New machine learning methods for prediction of protein secondary structures

• Autorzy: Błażewicz J. , Łukasiak P. , Wilk S.
• Języki publikacji: EN

Abstrakty

EN

The first and probably the most important step in predicting the tertiary structure of proteins from its primary structure is to predict as many as possible secondary structures in a protein chain. Secondary structure prediction problem has been known for almost a quarter of century. In this paper, new machine learning methods such as LAD, LEM2, and MODLEM have been used for secondary protein structure prediction with the aim to choose the best among them which will be later parallelized in order to handle a huge amount of data sets.

Słowa kluczowe

EN

machine learning; prediction of protein structures; LAD; LEM2; MODLEM

• Wydawca: Systems Research Institute, Polish Academy of Sciences
• Czasopismo: Control and Cybernetics
• Rocznik: 2007
• Tom: Vol. 36, no 1
• Strony: 183--201
• Opis fizyczny: Bibliogr. 39 poz.

Twórcy

autor

Błażewicz J.

autor

Łukasiak P.

autor

Wilk S.

• Institute of Computing Sciences, Poznań University of Technology, ul. Piotrowo 3a, 60-965 Poznań, Poland

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