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The Automated Protein Structure Analysis (APSA) method, which describes the protein backbone as a smooth line in 3-dimensional space and characterizes it by curvature kappa and torsion tau as a function of arc length s, was applied on 77…

Quantitative Methods · Quantitative Biology 2008-11-24 S. Ranganathan , D. Izotov , E. Kraka , D. Cremer

The protein backbone is described as a smooth curved and twisted line in three-dimensional (3D) space and characterized by its curvature $\kappa(s)$ and torsion $\tau(s)$ both expressed as a function of arc length s. It is shown that the…

Biomolecules · Quantitative Biology 2008-11-24 Sushilee Ranganathan , Dmitry Izotov , Elfi Kraka , Dieter Cremer

A new method for the Automated Protein Structure Analysis (APSA) is derived, which simplifies the protein backbone to a smooth curve in 3-dimensional space. For the purpose of obtaining this smooth line each amino acid is represented by its…

Quantitative Methods · Quantitative Biology 2008-11-24 Sushilee Raganathan , Dmitry Izotov , Elfi Kraka , Dieter Cremer

By using a mixture model for the density distribution of the three pseudobond angles formed by $C_\alpha$ atoms of four consecutive residues, the local structural states are discretized as 17 conformational letters of a protein structural…

Biomolecules · Quantitative Biology 2007-05-23 Wei-Mou Zheng , Xin Liu

Classification of proteins based on their structure provides a valuable resource for studying protein structure, function and evolutionary relationships. With the rapidly increasing number of known protein structures, manual and…

Computational Engineering, Finance, and Science · Computer Science 2009-07-14 Oktie Hassanzadeh

Protein one-dimensional (1D) structures such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence. However, it…

Biomolecules · Quantitative Biology 2007-05-23 Akira R. Kinjo , Ken Nishikawa

Recently developed deep learning techniques have significantly improved the accuracy of various speech and image recognition systems. In this paper we adapt some of these techniques for protein secondary structure prediction. We first train…

Machine Learning · Computer Science 2016-11-07 Akosua Busia , Jasmine Collins , Navdeep Jaitly

The tertiary structure of protein, as well as the local secondary structure organization are fully determined by the angles of the peptidic bound. The backbone dihedral angles not only determine the global fold of the protein, but also the…

Biomolecules · Quantitative Biology 2011-11-24 Matthieu Tanty , Marc-André Delsuc

The correct prediction of protein secondary structures is one of the key issues in predicting the correct protein folded shape, which is used for determining gene function. Existing methods make use of amino acids properties as indices to…

Quantitative Methods · Quantitative Biology 2017-05-01 Jian-Jun Shu , Kian-Yan Yong

Predicting protein structure from amino acid sequence is one of the most important unsolved problems of molecular biology and biophysics.Not only would a successful prediction algorithm be a tremendous advance in the understanding of the…

Computational Engineering, Finance, and Science · Computer Science 2010-06-15 K. K Senapati , G. Sahoo , D. Bhaumik

The paper presents a geometrical model for protein secondary structure analysis which uses only the positions of the $C_{\alpha}$-atoms. We construct a space curve connecting these positions by piecewise polynomial interpolation and…

Biomolecules · Quantitative Biology 2014-12-30 Gerald R. Kneller , Konrad Hinsen

Proteins are essential for life, and their structure determines their function. The protein secondary structure is formed by the folding of the protein primary structure, and the protein tertiary structure is formed by the bending and…

Biomolecules · Quantitative Biology 2024-03-11 Yanlin Zhou , Kai Tan , Xinyu Shen , Zheng He , Haotian Zheng

Predicting protein secondary structures such as alpha helices, beta sheets, and coils from amino acid sequences is essential for understanding protein function. This work presents a transformer-based model that applies attention mechanisms…

Artificial Intelligence · Computer Science 2025-12-10 Manzi Kevin Maxime

In this study, we tackle the challenging task of predicting secondary structures from protein primary sequences, a pivotal initial stride towards predicting tertiary structures, while yielding crucial insights into protein activity,…

Machine Learning · Computer Science 2025-11-18 Disha Varshney , Samarth Garg , Sarthak Tyagi , Deeksha Varshney , Nayan Deep , Asif Ekbal

Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive,…

Computer Vision and Pattern Recognition · Computer Science 2020-09-01 Alexander Hudson , Shaogang Gong

Background:Prediction of protein three-dimensional structures from amino acid sequences is a long-standing goal in computational/molecular biology. The successful discrimination of protein folds would help to improve the accuracy of protein…

Biomolecules · Quantitative Biology 2007-05-23 Y-h. Taguchi , M. Michael Gromiha

The biological function of a protein stems from its 3-dimensional structure, which is thermodynamically determined by the energetics of interatomic forces between its amino acid building blocks (the order of amino acids, known as the…

Biomolecules · Quantitative Biology 2019-05-03 Sean Mullane , Ruoyan Chen , Sri Vaishnavi Vemulapalli , Eli J. Draizen , Ke Wang , Cameron Mura , Philip E. Bourne

The Gene or DNA sequence in every cell does not control genetic properties on its own; Rather, this is done through translation of DNA into protein and subsequent formation of a certain 3D structure. The biological function of a protein is…

Computational Engineering, Finance, and Science · Computer Science 2019-05-30 Leila Khalatbari , Mohammad Reza Kangavari , Saeid Hosseini , Hongzhi Yin , Ngai-Man Cheung

In protein structure analysis, the accurate characterization of secondary structure elements is crucial for understanding protein function and dynamics. This paper presents a software system designed for the comprehensive analysis of the…

Biomolecules · Quantitative Biology 2024-04-05 Vedh Kannan

In this work we set out to find a method to classify protein structures using a Deep Learning methodology. Our Artificial Intelligence has been trained to recognize complex biomolecule structures extrapolated from the Protein Data Bank…

Machine Learning · Computer Science 2021-11-04 Damiano Perri , Marco Simonetti , Andrea Lombardi , Noelia Faginas-Lago , Osvaldo Gervasi
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