02588oam 2200577I 450 991078796340332120170822114836.00-429-19468-41-4822-9786-810.1201/b17979 (CKB)2670000000560197(EBL)1684509(SSID)ssj0001416960(PQKBManifestationID)11778137(PQKBTitleCode)TC0001416960(PQKBWorkID)11378060(PQKB)10908163(MiAaPQ)EBC1684509(OCoLC)900343699(CaSebORM)9781466561571(EXLCZ)99267000000056019720180331h20152015 uy 0engur|n|---|||||txtccrComputational approaches to protein dynamics from quantum to coarse-grained methods /edited by Monika Fuxreiter1st editionBoca Raton ;London :CRC Press,[2015]©20151 online resource (458 p.)Series in computational biophysicsDescription based upon print version of record.1-4987-0353-4 1-322-62927-7 1-4665-6157-2 Includes bibliographical references and index.section 1. Introduction -- section 2. Enzymatic catalysis : multiscale QM/MM calculations -- section 3. Protein motions : flexibility analysis -- section 4. Approaches to intrinsically disordered proteins -- section 5. Large-scale dynamics -- section 6. Ensemble methods.<P>This groundbreaking work addresses a crucial paradigm shift in structural molecular biology, illustrating how protein dynamics plays a central role in various functions, including enzymatic catalysis, protein-protein interactions, and the organization of complex assemblies. The book presents modern computational techniques for the characterization of proteins and their dynamic properties. The computational methods specifically address the dynamical aspects of protein functionalities, with special emphasis on the analysis of complex assemblies and intrinsically disordered proteins. </P>Series in computational biophysics.Protein engineeringProtein engineering.572/.633Fuxreiter Monika1969-FlBoTFGFlBoTFGBOOK9910787963403321Computational approaches to protein dynamics3849450UNINA04885nam 22006135 450 991104769080332120251010131535.03-031-96328-810.1007/978-3-031-96328-5(MiAaPQ)EBC32340631(Au-PeEL)EBL32340631(CKB)41603695800041(DE-He213)978-3-031-96328-5(EXLCZ)994160369580004120251010d2026 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine Learning Methods in Biomedical Field Computer-Aided Diagnostics, Healthcare and Biology Applications /edited by Ernesto Moya-Albor, Hiram Ponce, Jorge Brieva, Sandra L. Gomez-Coronel, Diego Renza Torres1st ed. 2026.Cham :Springer Nature Switzerland :Imprint: Springer,2026.1 online resource (620 pages)Studies in Computational Intelligence,1860-9503 ;12183-031-96327-X Edge-enhanced Knowledge Distillation System for Diabetic Retinopathy Lesions Computer-Aided Diagnosis -- Development of a Mobile Application for Dermatological Diagnosis Using Image Recognition: The DermAware Case Study -- Measuring the Diameter of Coronary Arteries via Skeletonization using a U-Net Architecture -- Deep Belief Networks for Efficient Macular Edema Detection in Retinal Fundus Images -- Automatic Spatial Localization of Coronary Stenosis in X-ray Angiograms Using Deep Learning -- Deep Learning for Pediatric Right Ventricle Segmentation in Echocardiography: Challenges and Strategies -- Challenges and Advances in Digital Processing of Fetal Phonocardiography Signal: A Review -- Implications of Model Loss and Configuration for Sparse Histological Segmentation -- Metaheuristic Strategy in Automatic Robotics Navigation for Patient Care in Hospitals -- Orthosis Control based on Electromyographic Signals and Machine Learning -- Internet of Medical Things Focused on Home Hospitalization for Diagnostic and Monitoring Support -- Automatic Robotics Medication Delivery System: The ANDIS Case Study -- Making Better Medical Decisions Using Machine Learning: A Bayesian Model -- Determining the Influence of Socioeconomic and Clinical Factors in Diabetes in the Mexican Population Using Machine Learning Techniques -- Sphonic: Development of a Mobile Application Using AI and AR for Learning Biomedical Concepts -- A Case Study on Pigmentation of Marine Species in Captivity and a Possible Application of AI to Marine Biomedical Research -- Ligand-based Virtual Screening Workflow for Antimalarial Repositioning from Known Drugs and Chemical Libraries -- Redefining Care: Hospitals’ Pivotal Role in Sustainable Development -- Cutting-Edge Technologies: Driving Sustainability in Hospital Operations.This book provides an in-depth exploration of machine learning techniques and their biomedical applications, particularly in developing intelligent computer-aided diagnostic systems, creating groundbreaking healthcare technologies, uncovering novel biological applications, and fostering sustainable health solutions. Integrating artificial intelligence, mathematical modeling, and emergent systems, this book highlights the profound impact of these advanced tools in not only enhancing problem-solving within the biomedical field but also in catalyzing the development of novel solutions. This book is a valuable resource for readers interested in understanding the revolutionary impact of novel machine learning methodologies on the biomedical landscape. Furthermore, it offers a blend of theory and practical applications for those interested in biomedical education and training, biology, medicine, and sustainable health development.Studies in Computational Intelligence,1860-9503 ;1218Computational intelligenceBiomedical engineeringArtificial intelligenceComputational IntelligenceBiomedical Engineering and BioengineeringArtificial IntelligenceComputational intelligence.Biomedical engineering.Artificial intelligence.Computational Intelligence.Biomedical Engineering and Bioengineering.Artificial Intelligence.006.3Moya-Albor Ernesto1769717Ponce Hiram1438319Brieva Jorge1769715Gomez-Coronel Sandra L1865371Torres Diego Renza1865372MiAaPQMiAaPQMiAaPQBOOK9911047690803321Machine Learning Methods in Biomedical Field4472431UNINA