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Graph Neural Networks for Molecular Discovery with Python: Geometric Deep Learning, Molecule Generation, and Property Prediction
Paperback
General ComputersGeneral Science
Publisher: Independently Published
Published: Jun 24 2026
Pages: 538
Weight: 1.41
Height: 1.33 Width: 6.00 Depth: 9.00
Language: English
Discover the future of molecular discovery with the power of Graph Neural Networks and Geometric Deep Learning.
In Graph Neural Networks for Molecular Discovery with Python, Livia Arden delivers a practical, hands-on guide to applying cutting-edge geometric deep learning techniques to one of the most exciting frontiers in science: accelerating the design and optimization of new molecules. Whether you're working in drug discovery, materials science, or chemical engineering, this book equips you with the tools to model molecular structures as graphs and extract powerful insights that traditional methods simply cannot match.
- Master the fundamentals of Graph Neural Networks (GNNs) and how they naturally represent atoms, bonds, and molecular geometry.
- Build and train sophisticated models for property prediction - from solubility and toxicity to bioactivity and quantum mechanical properties.
- Explore molecule generation techniques, including variational autoencoders, generative adversarial networks, and diffusion models adapted for graphs.
- Implement real-world workflows using Python libraries such as PyTorch Geometric, DGL, RDKit, and NetworkX.
- Tackle challenges like molecular featurization, graph pooling, attention mechanisms, and scalable training on large chemical datasets.
- Apply advanced topics including equivariant networks, 3D molecular modeling, and multi-task learning for accelerated virtual screening.
Every concept is reinforced with clean, well-documented Python code examples that you can immediately adapt to your own research or projects. From loading SMILES strings and building molecular graphs to deploying predictive models and generating novel candidate compounds, this book bridges theory and practice with a strong emphasis on reproducibility and real-world impact.
Who This Book Is For- Data scientists and machine learning engineers eager to apply GNNs to scientific domains.
- Computational chemists and researchers looking to modernize their discovery pipelines.
- Graduate students and professionals in cheminformatics, bioinformatics, and materials informatics.
- Anyone interested in the intersection of geometric deep learning and molecular science.
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Kapoor, Sayash
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AP Computer Science a Premium, 13th Edition: Prep Book with 6 Practice Tests + Comprehensive Review + Online Practice (2026)
Carman, Chris
Teukolsky, Roselyn, M. S.
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You to the Power of Two: Redefining Human Potential in the Age of Identic AI
Bradley, Joseph
Tapscott, Don
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You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It's Making the World a Weirder Place
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The AI Ultimatum: Preparing for a World of Intelligent Machines and Radical Transformation
Brown, Steve
Hill, Paul
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The Devops Handbook, 2nd Edition: How to Create World-Class Agility, Reliability, & Security in Technology Organizations
Humble, Jez
Debois, Patrick
Kim, Gene
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AP Computer Science Principles Premium, 2027: 6 Practice Tests + Comprehensive Review + Online Practice
Reichelson, Seth
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Artificial Intelligence All-In-One for Dummies
Minnick, Chris
Mueller, John Paul
Massaron, Luca
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The Fourth Intelligence Revolution: The Future of Espionage and the Battle to Save America
Vinci, Anthony
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The Death of Expertise: The Campaign Against Established Knowledge and Why It Matters
Nichols, Tom
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The Problem with Personalization: How Advertisers Learned to Make and Break Us from Ancient Times to the AI Age
Turow, Joseph
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
Huyen, Chip
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AI for Educators: Learning Strategies, Teacher Efficiencies, and a Vision for an Artificial Intelligence Future
Miller, Matt
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RHCSA Red Hat Enterprise Linux 10: Training and Exam Preparation Guide (EX200), Fourth Edition
Ghori, Asghar
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More Human: How the Power of AI Can Transform the Way You Lead
Hougaard, Rasmus
Carter, Jacqueline
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The Experimentation Machine: Finding Product-Market Fit in the Age of AI
Bussgang, Jeffrey J.
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Graphic Artists Guild Handbook, 17th Edition: Pricing & Ethical Guidelines
The Graphic Artists Guild
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Building Applications with AI Agents: Designing and Implementing Multiagent Systems
Albada, Michael
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Love Machines: How Artificial Intelligence Is Transforming Our Relationships
Muldoon, James
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Microsoft 365 Excel All-In-One for Dummies
Alexander, Michael
Kusleika, Dick
Ringstrom, David H.
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The Technological Republic: Hard Power, Soft Belief, and the Future of the West
Karp, Alexander C.
Zamiska, Nicholas W.
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The Empty Center: Permission, Connection, and What We Build When the Future is Uncertain
Drumwright, Hayes
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The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma
Suleyman, Mustafa
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What Is Intelligence?: Lessons from AI about Evolution, Computing, and Minds
Aguera Y. Arcas, Blaise
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Navigeren door het labyrint: Een handleiding voor het beheer van data
Sebastian-Coleman, Laura
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Hbr's 10 Must Reads on Artificial Intelligence, Updated and Expanded (Featuring How AI Can Help Managers Think Through Problems by Elisa Farri and Gab
Review, Harvard Business
Davenport, Thomas H.
Agrawal, Ajay
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Prediction Machines, Updated and Expanded: The Simple Economics of Artificial Intelligence
Goldfarb, Avi
Agrawal, Ajay
Gans, Joshua
Hardcover
The Empty Center: Permission, Connection, and What We Build When the Future is Uncertain
Drumwright, Hayes
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Laptops for Seniors in Easy Steps, 9th Edition: Covers All Laptops with the Windows 11 2024 Update
Vandome, Nick
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Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
Cox, Phillip
Lupi, Giorgia
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The Next Big Thing: Innovations for a Better, Smarter, Stronger Tomorrow
Marciano, Rob
Trefil, James
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A Whole New Human: Ten Ways We Must Evolve to Survive and Thrive in the AI Age
Rydall, Derek
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R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Grolemund, Garrett
Cetinkaya-Rundel, Mine
Wickham, Hadley
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On the Future of Species: Authoring Life by Means of Artificial Biological Intelligence
Woolfson, Adrian
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Comptia A+ Complete Study Guide, 2-Volume Set: Volume 1 Core 1 Exam 220-1201 and Volume 2 Core 2 Exam 220-1202
Docter, Quentin
Buhagiar, Jon
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Rewiring Democracy: How AI Will Transform Our Politics, Government, and Citizenship
Sanders, Nathan E.
Schneier, Bruce
Hardcover