Kyushu University Academic Staff Educational and Research Activities Database
List of Papers
Hanai Taizo Last modified date:2020.05.11

Professor / Synthetic Biology / Department of Bioscience and Biotechnology / Faculty of Agriculture


Papers
1. Yasutaka Hirokawa, Ryota Goto, Yoshitaka Umetani, Taizo Hanai, Construction of a novel D-lactate producing pathway from dihydroxyacetone phosphate of the Calvin cycle in cyanobacterium, Synechococcus elongates PCC 7942, Journal of Bioscience and Bioengineering, doi: 10.1016/j.jbiosc.2017.02.016, 124, 54-61, 2017.03.
2. Yasutaka Hirokawa, Takeshi Kubo, Yuki Soma, Fumiko Saruta, Taizo Hanai, Enhancement of acetyl-CoA flux for photosynthetic chemical production by pyruvate dehydrogenase complex overexpression in Synechococcus elongatus PCC 7942, Metabolic Engineering, 10.1016/j.ymben.2019.07.012, 57, 23-30, 2020.01, Genetic manipulation in cyanobacteria enables the direct production of valuable chemicals from carbon dioxide. However, there are still very few reports of the production of highly effective photosynthetic chemicals. Several synthetic metabolic pathways (e.g., isopropanol, acetone, isoprene, and fatty acids) have been constructed by branching from acetyl-CoA and malonyl-CoA, which are key intermediates for photosynthetic chemical production downstream of pyruvate decarboxylation. Recent reports of the absolute determination of cellular metabolites in Synechococcus elongatus PCC 7942 have shown that its acetyl-CoA levels corresponded to about one hundredth of the pyruvate levels. In short, one of the reasons for lower photosynthetic chemical production from acetyl-CoA and malonyl-CoA was the smaller flux to acetyl-CoA. Pyruvate decarboxylation is a primary pathway for acetyl-CoA synthesis from pyruvate and is mainly catalyzed by the pyruvate dehydrogenase complex (PDHc). In this study, we tried to enhance the flux toward acetyl-CoA from pyruvate by overexpressing PDH genes and, thus, catalyzing the conversion of pyruvate to acetyl-CoA via NADH generation. The overexpression of PDH genes cloned from S. elongatus PCC 7942 significantly increased PDHc enzymatic activity and intracellular acetyl-CoA levels in the crude cell extract. Although growth defects were observed in overexpressing strains of PDH genes, the combinational overexpression of PDH genes with the synthetic metabolic pathway for acetate or isopropanol resulted in about 7-fold to 9-fold improvement in its production titer, respectively (9.9 mM, 594.5 mg/L acetate, 4.9 mM, 294.5 mg/L isopropanol). PDH genes overexpression would, therefore, be useful not only for the production of these model chemicals, but also for the production of other chemicals that require acetyl-CoA as a key precursor..
3. Hiroshi Honjo, Kenshiro Iwasaki, Yuki Soma, K. Tsuruno, Hiroyuki Hamada, Taizo Hanai, Synthetic microbial consortium with specific roles designated by genetic circuits for cooperative chemical production, Metabolic Engineering, 10.1016/j.ymben.2019.08.007, 55, 268-275, 2019.09, Synthetic microbial consortia consisting of microorganisms with different synthetic genetic circuits or divided synthetic metabolic pathway components can exert functions that are beyond the capacities of single microorganisms. However, few consortia of microorganisms with different synthetic genetic circuits have been developed. We designed and constructed a synthetic microbial consortium composed of an enzyme-producing strain and a target chemical-producing strain using Escherichia coli for chemical production with efficient saccharification. The enzyme-producing strain harbored a synthetic genetic circuit to produce beta-glucosidase, which converts cellobiose to glucose, destroys itself via the lytic genes, and release the enzyme when the desired cell density is reached. The target chemical-producing strain was programmed by a synthetic genetic circuit to express enzymes in the synthetic metabolic pathway for isopropanol production when the enzyme-producing strain grows until release of the enzyme. Our results demonstrate the benefits of synthetic microbial consortia with distributed tasks for effective chemical production from biomass..
4. Naruhiko Sawa, Tsuneyuki Tatsuke, Atsushi Ogawa, Yasutaka Hirokawa, Takashi Osanai, Taizo Hanai1, Modification of carbon metabolism in Synechococcus elongatus PCC 7942 by cyanophage-derived sigma factors for bioproduction improvement, Journal of Bioscience and Bioengineering, 10.1016/j.jbiosc.2018.07.019, 127, 256-264, 2019.02.
