Publication Details

CalFitter: A web server for analysis of protein thermal denaturation data

BEDNÁŘ David, DAMBORSKÝ Jiří, KUNKA Antonín, MAZURENKO Stanislav, NEDELJKOVIĆ Sava, PROKOP Zbyněk and ŠTOURAČ Jan. CalFitter: A web server for analysis of protein thermal denaturation data. Biochemistry & Molecular Biology, vol. 8, 2018. ISSN 2211-5463.
Czech title
CalFitter: webový server pro analýzu dat tepelné denaturace proteinů
Type
abstract
Language
english
Authors
Bednář David, Mgr. (LL)
Damborský Jiří, prof. Mgr., Dr. (SCI MUNI)
Kunka Antonín, Mgr., Ph.D. (LL)
Mazurenko Stanislav, Ph.D. (LL)
Nedeljković Sava, Bc. (FIT BUT)
Prokop Zbyněk, doc. RnDr., Ph.D. (LL)
Štourač Jan (LL)
Keywords

Computational Bilology, Protein Denaturation, Internet, Protein Unfolding, Software

Abstract

Despite significant advances in the understanding of protein structure-function relationships, revealing protein folding pathways still poses a challenge due to a limited number of relevant experimental tools. Widely-used experimental techniques, such as calorimetry or spectroscopy, critically depend on a proper data analysis. Currently, there are only separate data analysis tools available for each type of experiment with a limited model selection. To address this problem, we have developed the CalFitter web server to be a unified platform for comprehensive data fitting and analysis of protein thermal denaturation data. The server allows simultaneous global data fitting using any combination of input data types and offers twelve protein unfolding pathway models for selection, including irreversible transitions often missing from other tools. The data fitting produces optimal parameters, their confidence intervals, and statistical information to define unfolding pathways. The server provides an interactive and easy-to-use interface that allows users to directly analyse input datasets and simulate modelled output based on the model parameters. CalFitter web server is available free at https://loschmidt.chemi.muni.cz/calfitter/.

Published
2018
Pages
404-404
Journal
Biochemistry & Molecular Biology, vol. 8, ISSN 2211-5463
Book
FEBS OPEN BIO
Publisher
Inria, Willow Computer vision and machine learning research laboratory
Place
Hoboken, US
UT WoS
000437674104296
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