Poster No. |
Title |
First Author |
Affiliation |
(1)分子認識と分子計算 (Molecular recognition and molecular modeling) |
*P1-01 |
Development status of ABINIT-MP program in 2019 |
Yuji Mochizuki |
Rikkyo University |
P1-02 |
Prediction of log P for cyclodextrin-drug complexes using computational chemistry |
Masao Fujisawa |
kindai University |
*P1-03 |
Binding Energy Calculation of Protein-Peptide Complex Using Unbiased MD Simulations and MSM Analysis |
Hiroaki Hata |
Tokyo Institute of Technology |
*P1-04 |
Interaction Analyses between Calcite/Apatite and Peptides by Fragment Molecular Orbital Method |
Ryo Hatada |
Rikkyo University |
*P1-05 |
Fragment Molecular Orbital Method Applied to Factor Xa Inhibitors |
Kazufumi Ohkawa |
Asahi Kasei Pharma Corporation |
P1-06 |
Influence of phosphorylation on structure and electronic states of tau-protein: MD and ab initio fragment MO simulation |
Katsumi Suzuki |
Toyohashi University of Technology |
P1-07 |
Determination of stable protonation states of amino acid residues in metalloproteinase-inhibitor complex: ab initio molecular simulations |
Takuya Ezawa |
Toyohashi University of Technology |
*P1-08 |
Regulation mechanism of agonistic / antagonistic activities of vitamin D receptor analyzed by generalized ensemble method |
Takafumi Kudo |
Yokohama City University |
P1-09 |
The inhibition mechanism of HSP90 function by a medium molecular drug |
Lisa Matsukura |
KINDAI Univ. |
P1-10 |
Molecular Dynamics Simulations of HIV Tat protein and Amyloid-β peptides |
Kazumi Omata |
National Center for Global Health and Medicine |
P1-11 |
*Cancelled Dynamics of the transmembrane region of β-secretase in raft environment |
Kaori Yanagino |
KINDAI Univ. |
*P1-12 |
Development of the CHARMM force field for Cyclosporine A and application to molecular dynamics simulations using a membrane-water system |
Tsutomu Yamane |
Yokohama City University |
P1-13 |
Analyzing intramolecular interaction using canonical Kohn-Sham molecular orbital calculation in protein |
Toshiyuki Hirano |
The University of Tokyo |
P1-14 |
Homology Modeling of the Protein Structure in the Solution using Deep Auto Encoder and Trajectories of the Long-time Molecular Dynamics Simulation of Template Proteins |
Masaya Furue |
KINDAI Univ. |
P1-15 |
Cluster Analysis of Amino Acid by Inter-Fragment Interaction Energy Using Non-Metric Multidimensional Scaling Method |
Yuki Abe |
Nihon University |
P1-16 |
Prediction of Inter-Fragment Interaction Energies in Janus Kinase by Neural Network with Geometrical Information on Ligand and Residues |
Shusuke Tokutomi |
Kobe University |
P1-17 |
Specific interactions between retinoic acid receptor-related orphan receptor and its ligands: molecular dynamics and ab initio fragment molecular orbital calculations |
Shusuke Suzuki |
Toyohashi University of Technology |
P1-18 |
Validation of conformer generation in solution using NMR data |
Paul Hawkins |
OpenEye Scientific |
P1-19 |
Molecular simulations on aggregation mechanism
of microtubule associated Tau proteins |
Riku Sato |
Toyohashi University of Technology |
*P1-20 |
Selectivity of phosphodiesterase-10A inhibitor for phosphodiesterase family elucidated by free energy perturbation approach |
Toru Ekimoto |
Yokohama City University |
*P1-21 |
De Novo Binding Prediction using gREST |
Suyong Re |
RIKEN BDR |
*P1-22 |
A binding free energy calculation method along a modified thermodynamic path which avoids exhaustive enumeration of multiple protein-ligand poses |
Yoshitake Sakae |
Research Organization for Information Science and Technology |
P1-23 |
Improvement of Carbohydrate Force Field for Molecular Dynamics |
Makoto Ikejo |
Kobe University |
P1-24 |
Systematic construction of the cosolvents sets for cosolvent MD (CMD) with the large-scale computation |
Keisuke Yanagisawa |
The University of Tokyo |
P1-25 |
A Method for Comparing Structural Ensembles: Applications to Molecular Dynamics Trajectory Data |
Takashi Amisaki |
Tottori University |
P1-26 |
Fast prediction of binding hotspots on a peptide ligand in complex by Digital Annealer |
Yoshiaki Tanida |
Fujitsu Laboratories Ltd. |
P1-27 |
Advanced methods to predict the property of cyclic peptides: reproduction of actual conformations |
Sakiko Mori |
Fujitsu Ltd |
*P1-28 |
Advanced methods to predict the property of cyclic peptides: exhaustive and efficient conformation search |
Kentaro Takai |
Fujitsu Ltd. |
*P1-29 |
Conformational Changes and Interactions of Calcium Ion Signal Transfer Protein Calmodulin and Calmodulin-binding Domain by Multi-scale and Docking Simulation |
Hiromitsu Shimoyama |
Kitasato University |
*P1-30 |
Autoencoder-based Analyses of Dynamic Allostery on Proteins by Regulator Binding |
Yuko Tsuchiya |
AIRC, AIST |
P1-31 |
Molecular dynamics simulation of drug efflux in multidrug ABC transporter |
Takumi Someya |
Yokohama City University |
P1-32 |
Characterization of water-molecule interaction based on fragment molecular orbital method |
Hiromichi Tsurui |
Juntendo University |
*P1-33 |
Computational approaches to drug-receptor binding kinetics |
Osamu Ichihara |
Schrödinger K.K. |
P1-34 |
Investigation of stabilization mechanism of amorphous solid dispersion by fragment molecular orbital calculation |
Xiaohan Ma |
Chiba University |
P1-35 |
Interaction analysis of HIV protease-inhibitor complex by fragment molecular orbital method |
Hirofumi FUJI |
Kindai University |
P1-36 |
Assessment of a simple pKa estimation scheme for drug molecules by quantum chemical calculations |
Takao Otsuka |
RIKEN BDR |
P1-37 |
Is hydrophobic group in osmolyte hydrophilic? (2):
A time series interaction energy decomposition analysis study by means of effective fragment potential molecular dynamics simulation |
Tamon Funakura |
Chuo University |
P1-38 |
Artificial ion channels studies by All-atom molecular dynamics simulations |
Takahiro Osamura |
Yokohama City University |
*P1-39 |
Thermodynamic, kinetic and computational analyses of the recognition mechanism of a flexible protein antigen by an antibody |
Ikuho KANEDA |
The University of Tokyo |
*P1-40 |
Ligand Binding Mechanism of an Enzyme Studied by Binding Free Energy Analyses for Mutants of the Protein |
Yoshiharu Mori |
Kitasato University |
P1-41 |
Conformation analysis of hydrogen atoms around ligand-binding pocket based on quantum chemical calculation |
Chiduru Watanabe |
RIKEN BDR |
P1-42 |
In vitro screening systems for influenza virus RNA polymerase inhibitors |
Miho Kobayashi |
Gifu University |
P1-43 |
Can Cryptic Binding Sites Be Characterised by Voids, Pocket Detection, and Molecular Dynamics? |
Shinji Iida |
Technology Research Association for Next-Generation Natural Products Chemistry |
P1-44 |
Computational study on conformational transition of protein binding pocket upon ligand binding |
Noriaki Okimoto |
RIKEN |
P1-45 |
The computational study of cycloaddition with Rhodium catalyst |
Watanabe Kazuki |
Osaka University |
P1-46 |
Analysis of target DNA recognition mechanism by Nrf2-small Maf heterodimer using fragment molecular orbital (FMO) method |
Toru Sengoku |
Yokohama City University |
*P1-47 |
Interaction Analysis between HEL and HyHEL10 by Fragment Orbital Method |
Norihito Kawashita |
Kindai University |
P1-48 |
Combined computational and experimental study on the binding mechanism of RNA aptamer to human Immunoglobulin G |
Keisuke Masukawa |
Nihon University |
P1-49 |
Investigation of drug resistance acquisition mechanism of influenza cap-dependent endonuclease against Baloxavir marboxil by molecular dynamics simulation |
Ryunosuke Yoshino |
University of Tsukuba |
(2)インシリコ創薬 (In silico drug discovery) |
P2-01 |
Suitable chemical library for academic researchers in Japan |
Hirotatsu Kojima |
The University of Tokyo |
*P2-02 |
Classification QSAR with Vanishing Kernels and a single parameter |
Francois Berenger |
Kyushu Institute of Technology |
P2-03 |
Automated Assessment of Binding Affinity via Free Energy Perturbation |
Giovanna Tedesco |
Cresset |
*P2-04 |
Discovery of novel selective CSF-1R Inhibitors with de novo drug design of FBDD and MD simulation |
Mutsuyo Wada |
Fujitsu Ltd. |
P2-05 |
Predicting pKa Using a Combination of Quantum and Machine Learning Methods |
Peter Hunt |
Optibrium Ltd. |
*P2-06 |
An in silico approach for integrating phenotypic and target-based approaches in drug discovery |
Hiroaki Iwata |
Kyoto University |
*P2-07 |
Analysis of subtype selectivity in estrogen-like compounds |
Yuya Seki |
Hoshi University |
P2-08 |
FMO analysis of binding property of estrogen receptor and β selective ligands |
Tsukasa Kato |
Hoshi University |
P2-09 |
High-speed geometry optimization for protein active site with the fragment molecular orbital method |
Koji Okuwaki |
Hoshi University |
*P2-10 |
Development of FMODB for analyzing protein-ligand interactions in 2019 |
Daisuke Takaya |
RIKEN BDR |
P2-11 |
Analysis of FMO-based intramolecular interaction energies for structural stability of apo structures |
Kikuko Kamisaka |
RIKEN BDR |
P2-12 |
Transformation-driven Molecule Generation as Another Benchmarking Model |
Ryuichiro Hara |
Lifematics, Inc. |
*P2-13 |
Inter-lobe motion of EGFR kinase: Determinants of structural variation in the crystal structures |
Kei Moritsugu |
Yokohama City University |
P2-14 |
UTOMATED PREDICTIVE MODELING OF BIOACTIVES |
Toshikazu DEWA |
Elsevier Japan KK |
*P2-15 |
Insights into the Mechanism of NA-I117V-Mediated Oseltamivir Resistance in H5N1 Avian Influenza Virus |
Mohini Yadav |
Chiba Institute of Technology |
P2-16 |
Biotherapeutics modeling and developability assessment by Bio-MOE |
Kentaro Kamiya |
MOLSIS Inc. |
P2-17 |
Design and Implementation of an Easy to Use High Performance Comput ing Service System for Large Scale Molecular Dynamics Simulations |
Yoshio Nakao |
Fujitsu Limited |
P2-18 |
Development of a Library Containing Billions of Virtual Compounds |
Aki Hasegawa |
RIKEN BDR |
(3)構造生物学 (Structural biology) |
*P3-01 |
IsdH: mechanism of action and novel antibacterial strategies |
Sandra Valenciano Bellido |
The University of Tokyo |
*P3-02 |
Effect of binning size of XFEL Diffraction Patterns on the resolution of reconstructed 3D-molecular structure |
Miki Nakano |
RIKEN, Center for Computational Science |
P3-03 |
Mail-in X-ray Diffraction Data Collection for High-throughput Crystal Structure Determination |
Hideaki Niwa |
RIKEN BDR |
P3-04 |
Structural basis for the binding of histo-blood group antigens to the norovirus capsid protein |
Tomomi Kimura-Someya |
RIKEN BDR |
P3-05 |
Crystal structures of GAS41 YEATS domain in complex with acylated histone peptides |
Masaki Kikuchi |
RIKEN BDR |
P3-06 |
Crystal structure of the Hepatitis B virus core protein complexed with a novel drug candidate |
Wakana Iwasaki |
RIKEN BDR, RIKEN Center for Life Science Technologies |
*P3-07 |
Structural insights into cyclic peptides in complex with target proteins |
Satoshi Sogabe |
Axcelead Drug Discovery Partners, Inc. |
P3-08 |
Prospects for applying in-silico crystal structure prediction to drug development |
Okimasa Okada |
Mitsubishi Tanabe Pharma Corp. |
*P3-09 |
Influence Analysis of Amino Acid Residues on Protein Functions using Attention-based Neural Networks |
Takato Kameyama |
Waseda University |
P3-10 |
A Novel Inhibitor Stabilizes the Inactive Conformation of MAPK-interacting Kinase 1 |
Yumi Matsui |
Daiichi Sankyo RD Novare Co., Ltd. |
P3-11 |
Structural changes in Cl- pump rhodopsin by time-resolved serial femtosecond crystallography |
Toshiaki Hosaka |
RIKEN BDR |
P3-12 |
Crystal Structure of EGFR T790M/C797S in complex with Brigatinib |
Mutsuko Kukimoto-Niino |
RIKEN BDR |
P3-13 |
Analyses based on statistical thermodynamics for large difference between thermophilic rhodopsin and xanthorhodopsin in terms of thermostability |
Satoshi Yasuda |
Chiba University |
P3-14 |
Analysis by an Accelerated Quantum Chemical Molecular Dynamics Method for the 8-oxoG added DNA Structure |
Ai Suzuki |
Tohoku University |
*P3-15 |
Validation of protein structure from low resolution density map using Deep Learning |
Miwa Sato |
Mitsui Knowledge Industry Co., LTD |
*P3-16 |
Automated X-ray crystallographical inhibitor screening against an insect ecdysteroidogenic enzyme, Noppera-bo |
Kotaro Koiwai |
Institute of Materials Structure Science, High Energy Accelerator Research Organization |
P3-17 |
Development of the screening system to create GPCR mutants stabilized in active states |
Ryosuke Nakano |
Chiba University |
P3-18 |
Identification of a conserved allosteric site in Heme-copper oxygen reductase |
Yuya Nishida |
National Cerebral and Cardiovascular Center Research Institute |
P3-19 |
The influence of cosolvent on thermal stability of membrane proteins |
Kazuki Kazama |
Chiba University |
(4)バイオインフォマティクスとその医学応用 (Bioinformatics and its applications in medicine) |
*P4-01 |
Identification of a biomarker for disease progression in heart failure using single-cell RNA sequencing data |
Momoko Hamano |
Kyushu Institute of Technology |
P4-02 |
An importance of polyamine metabolism regulated by cancer stem cells highlighted by our trans-omics method |
Jun Koseki |
Osaka University |
*P4-03 |
Interpreting Japanese GWAS Results on Multi-Omics Drug Target Validation Platform |
Wirawit Chaochaisit |
Genesis Healthcare Co. |
*P4-04 |
Development of Integrated Database “dbTMM” for stratification of cohort participant toward drug development |
Satoshi Nagaie |
Tohoku Medical Megabank Organization, Tohoku University |
*P4-05 |
Development of phenotyping algorithms for hypertensive disorders of pregnancy (HDP) for precise stratification toward drug development |
Satoshi Mizuno |
Tohoku Medical Megabank Organization, Tohoku University |
(5)医薬品研究とADMET (Information and computational approach for drug design and ADMET study) |
P5-01 |
Development of a Liver Toxicity Informatics System (AMED project) |
Hiroshi Yamada |
NIBIOHN |
P5-02 |
DILI-cSEARCH: a DILI database for drug safety assessment |
Yoshinobu Igarashi |
NIBIOHN |
P5-03 |
Ontology-based Toxic Process Interpretable Knowledge System for Drug-Induced Liver Injury |
Yuki Yamagata |
NIBIOHN |
P5-04 |
Development of an informatics system for predicting cardiotoxicity: 6. Update of the AMED cardiotoxicity database and the hERG prediction model with additional assays for the compounds selected by active learning |
Tomohiro Sato |
RIKEN BDR |
P5-05 |
Development of an informatics system for predicting cardiotoxicity: 7. hERG prediction model based on docking simulation and interaction descriptors with hERG residues |
Hitomi Yuki |
RIKEN BDR |
P5-06 |
Development of a pharmacokinetics prediction system using multiscale integrated modeling: 13. Development of DruMAP, Drug Metabolism and pharmacokinetics Analysis Platform |
Hitoshi Kawashima |
NIBIOHN |
P5-07 |
Development of a pharmacokinetics prediction system using multiscale integrated modeling:
14. In silico three-class predictor of human intestinal absorption with Caco-2 permeability and dried-DMSO solubility |
Tsuyoshi Esaki |
Shiga University |
P5-08 |
Development of a pharmacokinetics prediction system using multiscale integrated modeling:15. Development of an in silico prediction system of human renal excretion and clearance from chemical structure information |
Reiko Watanabe |
NIBIOHN |
P5-09 |
Development of a pharmacokinetics prediction system using multiscale integrated modeling:16. Prediction of sites of metabolism of drug by CYP2C9 by molecular simulation |
Hiroaki Saito |
RIKEN BDR |
P5-10 |
Development of a pharmacokinetics prediction system using multiscale integrated modeling:
17. Accuracy and performance of the MDGRAPE-4A system |
Gentaro Morimoto |
RIKEN BDR |
P5-11 |
QSAR model to predict Kp,uu,brain with small-scale dataset -incorporating predicted values of related parameters- |
Yuki Umemori |
Teijin Pharma Limited. |
*P5-12 |
Cluster Gauss-Newton method for efficiently estimating multiple sets of parameters: Application to Physiologically-Based PharmacoKinetic models |
Ken Hayami |
National Institute of Informatics and Department of Informatics,
School of Multidisciplinary Sciences,
SOKENDAI |
*P5-13 |
Prediction of Health Effects of Food Peptides and Elucidation of The Mode-of-action Using Multi-task Graph Convolutional Neural Networks |
Itsuki Fukunaga |
Kyushu Institute of Technology |
P5-14 |
Case study of machine learning for drug metabolism and pharmacokinetics properties |
Kazuyoshi Yoshii |
Zeria Pharmaceutical Co., Ltd |
*P5-15 |
Free Energy Landscapes of Cyclic Hexapeptide Diastereomers by Multicanonical Molecular Dynamics Simulations |
Satoshi Ono |
Mitsubishi Tanabe Pharma Corporation |
(6) 創薬・医療AI (AI for drug discovery and medical treatment) |
*P6-01 |
Interpretable Reaction Prediction using Graph Convolutional Networks |
Shoichi Ishida |
Kyoto University |
P6-02 |
Applicable Machine Learning Method to Predict Site of Metabolism ~Comparison of Various Methods Using In-house Compounds ~ |
Katsunori Sasahara |
Otsuka Pharmaceutical Co., Ltd. |
P6-03 |
In Silico Modeling to Predict Drug-induced Phospholipidosis Based on Machine Learning Approach |
Yui Migura |
Otsuka Pharmaceutical Co., Ltd. |
P6-04 |
In silico models for predicting hepatotoxicity and renal toxicity based on HESS database |
Tatsuya Ochibe |
Nagoya City University |
P6-05 |
Prediction of pharmacological activities from chemical structures with graph convolutional neural network |
Miyuki Sakai |
Kyoto University |
P6-06 |
Design of Selective GPCR Antagonists with a desired Pharmacophore using Deep Reinforcement Learning |
Chisato Kanai |
INTAGE Healthcare, Inc. |
*P6-07 |
High-performance predication model utilizing a novel deep learning-based QSAR analysis using Deep Snap and the Tox 21 10k library |
Yasunari Matsuzaka |
Meiji Pharmaceutical University |
*P6-08 |
Development of AI-aided hit compound finding/profiling system for imaging-based high content screening |
Hiroki Terauchi |
Eisai Co., Ltd. |
*P6-09 |
Computational drug target prediction using PU learning approach |
Kazuto Nakata |
NEC Corporation |
*P6-10 |
Meta-modeling for Optimization in QSAR Modeling Processes and Application to Estrogen Receptor Agonist Activity Prediction |
Kota Kurosaki |
Meiji Pharmaceutical University |
*P6-11 |
Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm |
Michio Iwata |
Kyushu Institute of Technology |
P6-12 |
3D-RISM-AI: A machine learning approach to predict protein-ligand binding affinity using 3D-RISM |
Kazu Osaki |
Yokohama City University |
*P6-13 |
Deep Learning-aided Label-free, Real-time and Time-lapse Cell Visualization System that Enables Live/Dead Cell Discrimination and Counting |
Tamio Mizukami |
Nagahama Institute of Bio-Science and Technology, Frontier Pharma Inc. |
P6-14 |
Deep-learning of cancer stem cell morphology |
Tomoyasu Sugiyama |
Tokyo University of Technology |
P6-15 |
Study on adverse outcome pathways related to drug-induced rhabdomyolysis using machine learning |
Shunichi Sasaki |
Meiji Pharmaceutical University |
P6-16 |
A New Scoring Function for Protein Structure Assessment Based on the Hydration Structure Information |
Yasuomi Kiyota |
Kitasato University |
P6-17 |
Development of in silico prediction model for skin sensitization using the alternative tests dataset |
Masaharu Suzuki |
Nagoya City University |
*P6-18 |
*This abstract was published on October 22. Focused Library Generative Model for GPCR Family |
Gen Li |
Tokyo Institute of Technology |
*P6-19 |
Prediction of G4MP2-level Molecular Properties from DFT-level Structures Using Deep Tensor Neural Network |
Mingda Wan |
Tokyo Institute of Technology |
(7)創薬データサイエンス (Drug Discovery Data Science) |
P7-01 |
Data set selection in deep learning based CYP3A4 binding mode prediction |
Atsuko Sato |
Tokyo Institute of Technology |
P7-02 |
An Approach to Investigate Disease Mechanisms by FAERS Data Mining |
Yoshito Ohya |
Kyowa Kirin Co., Ltd. |
*P7-03 |
Predicting drug indications and therapeutic target modules based on disease similarity by interpretable machine learning models |
Ryusuke Sawada |
Kyushu Institute of Technology |
P7-04 |
A Method for Systematic Analog Searching Using the Mega SAR Matrix Database |
Atsushi Yoshimori |
Institute for Theoretical Medicine, Inc. |
*P7-05 |
The Multiple Representation of Protein Sequence Motifs Using Sequence Binary Decision Diagrams |
Hiroaki Kato |
National Institute of Technology,
Hiroshima College |
P7-06 |
Development of preventive drugs against oxaliplatin-induced peripheral neuropathy using large-scale medical database |
Takahiro Niimura |
Tokushima University |
P7-07 |
Kampo Drug Repositioning and Compound Mixture Analyses using Multi-task Graph Convolutional Neural Networks |
Akihiro Douke |
Kyushu Institute of Technology |
*P7-08 |
Prediction of Compound-Protein Interactions and Visualization Based on Graph Convolutional Networks |
Marie Ikeguchi |
Kyoto University |
*P7-09 |
Development of data curation and integration protocol for the chemical library in early drug discovery |
Yugo Shimizu |
Keio University |
*P7-10 |
Clustering therapeutic drugs based on similarities of indications and side effects reported in public database |
Ryutaro Shinkawa |
Mie University School of Medicine |
*P7-11 |
Drug Discovery Raid Battle 2018: an open challenge to discover PD-1/PD-L1 small-molecule inhibitors |
Kazuki Yamamoto |
Isotope Science Center, University of Tokyo |
*P7-12 |
Automatic Reading of Tables and Figures in Scientific Papers |
Hiroyuki Shindo |
Nara Institute of Science and Technology |
(8)分子ロボティクス (Molecular Robotics) |
*P8-01 |
Functionalization of liposomes using artificially evolved peptides against lipid membranes |
Takuya Terai |
Saitama University |
P8-02 |
Experimental Investigation of DNA Generation Circuits toward Molecular Robot Control |
Ken Komiya |
Tokyo Institute of Technology |
*P8-03 |
A database to store design information of DNA nanostructure |
Ibuki Kawamata |
Tohoku University |
P8-04 |
Haptic Interactive Virtual Reality Simulation on Biomolecules |
Arif Pramudwiatmoko |
Tokyo Institute of Technology |
*P8-05 |
Molecular dynamics study on breakage of photoresponsive DNA |
Ryuzo Azuma |
Tokyo Institute of Technology |
P8-06 |
Formulating R&D Guidelines for Molecular Robotics |
Naoto Kawahara |
Kyushu University |
*P8-07 |
Programmable DNA reaction-diffusion system for a Voronoi pattern formation in hydrogel |
Keita Abe |
Tohoku University |
*P8-08 |
Reconstitution of kinesin-based transport complex using DNA origami |
Kodai Fukumoto |
Institute for Protein Research, Osaka University |
P8-09 |
Gold nanoparticle-loaded DNA hydrogel microparticles for catalysis in aqueous phase |
Daisuke Ishikawa |
Tokyo Metropolitan University |
*P8-10 |
Negating Latency for Fluid Interactions with Biomolecules in a Client/Server VR System |
Gregory Gutmann |
Tokyo Institute of Technology |
P8-11 |
Implementing Real Time Molecular Dynamics with in Haptic Molecular Modeling Environment |
Yutaka Ueno |
AIST |
P8-12 |
Design and optimization of a branching structure for dendric DNA structure |
Takayuki Kobayashi |
Kansai University |
(9)レギュラトリサイエンス (Regulatory Sciences) |
P9-01 |
Attempts to establish the in vitro BBB model suitable for drug development
― Comparative study of 2D rat model, 2D human cell line model, and 3D human cell line model― |
Kimiko Kitamura |
National Institute of Health Science |
P9-02 |
Small Compound-based Direct Reprogramming Using Large-scale Omics Data |
Toru Nakamura |
Kyushu Institute of Technology |
P9-03 |
CNN can detect the sensitivity for radioresistance of cancer cells |
Masamitsu Konno |
Osaka University |
P9-04 |
Media analysis of emerging sciences and technologies in Japan- implications for Molecular Robotics |
Ryuma Shineha |
Seijo University |
P9-05 |
Potential concerns regarding designated ingredient containing food of Food Sanitation Law of Japan |
Mitsuo Saito |
Institute for Health Vigilance |
P9-06 |
Multi-functional analysis for applicability evaluation of human iPS cell-derived hepatocytes to DILI assays |
Shinichiro Horiuchi |
National Institute of Health Sciences |
P9-07 |
Evaluation of Cell Culture Profiling System with HepG2 Cell Culture Using Microphysiological Systems |
Ryuya Fujii |
National Institute of Health Sciences |
(10)上記に属さない先進的研究(Emerging new technology) |
P10-01 |
Evidence for the utility of human induced pluripotent stem cell-derived neurons in safety pharmacology-fact data indicating the achievement of network activities |
Kanako Takahashi |
National Institute of Health Sciences |
P10-02 |
Development of automatic analysis and quality control of mass spectrometry-based metabolome data |
Yasuko Aita |
Tokyo Medical University |
P10-03 |
CASLcDB: Comprehensive Annotation of human SLc transporters DataBase |
Hafumi Nishi |
Tohoku University |
P10-04 |
Approach of the global QSAR modeling for fish acute toxicity and the future issue for improvement |
Koji Jojima |
Chemicals Evaluation and Research Institute, Japan |
P10-05 |
Attempt to Construct a Primitive Metabolic Network in Deep Hydrothermal Vent Environments |
Ryo Hamano |
Kobe University |
P10-06 |
Computational Direct Reprogramming by Integrating Genome, Transcriptome and Epigenome Data |
Ryohei Eguchi |
Kyushu Institute of Technology |