5. Yasutaka Hirokawa, Shingo Matsuo, Hiroyuki Hamada, Fumio Matsuda, Taizo Hanai, Metabolic engineering of Synechococcus elongatus PCC 7942 for improvement of 1,3‑propanediol and glycerol production based on in silico simulation of metabolic flux distribution, Microbial Cell Factories, 10.1186/s12934-017-0824-4, 16, 212, 2017.12, The introduction of a synthetic metabolic pathway consisting of multiple genes derived from various organisms enables cyanobacteria to directly produce valuable chemicals from carbon dioxide. We previously constructed a synthetic metabolic pathway composed of genes from Escherichia coli, Saccharomyces cerevisiae, and Klebsiella pneumoniae. This pathway enabled 1,3-propanediol (1,3-PDO) production from cellular DHAP via glycerol in the cyanobacterium, Synechococcus elongatus PCC 7942. The production of 1,3-PDO (3.79 mM, 0.29 g/l) directly from carbon dioxide by engineered S. elongatus PCC 7942 was successfully accomplished. However, the constructed strain accumulated a remarkable amount of glycerol (12.6 mM, 1.16 g/l), an intermediate metabolite in 1,3-PDO production. Notably, enhancement of latter reactions of synthetic metabolic pathway for conversion of glycerol to 1,3-PDO increases 1,3-PDO production. In this study, we aimed to increase the observed 1,3-PDO production titer. First, the weaker S. elongatus PCC 7942 promoter, PLlacO1, was replaced with a stronger promoter (Ptrc) to regulate genes involved in the conversion of glycerol to 1,3-PDO. Second, the induction timing for gene expression and medium composition were optimized. Promoter replacement resulted in higher 1,3-PDO production than glycerol accumulation, and the amount of products (1,3-PDO and glycerol) generated via the synthetic metabolic pathway increased with optimization of medium composition. Accordingly, we achieved the highest titer of 1,3-PDO (16.1 mM, 1.22 g/l) and this was higher than glycerol accumulation (9.46 mM, 0.87 g/l). The improved titer was over 4-fold higher than that of our previous study.  .
6. Sayuri Arai, Kayoko Hayashihara, Yuki Kanamoto, Kazunori Shimizu, Yasutaka Hirokawa, Taizo Hanai, Akio Murakami, Hiroyuki Honda, Alcohol-tolerant mutants of cyanobacterium 1 Synechococcus elongatus PCC7942 obtained by single-cell mutant screening system, Biotechnology and Bioengineering, 114, 1771-1778, 2017.08.
7. Yuki Soma, Yuri Fujiwara, Takuya Nakagawa, Keigo Tsuruno, Taizo Hanai, Reconstruction of a metabolic regulatory network in Escherichia coli for purposeful switching from cell growth mode to production mode in direct GABA fermentation from glucose, METABOLIC ENGINEERING, 43, 54-63, 2017.08, γ-aminobutyric acid (GABA) is a drug and functional food additive and is used as a monomer for producing the biodegradable plastic, polyamide 4. Recently, direct GABA fermentation from glucose has been developed as an alternative to glutamate-based whole cell bioconversion. Although total productivity in fermentation is determined by the specific productivity and cell amount responsible for GABA production, the optimal metabolic state for GABA production conflicts with that for bacterial cell growth. Herein, we demonstrated metabolic state switching from the cell growth mode based on the metabolic pathways of the wild type strain to a GABA production mode based on a synthetic metabolic pathway in Escherichia coli through rewriting of the metabolic regulatory network and pathway engineering. The GABA production mode was achieved by multiple strategies such as conditional interruption of the TCA and glyoxylate cycles, engineering of GABA production pathway including a bypass for precursor metabolite supply, and upregulation of GABA transporter. As a result, we achieved 3-fold improvement in total GABA production titer and yield (4.8 g/L, 49.2% (mol/mol glucose)) in batch fermentation compared to the case without metabolic state switching (1.6 g/L, 16.4% (mol/mol glucose)). This study reports the highest GABA production performance among previous reports on GABA fermentation from glucose using engineered E. coli..
