Protein threading by learning

被引：31

作者：

Chang, I

Cieplak, M

Dima, RI

Maritan, A

Banavar, JR

机构：

[1] Penn State Univ, Dept Phys, University Pk, PA 16802 USA

[2] Pusan Natl Univ, Dept Phys, Pusan 609735, South Korea

[3] Polish Acad Sci, Inst Phys, PL-02668 Warsaw, Poland

[4] Univ Maryland, Dept Chem & Biochem, College Pk, MD 20742 USA

[5] Univ Maryland, Inst Phys Sci & Technol, College Pk, MD 20742 USA

[6] Ist Nazl Fis Mat, I-34014 Trieste, Italy

[7] Abdus Salam Int Ctr Theoret Phys, I-34014 Trieste, Italy

来源：

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | 2001年 / 98卷 / 25期

关键词：

D O I：

10.1073/pnas.241133698

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

By using techniques borrowed from statistical physics and neural networks, we determine the parameters, associated with a scoring function, that are chosen optimally to ensure complete success in threading tests in a training set of proteins. These parameters provide a quantitative measure of the propensities of amino acids to be buried or exposed and to be in a given secondary structure and are a good starting point for solving both the threading and design problems.

引用

页码：14350 / 14355

页数：6

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