Recent advances in predicting protein–protein interactions with the aid of artificial intelligence algorithms
Protein–protein interactions (PPIs) are essential in the regulation of biological functions and
cell events, therefore understanding PPIs have become a key issue to understanding the …
cell events, therefore understanding PPIs have become a key issue to understanding the …
Protein‐protein interaction networks as miners of biological discovery
Protein‐protein interactions (PPIs) form the basis of a myriad of biological pathways and
mechanism, such as the formation of protein complexes or the components of signaling …
mechanism, such as the formation of protein complexes or the components of signaling …
SDNN-PPI: self-attention with deep neural network effect on protein-protein interaction prediction
Abstract Background Protein-protein interactions (PPIs) dominate intracellular molecules to
perform a series of tasks such as transcriptional regulation, information transduction, and …
perform a series of tasks such as transcriptional regulation, information transduction, and …
MARPPI: boosting prediction of protein–protein interactions with multi-scale architecture residual network
Protein–protein interactions (PPIs) are a major component of the cellular biochemical
reaction network. Rich sequence information and machine learning techniques reduce the …
reaction network. Rich sequence information and machine learning techniques reduce the …
Prediction of protein-protein interaction sites through eXtreme gradient boosting with kernel principal component analysis
X Wang, Y Zhang, B Yu, A Salhi, R Chen… - Computers in biology …, 2021 - Elsevier
Predicting protein-protein interaction sites (PPI sites) can provide important clues for
understanding biological activity. Using machine learning to predict PPI sites can mitigate …
understanding biological activity. Using machine learning to predict PPI sites can mitigate …
Learning-based robotic grasping: A review
Z Xie, X Liang, C Roberto - Frontiers in Robotics and AI, 2023 - frontiersin.org
As personalization technology increasingly orchestrates individualized shopping or
marketing experiences in industries such as logistics, fast-moving consumer goods, and …
marketing experiences in industries such as logistics, fast-moving consumer goods, and …
Benchmark evaluation of protein–protein interaction prediction algorithms
B Dunham, MK Ganapathiraju - Molecules, 2021 - mdpi.com
Protein–protein interactions (PPIs) perform various functions and regulate processes
throughout cells. Knowledge of the full network of PPIs is vital to biomedical research, but …
throughout cells. Knowledge of the full network of PPIs is vital to biomedical research, but …
[HTML][HTML] MM-StackEns: A new deep multimodal stacked generalization approach for protein–protein interaction prediction
Accurate in-silico identification of protein–protein interactions (PPIs) is a long-standing
problem in biology, with important implications in protein function prediction and drug …
problem in biology, with important implications in protein function prediction and drug …
RPI-MDLStack: Predicting RNA–protein interactions through deep learning with stacking strategy and LASSO
B Yu, X Wang, Y Zhang, H Gao, Y Wang, Y Liu… - Applied Soft …, 2022 - Elsevier
RNA–protein interactions (RPI) play a crucial role in foundational cellular physiological
processes. Traditional methods to predict RPI are implemented through expensive and labor …
processes. Traditional methods to predict RPI are implemented through expensive and labor …
Integrated modelling for mapping spatial sources of dust in central Asia-An important dust source in the global atmospheric system
H Gholami, A Mohammadifar, H Malakooti… - Atmospheric Pollution …, 2021 - Elsevier
Spatial mapping of dust sources in arid and semi-arid regions is necessary to mitigate on-
site and off-site impacts. In this study, we apply a novel integrated modelling approach …
site and off-site impacts. In this study, we apply a novel integrated modelling approach …