Biomarker Identification for Preterm Birth Susceptibility: Vaginal Microbiome Meta-Analysis Using Systems Biology and Machine Learning Approaches.

Journal: American journal of reproductive immunology (New York, N.Y. : 1989)
PMID: 39033501

Abstract

PROBLEM: The vaginal microbiome has a substantial role in the occurrence of preterm birth (PTB), which contributes substantially to neonatal mortality worldwide. However, current bioinformatics approaches mostly concentrate on the taxonomic classification and functional profiling of the microbiome, limiting their abilities to elucidate the complex factors that contribute to PTB.

Authors

  • Sudeepti Kulshrestha
    Systems Biology and Data Analytics Research Lab, Centre for Computational Biology and Bioinformatics, Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India.
  • Priyanka Narad
    Amity Institute of Biotechnology, Amity University Uttar Pradesh, Noida, India. Electronic address: pnarad@amity.edu.
  • Brojen Singh
    School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.
  • Somnath S Pai
    Amity Institute of Virology & Immunology, Amity University, Noida, Uttar Pradesh, India.
  • Pooja Vijayaraghavan
    Anti-mycotic Drug Susceptibility Laboratory, Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India.
  • Ansh Tandon
    Systems Biology and Data Analytics Research Lab, Centre for Computational Biology and Bioinformatics, Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India.
  • Payal Gupta
    Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India.
  • Deepak Modi
    Molecular and Cellular Biology Laboratory, National Institute for Research in Reproductive and Child Health, Mumbai, Maharashtra, India.
  • Abhishek Sengupta
    Amity Institute of Biotechnology, Amity University Uttar Pradesh, U.P., India.

Keywords

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