GKLOMLI: a link prediction model for inferring miRNA–lncRNA interactions by using Gaussian kernel-based method on network profile and linear optimization …
Background The limited knowledge of miRNA–lncRNA interactions is considered as an
obstruction of revealing the regulatory mechanism. Accumulating evidence on Human …
obstruction of revealing the regulatory mechanism. Accumulating evidence on Human …
ACP-DL: a deep learning long short-term memory model to predict anticancer peptides using high-efficiency feature representation
Cancer is a well-known killer of human beings, which has led to countless deaths and
misery. Anticancer peptides open a promising perspective for cancer treatment, and they …
misery. Anticancer peptides open a promising perspective for cancer treatment, and they …
MLMDA: a machine learning approach to predict and validate MicroRNA–disease associations by integrating of heterogenous information sources
Background Emerging evidences show that microRNA (miRNA) plays an important role in
many human complex diseases. However, considering the inherent time-consuming and …
many human complex diseases. However, considering the inherent time-consuming and …
An effective drug-disease associations prediction model based on graphic representation learning over multi-biomolecular network
H Jiang, Y Huang - BMC bioinformatics, 2022 - Springer
Abstract Background Drug-disease associations (DDAs) can provide important information
for exploring the potential efficacy of drugs. However, up to now, there are still few DDAs …
for exploring the potential efficacy of drugs. However, up to now, there are still few DDAs …
In silico prediction methods of self-interacting proteins: an empirical and academic survey
In silico prediction of self-interacting proteins (SIPs) has become an important part of
proteomics. There is an urgent need to develop effective and reliable prediction methods to …
proteomics. There is an urgent need to develop effective and reliable prediction methods to …
MIPDH: a novel computational model for predicting microRNA–mRNA interactions by DeepWalk on a heterogeneous network
Analysis of miRNA-target mRNA interaction (MTI) is of crucial significance in discovering
new target candidates for miRNAs. However, the biological experiments for identifying MTIs …
new target candidates for miRNAs. However, the biological experiments for identifying MTIs …
MMV method: a new approach to compare protein sequences under binary representation
In the present work, a new form of descriptor using minimal moment vector (MMV) is
introduced to compare protein sequences in the frequency domain under their component …
introduced to compare protein sequences in the frequency domain under their component …
Anti-cancer peptide recognition based on grouped sequence and spatial dimension integrated networks
H You, L Yu, S Tian, X Ma, Y Xing, J Song… - Interdisciplinary Sciences …, 2021 - Springer
The diversification of the characteristic sequences of anti-cancer peptides has imposed
difficulties on research. To effectively predict new anti-cancer peptides, this paper proposes …
difficulties on research. To effectively predict new anti-cancer peptides, this paper proposes …
Identification of self-interacting proteins by integrating random projection classifier and finite impulse response filter
Background Identification of protein-protein interactions (PPIs) is crucial for understanding
biological processes and investigating the cellular functions of genes. Self-interacting …
biological processes and investigating the cellular functions of genes. Self-interacting …
FFP: joint Fast Fourier transform and fractal dimension in amino acid property-aware phylogenetic analysis
W Li, L Yang, Y Qiu, Y Yuan, X Li, Z Meng - BMC bioinformatics, 2022 - Springer
Background Amino acid property-aware phylogenetic analysis (APPA) refers to the
phylogenetic analysis method based on amino acid property encoding, which is used for …
phylogenetic analysis method based on amino acid property encoding, which is used for …