Title (J) field includes “構築”; 24 programs are found. (“Poster with Flash” presentations are double-counted.)
The search results are sorted by the start time.
Time | Paper ID | Title / Authors | Keywords | Topic code | Ack. number |
---|---|---|---|---|---|
Day 1 | PB114 | Construction of Sequence-based prediction model for high expression VHH clones using machine learning | VHH machine learning production | SY-67 | 733 |
Day 1 | PB160 | Cell-arrayed tissues consisting of hepatocytes and sinusoidal endothelial cells achieve high functionality | sinusoidal endothelial cells cell-arrayed tissues | SY-67 | 753 |
Day 1 | PA101 | Automatic construction of kinetic models from a small number of data using chemical reaction neural network | physics informed machine learning kinetics model data-driven | SY-61 | 216 |
Day 1 | PB136 | Construction of immunosensors using peptides with attached luminescent tags | immunosensor nanoluc coiled-coil | SY-67 | 427 |
Day 1 | PB172 | Basic study of high throughput screening system for phenol oxidase | Laccase High through screening Hydrogel Beads | SY-67 | 324 |
Day 1 | PB173 | Development of a high-throughput screening system for directional evolution of bond-forming enzymes | Hydrogel beads Cell-free protein synthesis High throughput screening | SY-67 | 192 |
Day 1 | DG106 | Thermodynamic modeling of critical point in nanopores validated with molecular dynamics simulation | Nanopores Supercritical Phase Equilibrium | SY-77 | 812 |
Day 1 | PA101 | Automatic construction of kinetic models from a small number of data using chemical reaction neural network | physics informed machine learning kinetics model data-driven | SY-61 | 216 |
Day 1 | DG115 | A new correlation between permittivity at the periphery of nanoparticles and Hansen Solubility Parameter | nanoparticle permittivity Hansen Solubility Paramter | SY-77 | 240 |
Day 1 | PB173 | Development of a high-throughput screening system for directional evolution of bond-forming enzymes | Hydrogel beads Cell-free protein synthesis High throughput screening | SY-67 | 192 |
Day 1 | PB114 | Construction of Sequence-based prediction model for high expression VHH clones using machine learning | VHH machine learning production | SY-67 | 733 |
Day 1 | PB136 | Construction of immunosensors using peptides with attached luminescent tags | immunosensor nanoluc coiled-coil | SY-67 | 427 |
Day 1 | PB160 | Cell-arrayed tissues consisting of hepatocytes and sinusoidal endothelial cells achieve high functionality | sinusoidal endothelial cells cell-arrayed tissues | SY-67 | 753 |
Day 1 | PB172 | Basic study of high throughput screening system for phenol oxidase | Laccase High through screening Hydrogel Beads | SY-67 | 324 |
Day 2 | DA205 | Development of single nozzle in multi-material 3D bioprinting for the construction of advanced cell | 3D extrusion printing multi-material printing numerical simulation | SY-70 | 514 |
Day 2 | DA206 | Development of a companion diagnostic model for the lymphoma therapy based on miRNAs as a biomarker panel | Companion diagnosis miRNA Biomarker panel | SY-70 | 191 |
Day 2 | DH208 | Machine-learning model for protease cleavage site prediction using 1990 peptides | Bioactive peptide Cleavage site Machine-learning | SY-71 | 337 |
Day 2 | AA208 | [Requested talk] Vision and Current Progress of the Foundation of Model Based CCUS Technology Evaluation | CCUS Model base Technology evaluation | HQ-12 | 482 |
Day 2 | BA217 | Reliability Assessment for a Multivariate Model from Closed-loop Data Based on the SPS Method | Finite-sample data Closed-loop identification Multivariate process | SY-65 | 108 |
Day 2 | CA220 | A simplified approach for estimating water contact angles by using molecular dynamics simulations | molecular dynamics poly(2-methoxyethyl acrylate) water contact angle | SY-51 | 796 |
Day 2 | CB221 | Modeling of solute elution behavior in supercritical fluid chromatography based on distribution coefficient | supercritical CO2 ethanol partition coefficient | SY-73 | 740 |
Day 3 | PA313 | Study and analysis of clustering methods for high-dimensional "Energy Data" for building power forecasting models | energy system machine learning data science | ST-23 | 544 |
Day 3 | PA320 | Prediction of an in-Plane Anomalous Current Using Numerical Simulation and Machine Learning | Modeling Machine learning Current distribution | ST-23 | 100 |
Day 3 | DC319 | [Featured presentation] Development of digital twin of the bulk single crystal growth of Si by using PINNs (Physics Informed Neural Networks) | Digital twin Machine learning Physics Informed Neural Networks | ST-21 | 396 |
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SCEJ 53rd Autumn Meeting (Nagano, 2022)