Systems Biology and Machine Learning Methods in Reproductive Health | Agenda Bookshop Skip to content
Online orders placed from 19/12 onward will not arrive in time for Christmas.
Online orders placed from 19/12 onward will not arrive in time for Christmas.
Age Group_Uncategorized
Age Group_Uncategorized
automatic-update
B01=Abhishek Sengupta
B01=Deepak Modi
B01=Dinesh Gupta
B01=Priyanka Narad
Category1=Non-Fiction
Category=MBNH4
Category=MFKC
Category=PS
Category=TJFM
Category=UYD
Category=UYQ
COP=United Kingdom
Delivery_Pre-order
Language_English
PA=Not yet available
Price_€100 and above
PS=Forthcoming
softlaunch

Systems Biology and Machine Learning Methods in Reproductive Health

English

Systems Biology and Machine Learning Methods in Reproductive Health is an innovative and wide-ranging book that discovers the synergetic combination of disciplines: systems biology and machine learning, with an application in the field of reproductive health. This book assembles the expertise of leading scientists and clinicians to present a compilation of cutting-edge techniques and case studies utilizing computational methods to elucidate intricate biological systems, elucidate reproductive pathways, and address critical issues in the fields of fertility, pregnancy, and reproductive disorders. Bringing science and data science together, this groundbreaking book provides scientists, clinicians, and students with a step-by-step guide to uncovering the complexities of reproductive health through cutting-edge computational tools. See more
Current price €127.29
Original price €133.99
Save 5%
Age Group_Uncategorizedautomatic-updateB01=Abhishek SenguptaB01=Deepak ModiB01=Dinesh GuptaB01=Priyanka NaradCategory1=Non-FictionCategory=MBNH4Category=MFKCCategory=PSCategory=TJFMCategory=UYDCategory=UYQCOP=United KingdomDelivery_Pre-orderLanguage_EnglishPA=Not yet availablePrice_€100 and abovePS=Forthcomingsoftlaunch

Will deliver when available. Publication date 10 Jan 2025

Product Details
  • Dimensions: 178 x 254mm
  • Publication Date: 10 Jan 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: United Kingdom
  • Language: English
  • ISBN13: 9781032755519

About

Abhishek Sengupta is Assistant Professor at the Centre of Computational Biology and Bioinformatics Amity Institute of Biotechnology Amity University Noida Uttar Pradesh India. He received his MSc from Nottingham Trent University UK and PhD from Amity University India. With 15 years of experience in genome- scale metabolic reconstructions constraint- based modeling network biology systems biology metabolomics and flux balance analysis he has developed the HEPNet knowledge base contributed to software like TFIS ARTPre and PluriMetNet and databases like VIRdb. He has published extensively in reputed journals and received grants from DST- SERB (a statutory body of the Department of Science and Technology) Government of India. Sengupta has also led technology transfer and licensing of the ML- based software FertilitY Predictor and been awarded copyrights for ARTPre: An Online Tool to Predict the Success Rates of Assisted Reproductive Procedures in Indian Subcontinent. Priyanka Narad is an experienced Bioinformatician and AI expert. She is currently working as a Scientist at the Indian Council of Medical Research (ICMR) New Delhi. With over 13 years of experience including as an assistant professor at Amity University her expertise lies in stem cell bioinformatics machine learning multi- omics data integration and predictive modeling. Narad has made significant contributions through numerous publications in prestigious journals like Nature Scientific Reports and PeerJ. She has secured funding for projects like A Hybrid Bayesian Approach to Address Socio- Economic Challenges in Assisted Reproductive Techniques Across the Indian Sub- population. Narad has developed and deployed software/ databases such as TFIS ARTPre VIRdb and FertilitY Predictor for which she holds technology transfer and copyright licenses. Her academic excellence was recognized with the DST SERB Young Scientists Travel Award to attend a systems biology course at EMBL- EBI (European Molecular Biology Laboratory- European Bioinformatics Institute) UK. Dinesh Gupta is a distinguished bioinformatician and computational biologist. He obtained his PhD from All India Institute of Medical Sciences in New Delhi. He currently serves as Group Leader of the Translational Bioinformatics Group at the International Centre for Genetic Engineering and Biotechnology (ICGEB) in New Delhi India. With over two decades of experience in the field Gupta has made significant contributions to the development and application of bioinformatics tools and artificial intelligence methods for solving complex biological problems. His research interests span a wide range of areas including machine learning for biological data analysis computer- aided drug design comparative genomics systems biology and next- generation sequencing data analysis. Gupta has published extensively in prestigious journals and has been actively involved in organizing international bioinformatics workshops and training programs.Deepak Modi is a renowned scientist in Reproductive Biology and Genetics currently associated with the National Institute for Research in Reproductive and Child Health Indian Council of Medical Research (ICMR). With a PhD from the University of Mumbai and an extensive academic background he has received prestigious awards like the PM Bhargava Oration Award and GP Talwar Middle Career Scientist Award. His research focuses on embryo implantation infertility and disorders of sex development. Modi has an impressive publication record with 85 publications and 3 book chapters in reputed journals. He has contributed significantly through projects on topics like immunomodulatory roles of HOXA10 microfluidic placental function assessment endometriosis pathogenesis and COVID- 19 placenta. In addition he actively participates in scientific conferences and serves as an invited speaker and panelist reflecting his expertise in the field.

Customer Reviews

Be the first to write a review
0%
(0)
0%
(0)
0%
(0)
0%
(0)
0%
(0)
We use cookies to ensure that we give you the best experience on our website. If you continue we'll assume that you are understand this. Learn more
Accept