8. Yuki Soma, Taiki Yamaji, Fumio Matsuda, Taizo Hanai, Synthetic metabolic bypass for a metabolic toggle switch enhances acetyl-CoA supply for isopropanol production by Escherichia coli, Journal of Bioscience and Bioengineering, 123, 625-633, 2017.05.
9. Yasutaka Hirokawa, Yu Kanesaki, Sayuri Arai, Fumiko Saruta, Kayoko Hayashihara, Akio Murakami, Kazunori Shimizu, Hiroyuki Honda, Hirofumi Yoshikawa, Taizo Hanai, Mutations responsible for alcohol tolerance in the mutant of Synechococcus elongatus PCC 7942 (SY1043) obtained by single-cell screening system, Journal of Bioscience and Bioengineering, 125, 572-577, 2017.05.
10. Yasutaka Hirokawa, Yuki Maki, Taizo Hanai, Improvement of 1,3-propanediol production using an engineered cyanobacterium, Synechococcus elongatus by optimization of the gene expression level of a synthetic metabolic pathway and production conditions, METABOLIC ENGINEERING, 39, 192-199, 2017.03.
11. Yasutaka Hirokawa, Yudai Dempo, Eiichiro Fukusaki, Taizo Hanai, Metabolic engineering for isopropanol production by an engineered cyanobacterium, Synechococcus elongatus PCC 7942, under photosynthetic conditions, Journal of Bioscience and Bioengineering, 123, 39-1233945, 2017.01.
12. Sayuri Arai, Mina Okochi, Kazunori Shimizu, Taizo Hanai, Hiroyuki Honda, A single cell culture system using lectin-conjugated magnetite nanoparticles and magnetic force to screen mutant cyanobacteria, Biotechnology and Bioengineering, 113, 112-119, 2016.12.
13. Yasutaka Hirokawa, Yuki Maki, Tsuneyuki Tatsuke, Taizo Hanai, Cyanobacterial production of 1,3-propanediol directly from carbon dioxide using a synthetic metabolic pathway, METABOLIC ENGINEERING, 10.1016/j.ymben.2015.12.008, 34, 97-103, 2016.03.
14. Keigo Tsuruno, Hiroshi Honjo, Taizo Hanai, Enhancement of 3-hydroxypropionic acid production from glycerol by using a metabolic toggle switch, MICROBIAL CELL FACTORIES, 10.1186/s12934-015-0342-1, 14, 2015.10.
15. Yasutaka Hirokawa, Iwane Suzuki, Taizo Hanai, Optimization of isopropanol production by engineered cyanobacteria with a synthetic metabolic pathway, Journal of Bioscience and Bioengineering, 10.1016/j.jbiosc.2014.10.005, 119, 5, 585-590, 2015.05.
16. Yuki Soma, Taizo Hanai, Self-induced metabolic state switching by a tunable cell density sensor for microbial isopropanol production, Metabolic Engineering, 10.1016/j.ymben.2015.04.005, 2015.04.
17. Hiroshi Honjo, Keigo Tsuruno, Tsuneyuki Tatsuke, Masaki Sato, Taizo Hanai, Dual synthetic pathway for 3-hydroxypropionic acid production in engineered Escherichia coli, Journal of Bioscience and Bioengineering, 10.1016/j.jbiosc.2014.12.023, 2015.01.
18. Sayuri Arai, Mina Okochi, Taizo Hanai, Hiroyuki Honda, Micro-compartmentalized cultivation of cyanobacteria for mutant screening using glass slides with highly water-repellent mark, Biotechnology Reports, 4, 151-155, 2014.08.
19. Yuki Soma, Keigo Tsuruno, Masaru Wada, Atsushi Yokota, Taizo Hanai, Metabolic flux redirection from a central metabolic pathway toward a synthetic pathway using a
metabolic toggle switch, Metabolic Engineering, 10.1016/j.ymben.2014.02.008, 23, 175-184, 2014.02, Overexpression of genes in production pathways and permanent knockout of genes in competing pathways are often employed to improve production titer and yield in metabolic engineering. However, the deletion of a pathway responsible for growth and cell maintenance has not previously been employed, even if its competition with the production pathway is obvious. In order to optimize intracellular metabolism at each fermentation phase for bacterial growth and production, a
methodology employing conditional knockout is required. We constructed a metabolic toggle switch in E. coli as a novel conditional knockout approach and applied it to isopropanol production. The resulting redirection of excess carbon flux caused by interruption of the TCA cycle via switching gltA OFF improved isopropanol production titer and yield up to 3.7 and 3.1 times, respectively. This approach is a useful tool to redirect carbon flux responsible for bacterial growth and/or cell
maintenance toward a synthetic production pathway..
