Prediction of Protein Backbone Torsion Angles Using Deep Residual Inception Neural Networks
نویسندگان
چکیده
منابع مشابه
Real-value prediction of backbone torsion angles.
The backbone structure of a protein is largely determined by the phi and psi torsion angles. Thus, knowing these angles, even if approximately, will be very useful for protein-structure prediction. However, in a previous work, a sequence-based, real-value prediction of psi angle could only achieve a mean absolute error of 54 degrees (83 degrees, 35 degrees, 33 degrees for coil, strand, and heli...
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A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥90 % fraction of the residues, with an error rate s...
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This article introduces a novel protein structure alignment method (named TALI) based on protein backbone torsion angle instead of the more traditional distance matrix. Representing protein structure by a serial backbone torsion angles (φ, ψ), protein structure have a simple mapping relationship to protein sequence. Thus, TALI can naturally incorporate sequence information and sequence analysis...
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در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...
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ژورنال
عنوان ژورنال: IEEE/ACM Transactions on Computational Biology and Bioinformatics
سال: 2019
ISSN: 1545-5963,1557-9964,2374-0043
DOI: 10.1109/tcbb.2018.2814586