HYBRID MODELS OF UNCERTAINTY IN PROTEIN TOPOLOGY PREDICTION
作者:
SIMON PARSONS,
期刊:
Applied Artificial Intelligence
(Taylor Available online 1995)
卷期:
Volume 9,
issue 3
页码: 335-351
ISSN:0883-9514
年代: 1995
DOI:10.1080/08839519508945478
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
Predicting protein structure is an important problem in molecular biology, and one that has attracted much attention. It is also a difficult problem, since the available data are incomplete and pervaded with uncertainty. This paper describes models for the prediction of an intermediate level of protein structure known as the topology of the protein. The models handle uncertainty explicitly, making use of probability, possibility, and evidence theories singly and in combination to handle different aspects of the problem.
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