The future of zoonotic risk prediction

CJ Carlson, MJ Farrell, Z Grange… - … of the Royal …, 2021 - royalsocietypublishing.org
In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife
virology is likely to increase, and new surveillance programmes will identify hundreds of …

Integrating multi-omics to unravel host-microbiome interactions in inflammatory bowel disease

Y Zhang, JP Thomas, T Korcsmaros, L Gul - Cell Reports Medicine, 2024 - cell.com
The gut microbiome is crucial for nutrient metabolism, immune regulation, and intestinal
homeostasis with changes in its composition linked to complex diseases like inflammatory …

[HTML][HTML] Deep learning frameworks for protein–protein interaction prediction

X Hu, C Feng, T Ling, M Chen - Computational and structural …, 2022 - Elsevier
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 …

Recent advances in deep learning for protein-protein interaction analysis: A comprehensive review

M Lee - Molecules, 2023 - mdpi.com
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 …

DeepTrio: a ternary prediction system for protein–protein interaction using mask multiple parallel convolutional neural networks

X Hu, C Feng, Y Zhou, A Harrison, M Chen - Bioinformatics, 2022 - academic.oup.com
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 …

[HTML][HTML] Unleashing the power of artificial intelligence for diagnosing and treating infectious diseases: A comprehensive review

AA Rabaan, MA Bakhrebah, J Alotaibi, ZS Natto… - Journal of Infection and …, 2023 - Elsevier
Infectious diseases present a global challenge, requiring accurate diagnosis, effective
treatments, and preventive measures. Artificial intelligence (AI) has emerged as a promising …

Transfer learning via multi-scale convolutional neural layers for human–virus protein–protein interaction prediction

X Yang, S Yang, X Lian, S Wuchty, Z Zhang - Bioinformatics, 2021 - academic.oup.com
Motivation To complement experimental efforts, machine learning-based computational
methods are playing an increasingly important role to predict human–virus protein–protein …

Bioinformatics approaches for unveiling virus-host interactions

H Iuchi, J Kawasaki, K Kubo, T Fukunaga… - Computational and …, 2023 - Elsevier
Abstract The coronavirus disease-2019 (COVID-19) pandemic has elucidated major
limitations in the capacity of medical and research institutions to appropriately manage …

Bibliometric analysis of artificial intelligence for biotechnology and applied microbiology: Exploring research hotspots and frontiers

D Xu, B Liu, J Wang, Z Zhang - Frontiers in bioengineering and …, 2022 - frontiersin.org
Background: In the biotechnology and applied microbiology sectors, artificial intelligence
(AI) has been extensively used in disease diagnostics, drug research and development …

[HTML][HTML] Artificial intelligence approaches to human-microbiome protein–protein interactions

H Lim, F Cankara, CJ Tsai, O Keskin… - Current Opinion in …, 2022 - Elsevier
Host-microbiome interactions play significant roles in human health and disease. Artificial
intelligence approaches have been developed to better understand and predict the …