This book explores the "triple helix" of data, cloud computing, and artificial intelligence, exploring how this powerful convergence is reshaping life sciences. It serves as a comprehensive guide to the technologies driving this revolution, from the foundational principles of scalable cloud infrastructure to the architecture of the generative AI and Large Language Models that are learning to speak the language of biology. The book examines the practical application of these tools across several domains, including pandemic mitigation, the future of personalized health, and the development of a sustainable bioeconomy, offering readers a clear understanding of both the technological underpinnings and their real-world impact.
Moving beyond theory, the book provides a pragmatic roadmap for implementation, tackling the significant challenges of R&D productivity, data quality, and operational efficiency. It founds a blueprint for building trustworthy AI by detailing the essential pillars of security, privacy, and compliance. Finally, this work presents a compelling vision for an "Intelligent Discovery Environment for Science," where human-AI partnerships dissolve the barriers between idea and execution. It is a call to action for researchers, technologists, and leaders to collaboratively build a more efficient, equitable, and human-centric future for science.
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Verlagsort
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Springer International Publishing
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ISBN-13
978-3-032-14222-1 (9783032142221)
Schweitzer Klassifikation
Dr. Zhong Wang is a career computational biologist at Lawrence Berkeley Lab and DOE Joint Genome Institute (JGI); he is also an adjunct professor at University of California, Merced. He received his B.S in Microbiology from Shandong University in 1994, and his Ph.D. in Cell Biology from Duke University in 2004. He did his postdoc in the Institute of Genome Science and Policy at Duke University before becoming a research scientist at Yale University in 2008 and director of bioinformatics at Yale Stem Cell Center. He joined JGI in 2009 and established his research group. His research interests include metagenomics algorithm development, scalable software solutions for genomics analysis, and AI applications in genomics. Dr. Wang published many scientific papers and book chapters including several on Science and Nature. He recently authored a book "Introduction to computational metagenomics".
Adrish Sannyasi is an accomplished AI solutions leader with deep expertise in cloud data platforms, artificial intelligence, and healthcare and life sciences applications. He has consistently leveraged data and AI technologies to address complex industry challenges and drive measurable business outcomes across the healthcare and life sciences ecosystem. As Vice President of Customer Engineering and Delivery at Rhino Federated Computing Platform, Adrish helps organizations advance their AI initiatives across a wide range of projects, including large language models, protein language modeling, molecular property prediction, healthcare data analytics, data harmonization, and medical imaging AI. Adrish holds a Bachelor's degree in Electrical Engineering from Visvesvaraya National Institute of Technology (India), an MBA from the University of Maryland, and a Graduate Certificate in Biomedical Data Science from the Stanford School of Medicine.
Mr. Jonathan Jiang is a computer scientist and entrepreneur who has been tackling hard problems in a variety of industries using cloud computing and AI. At MemVerge Inc., Jiang led the development of Memory Machine Cloud, an AI and Cloud Computing platform optimized for life sciences. Prior to MemVerge, he worked in Big Data, virtualization, and internetworking at VMware, EMC, and Cisco Systems. He also founded several software startups in eCommerce and TravelTech. Jiang received his MS in Information Systems from New York University, and BS (summa cum laude) in Interdisciplinary Engineering from Cooper Union.
