In this paper, we propose a new algorithm called multiple physicochemical properties and support vector machines (MppS) which uses support vector machines (SVM) in conjunction with multiple physicochemical properties of amino acids. The algorithm was tested in two problems: HIV-protease and recognition of T-cell epitopes. A series of SVM classifiers combined with the “max rule” enables us to obtain an improvement over other algorithms based on various types of amino acid composition
Abstract. The cysteine knot motifs are widely spread in several classes of peptides including those ...
Abstract — This paper introduces novel methods for feature selection (FS) based on support vector ma...
Abstract Background The challenge of remote homology detection is that many evolutionarily related s...
In this paper, we propose a new algorithm called multiple physicochemical properties and support vec...
In this paper, we study the performance improvement that it is possible to obtain combining classifi...
In this paper, we propose a new encoding technique that combines the different physicochemical prope...
Membrane proteins play important roles in many biochemical processes and are also attractive targets...
Research on cytokine recognition is of great significance in the medical field due to the fact cytok...
Given a particular membrane protein, it is very important to know which membrane type it belongs to ...
Proteins can be classified into four structural classes (all-a, all-beta, alpha/beta, alpha+beta) ac...
AbstractIntrinsically disordered proteins are an important class of proteins with unique functions a...
SVM is one of the most widely used and powerful classification algorithms to predict protein structu...
In this study, n-peptide compositions are utilized for protein vectorization over a discriminative r...
Abstract-Machine learning technique is introduced as a method for the classification of proteins int...
One key element in understanding the molecular machinery of the cell is to understand the meaning, o...
Abstract. The cysteine knot motifs are widely spread in several classes of peptides including those ...
Abstract — This paper introduces novel methods for feature selection (FS) based on support vector ma...
Abstract Background The challenge of remote homology detection is that many evolutionarily related s...
In this paper, we propose a new algorithm called multiple physicochemical properties and support vec...
In this paper, we study the performance improvement that it is possible to obtain combining classifi...
In this paper, we propose a new encoding technique that combines the different physicochemical prope...
Membrane proteins play important roles in many biochemical processes and are also attractive targets...
Research on cytokine recognition is of great significance in the medical field due to the fact cytok...
Given a particular membrane protein, it is very important to know which membrane type it belongs to ...
Proteins can be classified into four structural classes (all-a, all-beta, alpha/beta, alpha+beta) ac...
AbstractIntrinsically disordered proteins are an important class of proteins with unique functions a...
SVM is one of the most widely used and powerful classification algorithms to predict protein structu...
In this study, n-peptide compositions are utilized for protein vectorization over a discriminative r...
Abstract-Machine learning technique is introduced as a method for the classification of proteins int...
One key element in understanding the molecular machinery of the cell is to understand the meaning, o...
Abstract. The cysteine knot motifs are widely spread in several classes of peptides including those ...
Abstract — This paper introduces novel methods for feature selection (FS) based on support vector ma...
Abstract Background The challenge of remote homology detection is that many evolutionarily related s...