstruction for Co-evolutionary models

Autori: Rodríguez-Horta, Edwin; Lage-Castellanos, Alejandro; Mulet, Roberto
Pubblicato in: Journal of Statistical Mechanics: Theory and Experiment, Numero 9, 2022, ISSN 1742-5468
Editore: Institute of Physics
DOI: 10.48550/arxiv.2108.03801

Unsupervised Inference of Protein Fitness Landscape from Deep Mutational Scan

Autori: Jorge Fernandez-de-Cossio-Diaz; Guido Uguzzoni; Andrea Pagnani
Pubblicato in: Molecular Biology and Evolution, 2020, ISSN 0737-4038
Editore: Oxford University Press
DOI: 10.1093/molbev/msaa204

Initial cell density encodes proliferative potential in cancer cell populations

Autori: Chiara Enrico Bena; Marco Del Giudice; Alice Grob; Thomas Gueudré; Mattia Miotto; Dimitra Gialama; Matteo Osella; Emilia Turco; Francesca Ceroni; Andrea De Martino; Carla Bosia
Pubblicato in: Scientific Reports, Numero 5, 2021, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-021-85406-z

AMaLa: Analysis of Directed Evolution Experiments via Annealed Mutational Approximated Landscape

Autori: Luca Sesta; Guido Uguzzoni; Jorge Fernandez-de-Cossio-Diaz; Andrea Pagnani
Pubblicato in: International Journal of Molecular Sciences, Numero 20, 2021, ISSN 1422-0067
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/ijms222010908

Network reconstruction from infection cascades

Autori: Alfredo Braunstein; Alessandro Ingrosso; Anna Paola Muntoni; Anna Paola Muntoni; Anna Paola Muntoni
Pubblicato in: Journal of the Royal Society Interface, Numero 9, 2019, ISSN 1742-5689
Editore: The Royal Society
DOI: 10.48550/arxiv.1609.00432

adabmDCA: adaptive Boltzmann machine learning for biological sequences.

Autori: Anna Paola Muntoni; Andrea Pagnani; Martin Weigt; Francesco Zamponi
Pubblicato in: BMC Bioinformatics, Numero 11, 2021, ISSN 1471-2105
Editore: BioMed Central
DOI: 10.1186/s12859-021-04441-9

Exploration-exploitation tradeoffs dictate the optimal distributions of phenotypes for populations subject to fitness fluctuations.

Autori: "De Martino, Andrea; Gueudré , Thomas; Miotto, Mattia"
Pubblicato in: Physical Review E, Numero 21, 2019, ISSN 1539-3755
Editore: American Physical Society
DOI: 10.48550/arxiv.1809.11030

Stochastic cell renewal process and lengthening of cell cycle

Autori: Alejandro Fendrik; Lilia Romanelli; Ernesto Rotondo
Pubblicato in: Physical Biology, 2019, ISSN 1478-3967
Editore: Institute of Physics Publishing
DOI: 10.1088/1478-3975/ab576c

Limits of aerobic metabolism in cancer cells

Autori: Jorge Fernandez-de-Cossio-Diaz, Alexei Vazquez
Pubblicato in: Scientific Reports, Numero 7/1, 2017, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-017-14071-y

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures

Autori: Jorge Fernandez-de-Cossio-Diaz, Kalet Leon, Roberto Mulet
Pubblicato in: PLOS Computational Biology, Numero 13/11, 2017, Pagina/e e1005835, ISSN 1553-7358
Editore: Jorge Fernandez-de-Cossio-Diaz
DOI: 10.1371/journal.pcbi.1005835

Exploring the diluted ferromagnetic p-spin model with a Cavity Master Equation

Autori: Aurell, Erik; Domínguez, Eduardo; Machado, David; Mulet, Roberto
Pubblicato in: Physical Review E, Numero 1, 2018, ISSN 2470-0053
Editore: Roberto Mulet
DOI: 10.1103/PhysRevE.97.050103

Independent channels for miRNA biosynthesis ensure efficient static and dynamic control in the regulation of the early stages of myogenesis

Autori: Jonathan Fiorentino, Andrea De Martino
Pubblicato in: Journal of Theoretical Biology, Numero 430, 2017, Pagina/e 53-63, ISSN 0022-5193
Editore: Academic Press
DOI: 10.1016/j.jtbi.2017.06.038

Somatic mutagenesis in satellite cells associates with human skeletal muscle aging

