Kazunari Kaizu

ORCID: 0000-0003-1982-538X
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About
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Research Areas
  • Gene Regulatory Network Analysis
  • Advanced Fluorescence Microscopy Techniques
  • Bioinformatics and Genomic Networks
  • Microbial Metabolic Engineering and Bioproduction
  • Genomics and Chromatin Dynamics
  • Receptor Mechanisms and Signaling
  • Diffusion and Search Dynamics
  • Single-cell and spatial transcriptomics
  • thermodynamics and calorimetric analyses
  • Cellular Automata and Applications
  • Advanced Biosensing Techniques and Applications
  • Fungal and yeast genetics research
  • Gene expression and cancer classification
  • Bacterial Genetics and Biotechnology
  • Mass Spectrometry Techniques and Applications
  • Molecular Communication and Nanonetworks
  • DNA Repair Mechanisms
  • Cell Image Analysis Techniques
  • Evolution and Genetic Dynamics
  • Light effects on plants
  • Protein Interaction Studies and Fluorescence Analysis
  • Quantum-Dot Cellular Automata
  • Phytoestrogen effects and research
  • Mechanical and Optical Resonators
  • Protein Kinase Regulation and GTPase Signaling

RIKEN Center for Biosystems Dynamics Research
2018-2025

National Institutes of Natural Sciences
2025

RIKEN
2012-2023

Quantitative Biology Center
2012-2016

RIKEN BioResource Research Center
2014

Keio University
2003-2010

Sony Computer Science Laboratories
2010

Systems Biology Institute
2010

Keio University Shonan Fujisawa
2007

Genome information, which is three-dimensionally organized within cells as chromatin, searched and read by various proteins for diverse cell functions. Although how the protein factors find their targets remains unclear, dynamic flexible nature of chromatin likely crucial. Using a combined approach fluorescence correlation spectroscopy, single-nucleosome imaging, Monte Carlo computer simulations, we demonstrate local dynamics in living mammalian cells. We show that similar to interphase...

10.1016/j.celrep.2012.11.008 article EN cc-by-nc-nd Cell Reports 2012-12-01

In eukaryotic cells, highly condensed inactive/silenced chromatin has long been called "heterochromatin." However, recent research suggests that such regions are in fact not fully transcriptionally silent and there exists only a moderate access barrier to heterochromatin. To further investigate this issue, it is critical elucidate the physical properties of heterochromatin as its total density live cells. Here, using orientation-independent differential interference contrast (OI-DIC)...

10.1091/mbc.e17-06-0359 article EN cc-by-nc-sa Molecular Biology of the Cell 2017-08-23

A string of nucleosomes, where genomic DNA is wrapped around histones, organized in the cell as chromatin, ranging from euchromatin to heterochromatin, with distinct genome functions. Understanding physical differences between and heterochromatin crucial, yet specific labeling methods living cells remain limited. Here, we have developed replication-dependent histone (Repli-Histo) mark nucleosomes based on replication timing. Using this approach, investigated local nucleosome motion four...

10.1126/sciadv.adu8400 article EN cc-by-nc Science Advances 2025-03-28

Abstract Motivation: Many important problems in cell biology require the dense nonlinear interactions between functional modules to be considered. The importance of computer simulation understanding cellular processes is now widely accepted, and a variety algorithms useful for studying certain subsystems have been designed. these are already used, large number models constructed on existing formalisms available. A significant computational challenge how we can integrate such sub-cellular...

10.1093/bioinformatics/btg442 article EN Bioinformatics 2004-01-22

Genetic information, which is stored in the long strand of genomic DNA as chromatin, must be scanned and read out by various transcription factors. First, gene-specific factors, are relatively small (∼50 kDa), scan genome bind regulatory elements. Such factors then recruit general Mediators, RNA polymerases, nucleosome remodellers, histone modifiers, most large protein complexes 1–3 MDa size. Here, we propose a new model for functional significance size (or complexes) gene regulation...

10.1088/0953-8984/27/6/064116 article EN cc-by Journal of Physics Condensed Matter 2015-01-07

Cytoplasm contains a large number of macromolecules at extremely high densities. How this striking nature intracellular milieu called macromolecular crowding affects signaling remains uncharacterized. Here, we examined the effect on ERK MAPK phosphorylation by MEK MAPKK. Addition polyethylene glycol-6000 (PEG-6000) as crowder to mimic environments, elicited biphasic response overall rate. Furthermore, probability processive (processivity) tyrosine and threonine residues within activation...

10.1038/srep01541 article EN cc-by-nc-nd Scientific Reports 2013-03-26

Biochemical reactions often occur at low copy numbers but once in crowded and diverse environments. Space stochasticity therefore play an essential role biochemical networks. Spatial-stochastic simulations have become a prominent tool for understanding how the microscopic level influences macroscopic behavior of such systems. While particle-based models guarantee detail necessary to accurately describe dynamics very numbers, algorithms used simulate them typically imply trade-offs between...

10.1063/1.5064867 article EN The Journal of Chemical Physics 2019-02-07

Genomic DNA is organized three dimensionally within cells as chromatin and searched read by various proteins an unknown mechanism; this mediates diverse cell functions. Recently, several pieces of evidence, including our cryomicroscopy synchrotron X-ray scattering analyses, have demonstrated that consists irregularly folded nucleosome fibers without a 30-nm fiber (i.e., polymer melt-like structure). This structure implies less physically constrained locally more dynamic state, which may be...

