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Ken-ichi Hironaka
Ken-ichi Hironaka
Bestätigte E-Mail-Adresse bei bs.s.u-tokyo.ac.jp
Titel
Zitiert von
Zitiert von
Jahr
Encoding and decoding of positional information in morphogen-dependent patterning
K Hironaka, Y Morishita
Current opinion in genetics & development 22 (6), 553-561, 2012
412012
A developmental checkpoint directs metabolic remodelling as a strategy against starvation in Drosophila
T Yamada, K Hironaka, O Habara, Y Morishita, T Nishimura
Nature Metabolism 2 (10), 1096-1112, 2020
202020
Variant PRC1 competes with retinoic acid-related signals to repress Meis2 in the mouse distal forelimb bud
N Yakushiji-Kaminatsui, T Kondo, K Hironaka, J Sharif, TA Endo, ...
Development 145 (19), dev166348, 2018
202018
Quantitative analysis of 3D tissue deformation reveals key cellular mechanism associated with initial heart looping
N Kawahira, D Ohtsuka, N Kida, K Hironaka, Y Morishita
Cell reports 30 (11), 3889-3903. e5, 2020
192020
Optimal scaling of critical size for metamorphosis in the genus Drosophila
K Hironaka, K Fujimoto, T Nishimura
Iscience 20, 348-358, 2019
192019
Cellular sensory mechanisms for detecting specific fold-changes in extracellular cues
K Hironaka, Y Morishita
Biophysical journal 106 (1), 279-288, 2014
192014
Trans-omic analysis reveals obesity-associated dysregulation of inter-organ metabolic cycles between the liver and skeletal muscle
R Egami, T Kokaji, A Hatano, K Yugi, M Eto, K Morita, S Ohno, M Fujii, ...
IScience 24 (3), 2021
182021
Reconstructing 3D deformation dynamics for curved epithelial sheet morphogenesis from positional data of sparsely-labeled cells
Y Morishita, K Hironaka, SW Lee, T Jin, D Ohtsuka
Nature communications 8 (1), 15, 2017
182017
Transomics analysis reveals allosteric and gene regulation axes for altered hepatic glucose-responsive metabolism in obesity
T Kokaji, A Hatano, Y Ito, K Yugi, M Eto, K Morita, S Ohno, M Fujii, ...
Science Signaling 13 (660), eaaz1236, 2020
172020
Single-cell information analysis reveals that skeletal muscles incorporate cell-to-cell variability as information not noise
T Wada, K Hironaka, M Wataya, M Fujii, M Eto, S Uda, D Hoshino, ...
Cell Reports 32 (9), 2020
162020
Curved surface geometry-induced topological change of an excitable planar wavefront
K Horibe, K Hironaka, K Matsushita, K Fujimoto
Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (9), 2019
122019
Multi-omics-based label-free metabolic flux inference reveals obesity-associated dysregulatory mechanisms in liver glucose metabolism
S Uematsu, S Ohno, KY Tanaka, A Hatano, T Kokaji, Y Ito, H Kubota, ...
Iscience 25 (2), 2022
102022
Cell-to-cell variability serves as information not noise
T Wada, K Hironaka, S Kuroda
Current Opinion in Systems Biology 27, 100339, 2021
92021
Adaptive significance of critical weight for metamorphosis in holometabolous insects
K Hironaka, Y Morishita
Journal of Theoretical Biology 417, 68-83, 2017
82017
Multiple feedback loops achieve robust localization of wingless expression in Drosophila notum development
K Hironaka, Y Iwasa, Y Morishita
Journal of theoretical biology 292, 18-29, 2012
72012
Systems approach to developmental biology–designs for robust patterning
Y Morishita, K Hironaka
IET Systems Biology 7 (2), 38-49, 2013
52013
Monitoring and mathematical modeling of mitochondrial ATP in myotubes at single‐cell level reveals two distinct population with different kinetics
N Matsuda, K Hironaka, M Fujii, T Wada, K Kunida, H Inoue, M Eto, ...
Quantitative Biology 8 (3), 228-237, 2020
42020
Four features of temporal patterns characterize similarity among individuals and molecules by glucose ingestion in humans
S Fujita, Y Karasawa, M Fujii, K Hironaka, S Uda, H Kubota, H Inoue, ...
NPJ systems biology and applications 8 (1), 6, 2022
32022
Features extracted using tensor decomposition reflect the biological features of the temporal patterns of human blood multimodal metabolome
S Fujita, Y Karasawa, K Hironaka, Y Taguchi, S Kuroda
Plos one 18 (2), e0281594, 2023
22023
Single-cell information analysis reveals small intra-and large intercellular variations increase cellular information capacity
T Wada, M Wataya, M Fujii, K Hironaka, M Eto, S Uda, D Hoshino, ...
bioRxiv, 653832, 2019
22019
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