Overview of methods for characterization and visualization of a protein–protein interaction network in a multi-omics integration context
V Robin, A Bodein, MP Scott-Boyer… - Frontiers in Molecular …, 2022 - frontiersin.org
At the heart of the cellular machinery through the regulation of cellular functions, protein–
protein interactions (PPIs) have a significant role. PPIs can be analyzed with network …
protein interactions (PPIs) have a significant role. PPIs can be analyzed with network …
A survey of current trends in computational predictions of protein-protein interactions
Proteomics become an important research area of interests in life science after the
completion of the human genome project. This scientific is to study the characteristics of …
completion of the human genome project. This scientific is to study the characteristics of …
Unifying structural descriptors for biological and bioinspired nanoscale complexes
Biomimetic nanoparticles are known to serve as nanoscale adjuvants, enzyme mimics and
amyloid fibrillation inhibitors. Their further development requires better understanding of …
amyloid fibrillation inhibitors. Their further development requires better understanding of …
DeepTrio: a ternary prediction system for protein–protein interaction using mask multiple parallel convolutional neural networks
Motivation Protein–protein interaction (PPI), as a relative property, is determined by two
binding proteins, which brings a great challenge to design an expert model with an …
binding proteins, which brings a great challenge to design an expert model with an …
ACP-MHCNN: an accurate multi-headed deep-convolutional neural network to predict anticancer peptides
Although advancing the therapeutic alternatives for treating deadly cancers has gained
much attention globally, still the primary methods such as chemotherapy have significant …
much attention globally, still the primary methods such as chemotherapy have significant …
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 …
A high efficient biological language model for predicting protein–protein interactions
Many life activities and key functions in organisms are maintained by different types of
protein–protein interactions (PPIs). In order to accelerate the discovery of PPIs for different …
protein–protein interactions (PPIs). In order to accelerate the discovery of PPIs for different …
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 …
Predicting drug− disease associations via sigmoid kernel-based convolutional neural networks
Background In the process of drug development, computational drug repositioning is
effective and resource-saving with regards to its important functions on identifying new drug …
effective and resource-saving with regards to its important functions on identifying new drug …
AutoPPI: An Ensemble of Deep Autoencoders for Protein–Protein Interaction Prediction
Proteins are essential molecules, that must correctly perform their roles for the good health
of living organisms. The majority of proteins operate in complexes and the way they interact …
of living organisms. The majority of proteins operate in complexes and the way they interact …