Lorenzo Di Rienzo

dblp:246/1643 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0003-4114-5049ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
protein structure analysis
1.022022
Thermometer: a webserver to predict protein thermal stability · Bioinform. 2022
Insights on protein thermal stability: a graph representation of molecular interactions · Bioinform. 2019
Bioinformatics and computational biology › molecular property prediction › protein property prediction
protein thermostability prediction
1.022022
Thermometer: a webserver to predict protein thermal stability · Bioinform. 2022
Insights on protein thermal stability: a graph representation of molecular interactions · Bioinform. 2019

Methods — techniques the papers use, named apart from their topics

structural information · 0.6network descriptor · 0.4graph theory · 0.4energy-weighted graphs · 0.4
YearPublicationVenuePosition
2022 Thermometer: a webserver to predict protein thermal stability
abstract
MOTIVATION: Thermal properties of proteins are of great importance for a number of theoretical and practical implications. Predicting the thermal stability of a protein is a difficult and still scarcely addressed task. RESULTS: Here, we introduce Thermometer, a webserver to assess the thermal stability of a protein using structural information. Thermometer is implemented as a publicly available, user-friendly interface. AVAILABILITY AND IMPLEMENTATION: Our server can be found at the following link (all major browser supported): http://service.tartaglialab.com/new_submission/thermometer_file. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Mattia Miotto, Alexandros Armaos, Lorenzo Di Rienzo, Giancarlo Ruocco, Edoardo Milanetti, Gian Gaetano Tartaglia
Bioinform.3
2019 Insights on protein thermal stability: a graph representation of molecular interactions
abstract
MOTIVATION: Understanding the molecular mechanisms of thermal stability is a challenge in protein biology. Indeed, knowing the temperature at which proteins are stable has important theoretical implications, which are intimately linked with properties of the native fold, and a wide range of potential applications from drug design to the optimization of enzyme activity. RESULTS: Here, we present a novel graph-theoretical framework to assess thermal stability based on the structure without any a priori information. In this approach we describe proteins as energy-weighted graphs and compare them using ensembles of interaction networks. Investigating the position of specific interactions within the 3D native structure, we developed a parameter-free network descriptor that permits to distinguish thermostable and mesostable proteins with an accuracy of 76% and area under the receiver operating characteristic curve of 78%. AVAILABILITY AND IMPLEMENTATION: Code is available upon request to [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Mattia Miotto, Pier Paolo Olimpieri, Lorenzo Di Rienzo, Francesco Ambrosetti, Pietro Corsi, Rosalba Lepore, Gian Gaetano Tartaglia, Edoardo Milanetti
Bioinform.3