Systems Biology and Machine Learning Methods in Reproductive Health
暫譯: 生物系統與機器學習方法在生殖健康中的應用

《生物系統與機器學習方法在生殖健康中的應用》是一本創新且範圍廣泛的書籍，探索了系統生物學與機器學習這兩個學科的協同結合，並應用於生殖健康領域。本書匯集了領先科學家和臨床醫生的專業知識，呈現了一系列尖端技術和案例研究，利用計算方法來闡明複雜的生物系統、解析生殖途徑，並解決生育、懷孕和生殖疾病等領域的關鍵問題。這本開創性的書籍將科學與數據科學結合在一起，為科學家、臨床醫生和學生提供了一個逐步指南，幫助他們通過尖端的計算工具揭示生殖健康的複雜性。

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.

Abhishek Sengupta 是印度烏塔爾邦諾伊達阿米提大學生物技術學院計算生物學與生物資訊中心的助理教授。他在英國諾丁漢特倫特大學獲得碩士學位，並在印度阿米提大學獲得博士學位。擁有15年的基因組規模代謝重建、基於約束的建模、網絡生物學、系統生物學、代謝組學和通量平衡分析的經驗，他開發了HEPNet知識庫，並為TFIS、ARTPre和PluriMetNet等軟體以及VIRdb等數據庫做出了貢獻。他在知名期刊上發表了大量文章，並獲得了印度政府科技部（DST-SERB）提供的資助。Sengupta還主導了基於機器學習的軟體「FertilitY Predictor」的技術轉移和授權，並獲得了「ARTPre：一個預測印度次大陸輔助生殖程序成功率的在線工具」的版權。

Priyanka Narad 是一位經驗豐富的生物資訊學家和人工智慧專家。她目前在印度醫學研究委員會（ICMR）新德里擔任科學家。擁有超過13年的經驗，包括在阿米提大學擔任助理教授，她的專長在於幹細胞生物資訊學、機器學習、多組學數據整合和預測建模。Narad通過在《Nature Scientific Reports》和《PeerJ》等知名期刊上發表的多篇文章做出了重要貢獻。她為「一種混合貝葉斯方法應對印度次族群輔助生殖技術中的社會經濟挑戰」等項目獲得了資金支持。Narad開發並部署了TFIS、ARTPre、VIRdb和FertilitY Predictor等軟體/數據庫，並持有技術轉移和版權許可。她的學術成就獲得了DST SERB青年科學家旅行獎，以參加英國EMBL-EBI（歐洲分子生物學實驗室-歐洲生物資訊研究所）的系統生物學課程。

Dinesh Gupta 是一位傑出的生物資訊學家和計算生物學家。他在新德里的全印度醫學科學院獲得博士學位。目前，他在印度新德里國際基因工程與生物技術中心（ICGEB）擔任轉化生物資訊學小組的組長。擁有超過二十年的經驗，Gupta在生物資訊工具和人工智慧方法的開發與應用方面做出了重要貢獻，以解決複雜的生物學問題。他的研究興趣涵蓋廣泛，包括生物數據分析的機器學習、計算輔助藥物設計、比較基因組學、系統生物學和下一代測序數據分析。Gupta在知名期刊上發表了大量文章，並積極參與國際生物資訊學研討會和培訓計劃的組織。

Deepak Modi 是生殖生物學和遺傳學領域的知名科學家，目前與印度醫學研究委員會（ICMR）國家生殖與兒童健康研究所合作。擁有孟買大學的博士學位和豐富的學術背景，他獲得了PM Bhargava演講獎和GP Talwar中期科學家獎等多項榮譽。他的研究重點在於胚胎植入、不孕症和性發育障礙。Modi擁有85篇發表文章和3章書籍的驚人出版紀錄。他在HOXA10的免疫調節作用、微流體胎盤功能評估、子宮內膜異位症發病機制和COVID-19胎盤等主題的項目中做出了重要貢獻。此外，他積極參加科學會議，並擔任受邀演講者和小組成員，反映了他在該領域的專業知識。