Info
Biomolecular Data Science-in Honor of Professor Philip E. Bourne
| Biomolecular Data Science-in Honor of Professor Philip E. Bourne |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2023 |
| Descrizione fisica | 1 online resource (232 p.) |
| Soggetto topico |
Biology, life sciences
Research & information: general |
| Soggetto non controllato |
amino acids
and graph neural network APOBEC basal cells binding energy bioinformatics biological macromolecules carbohydrates cell-type composition census tract ciliated cells CRISPR/Cas9 cryogenic electron microscopy cryogenic electron tomography data science deep learning DNA DNA sequencing drug discovery drug repositioning drugs of abuse electron crystallography electronic health records entropy FAIR function annotation functional families genome editing goblet cells graph neural network immune response to smoking kernel classifiers kernel method KinBase classification KinFams large language models ligand binding sites lung cancers machine learning macromolecular crystallography metagenomics micro-electron diffraction MSA mutational signatures n/a nuclear magnetic resonance spectroscopy nucleic acids off-targets Open Access pharmacovigilance Philip Bourne prioritization algorithm Protein Data Bank protein database protein kinases proteins quantum machine learning quantum metric learning reaction template read classification real-world evidence recurrent neural network retrosynthesis RNA search tool SHAP values small-molecule ligands smoking social determinants of health social media specificity annotation structural bioinformatics structure-based drug discovery variability Worldwide Protein Data Bank |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911053031203321 |
| MDPI - Multidisciplinary Digital Publishing Institute, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Quantum Information and Symmetry
| Quantum Information and Symmetry |
| Autore | Leonski Wiesław |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (104 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
??-symmetry
associative memory attractor BaGe3 superconductor complex Ginzburg-Landau equation cross-Kerr nonlinearity entanglement fermion quartets four-fermion attraction Mathieu functions Meissner effect negativity nonlinear oscillator nonlinearly coupled oscillators open system PT symmetry quantum control quantum entanglement quantum machine learning quantum properties s-wave symmetry Eliashberg formalism soliton stability analysis superconductivity thermodynamic properties time-dependent driving fields |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557134603321 |
Leonski Wiesław
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||