A Hybrid Classifier for Protein Secondary Structure Prediction
نویسندگان
چکیده
منابع مشابه
Hybrid system for protein secondary structure prediction.
We have developed a hybrid system to predict the secondary structures (alpha-helix, beta-sheet and coil) of proteins and achieved 66.4% accuracy, with correlation coefficients of C(coil) = 0.429, C alpha = 0.470 and C beta = 0.387. This system contains three subsystems ("experts"): a neural network module, a statistical module and a memory-based reasoning module. First, the three experts indepe...
متن کاملUsing classifier fusion techniques for protein secondary structure prediction
Classifier fusion techniques are gaining more popularity for their capability of improving the accuracy achieved by individual classifiers. A common approach is to combine the classifiers’ outcome using simple methods, such as majority voting. In this paper, we build a meta-classifier by fusing some already well-known classifiers for protein structure prediction. Each individual classifier outp...
متن کاملA Hybrid Method for Protein Secondary Structure Prediction
Protein secondary structure can be used to help determine the tertiary structure via the fold recognition. Predicting the secondary structure from the protein sequence has attracted the attention of many researchers. Support Vector Machine (SVM) is a new learning algorithm based on statistical learning theory that has been successfully applied to the protein secondary structure prediction probl...
متن کاملProtein secondary structure prediction.
The past year has seen a consolidation of protein secondary structure prediction methods. The advantages of prediction from an aligned family of proteins have been highlighted by several accurate predictions made 'blind', before any X-ray or NMR structure was known for the family. New techniques that apply machine learning and discriminant analysis show promise as alternatives to neural networks.
متن کاملA knowledge-based hybrid method for protein secondary structure prediction based on local prediction confidence
Motivation: In our previous approach, we proposed a hybrid method for protein secondary structure prediction, called HYPROSP, which combined our proposed knowledge-based prediction algorithm PROSP and PSIPRED. The knowledge base constructed for PROSP contains small peptides together with their secondary structural information. The hybrid strategy of HYPROSP uses a global quantitative measure, m...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information Technology Journal
سال: 2005
ISSN: 1812-5638
DOI: 10.3923/itj.2005.433.438