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Enhanced diagnosis of multi-drug-resistant microbes using group association modeling and machine learning

In this work, authors describe a Group Association Model (GAM) that detects genotype phenotype associations in microbial drug resistance; refined with the machine learning, it identifies features for predictive modelling, reducing cross-resistance artifacts and potentially improving treatment decisions.

Julian G. Saliba
Wenshu Zheng
Tony Ye Hu
ResearchOpen Access25 Mar 2025
Nature Communications

Volume: 16, P: 1-15
Controlling CRISPR-Cas9 with ligand-activated and ligand-deactivated sgRNAs

Control of CRISPR-Cas9 activity allows for fine-tuning of editing and gene expression. Here the authors use gRNAs modified with RNA aptamers to enable small molecule control in bacterial systems.

Kale Kundert
James E. Lucas
Tanja Kortemme
ResearchOpen Access09 May 2019
Nature Communications

Volume: 10, P: 1-11
Enabling genetic analysis of diverse bacteria with Mobile-CRISPRi

The development of mobile CRISPR interference (CRISPRi), a modular dCas9-based system that facilitates blocking of gene expression and is easily transferred via conjugation, enables genetic investigations in non-model bacteria.

Jason M. Peters
Byoung-Mo Koo
Oren S. Rosenberg
Research07 Jan 2019
Nature Microbiology

Volume: 4, P: 244-250
Immunological and metabolic characteristics of the Omicron variants infection

Jiejie Geng
Xu Yang
Liang Chen
ResearchOpen Access21 Jan 2023
Signal Transduction and Targeted Therapy

Volume: 8, P: 1-11

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Enhanced diagnosis of multi-drug-resistant microbes using group association modeling and machine learning

Controlling CRISPR-Cas9 with ligand-activated and ligand-deactivated sgRNAs

Enabling genetic analysis of diverse bacteria with Mobile-CRISPRi

Immunological and metabolic characteristics of the Omicron variants infection

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