DNNAce: prediction of prokaryote lysine acetylation sites through deep neural networks with multi-information fusion
As a reversible and widely existing post-translational modification of proteins, acetylation
plays a crucial role in transcriptional regulation, apoptosis, and cytokine signaling. To better …
plays a crucial role in transcriptional regulation, apoptosis, and cytokine signaling. To better …
DRBPPred-GAT: Accurate prediction of DNA-binding proteins and RNA-binding proteins based on graph multi-head attention network
X Zhang, Y Wang, Q Wei, S He, A Salhi, B Yu - Knowledge-Based Systems, 2024 - Elsevier
DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) play a crucial role in
regulating various cellular functions that are closely associated with human disease …
regulating various cellular functions that are closely associated with human disease …
Unlocking the microbial studies through computational approaches: how far have we reached?
The metagenomics approach accelerated the study of genetic information from uncultured
microbes and complex microbial communities. In silico research also facilitated an …
microbes and complex microbial communities. In silico research also facilitated an …
Prediction of anticancer peptides using a low-dimensional feature model
Q Li, W Zhou, D Wang, S Wang, Q Li - Frontiers in Bioengineering …, 2020 - frontiersin.org
Cancer is still a severe health problem globally. The therapy of cancer traditionally involves
the use of radiotherapy or anticancer drugs to kill cancer cells, but these methods are quite …
the use of radiotherapy or anticancer drugs to kill cancer cells, but these methods are quite …
Machine learning and its applications in plant molecular studies
The advent of high-throughput genomic technologies has resulted in the accumulation of
massive amounts of genomic information. However, biologists are challenged with how to …
massive amounts of genomic information. However, biologists are challenged with how to …
Recent advances in the machine learning-based drug-target interaction prediction
W Zhang, W Lin, D Zhang, S Wang… - Current drug …, 2019 - ingentaconnect.com
Background: The identification of drug-target interactions is a crucial issue in drug discovery.
In recent years, researchers have made great efforts on the drug-target interaction …
In recent years, researchers have made great efforts on the drug-target interaction …
Drug-target interaction prediction with graph attention networks
Motivation: Predicting Drug-Target Interaction (DTI) is a well-studied topic in bioinformatics
due to its relevance in the fields of proteomics and pharmaceutical research. Although many …
due to its relevance in the fields of proteomics and pharmaceutical research. Although many …
LPI-KTASLP: prediction of lncRNA-protein interaction by semi-supervised link learning with multivariate information
Long non-coding RNA, also known as lncRNA, is a series of single-stranded
polynucleotides (no less than 200 nucleotides each), consisting of non-protein coding …
polynucleotides (no less than 200 nucleotides each), consisting of non-protein coding …
6mA-RicePred: A Method for Identifying DNA N 6-Methyladenine Sites in the Rice Genome Based on Feature Fusion
Motivation The biological function of N 6-methyladenine DNA (6mA) in plants is largely
unknown. Rice is one of the most important crops worldwide and is a model species for …
unknown. Rice is one of the most important crops worldwide and is a model species for …
iGlu_AdaBoost: identification of lysine glutarylation using the AdaBoost classifier
L Dou, X Li, L Zhang, H Xiang, L Xu - Journal of Proteome …, 2020 - ACS Publications
Lysine glutarylation is a newly reported post-translational modification (PTM) that plays
significant roles in regulating metabolic and mitochondrial processes. Accurate identification …
significant roles in regulating metabolic and mitochondrial processes. Accurate identification …