aiGeneR 3.0: an enhanced deep network model for resistant strain identification and multi-drug resistance prediction in Escherichia coli causing urinary tract infection using next-generation sequencing data
This work uniquely integrates SNP-level insights with DL, offering potential clinical utility in guiding antibiotic stewardship. It also enables a robust, generalized, and memorized model for future use in AMR analysis.
Authors
- Tripti Swarnkar (ORCID: https://orcid.org/0000-0002-1853-4874)
- Abrar Almjally (ORCID: https://orcid.org/0000-0002-5709-2140)
- Mudassir Khan (ORCID: https://orcid.org/0000-0002-1117-7819)
- Amrutanshu Panigrahi (ORCID: https://orcid.org/0000-0002-1077-8532)
- Saurav Mallik (ORCID: https://orcid.org/0000-0003-4107-6784)
- Bibhuprasad Sahu (ORCID: https://orcid.org/0000-0003-3951-9312)
- Debasish Swapnesh Kumar Nayak (ORCID: https://orcid.org/0000-0001-5553-5692)
- Bayan Ibrahimm Alabdullah (ORCID: https://orcid.org/0000-0002-6252-1800)
- Santanu Kumar Sahoo (ORCID: https://orcid.org/0000-0001-8324-3101)
- Abhilash Pati (ORCID: https://orcid.org/0000-0002-3418-4202)
Institutions
- Princess Nourah bint Abdulrahman University (SA)
- Harvard University (US)
- University of Arizona (US)
- Siksha O Anusandhan University (IN)
- Imam Mohammad ibn Saud Islamic University (SA)
- Symbiosis International University (IN)
- Jadara University (JO)
- National Institute of Technology Raipur (IN)
- Indian Institute of Technology Bhilai (IN)
- Centurion University of Technology and Management (IN)
- King Khalid University (SA)
Publication Details
- Journal
- Frontiers in Genetics
- Published
- 2025-10-22
- DOI
- https://doi.org/10.3389/fgene.2025.1651917
- Primary Topic
- Urinary Tract Infections Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Princess Nourah Bint Abdulrahman University