Multiple linear regression for protein secondary structure prediction.
نویسنده
چکیده
In the present work, a novel method was proposed for prediction of secondary structure. Over a database of 396 proteins (CB396) with a three-state-defining secondary structure, this method with jackknife procedure achieved an accuracy of 68.8% and SOV score of 71.4% using single sequence and an accuracy of 73.7% and SOV score of 77.3% using multiple sequence alignments. Combination of this method with DSC, PHD, PREDATOR, and NNSSP gives Q3 = 76.2% and SOV = 79.8%.
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ورودعنوان ژورنال:
- Proteins
دوره 43 3 شماره
صفحات -
تاریخ انتشار 2001