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- W1569496802 abstract "Proteins are the fundamental molecules of life, they form both the structural and the functional building blocks of cells in all living organisms. Proteins are also the most complex molecules. Their three-dimensional structures are extremely diverse, and so are their biological functions. Elucidation of the relationship between protein sequence, structure, and function is one of the most significant open problems in science and technology. Despite the growing body of observed data and partial theories, there are still no satisfactory methods which would enable us to analyze, characterize, and predict a protein's structure and/or function with regard to its known primary sequence. There are two fundamentally different approaches to the problem, and a continuum of their combinations. The first approach is based on theory and models from physics and chemistry, the other is based on computational and statistical analysis of observed data. This paper belongs to the second direction. From the data analysis perspective, we can observe, first, that there has not been much achieved in terms of producing reasonable feature spaces except for those directly related to amino acid sequence similarity data, and, second, the specifics of emerging problems yet have not been addressed in full. One of the specific issues is related to difference between prediction and description. Typically, prediction is based on a description of the phenomenon in question in the framework of a prediction model. However," @default.
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- W1569496802 date "2006-01-06" @default.
- W1569496802 modified "2023-09-23" @default.
- W1569496802 title "A Feature-Based Approach to Discrimination and Prediction of Protein Folding" @default.
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- W1569496802 doi "https://doi.org/10.1007/0-306-46823-9_14" @default.
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