High Performance Computing for Drug Discovery and Biomedicine

Buch | Softcover

429 Seiten

2024 | 2024 ed.
Springer-Verlag New York Inc.
978-1-0716-3451-6 (ISBN)

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This volume explores the application of high-performance computing (HPC) technologies to computational drug discovery (CDD) and biomedicine. The first section collects CDD approaches that, together with HPC, can revolutionize and automate drug discovery process, such as knowledge graphs, natural language processing (NLP), Bayesian optimization, automated virtual screening platforms, alchemical free energy workflows, fragment-molecular orbitals (FMO), HPC-adapted molecular dynamic simulation (MD-HPC), and the potential of cloud computing for drug discovery. The second section delves into computational algorithms and workflows for biomedicine, featuring an HPC framework to assess drug-induced arrhythmic risk, digital patient applications relevant to the clinic, virtual human simulations, cellular and whole-body blood flow modeling for stroke treatments, prediction of the femoral bone strength from CT data, and many more subjects. Written for the highly successful Methods inMolecular Biology series, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step and readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls.
Authoritative and practical, High Performance Computing for Drug Discovery and Biomedicine allows a diverse audience, including computer scientists, computational and medicinal chemists, biologists, clinicians, pharmacologists and drug designers, to navigate the complex landscape of what is currently possible and to understand the challenges and future directions of HPC-based technologies.

Introduction to Computational Biomedicine.- Introduction to High Performance Computing.- Computational Biomedicine (CompBioMed) Centre of Excellence: Selected Key Achievements.- In Silico Clinical Trials: Is It Possible?.- Bayesian Optimization in Drug Discovery.- Automated Virtual Screening.- The Future of Drug Development with Quantum Computing.- Edge, Fog, and Cloud Against Disease: The Potential of High-Performance Cloud Computing for Pharma Drug Discovery.- Knowledge Graphs and Their Applications in Drug Discovery.- Natural Language Processing for Drug Discovery Knowledge Graphs: Promises and Pitfalls.- Alchemical Free Energy Workflows for the Computation of Protein-Ligand Binding Affinities.- Molecular Dynamics and Other HPC Simulations for Drug Discovery.- High Throughput Structure-Based Drug Design (HT-SBDD) Using Drug Docking, Fragment Molecular Orbital Calculations, and Molecular Dynamic Techniques.- HPC Framework for Performing In Silico Trials Using a 3D Virtual Human Cardiac Population as Means to Assess Drug-Induced Arrhythmic Risk.- Effect of Muscle Forces on Femur during Level Walking Using a Virtual Population of Older Women.- Cellular Blood Flow Modeling with HemoCell.- A Blood Flow Modeling Framework for Stroke Treatments.- Efficient and Reliable Data Management for Biomedical Applications.- Accelerating COVID-19 Drug Discovery with High-Performance Computing.- Teaching Medical Students to Use Supercomputers: A Personal Reflection.

Erscheinungsdatum	21.09.2024
Reihe/Serie	Methods in Molecular Biology
Zusatzinfo	XIII, 429 p.
Verlagsort	New York, NY
Sprache	englisch
Maße	178 x 254 mm
Themenwelt	Mathematik / Informatik ► Informatik ► Theorie / Studium
	Informatik ► Weitere Themen ► Bioinformatik
	Medizin / Pharmazie ► Medizinische Fachgebiete ► Biomedizin
	Medizin / Pharmazie ► Medizinische Fachgebiete ► Pharmakologie / Pharmakotherapie
	Naturwissenschaften ► Biologie
Schlagworte	Artificial Intelligence and Machine Learning • Cloud Computing • Computational drug discovery (CDD) • drug design • HPC • In silico biomedicine • Personalized medicine • Precision medicine
ISBN-10	1-0716-3451-8 / 1071634518
ISBN-13	978-1-0716-3451-6 / 9781071634516
Zustand	Neuware