[HTML][HTML] Deep learning frameworks for protein–protein interaction prediction
Protein-protein interactions (PPIs) play key roles in a broad range of biological processes.
The disorder of PPIs often causes various physical and mental diseases, which makes PPIs …
The disorder of PPIs often causes various physical and mental diseases, which makes PPIs …
Recent advances in deep learning for protein-protein interaction analysis: A comprehensive review
Deep learning, a potent branch of artificial intelligence, is steadily leaving its transformative
imprint across multiple disciplines. Within computational biology, it is expediting progress in …
imprint across multiple disciplines. Within computational biology, it is expediting progress in …
Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering
P Cheng, C Mao, J Tang, S Yang, Y Cheng, W Wang… - Cell Research, 2024 - nature.com
Mutations in amino acid sequences can provoke changes in protein function. Accurate and
unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but …
unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but …
Bioinformatics approaches for unveiling virus-host interactions
Abstract The coronavirus disease-2019 (COVID-19) pandemic has elucidated major
limitations in the capacity of medical and research institutions to appropriately manage …
limitations in the capacity of medical and research institutions to appropriately manage …
Viral informatics: bioinformatics-based solution for managing viral infections
Several new viral infections have emerged in the human population and establishing as
global pandemics. With advancements in translation research, the scientific community has …
global pandemics. With advancements in translation research, the scientific community has …
MaTPIP: A deep-learning architecture with eXplainable AI for sequence-driven, feature mixed protein-protein interaction prediction
Abstract Background and Objective Protein-protein interaction (PPI) is a vital process in all
living cells, controlling essential cell functions such as cell cycle regulation, signal …
living cells, controlling essential cell functions such as cell cycle regulation, signal …
Transfer learning for genotype–phenotype prediction using deep learning models
Background For some understudied populations, genotype data is minimal for genotype-
phenotype prediction. However, we can use the data of some other large populations to …
phenotype prediction. However, we can use the data of some other large populations to …
MpbPPI: a multi-task pre-training-based equivariant approach for the prediction of the effect of amino acid mutations on protein–protein interactions
The accurate prediction of the effect of amino acid mutations for protein–protein interactions
(PPI) is a crucial task in protein engineering, as it provides insight into the relevant biological …
(PPI) is a crucial task in protein engineering, as it provides insight into the relevant biological …
Growing ecosystem of deep learning methods for modeling protein–protein interactions
Numerous cellular functions rely on protein–protein interactions. Efforts to comprehensively
characterize them remain challenged however by the diversity of molecular recognition …
characterize them remain challenged however by the diversity of molecular recognition …
Recent developments of sequence-based prediction of protein–protein interactions
The identification of protein–protein interactions (PPIs) can lead to a better understanding of
cellular functions and biological processes of proteins and contribute to the design of drugs …
cellular functions and biological processes of proteins and contribute to the design of drugs …