Work

Artificial intelligence approaches to human-microbiome protein–protein interactions

Year: 2022

Type: review

Abstract: Host-microbiome interactions play significant roles in human health and disease. Artificial intelligence approaches have been developed to better understand and predict the molecular interplay between the host and its microbiome. Here, we review recent advancements in computational methods to predict microbial effects on human cells with a special focus on protein-protein interactions. We categorize recent methods from traditional ones to more recent deep learning methods, followed by several challenges and potential solutions in structure-based approaches. This review serves as a brief guide to the current status and future directions in the field.

Source: Current Opinion in Structural Biology

DOI: 10.1016/j.sbi.2022.102328

Authors: Hansaim Lim, Fatma Cankara, Chung-Jung Tsai, Ozlem Keskin, Ruth Nussinov, Attila Gursoy

Institutions: Frederick National Laboratory for Cancer Research, National Cancer Institute, Koç University, Tel Aviv University

Language: English

Topic: Machine Learning in Bioinformatics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,400