20. Tamami Kusakabe, Tsuneyuki Tatsuke, Keigo Tsuruno, Shota Atsumi, James C. Liao, Taizo Hanai, Engineering synthetic pathway in cyanobacteria for isopropanol production directly from carbon dioxide and light, Metabolic Engineering, 10.1016/j.ymben.2013.09.007, 20, 101-108, 2013.09, Production of alternate fuels or chemicals directly from solar energy and carbon dioxide using engineered cyanobacteria is an attractive method to reduce petroleum dependency and minimize carbon emission. Here, a synthetic pathway using thl (acetyl-CoA acetyltransferase) and adc (acetoacetate decarboxylase) from Clostridium acetobutylicum ATCC824, and atoAD (acetoacetyl-CoA transferase) from Escherichia coli K-12 MG1655, and adh (secondary alcohol dehydrogenase) from Clostridium beijerinckii NRRL B593 were integrated into a genome of Synechococcus elongatus strain PCC7942 to produce isopropanol. Under optimized production conditions, the engineered cyanobacteria produced 26.5 mg/L of isopropanol after 9
days. While nitrogen starving conditions improved isopropanol production 7.2-fold, dark conditions lead to a 27-fold improvement over light conditions..
21. Yuki Souma, Kentaro Inokuma, Tsutomu Tanaka, Chiaki Ogino, Akihiko Kondo, Taizo Hanai, Direct isopropanol production from cellobiose by engineered Escherichia coli using a synthetic pathway and a cell surface display system, J Biosci Bioeng, 114, 80-85, 2012.05.
22. Kuriya, Y., Tanaka, S., Kobayashi, G., Hanai, T., and Okamoto, M., Development of an Analytical Pipeline for Optimizing Substrate Feeding and Eliminating Metabolic Bottlenecks., Chem-Bio Info., 11, 1-23, 2011.01.
23. Kentaro Inokuma, Masahiro Okamoto, Taizo Hanai, Improvement of isopropanol production by metabolically engineered Escherichia coli using gas stripping., J Biosci Bioeng, 110, 696-701, 2010.08.
24. Wong, I., Atsumi, S., Huang, W. C., Wu, T. Y., Hanai, T., Lam, M. L., Tang, P., Yang, J., Liao, J. C., and Ho, C. M., An agar gel membrane-PDMS hybrid microfluidic device for long term single cell dynamic study., Lab Chip, 2010.07.
25. Hideaki Shinto, Yukihiro Tashiro, Genta Kobayashi, Tatsuya Sekiguchi, Taizo Hanai, Yuki Kuriya, Masahiro Okamoto, Kenji Sonomoto, Kinetic study of substrate dependency for higher butanol production in acetone-butanol-ethanol fermentation, Process Biochemistry, 43, 1452-1461, 2008.11.
26. Shota Atsumi, Anthony F. Cann, Michael R. Connor, Claire R. Shen, Kevin M. Smith, Mark P. Brynildsen, Katherine J.Y. Chou, Taizo Hanai, James C. Liao, Metabolic engineering of Escherichia coli for 1-butanol production, Metabolic Engineering, 10(6), 305-311, 2008.11.
27. Yoshihiko Tashima, Hiroyuki Hamada, Masahiro Okamoto, Taizo Hanai, Prediction of Key Factor for Control of G1/S Phase in Mammalian Cell Cycle by using System Analysis, Journal of Bioscience and Bioengineering, 2008.09.
28. Chinatsu Arima, Kazumi Hakamada, Masahiro Okamoto, and Taizo Hanai, Modified Fuzzy Gap statistic for estimating the preferable number of clusters in fuzzy k-means clustering, Journal of Bioscience and Bioengineering, 105, 3, 273-281, 2008.03.
