scholarly journals DNA-binding protein prediction using plant specific support vector machines: validation and application of a new genome annotation tool

2015 ◽  
Vol 43 (22) ◽  
pp. e158-e158 ◽  
Author(s):  
Graham B. Motion ◽  
Andrew J. M. Howden ◽  
Edgar Huitema ◽  
Susan Jones
2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Rianon Zaman ◽  
Shahana Yasmin Chowdhury ◽  
Mahmood A. Rashid ◽  
Alok Sharma ◽  
Abdollah Dehzangi ◽  
...  

DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.


2018 ◽  
Vol 452 ◽  
pp. 22-34 ◽  
Author(s):  
M. Saifur Rahman ◽  
Swakkhar Shatabda ◽  
Sanjay Saha ◽  
M. Kaykobad ◽  
M. Sohel Rahman

2021 ◽  
Vol 612 ◽  
pp. 113954
Author(s):  
Ronesh Sharma ◽  
Shiu Kumar ◽  
Tatsuhiko Tsunoda ◽  
Thirumananseri Kumarevel ◽  
Alok Sharma

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