10.4161/nucl.26053 article EN Nucleus 2013-08-29

In the cyanobacterium, Synechococcus elongatus, most promoters are regulated by a circadian clock under continuous light (LL) conditions. Nevertheless, basic oscillation is primarily generated alternating KaiC phosphorylation/dephosphorylation reactions at posttranslational level. Indeed, phosphorylation cycle was recently reconstituted in vitro incubating KaiA, KaiB, and proteins with ATP. However, molecular dynamics of this chemical mechanism that drives transcription/translation rhythms...

10.1177/0748730406295749 article EN Journal of Biological Rhythms 2007-01-17

Cells can maintain their functions despite fluctuations in intracellular parameters, such as protein activities and gene expression levels. This commonly observed biological property of cells is called robustness. On the other hand, these parameters have different limitations, each reflecting subsystem containing parameter. The budding yeast cell cycle quite fragile upon overexpression CDC14, but robust ESP1. products both CDC14 ESP1 are regulated by 1∶1 binding with inhibitors (Net1 Pds1),...

10.1371/journal.pgen.1000919 article EN cc-by PLoS Genetics 2010-04-22

Biochemical network visualization is one of the essential technologies for mechanistic interpretation omics data. In particular, recent advances in multi-omics measurement and analysis require development methods that encompass multiple Visualization 2.5 dimension (2.5D visualization), which an isometric view stacked X-Y planes, a convenient way to interpret multi-omics/trans-omics data context conventional layouts biochemical networks drawn on each layers. However, 2.5D trans-omics...

10.1038/s41540-024-00342-8 article EN cc-by npj Systems Biology and Applications 2024-02-19

The automation of experiments in life sciences and chemistry has significantly advanced with the development various instruments AI technologies. However, achieving full laboratory automation, where conceived by scientists are seamlessly executed automated laboratories, remains a challenge. We identify lack planning operational tasks--critical human-managed processes collectively termed "care"--as major barrier. Automating care is key enabler for automation. To address this, we propose...

10.48550/arxiv.2501.05789 preprint EN arXiv (Cornell University) 2025-01-10

Abstract As the current state of Metaverse is largely driven by corporate interests, which may not align with scientific goals and values, academia should play a more active role in its development. Here, we present challenges solutions for building that supports systems biology research collaboration. Our solution consists two components: Kosmogora , server ensuring biological data access, traceability, integrity context highly collaborative environment such as metaverse; ECellDive virtual...

10.1038/s41540-024-00334-8 article EN cc-by npj Systems Biology and Applications 2024-01-27

Abstract A string of nucleosomes, where genomic DNA is wrapped around histones, organized in the cell as chromatin. Chromatin varies greatly, from euchromatin to heterochromatin, its genome functions. It important understand how heterochromatin physically different euchromatin. However, their specific labeling methods living cells are limited. To address this, we have developed replication-dependent histone (Repli-Histo labeling) label nucleosomes and based on replication timing. We...

10.1101/2024.10.20.618801 preprint EN cc-by-nc bioRxiv (Cold Spring Harbor Laboratory) 2024-10-21

Microscopic models of reaction-diffusion processes on the cell membrane can link local spatiotemporal effects to macroscopic self-organized patterns often observed membrane. Simulation schemes based microscopic lattice method (MLM) model these at scale by tracking individual molecules, represented as hard-spheres, fine voxels. Although MLM is simple implement and generally less computationally demanding than off-lattice approaches, its accuracy consistency in modeling surface reactions have...

10.1103/physreve.99.042411 article EN cc-by Physical review. E 2019-04-19

Lattice-based stochastic simulators are commonly used to study biological reaction-diffusion processes. Some of these schemes that based on the master equation (RDME) can simulate for extended spatial and temporal scales but cannot directly account microscopic effects in cell such as volume exclusion diffusion-influenced reactions. Nonetheless, high-resolution lattice method (MLM) by representing each finite-sized molecule explicitly a random walker fine voxels. The theory consistency MLM...

10.1103/physreve.98.032418 article EN cc-by Physical review. E 2018-09-28

Identifying permissible limits of intracellular parameters such as protein expression provides important information for examining robustness. In this study, we used the TEV protease-mediated induction instability (TIPI) in combination with genetic Tug-of-War (gTOW) to develop a method measure lower limit level. We first tested feasibility using ADE2 marker and then analyzed some cell cycle regulators reveal interactions.Using TIPI-gTOW, successfully constructed strain which GFP-(TDegF)Ade2...

10.1186/1752-0509-8-2 article EN BMC Systems Biology 2014-01-07

Eukaryotic cells transmit extracellular signal information to cellular interiors through the formation of a ternary complex made up ligand (or agonist), G-protein, and G-protein-coupled receptor (GPCR). Previously formalized theories have mainly assumed that observable states receptors can only take form monomers. Here, we propose multiary model GPCR signaling activations via vector representation various unobserved aggregated states. Our results from simulations imply aggregation processes...

10.1103/physreve.102.032413 article EN Physical review. E 2020-09-22

The circadian clock of Drosophila is a model pathway for research in biological mechanisms, both with traditional experimental approaches and emerging systems biology utilizing mathematical modeling silico computer simulation. Dynamic diurnal oscillations are achieved by the complex interaction components as system, reconstruction has proven to be an invaluable means understanding such systematic behavior. In this study, we implemented eight published models Systems Biology Markup Language...

10.1162/artl.2008.14.1.29 article EN Artificial Life 2008-01-01
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