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Article
Using k-mer embeddings learned from a Skip-gram based neural network for building a cross-species DNA N6-methyladenine site prediction model
This study used k-mer embeddings as effective feature to identify DNA N6-Methyladenine sites in plant genomes and obtained improved performance without substantial effort in feature extraction, combination and...
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Article
Open AccessTNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings
Cytokines are a class of small proteins that act as chemical messengers and play a significant role in essential cellular processes including immunity regulation, hematopoiesis, and inflammation. As one import...
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Article
Open AccessIncorporating efficient radial basis function networks and significant amino acid pairs for predicting GTP binding sites in transport proteins
Guanonine-protein (G-protein) is known as molecular switches inside cells, and is very important in signals transmission from outside to inside cell. Especially in transport protein, most of G-proteins play an...
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Article
Open AccessPrediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs
Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respi...
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Chapter
Structural and Functional Discrimination of Membrane Proteins
Membrane proteins perform diverse functions inside the cell including transporters, receptors, and channels. Ion channels are integral membrane proteins that regulate the flow of ions across the membranes and ...
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Article
Open AccessIncorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins
While occurring enzymatically in biological systems, O-linked glycosylation affects protein folding, localization and trafficking, protein solubility, antigenicity, biological activity, as well as cell-cell in...
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Chapter and Conference Paper
Topology Prediction of α-Helical and β-Barrel Transmembrane Proteins Using RBF Networks
Transmembrane proteins are difficult to crystallize owing to the presence of lipid environment and the number of membrane protein structures deposited in Protein Data Bank is limited. Hence, computational tech...
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Chapter and Conference Paper
Using Efficient RBF Networks to Classify Transport Proteins Based on PSSM Profiles and Biochemical Properties
Transport proteins are difficult to understand by biological experiments due to the difficulty in obtaining crystals suitable for X-ray diffraction. Therefore, the use of computational techniques is a powerful...
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Article
Open AccessPrediction of protein secondary structures with a novel kernel density estimation based classifier
Though prediction of protein secondary structures has been an active research issue in bioinformatics for quite a few years and many approaches have been proposed, a new challenge emerges as the sizes of conte...
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Chapter and Conference Paper
Using Efficient RBF Network to Identify Interface Residues Based on PSSM Profiles and Biochemical Properties
Protein-protein interactions play a very important role in many biological processes, for example, information transfer along signaling pathways, and enzyme catalysis. Recently, scientists tried to predict the...
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Chapter and Conference Paper
Enhancing Protein Disorder Detection by Refined Secondary Structure Prediction
More and more proteins have been observed to display functions through intrinsic disorder. Such structurally flexible regions are shown to play important roles in biological processes and are estimated to be a...
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Article
Open AccessProtein disorder prediction by condensed PSSM considering propensity for order or disorder
More and more disordered regions have been discovered in protein sequences, and many of them are found to be functionally significant. Previous studies reveal that disordered regions of a protein can be predic...
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Chapter and Conference Paper
Expediting Model Selection for Support Vector Machines Based on an Advanced Data Reduction Algorithm
In recent years, the support vector machine (SVM) has been extensively applied to deal with various data classification problems. However, it has also been observed that, for some datasets, the classification ...
