loading page

AI-based Dynamic web server for real-time classification of raw genome sequences of ESKAPEE pathogens
  • +9
  • Sarthak Mishra ,
  • Priyanka Sharma ,
  • Suraiya Jabin ,
  • Sumaiya Ahmad ,
  • Divanshu Srivastava ,
  • Krishna Mohan Tiwari ,
  • Arzoo Khan ,
  • Pulkit Singh ,
  • Punit Kaur ,
  • Harpreet Singh ,
  • Divyanshu Srivastava ,
  • Wanchha Maurya
Sarthak Mishra
Author Profile
Priyanka Sharma
Author Profile
Suraiya Jabin
Jamia Millia Islamia, Jamia Millia Islamia, Jamia Millia Islamia, Jamia Millia Islamia, Jamia Millia Islamia

Corresponding Author:[email protected]

Author Profile
Sumaiya Ahmad
Author Profile
Divanshu Srivastava
Author Profile
Krishna Mohan Tiwari
Author Profile
Arzoo Khan
Author Profile
Pulkit Singh
Author Profile
Punit Kaur
Author Profile
Harpreet Singh
Author Profile
Divyanshu Srivastava
Author Profile
Wanchha Maurya
Author Profile


It’s a collaborative effort of JMI, AIIMS, and ICMR, New Delhi, India.
Dynamic Web Server for ESKAPEE Pathogen classification” is the deployment of a robust machine learning model which accepts raw clinical sequences i.e. SRA data in the fast/fq format, and classifies it into 8 classes of Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter species, E. coli (i.e. ESKAPEE) and non-ESKAPEE that consists of Human DNA, Fungi, and bacteria other than ESKAPEE.