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 …
Cracking the black box of deep sequence-based protein–protein interaction prediction
Identifying protein–protein interactions (PPIs) is crucial for deciphering biological pathways.
Numerous prediction methods have been developed as cheap alternatives to biological …
Numerous prediction methods have been developed as cheap alternatives to biological …
Structure-aware protein–protein interaction site prediction using deep graph convolutional network
Motivation Protein–protein interactions (PPI) play crucial roles in many biological processes,
and identifying PPI sites is an important step for mechanistic understanding of diseases and …
and identifying PPI sites is an important step for mechanistic understanding of diseases and …
DELPHI: accurate deep ensemble model for protein interaction sites prediction
Motivation Proteins usually perform their functions by interacting with other proteins, which is
why accurately predicting protein–protein interaction (PPI) binding sites is a fundamental …
why accurately predicting protein–protein interaction (PPI) binding sites is a fundamental …
Benchmark evaluation of protein–protein interaction prediction algorithms
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 …
A review of bioinformatics tools and web servers in different microarray platforms used in cancer research
Over the past decade, conventional lab work strategies have gradually shifted from being
limited to a laboratory setting towards a bioinformatics era to help manage and process the …
limited to a laboratory setting towards a bioinformatics era to help manage and process the …
Computational Approaches to Predict Protein–Protein Interactions in Crowded Cellular Environments
Investigating protein–protein interactions is crucial for understanding cellular biological
processes because proteins often function within molecular complexes rather than in …
processes because proteins often function within molecular complexes rather than in …
Protein-protein interaction prediction using a hybrid feature representation and a stacked generalization scheme
KH Chen, TF Wang, YJ Hu - BMC bioinformatics, 2019 - Springer
Background Although various machine learning-based predictors have been developed for
estimating protein–protein interactions, their performances vary with dataset and species …
estimating protein–protein interactions, their performances vary with dataset and species …
FINDER: an automated software package to annotate eukaryotic genes from RNA-Seq data and associated protein sequences
Background Gene annotation in eukaryotes is a non-trivial task that requires meticulous
analysis of accumulated transcript data. Challenges include transcriptionally active regions …
analysis of accumulated transcript data. Challenges include transcriptionally active regions …