Autori: Irene Franco, Anna Johansson, Karl Olsson, Peter Vrtačnik, Pär Lundin, Hafdis T. Helgadottir, Malin Larsson, Gwladys Revêchon, Carla Bosia, Andrea Pagnani, Paolo Provero, Thomas Gustafsson, Helene Fischer, Maria Eriksson
Pubblicato in: Nature Communications, Numero 9/1, 2018, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.1038/s41467-018-03244-6

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

Autori: Hendrik Szurmant, Martin Weigt
Pubblicato in: Current Opinion in Structural Biology, Numero 50, 2018, Pagina/e 26-32, ISSN 0959-440X
Editore: Elsevier BV
DOI: 10.1016/j.sbi.2017.10.014

Microenvironmental cooperation promotes early spread and bistability of a Warburg-like phenotype

Autori: Jorge Fernandez-de-Cossio-Diaz, Andrea De Martino, Roberto Mulet
Pubblicato in: Scientific Reports, Numero 7/1, 2017, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-017-03342-3

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

Autori: Matteo Figliuzzi, Pierre Barrat-Charlaix, Martin Weigt
Pubblicato in: Molecular Biology and Evolution, Numero 35/4, 2018, Pagina/e 1018-1027, ISSN 0737-4038
Editore: Oxford University Press
DOI: 10.1093/molbev/msy007

Translating ceRNA Susceptibilities into Correlation Functions

Autori: Araks Martirosyan, Matteo Marsili, Andrea De Martino
Pubblicato in: Biophysical Journal, Numero 113/1, 2017, Pagina/e 206-213, ISSN 0006-3495
Editore: Biophysical Society
DOI: 10.1016/j.bpj.2017.05.042

A physical model of cell metabolism

Autori: Jorge Fernandez-de-Cossio-Diaz, Alexei Vazquez
Pubblicato in: Scientific Reports, Numero 8/1, 2018, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-018-26724-7

An introduction to the maximum entropy approach and its application to inference problems in biology

Autori: Andrea De Martino, Daniele De Martino
Pubblicato in: Heliyon, Numero 4/4, 2018, Pagina/e e00596, ISSN 2405-8440
Editore: Helyon
DOI: 10.1016/j.heliyon.2018.e00596

Maximum entropy and population heterogeneity in continuous cell cultures

Autori: Jorge Fernandez-de-Cossio-Diaz, Roberto Mulet
Pubblicato in: PLOS Computational Biology, Numero 15/2, 2019, Pagina/e e1006823, ISSN 1553-7358
Editore: Public Library of Science
DOI: 10.1371/journal.pcbi.1006823

The intrinsic dimension of protein sequence evolution

Autori: Elena Facco, Andrea Pagnani, Elena Tea Russo, Alessandro Laio
Pubblicato in: PLOS Computational Biology, Numero 15/4, 2019, Pagina/e e1006767, ISSN 1553-7358
Editore: The Public Library of Science
DOI: 10.1371/journal.pcbi.1006767

Compressed sensing reconstruction using Expectation Propagation

Autori: Alfredo Braunstein, Anna Paola Muntoni, Andrea Pagnani, Mirko Pieropan
Pubblicato in: Journal of Physics A: Mathematical and Theoretical, 2019, ISSN 1751-8113
Editore: Institute of Physics Publishing
DOI: 10.1088/1751-8121/ab3065

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

Autori: Giancarlo Croce, Thomas Gueudré, Maria Virginia Ruiz Cuevas, Victoria Keidel, Matteo Figliuzzi, Hendrik Szurmant, Martin Weigt
Pubblicato in: PLOS Computational Biology, Numero 15/10, 2019, Pagina/e e1006891, ISSN 1553-7358
Editore: Public Library of Science
DOI: 10.1371/journal.pcbi.1006891

A common root for coevolution and substitution rate variability in protein sequence evolution

Autori: Francesca Rizzato, Stefano Zamuner, Andrea Pagnani, Alessandro Laio
Pubblicato in: Scientific Reports, Numero 9/1, 2019, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-019-53958-w

Theory of Nonequilibrium Local Search on Random Satisfaction Problems

Autori: Erik Aurell, Eduardo Domínguez, David Machado, Roberto Mulet
Pubblicato in: Physical Review Letters, Numero 123/23, 2019, ISSN 0031-9007
Editore: American Physical Society
DOI: 10.1103/physrevlett.123.230602

