Prediction of protein secondary structure using the 30D- 1D compatibility algorithm
نویسندگان
چکیده
منابع مشابه
Prediction of protein secondary structure using the 3D-1D compatibility algorithm
A new method for the prediction of protein secondary structure is proposed, which relies totally on the global aspect of a protein. The prediction scheme is as follows. A structural library is first scanned with a query sequence by the 3D-1D compatibility method developed before. All the structures examined are sorted with the compatibility score and the top 50 in the list are picked out. Then,...
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 کاملPrediction of Protein Secondary Structure
In the wake of large-scale DNA sequencing projects, accurate tools are needed to predict protein structures. The problem of predicting protein structure from DNA sequence remains fundamentally unsolved even after more than three decades of intensive research. In this paper, fundamental theory of the protein structure will be presented as a general guide to protein secondary structure prediction...
متن کاملPrediction of Protein Secondary Structure Using Genetic Programming
Certificate This is to certify that, Varun Aggarwal, (104/ECE/2000) a student of NSIT, Delhi, India did his summer training under me at Stockholm Bioinformatics Center for the months of June-July 2003. He worked on two projects documented in this report. Acknowledgement I will like to thanks Dr. Bob MacCallum for giving me this opportunity to work with his group. I hugely benefited and wish to ...
متن کاملPrediction of Protein Secondary Structure Using Nonlinear Method
This paper presents the use of neural networks for the prediction of protein Secondary Structure. We propose a pre-processing stage based on the method of Cascaded Nonlinear Components Analysis (CNLPCA), in order to get a dimensional reduction of the data which may consider its nonlinearity. Then, the reduced data are placed in predictor networks and its results are combined. For the verificati...
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: Bioinformatics
سال: 1997
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/13.4.415