- Mandar Bedse - Bioclues.org, India (Tech Lead)
- Gautam Kr. Dhandh - Bioclues.org, India (Writer)
- VS Sundararajan, PhD - Bioclues.org, India (Flex)
- Girik Malik, PhD - Bioclues.org, India (Flex)
- Prashanth N Suravajhala, PhD - Amrita Vishwa Vidyapeetham, Kerala and Bioclues.org, India (Team Co-Lead)
- R Shyam Prasad Rao, PhD - NITTE University, Mangalore and Bioclues.org, India (Team Co-Lead)
This project integrates data and tools for analyzing antimicrobial resistance (AMR) genes in ESKAPEE pathogens. The focus is to examine these genes in the context of mobile genetic elements (MGEs), such as plasmids, and their associated phenotypes derived from antimicrobial susceptibility tests (AST) and clinical data.
Initially, the project will focus on Acinetobacter and plasmids. The broader goal is to provide a comprehensive pangenomic profile of AMR and AST in the context of MGEs/plasmids.
- Acinetobacter
- Antimicrobial Resistance (AMR)
- ESKAPEE Pathogens
- Mobile Genetic Elements (MGEs)
- Pangenome
- Plasmids
This section will cover the methodology and tools used to analyze AMR genes in Acinetobacter and their relationship with plasmids/MGEs. We aim to use various data integration techniques to map AMR genes to their plasmids and correlate them with clinical AST data.
Here, we will present our findings and pangenomic profile of AMR in Acinetobacter, highlighting the correlation between AMR genes, plasmids, and AST data.
To be completed upon project milestones.
- Extend the analysis to other ESKAPEE pathogens.
- Improve tools for MGE and plasmid correlation with AMR.
- Incorporate more clinical data for AST and explore additional pathogens.
This software was created as part of an NCBI codeathon, a hackathon-style event focused on rapid innovation. While we encourage you to explore and adapt this code, please be aware that NCBI does not provide ongoing support for it.
For general questions about NCBI software and tools, please visit: NCBI Contact Page
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