Sayan Das

Experienced bioinformatician specializing in maternal and child health, focusing on omics studies to uncover biomarkers and genetic factors affecting pregnancy outcomes. Demonstrated proficiency in integrating extensive datasets to advance research on prenatal and neonatal health in low- and middle-income countries. Adept at translating intricate bioinformatics data into actionable insights for public health interventions.

• Cleared GRE (319) and TOEFL (89) in 2012.
• Certification in Java programming language using SE 6 by NIIT, Kolkata.

• Database management, National Institute of Cholera and Enteric Diseases, Kolkata, 11/29/10 - 12/10/10
• Estimation, extraction of soluble protein from the seeds of a legume crop and SDS PAGE, Ramakrishna Mission Vivekananda University, Narendrapur, 06/06/12 - 06/29/12
• Bioinformatics analysis of a protein which is involved in regulation activity of other proteins, Bose Institute, Kolkata, 05/20/14 - 07/11/14
• Designing of a database using XML, Birla Institute of Technology, Mesra, 01/01/15 - 05/07/15

• Presented a poster titled “Differential Microbiome Profiles in Healing and Non-Healing Chronic Diabetic Foot Ulcers” at the Symposium on “Genomics in Clinical practice : Future and precision medicine” held at Yenepoya University, Mangalore in June, 2016
• Successfully completed the NIBMG Winter School 2017 on “Analysis of Next Generation Data in Populations, Families and Tumours held on March, 2017
• Participated in the Indo-US Workshop on Genomics and Bioinformatics to explore Human Microbial Ecology in “Health and Disease” held at THSTI, Faridabad on September, 2017
• Attended the discussion meeting on “Human Ancestry and Diversity in India” held at JNCSAR in September, 2018
• Attended a One Day Symposium on “Recent Trends in Biological Research” at Amity University, Kolkata organized by the Society of Biological Chemists, Kolkata Chapter on September, 2018
• Lead trainer in two workshops on big data analysis in Zanzibar

• Father's Name : Dr. Krishnendu Das
• Mother's Name : Mrs. Ashokamitra Das
• Gender: Male
• Nationality: Indian

1. Reading current affairs articles

2. Watching movies

3. Watching any kind of sports

4. Eating and listening to songs

• Robinson JF, Das S, Khan W, et al. High rates of placental inflammation among samples collected by the Multi-Omics for Mothers and Infants consortium. Am J Obstet Gynecol. Published online April 30, 2024. doi:10.1016/j.ajog.2024.04.034
• Nisar MI, das S, Khanam R, et al. Early to mid-pregnancy HbA1c levels and its association with adverse pregnancy outcomes in three low middle-income countries in Asia and Sub-Saharan Africa. BMC Pregnancy Childbirth. 2024;24(1):66. Published 2024 Jan 15. doi:10.1186/s12884-023-06241-w
• Espinosa CA, Khan W, Khanam R, et al. Multiomic signals associated with maternal epidemiological factors contributing to preterm birth in low- and middle-income countries. Sci Adv. 2023;9(21):eade7692. doi:10.1126/sciadv.ade7692
• Contrepois K, Chen S, Ghaemi MS, et al. Prediction of gestational age using urinary metabolites in term and preterm pregnancies [published correction appears in Sci Rep. 2022 Nov 17;12(1):19753. doi: 10.1038/s41598-022-23715-7]. Sci Rep. 2022;12(1):8033. Published 2022 May 16. doi:10.1038/s41598-022-11866-6
• Khanam R, Applegate J, Nisar I, et al. Burden and risk factors for antenatal depression and its effect on preterm birth in South Asia: A population-based cohort study. PLoS One. 2022;17(2):e0263091. Published 2022 Feb 7. doi:10.1371/journal.pone.0263091
• Alliance for Maternal and Newborn Health Improvement (AMANHI) GA Study Group. Population-based rates, risk factors and consequences of preterm births in South-Asia and sub-Saharan Africa: A multi-country prospective cohort study. J Glob Health. 2022;12:04011. Published 2022 Feb 19. doi:10.7189/jogh.12.04011
• Sazawal S, Das S, Ryckman KK, et al. Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation: Facilitating use of this technology in low resource settings of South Asia and East Africa. J Glob Health. 2022;12:04021. Published 2022 Apr 23. doi:10.7189/jogh.12.04021
• Sazawal S, Ryckman KK, Das S, et al. Machine learning guided postnatal gestational age assessment using new-born screening metabolomic data in South Asia and sub-Saharan Africa. BMC Pregnancy Childbirth. 2021;21(1):609. Published 2021 Sep 7. doi:10.1186/s12884-021-04067-y
• Sazawal S, Ryckman KK, Mittal H, et al. Using AMANHI-ACT cohorts for external validation of Iowa new-born metabolic profiles based models for postnatal gestational age estimation. J Glob Health. 2021;11:04044. Published 2021 Jul 17. doi:10.7189/jogh.11.04044
• Jehan F, Sazawal S, Baqui AH, et al. Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries [published correction appears in JAMA Netw Open. 2021 Feb 1;4(2):e210399. doi: 10.1001/jamanetworkopen.2021.0399]. JAMA Netw Open. 2020;3(12):e2029655. Published 2020 Dec 1. doi:10.1001/jamanetworkopen.2020.29655
• Have been acknowledged in the journal: Mukherjee, S. et al. Sebum and Hydration Levels in Specific Regions of Human Face Significantly Predict the Nature and Diversity of Facial Skin Microbiome. Sci. Rep. 6, 36062; doi: 10.1038/srep36062 (2016)
• Have been acknowledged in the journal: Nath S, Kumari N, Bandyopadhyay D, et al. Dysbiotic Lesional Microbiome With Filaggrin Missense Variants Associate With Atopic Dermatitis in India. Front Cell Infect Microbiol. 2020;10:570423. Published 2020 Nov 17. doi:10.3389/fcimb.2020.570423
• Wrote a thesis on “Designing of a multiuse database using XML” in the year 2015 at Birla Institute of Technology, Mesra