Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways
Identifying essential genes in a given organism is important for research on their
fundamental roles in organism survival. Furthermore, if possible, uncovering the links …
fundamental roles in organism survival. Furthermore, if possible, uncovering the links …
M6APred-EL: a sequence-based predictor for identifying N6-methyladenosine sites using ensemble learning
L Wei, H Chen, R Su - Molecular Therapy-Nucleic Acids, 2018 - cell.com
N6-methyladenosine (m 6 A) modification is the most abundant RNA methylation
modification and involves various biological processes, such as RNA splicing and …
modification and involves various biological processes, such as RNA splicing and …
A novel hierarchical selective ensemble classifier with bioinformatics application
Selective ensemble learning is a technique that selects a subset of diverse and accurate
basic models in order to generate stronger generalization ability. In this paper, we proposed …
basic models in order to generate stronger generalization ability. In this paper, we proposed …
Fast prediction of protein methylation sites using a sequence-based feature selection technique
Protein methylation, an important post-translational modification, plays crucial roles in many
cellular processes. The accurate prediction of protein methylation sites is fundamentally …
cellular processes. The accurate prediction of protein methylation sites is fundamentally …
CPPred-RF: a sequence-based predictor for identifying cell-penetrating peptides and their uptake efficiency
Cell-penetrating peptides (CPPs), have been proven as important drug-delivery vehicles,
demonstrating the potential as therapeutic candidates. The past decade has witnessed a …
demonstrating the potential as therapeutic candidates. The past decade has witnessed a …
SkipCPP-Pred: an improved and promising sequence-based predictor for predicting cell-penetrating peptides
Abstract Background Cell-penetrating peptides (CPPs) are short peptides (5–30 amino
acids) that can enter almost any cell without significant damage. On account of their high …
acids) that can enter almost any cell without significant damage. On account of their high …
PhosPred-RF: a novel sequence-based predictor for phosphorylation sites using sequential information only
Many recent efforts have been made for the development of machine learning-based
methods for fast and accurate phosphorylation site prediction. Currently, a majority of well …
methods for fast and accurate phosphorylation site prediction. Currently, a majority of well …
Medical image classification based on multi-scale non-negative sparse coding
With the rapid development of modern medical imaging technology, medical image
classification has become more and more important in medical diagnosis and clinical …
classification has become more and more important in medical diagnosis and clinical …
A novel modeling in mathematical biology for classification of signal peptides
The molecular structure of macromolecules in living cells is ambiguous unless we classify
them in a scientific manner. Signal peptides are of vital importance in determining the …
them in a scientific manner. Signal peptides are of vital importance in determining the …
Identifying N6-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine
Abstract N6-methyladenosine (m6A) refers to methylation of the adenosine nucleotide acid
at the nitrogen-6 position. It plays an important role in a series of biological processes, such …
at the nitrogen-6 position. It plays an important role in a series of biological processes, such …