Nonconvex image reconstruction via expectation propagation

Autori: Anna Paola Muntoni, Rafael Díaz Hernández Rojas, Alfredo Braunstein, Andrea Pagnani, Isaac Pérez Castillo
Pubblicato in: Physical Review E, Numero 100/3, 2019, ISSN 2470-0045
Editore: APS
DOI: 10.1103/PhysRevE.100.032134

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

Autori: Kai Shimagaki, Martin Weigt
Pubblicato in: Physical Review E, Numero 100/3, 2019, ISSN 2470-0045
Editore: APS
DOI: 10.1103/PhysRevE.100.032128

Phylogenetic correlations can suffice to infer protein partners from sequences

Autori: Guillaume Marmier, Martin Weigt, Anne-Florence Bitbol
Pubblicato in: PLOS Computational Biology, Numero 15/10, 2019, Pagina/e e1007179, ISSN 1553-7358
Editore: Public Library of Science
DOI: 10.1371/journal.pcbi.1007179

Modeling functional resting-state brain networks through neural message passing on the human connectome

Autori: Julio A. Peraza-Goicolea, Eduardo Martínez-Montes, Eduardo Aubert, Pedro A. Valdés-Hernández, Roberto Mulet
Pubblicato in: Neural Networks, Numero 123, 2020, Pagina/e 52-69, ISSN 0893-6080
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2019.11.014

Cell population heterogeneity driven by stochastic partition and growth optimality

Autori: Jorge Fernandez-de-Cossio-Diaz, Roberto Mulet, Alexei Vazquez
Pubblicato in: Scientific Reports, Numero 9/1, 2019, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-019-45882-w

Toward Inferring Potts Models for Phylogenetically Correlated Sequence Data

Autori: Edwin Rodriguez Horta, Pierre Barrat-Charlaix, Martin Weigt
Pubblicato in: Entropy, Numero 21/11, 2019, Pagina/e 1090, ISSN 1099-4300
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/e21111090

Competing endogenous RNA crosstalk at system level

Autori: Mattia Miotto, Enzo Marinari, Andrea De Martino
Pubblicato in: PLOS Computational Biology, Numero 15/11, 2019, Pagina/e e1007474, ISSN 1553-7358
Editore: Public Library of Science
DOI: 10.1371/journal.pcbi.1007474

Formate Induces a Metabolic Switch in Nucleotide and Energy Metabolism

Autori: Kristell Oizel, Jacqueline Tait-Mulder, Jorge Fernandez-de-Cossio-Diaz, Matthias Pietzke, Holly Brunton, Sandeep Dhayade, Dimitris Athineos, Sergio Lilla, Giovanny Rodriguez Blanco, David Sumpton, Gillian Mackay, Karen Blyth, Sara Zanivan, Johannes Meiser, Alexei Vazquez
Pubblicato in: SSRN Electronic Journal, 2019, ISSN 1556-5068
Editore: Cell Press
DOI: 10.2139/ssrn.3456295

A yield-cost tradeoff governs Escherichia coli's decision between fermentation and respiration in carbon-limited growth

Autori: Matteo Mori; Enzo Marinari; Andrea De Martino
Pubblicato in: NPJ Systems Biology and Applications, Numero 30, 2019, ISSN 2056-7189
Editore: Springer Nature
DOI: 10.1101/113183

Ancestral sequence reconstruction for co-evolutionary models

Autori: E Rodríguez-Horta; A Lage-Castellanos; R Mulet
Pubblicato in: Journal of Statistical Mechanics: Theory and Experiment, 2021, ISSN 1742-5468
Editore: Institute of Physics
DOI: 10.1088/1742-5468/ac3d93

Relationship between fitness and heterogeneity in exponentially growing microbial populations

Autori: Anna Paola Muntoni; Alfredo Braunstein; Andrea Pagnani; Daniele De Martino; Andrea De Martino
Pubblicato in: Biophysical Journal, Numero 1, 2022, ISSN 0006-3495
Editore: Biophysical Society
DOI: 10.48550/arxiv.2104.02594

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

Autori: Carlos A. Gandarilla-Pérez; Carlos A. Gandarilla-Pérez; Pierre Mergny; Martin Weigt; Anne-Florence Bitbol; Anne-Florence Bitbol
Pubblicato in: Physical Review E, Numero 18, 2020, ISSN 1539-3755
Editore: American Physical Society
DOI: 10.1101/2019.12.23.887307

Optimizing the Dilution Protocol in Continuous Cell Cultures

Autori: Barbara Ariane Perez Fernandez; Roberto Mulet
Pubblicato in: Revista Cubana de Fisica, 2021, ISSN 2224-7939
Editore: Sociedad Cubana de Fisica

Aligning biological sequences by exploiting residue conservation and coevolution.

Autori: Anna Paola Muntoni; Anna Paola Muntoni; Anna Paola Muntoni; Andrea Pagnani; Martin Weigt; Francesco Zamponi
Pubblicato in: Physical Review E, Numero 15, 2020, ISSN 1539-3755
Editore: American Physical Society
DOI: 10.48550/arxiv.2005.08500

Probing Single-Cell Fermentation Fluxes and Exchange Networks via pH-Sensing Hybrid Nanofibers

Autori: Valentina Onesto, Stefania Forciniti, Francesco Alemanno, Krishnadev Narayanankutty Krishnadev Narayanankutty Biofisika Institutua (UPV/EHU, CSIC) and Fundación Biofísica Bizkaia, LeioaE-48940, Spain More by Krishnadev Narayanankutty Orcidhttps://orcid.org/0000-0001-7705-3213 , Anil Chandra, Saumya Prasad, Amalia Azzariti, Giuseppe Gigli, Adriano Barra, Andrea De Martino, Daniele De Martino, Lor
Pubblicato in: ACS Nano, 2022, ISSN 1936-0851
Editore: American Chemical Society
DOI: 10.1021/acsnano.2c06114

MicroRNAs organize intrinsic variation into stem cell states

Autori: Meenakshi Chakraborty; Meenakshi Chakraborty; Sofia Hu; Erica Visness; Marco Del Giudice; Andrea De Martino; Carla Bosia; Phillip A. Sharp; Salil Garg; Salil Garg
Pubblicato in: PNAS, Numero 33, 2020, ISSN 0027-8424
Editore: National Academy of Sciences
DOI: 10.1073/pnas.1920695117

Dynamics of epidemics from cavity master equations: Susceptible-infectious-susceptible models

Autori: Ernesto Ortega; David Machado; Alejandro Lage-Castellanos
Pubblicato in: Physical Review E, Numero 9, 2022, ISSN 1539-3755
Editore: American Physical Society
DOI: 10.1103/physreve.105.024308

Modeling sequence-space exploration and emergence of epistatic signals in protein evolution

Autori: Bisardi, Matteo; Rodriguez-Rivas, Juan; Zamponi, Francesco; Weigt, Martin
Pubblicato in: Molecular Biology and Evolution, Numero 9, 2022, ISSN 0737-4038
Editore: Oxford University Press
DOI: 10.48550/arxiv.2106.02441

Predicting Interacting Protein Pairs by Coevolutionary Paralog Matching.

Autori: Thomas Gueudré; Carlo Baldassi; Andrea Pagnani; Martin Weigt
Pubblicato in: Protein-Protein Interaction Networks, Numero 15, 2019, Pagina/e 57–65, ISBN 978-1-4939-9872-2
Editore: Humana, New York, NY
DOI: 10.1007/978-1-4939-9873-9_5

Kinetic modelling of competition and depletion of shared miRNAs by competing endogenous RNAs

Autori: Martirosyan, Araks; Del Giudice, Marco; Bena, Chiara Enrico; Pagnani, Andrea; Bosia, Carla; De Martino, Andrea
Pubblicato in: Computational Biology of Non-Coding RNA, Numero 15, 2019, Pagina/e 367–409, ISBN 978-1-4939-8981-2
Editore: Humana Press, New York, NY
DOI: 10.48550/arxiv.1812.09538

Kinetic Modelling of Competition and Depletion of Shared miRNAs by Competing Endogenous RNAs

Autori: Araks Martirosyan, Marco Del Giudice, Chiara Enrico Bena, Andrea Pagnani, Carla Bosia, Andrea De Martino
Pubblicato in: Computational Biology of Non-Coding RNA - Methods and Protocols, Numero 1912, 2019, Pagina/e 367-409, ISBN 978-1-4939-8981-2
Editore: Springer New York
DOI: 10.1007/978-1-4939-8982-9_15

Influence of settings and predictors in neural network model performance: a Buenos Aires air quality case

Autori: Ariel F. Scagliotti; David H. Margarit; Marcela V. Reale; Guillermo A. Jorge
Pubblicato in: Procedia Computer Science, 2022, ISSN 1877-0509
Editore: Elsevier
DOI: 10.1016/j.procs.2022.11.019

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