Identification of DNA-binding protein based multiple kernel model

DNA-binding proteins (DBPs) play a critical role in the development of drugs for treating genetic diseases and in DNA biology research. It is essential for predicting DNA-binding proteins more accurately and efficiently. In this paper, a Laplacian Local Kernel Alignment-based Restricted Kernel Machi...

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Main Authors: Yuqing Qian, Tingting Shang, Fei Guo, Chunliang Wang, Zhiming Cui, Yijie Ding, Hongjie Wu
Format: Article
Language:English
Published: AIMS Press 2023-06-01
Series:Mathematical Biosciences and Engineering
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2023586?viewType=HTML
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author Yuqing Qian
Tingting Shang
Fei Guo
Chunliang Wang
Zhiming Cui
Yijie Ding
Hongjie Wu
author_facet Yuqing Qian
Tingting Shang
Fei Guo
Chunliang Wang
Zhiming Cui
Yijie Ding
Hongjie Wu
author_sort Yuqing Qian
collection DOAJ
description DNA-binding proteins (DBPs) play a critical role in the development of drugs for treating genetic diseases and in DNA biology research. It is essential for predicting DNA-binding proteins more accurately and efficiently. In this paper, a Laplacian Local Kernel Alignment-based Restricted Kernel Machine (LapLKA-RKM) is proposed to predict DBPs. In detail, we first extract features from the protein sequence using six methods. Second, the Radial Basis Function (RBF) kernel function is utilized to construct pre-defined kernel metrics. Then, these metrics are combined linearly by weights calculated by LapLKA. Finally, the fused kernel is input to RKM for training and prediction. Independent tests and leave-one-out cross-validation were used to validate the performance of our method on a small dataset and two large datasets. Importantly, we built an online platform to represent our model, which is now freely accessible via http://8.130.69.121:8082/.
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spelling doaj.art-dbc1cea8e5e5400784f34091b2a81b2f2023-06-28T06:28:11ZengAIMS PressMathematical Biosciences and Engineering1551-00182023-06-01207131491317010.3934/mbe.2023586Identification of DNA-binding protein based multiple kernel modelYuqing Qian0Tingting Shang1Fei Guo 2Chunliang Wang3Zhiming Cui 4Yijie Ding5Hongjie Wu 61. College of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, China1. College of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, China2. School of Computer Science and Engineering, Central South University, Changsha, China3. The Second Affiliated Hospital of Soochow University, Suzhou, China1. College of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, China4. Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China1. College of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, ChinaDNA-binding proteins (DBPs) play a critical role in the development of drugs for treating genetic diseases and in DNA biology research. It is essential for predicting DNA-binding proteins more accurately and efficiently. In this paper, a Laplacian Local Kernel Alignment-based Restricted Kernel Machine (LapLKA-RKM) is proposed to predict DBPs. In detail, we first extract features from the protein sequence using six methods. Second, the Radial Basis Function (RBF) kernel function is utilized to construct pre-defined kernel metrics. Then, these metrics are combined linearly by weights calculated by LapLKA. Finally, the fused kernel is input to RKM for training and prediction. Independent tests and leave-one-out cross-validation were used to validate the performance of our method on a small dataset and two large datasets. Importantly, we built an online platform to represent our model, which is now freely accessible via http://8.130.69.121:8082/.https://www.aimspress.com/article/doi/10.3934/mbe.2023586?viewType=HTMLdna-binding proteinsmultiple kernel learninglocal kernel alignmentrestricted kernel machine
spellingShingle Yuqing Qian
Tingting Shang
Fei Guo
Chunliang Wang
Zhiming Cui
Yijie Ding
Hongjie Wu
Identification of DNA-binding protein based multiple kernel model
Mathematical Biosciences and Engineering
dna-binding proteins
multiple kernel learning
local kernel alignment
restricted kernel machine
title Identification of DNA-binding protein based multiple kernel model
title_full Identification of DNA-binding protein based multiple kernel model
title_fullStr Identification of DNA-binding protein based multiple kernel model
title_full_unstemmed Identification of DNA-binding protein based multiple kernel model
title_short Identification of DNA-binding protein based multiple kernel model
title_sort identification of dna binding protein based multiple kernel model
topic dna-binding proteins
multiple kernel learning
local kernel alignment
restricted kernel machine
url https://www.aimspress.com/article/doi/10.3934/mbe.2023586?viewType=HTML
work_keys_str_mv AT yuqingqian identificationofdnabindingproteinbasedmultiplekernelmodel
AT tingtingshang identificationofdnabindingproteinbasedmultiplekernelmodel
AT feiguo identificationofdnabindingproteinbasedmultiplekernelmodel
AT chunliangwang identificationofdnabindingproteinbasedmultiplekernelmodel
AT zhimingcui identificationofdnabindingproteinbasedmultiplekernelmodel
AT yijieding identificationofdnabindingproteinbasedmultiplekernelmodel
AT hongjiewu identificationofdnabindingproteinbasedmultiplekernelmodel