𝔖 Bobbio Scriptorium
✦   LIBER   ✦

γ-Turn types prediction in proteins using the support vector machines

✍ Scribed by Samad Jahandideh; Amir Sabet Sarvestani; Parviz Abdolmaleki; Mina Jahandideh; Mahdyar Barfeie

Book ID
108196319
Publisher
Elsevier Science
Year
2007
Tongue
English
Weight
151 KB
Volume
249
Category
Article
ISSN
0022-5193

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Using support vector machine to predict
Using support vector machine to predict β- and γ-turns in proteins
✍ Xiuzhen Hu; Qianzhong Li 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 159 KB

## Abstract By using the composite vector with increment of diversity, position conservation scoring function, and predictive secondary structures to express the information of sequence, a support vector machine (SVM) algorithm for predicting β‐ and γ‐turns in the proteins is proposed. The 426 and

Support vector machines for the classifi
Support vector machines for the classification and prediction of β-turn types
✍ Dr Yu-Dong Cai; Xiao-Jun Liu; Xue-biao Xu; Kuo-Chen Chou 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 73 KB

## Abstract The support vector machines (SVMs) method is proposed because it can reflect the sequence‐coupling effect for a tetrapeptide in not only a β‐turn or non‐β‐turn, but also in different types of β‐turn. The results of the model for 6022 tetrapeptides indicate that the rates of self‐consist