LEADER 04051nam 22007575 450 001 9910746977103321 005 20231001143314.0 010 $a3-031-37196-8 024 7 $a10.1007/978-3-031-37196-7 035 $a(MiAaPQ)EBC30766348 035 $a(Au-PeEL)EBL30766348 035 $a(DE-He213)978-3-031-37196-7 035 $a(PPN)272914800 035 $a(CKB)28446169700041 035 $a(EXLCZ)9928446169700041 100 $a20231001d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning in Molecular Sciences /$fedited by Chen Qu, Hanchao Liu 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (323 pages) 225 1 $aChallenges and Advances in Computational Chemistry and Physics,$x2542-4483 ;$v36 311 08$aPrint version: Qu, Chen Machine Learning in Molecular Sciences Cham : Springer International Publishing AG,c2023 9783031371950 320 $aIncludes bibliographical references and index. 327 $aAn Introduction to Machine Learning in Molecular Sciences -- Graph Neural Networks for Molecules -- Voxelized representations of atomic systems for machine learning applications -- Development of exchange-correlation functionals assisted by machine learning -- Machine-Learning for Static and Dynamic Electronic Structure Theory -- Data Quality, Data Sampling and Data Fitting: A Tutorial Guide for Constructing Full-dimensional Accurate Potential Energy Surfaces (PESs) of Molecules and Reactions -- Machine Learning Applications in Chemical Kinetics and Thermochemistry -- Synthesize in A Smart Way: A Brief Introduction to Intelligence and Automation in Organic Synthesis -- Machine Learning for Protein Engineering. 330 $aMachine learning and artificial intelligence have propelled research across various molecular science disciplines thanks to the rapid progress in computing hardware, algorithms, and data accumulation. This book presents recent machine learning applications in the broad research field of molecular sciences. Written by an international group of renowned experts, this edited volume covers both the machine learning methodologies and state-of-the-art machine learning applications in a wide range of topics in molecular sciences, from electronic structure theory to nuclear dynamics of small molecules, to the design and synthesis of large organic and biological molecules. This book is a valuable resource for researchers and students interested in applying machine learning in the research of molecular sciences. 410 0$aChallenges and Advances in Computational Chemistry and Physics,$x2542-4483 ;$v36 606 $aMachine learning 606 $aArtificial intelligence 606 $aMolecules$xModels 606 $aChemistry, Physical and theoretical 606 $aChemistry$xData processing 606 $aBioinformatics 606 $aMachine Learning 606 $aArtificial Intelligence 606 $aMolecular Modelling 606 $aTheoretical Chemistry 606 $aComputational Chemistry 606 $aComputational and Systems Biology 615 0$aMachine learning. 615 0$aArtificial intelligence. 615 0$aMolecules$xModels. 615 0$aChemistry, Physical and theoretical. 615 0$aChemistry$xData processing. 615 0$aBioinformatics. 615 14$aMachine Learning. 615 24$aArtificial Intelligence. 615 24$aMolecular Modelling. 615 24$aTheoretical Chemistry. 615 24$aComputational Chemistry. 615 24$aComputational and Systems Biology. 676 $a006.31 676 $a006.31 702 $aQu$b Chen 702 $aLiu$b Hanchao 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910746977103321 996 $aMachine Learning in Molecular Sciences$93573372 997 $aUNINA