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Article
Open AccessDiCleave: a deep learning model for predicting human Dicer cleavage sites
MicroRNAs (miRNAs) are a class of non-coding RNAs that play a pivotal role as gene expression regulators. These miRNAs are typically approximately 20 to 25 nucleotides long. The maturation of miRNAs requires D...
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Article
Open AccessGenetic algorithm-based feature selection with manifold learning for cancer classification using microarray data
Microarray data have been widely utilized for cancer classification. The main characteristic of microarray data is “large p and small n” in that data contain a small number of subjects but a large number of ge...
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Article
Open AccessPreAcrs: a machine learning framework for identifying anti-CRISPR proteins
Anti-CRISPR proteins are potent modulators that inhibit the CRISPR-Cas immunity system and have huge potential in gene editing and gene therapy as a genome-editing tool. Extensive studies have shown that anti-...
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Article
Open AccessReCGBM: a gradient boosting-based method for predicting human dicer cleavage sites
Human dicer is an enzyme that cleaves pre-miRNAs into miRNAs. Several models have been developed to predict human dicer cleavage sites, including PHDCleav and LBSizeCleav. Given an input sequence, these models...
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Article
Open AccessSIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models
S-sulphenylation is a ubiquitous protein post-translational modification (PTM) where an S-hydroxyl (−SOH) bond is formed via the reversible oxidation on the Sulfhydryl group of cysteine (C). Recent experimenta...
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Article
Open AccessPositive-unlabelled learning of glycosylation sites in the human proteome
As an important type of post-translational modification (PTM), protein glycosylation plays a crucial role in protein stability and protein function. The abundance and ubiquity of protein glycosylation across t...
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Article
Open AccessStaged heterogeneity learning to identify conformational B-cell epitopes from antigen sequences
The broad heterogeneity of antigen-antibody interactions brings tremendous challenges to the design of a widely applicable learning algorithm to identify conformational B-cell epitopes. Besides the intrinsic h...
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Article
Open AccessExploring drug combinations in genetic interaction network
Drug combination that consists of distinctive agents is an attractive strategy to combat complex diseases and has been widely used clinically with improved therapeutic effects. However, the identification of e...
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Article
Open AccessAPIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility
It is well known that most of the binding free energy of protein interaction is contributed by a few key hot spot residues. These residues are crucial for understanding the function of proteins and studying th...
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Article
Open AccessPredicting residue-wise contact orders in proteins by support vector regression
The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structur...
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Article
Open AccessPrediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information
The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomeri...