A5067063386- Gene Regulatory Network Analysis
- Advanced Control Systems Optimization
- Model Reduction and Neural Networks
- Protein Structure and Dynamics
- Advanced Fluorescence Microscopy Techniques
- Time Series Analysis and Forecasting
- thermodynamics and calorimetric analyses
- Chronic Myeloid Leukemia Treatments
- Chronic Lymphocytic Leukemia Research
- Advanced Electron Microscopy Techniques and Applications
- Mathematical Biology Tumor Growth
- Mathematical and Theoretical Epidemiology and Ecology Models
- T-cell and B-cell Immunology
- Myeloproliferative Neoplasms: Diagnosis and Treatment
- Evolution and Genetic Dynamics
- Advanced X-ray Imaging Techniques
- Quinazolinone synthesis and applications
- Machine Learning in Healthcare
- Numerical methods for differential equations
- stochastic dynamics and bifurcation
- Mental Health Research Topics
- Nonlinear Dynamics and Pattern Formation
- Adaptive Control of Nonlinear Systems
- Machine Learning and ELM
- Evolutionary Game Theory and Cooperation
Kyoto University
2021-2025
Sysmex (Japan)
2020-2025
The University of Tokyo
2016-2022
Tokyo Institute of Technology
2015-2017
Osaka University
2017
RIKEN Center for Integrative Medical Sciences
2016
Tokyo University of Information Sciences
2016
ABSTRACT T cells play a pivotal role in the immune system's response to various conditions. They are activated by antigen‐presenting (APCs) via T‐cell surface receptors, resulting cytokine production and proliferation. These interactions occur through formation of immunological synapses. The advent imaging flow cytometry has enabled detailed statistical analyses these cellular interactions. However, dynamics receptors vitro stimulation yet receive attention, despite it being crucial aspect...
This study challenges strictly guaranteeing ``dissipativity'' of a dynamical system represented by neural networks learned from given time-series data. Dissipativity is crucial indicator for systems that generalizes stability and input-output stability, known to be valid across various including robotics, biological systems, molecular dynamics. By analytically proving the general solution nonlinear Kalman–Yakubovich–Popov (KYP) lemma, which necessary sufficient condition dissipativity, we...
Early evaluation of absorption, distribution, metabolism, and excretion(ADME) properties is crucial for streamlining drug development. Traditional in vivo/in vitro approaches are often expensive. Moreover, during lead optimization, these methods rely heavily on the expertise specialists, leading to efficiency challenges. Consequently, silico ADME prediction attracting increasing attention. However, existing face two major issues: a decline predictive performance caused by limited data lack...
Our previous study has proposed a positive quadratic system representation for molecular interaction in cell, including signal transduction pathway and gene regulatory network, also presented method finding invariant set depending on the initial state. Furthermore, we have shown that every rational system, which is used as mathematical model expressing biological behavior, can be approximately represented by singular perturbed system. This paper continues upon this research proposes new...
This paper proposes a new system model called positive quadratic for molecular interaction in cell, including signal transduction pathway and gene regulatory pathway. Although the whole network of these pathways is far more complex than simple chemical reactions, one features proposed that it can capture property as well positivity properties state variables with rather form. Based on this model, we derive sufficient condition stability sense Lyapunov, present method estimating invariant set...
Our previous study proposed a positive quadratic system representation for molecular interaction in cell, including signal transduction pathway and gene regulatory network, also presented method estimating invariant set depending on the initial state. As an extension towards wider applications of this approach, paper proposes called here singularly perturbed system, shows that every rational which is used as mathematical model expressing biological behavior, can be approximately represented...
In-memory computing (IMC) architectures mitigate the von Neumann bottleneck encountered in traditional deep learning accelerators. Its energy efficiency can realize learning-based edge applications. However, because IMC is implemented using analog circuits, inherent non-idealities hardware pose significant challenges. This paper presents physical neural networks (PNNs) for constructing models of IMC. PNNs address synaptic current's dependence on membrane potential, a challenge charge-domain...
This study challenges strictly guaranteeing ``dissipativity'' of a dynamical system represented by neural networks learned from given time-series data. Dissipativity is crucial indicator for systems that generalizes stability and input-output stability, known to be valid across various including robotics, biological systems, molecular dynamics. By analytically proving the general solution nonlinear Kalman-Yakubovich-Popov (KYP) lemma, which necessary sufficient condition dissipativity, we...
Single molecule localization microscopy (SMLM) relies on the detection of fluorescence emission from a single fluorophore molecule. Recently, several fluorescent dyes with spontaneous blinking have been reported. Last year, we reported near-infrared dye and high photostability. Here, present new orangefluorescent that exhibits based equilibrium between non-fluorescent forms. We also ascertained can be used to create super-resolution image cytoskeletal microtubules. In combination our last is...
Abstract Chronic myeloid leukemia (CML) is a myeloproliferative disorder caused by the BCR-ABL1 tyrosine kinase. Although ABL1 -specific kinase inhibitors (TKIs) including nilotinib have dramatically improved prognosis of patients with CML, TKI efficacy depends on individual patient. In this work, we found that different responses can be classified using estimated parameters our simple dynamical model two common laboratory findings. Furthermore, proposed method identified who failed to...
This paper proposes a new system representation called positive quadratic for analysis and synthesis of molecular interaction in cell, which includes signal transduction pathway gene expression transcriptional regulation. One the features proposed model is that it can capture property as well positivity properties state variables terms rather simple form. Based on this model, we derive sufficient condition stability origin sense Lyapunov, present method estimating an invariant set depending...
Many diseases, including cancer and chronic conditions, require extended treatment periods long-term strategies. Machine learning AI research focusing on electronic health records (EHRs) have emerged to address this need. Effective strategies involve more than capturing sequential changes in patient test values. It requires an explainable clinically interpretable model by the patient's internal state over time. In study, we propose "deep state-space analysis framework," using time-series...
Our previous study proposed a positive quadratic system representation for molecular interaction in cell, including signal transduction pathway and gene regulatory network, also presented method estimating invariant set depending on the initial state. As an extension towards wider applications of this approach, paper proposes called here singularly perturbed system, shows that every rational which is used as mathematical model expressing biological behavior, can be approximately represented...
Learning stable dynamics from observed time-series data is an essential problem in robotics, physical modeling, and systems biology. Many of these are represented as inputs-output system to communicate with the external environment. In this study, we focus on input-output systems, exhibiting robustness against unexpected stimuli noise. We propose a method learn nonlinear guaranteeing stability. Our proposed utilizes differentiable projection onto space satisfying Hamilton-Jacobi inequality...
Abstract Chronic myeloid leukemia (CML) is a myeloproliferative disorder caused by the BCR-ABL1 tyrosine kinase 1,2 . ABL1 -selective inhibitors (TKIs) including nilotinib have dramatically improved prognosis of patients with CML 3–7 The ultimate goal treatment likely to be TKI-free maintenance deep molecular response (DMR), which defined quantitative measurement transcripts on international scale (IS) 8 , and durable DMR prerequisite reach this 9 Thus, an algorithm enable early prediction...