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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Razmara, Jafar Deris, Safaai B. Parvizpour, Sepideh |
| Description | Author Affiliation: Razmara J ( Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia. Electronic address: razmaraj@gmail.com.) |
| Abstract | The structural comparison of proteins is a vital step in structural biology that is used to predict and analyse a new unknown protein function. Although a number of different techniques have been explored, the study to develop new alternative methods is still an active research area. The present paper introduces a text modelling-based technique for the structural comparison of proteins. The method models the secondary and tertiary structure of proteins in two linear sequences and then applies them to the comparison of two structures. The technique used for pairwise comparison of the sequences has been adopted from computational linguistics and its well-known techniques for analysing and quantifying textual sequences. To this end, an n-gram modelling technique is used to capture regularities between sequences, and then, the cross-entropy concept is employed to measure their similarities. Several experiments are conducted to evaluate the performance of the method and compare it with other commonly used programs. The assessments for information retrieval evaluation demonstrate that the technique has a high running speed, which is similar to other linear encoding methods, such as 3D-BLAST, SARST, and TS-AMIR, whereas its accuracy is comparable to CE and TM-align, which are high accuracy comparison tools. Accordingly, the results demonstrate that the algorithm has high efficiency compared with other state-of-the-art methods. |
| File Format | HTM / HTML |
| ISSN | 00104825 |
| Issue Number | 10 |
| Volume Number | 43 |
| e-ISSN | 18790534 |
| Journal | Computers in Biology and Medicine |
| Language | English |
| Publisher | Elsevier |
| Publisher Date | 2013-10-01 |
| Publisher Place | United States |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Discipline Biology Discipline Biomedical Informatics Computational Biology Methods Proteins Chemistry Sequence Alignment Sequence Analysis, Protein Algorithms Amino Acid Sequence Databases, Protein Molecular Sequence Data Protein Conformation Journal Article Research Support, Non-u.s. Gov't |
| Content Type | Text |
| Resource Type | Article |
| Subject | Health Informatics Computer Science Applications |
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