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.
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Titolo: | A Review of Quasi-perfect Secondary Structure Prediction Servers |
Autori: | MUSCI, MIRTO (Corresponding) |
Data di pubblicazione: | 2019 |
Serie: | |
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. |
Handle: | http://hdl.handle.net/11571/1288191 |
ISBN: | 978-3-030-27683-6 978-3-030-27684-3 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |