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Emanuele Paci
PeerJ Editor
700 Points

Contributions by role

Editor 700

Contributions by subject area

Biochemistry
Bioinformatics
Biophysics
Biotechnology
Computational Biology
Genomics
Computational Science
Molecular Biology

Emanuele Paci

PeerJ Editor

Summary

Professor at University of Bologna. From 2004 to 2021 Associate Professor in Computational Biophysics at University of Leeds. From 2001 to 2004, Oberassistent at the Department of Biochemistry, University of Zurich.

Biochemistry Biophysics Computational Biology

Editing Journals

PeerJ - the Journal of Life & Environmental Sciences

Past or current institution affiliations

University of Bologna

Work details

Associate Professor in Computational Biophysics

University of Bologna
Dipartimento di Fisica e Astronomia
Most of my research in the past decade has been devoted to advance understanding of properties of macromolecules in biological contexts, by using computer simulations to establish a relation between physical models and experimental measurements. One unique property of biological polymers such as proteins and RNA is their ability to populate a state characterised by a precisely defined conformation, unlike any man-made polymers. Protein folding is one of the major focuses of our recent research, with a particular interest to the relation between folded structure, unfolding pathway and mechanical properties. Our theoretical and computational research in this field has had impact on the way experiments are performed and interpreted, while mechanical response is increasingly recognised as an essential part of many biological processes. More recently we have turned our interests to the growth of bacterial pili, rational design of symmetric protein complexes such as capsids (with B. Turnbull), analysis of time resolved X-ray spectroscopy data (with A. Pearson), determination of structure and dynamics of macromolecular compounds from cryo-EM (with S. Muench) and hydrogen-exchange mass spectroscopy experiments (with R. Tuma).

Websites

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PeerJ Contributions

  • Edited 7

Academic Editor on

June 26, 2020
Conformational heterogeneity of Savinase from NMR, HDX-MS and X-ray diffraction analysis
Shanshan Wu, Tam T.T.N. Nguyen, Olga V. Moroz, Johan P. Turkenburg, Jens E. Nielsen, Keith S. Wilson, Kasper D. Rand, Kaare Teilum
https://doi.org/10.7717/peerj.9408 PubMed 32617193
December 18, 2019
Charge and hydrophobicity are key features in sequence-trained machine learning models for predicting the biophysical properties of clinical-stage antibodies
Max Hebditch, Jim Warwicker
https://doi.org/10.7717/peerj.8199 PubMed 31976163
June 28, 2019
TOXIFY: a deep learning approach to classify animal venom proteins
T. Jeffrey Cole, Michael S. Brewer
https://doi.org/10.7717/peerj.7200 PubMed 31293833
June 11, 2018
How well do force fields capture the strength of salt bridges in proteins?
Mustapha Carab Ahmed, Elena Papaleo, Kresten Lindorff-Larsen
https://doi.org/10.7717/peerj.4967 PubMed 29910983
May 3, 2016
Towards a barrier height benchmark set for biologically relevant systems
Jimmy C. Kromann, Anders S. Christensen, Qiang Cui, Jan H. Jensen
https://doi.org/10.7717/peerj.1994 PubMed 27168993
May 21, 2013
PeptideBuilder: A simple Python library to generate model peptides
Matthew Z. Tien, Dariya K. Sydykova, Austin G. Meyer, Claus O. Wilke
https://doi.org/10.7717/peerj.80 PubMed 23717802
February 12, 2013
Malleable ribonucleoprotein machine: protein intrinsic disorder in the Saccharomyces cerevisiae spliceosome
Maria de Lourdes Coelho Ribeiro, Julio Espinosa, Sameen Islam, Osvaldo Martinez, Jayesh Jamnadas Thanki, Stephanie Mazariegos, Tam Nguyen, Maya Larina, Bin Xue, Vladimir N. Uversky
https://doi.org/10.7717/peerj.2 PubMed 23638354