The secondary structure was rst described by Pauling et al. in 1951 [14] in their ndings of helical and sheet hydrogen bounding patterns in a protein backbone. Further re nements have been made since then, such as the description and identi cation of rst 3, then 8 local conformational states [10]. The accuracy of 3-state secondary structure prediction has risen during last 3 decades and now we are approaching to the theoretical limit of 88-90%. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. In this paper we review the best four scorer servers which provide the highest accuracy for 3- and 8-state secondary structure prediction.

A Review of Quasi-perfect Secondary Structure Prediction Servers

Marco Ferretti;Mirto Musci
2019-01-01

Abstract

The secondary structure was rst described by Pauling et al. in 1951 [14] in their ndings of helical and sheet hydrogen bounding patterns in a protein backbone. Further re nements have been made since then, such as the description and identi cation of rst 3, then 8 local conformational states [10]. The accuracy of 3-state secondary structure prediction has risen during last 3 decades and now we are approaching to the theoretical limit of 88-90%. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. In this paper we review the best four scorer servers which provide the highest accuracy for 3- and 8-state secondary structure prediction.
2019
Database and Expert Systems Applications. DEXA 2019
Anderst-Kotsis G. et al. (eds)
Computer Science & Engineering
Comitato scientifico
Inglese
contributo
30th International Conference on Database and Expert Systems Applications - DEXA 2019
August 26 - 29, 2019
Linz, Austria
Internazionale
ELETTRONICO
Communications in Computer and Information Science
1062
21
26
6
978-3-030-27683-6
978-3-030-27684-3
Springer
Protein seconday structure, deep neural networks, machine learning
none
Ferretti, Marco; Musci, Mirto
273
info:eu-repo/semantics/conferenceObject
2
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1288191
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