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EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features
J Bioinform Comput Biol. 2024 Feb 26:2450001. doi: 10.1142/S021972002450001X. Online ahead of print.ABSTRACTAntimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have been proposed to predict AMPs and achieved good results. In this work, we combine two kinds of word embedding features with the statistical features of peptide sequences to develop an ensemble classifier, named EnAMP, in which, two deep neural networks are trained based ...
Source: Journal of Bioinformatics and Computational Biology - February 26, 2024 Category: Bioinformatics Authors: Jujuan Zhuang Wanquan Gao Rui Su Source Type: research