29. Shota Atsumi, Taizo Hanai, James C. Liao, Non-fermentative pathways for synthesis of branched-chain higher alcohols as biofuels, Nature, 451, 7174, 86-89, 2008.01, 再生可能資源であるバイオマスから、代替燃料イソブタノールを効率的に生産する方法を開発することは重要である。本研究では、組換えが容易な大腸菌に、Ehrlich経路(合成代謝経路)を外部から導入し、本来生産されないイソブタノールを生産することに成功した。また、この生産大腸菌のもつ目的生産物との競合代謝経路遺伝子を破壊、または必要な反応酵素遺伝子を増強し、20g/Lまでの生産性の向上を達成した。.
30. Taizo Hanai, Shota Atsumi, James C. Liao, Engineered synthetic pathway for isopropanol production in Escherichia coli, Applied and Environmental Microbiology, 73, 24, 7814-7818 , 2007.12.
31. Koujiro Nishida, Shinji Mine, Tohru Utsunomiya, Hiroshi, Inoue, Masahiro Okamoto, Harushi Udagawa, Taizo Hanai, Masaki Mori, Global analysis of altered gene expressions during the process esophageal squamous cell carcinogenesis in the rat: a study combined with a laser microdissection and cDNA microarray, Cancer Research, 65, 2, 401-409, 65, 2, 401-409, 2005.02.
32. Xicheng Liu, Shin Hibino, Yoshihiro Hasegawa, Taizo Hanai, Takeju Mitsushima, Akihiko Iida, Michitaka Matsubara, Hiroyuki Honda and Takeshi Kobayashi, Evaluation of the Alzheimer-type dementia by magnetic resonance imaging using Fuzzy neural network, Journal of Chemical Engineering of Japan, 37, 3, 523-530, 2004.06.
33. Kazumi Hakamada, Taizo Hanai, Hiroyuki Honda and Takeshi Kobayashi, A preprocessing method for genetic interaction inferring from gene expression data using Boolean algorithm, Journal of Bioscience and Bioengineering, 98, 6, 457-463, 2004.06.
34. Taizo Hanai, Naoya Iwata, Takeshi Furuhashi, Hiroyuki Honda and Takeshi Kobayashi, Proposal of Reliability Index for Estimation Accuracy of Fuzzy Neural Network and Reverse Calculation using Genetic Algorithm with Reliability Index, Journal of Chemical Engineering of Japan, 37, 4, 523 - 530, 2004.04.
35. Chinatsu Arima, Taizo Hanai, Masahiro Okamoto, Gene Expression Analysis Using K-means Clustering, Genome Informatics, 14, 334-335, 2003.12.
36. Chihoko Tago, Taizo Hanai, Masahiro Okamoto, Prognosis prediction by microarray gene expression using Support Vector Machine, Genome Informatics, 14, 324-325, 2003.12.
37. Kazumi Hakamada, Taizo Hanai, Masahiro Okamoto, Clustering Method Based on Onset and Cessation of Gene Expression, Genome Informatics, 14, 330-331, 2003.12.
38. Yoshihiko Tashima, Taizo Hanai, Hiroyuki Hamada, Masahiro Okamoto, Kinetics Behavior of G1-to-S Cell Cycle Phase Transition Model, Genome Informatics, 14, 607-608, 2003.12.
39. Taizo Hanai, Toshihiko Oki, Hiroyuki Honda, Takeshi Kobayashi, Analysis of initial conditions for polymerization reaction using fuzzy neural network and genetic Algorithm, Computers and Chemical Engineering, 10.1016/S0098-1354(03)00034-6, 27, 7, 1011-1019, 27, 1011-1019, 2003.10.
40. Xicheng Liu, Shin Hibino, Taizo Hanai, Toshiaki Imanishi, Tatsuaki Shirataki, Tetsuo Ogawa, Hiroyuki Honda and Takeshi Kobayashi, Construction of electroencephalogram-based brain-computer interface using an artificial neural network, The Institute of Electronics, Information and Communication Engineers Transduction, 86-D, 9, 1879-1886, 2003.09.
41. Taizo Hanai, Yasushi Yatabe, Yusuke Nakayama, Takeshi Takahashi, Hiroyuki Honda, Tetsuya Mitsudomi and Takeshi Kobayashi, Prediction of prognosis for patients with nonsmall cell lung carcinoma from pathological immunohistological items using an artificial neural network, Cancer Science, 94, 5, 473-477, 2003.05.
42. Shuhei Hayashi, Rikizo Aono, Taizo Hanai, Hirotada Mori, Takeshi Kobayashi and Hiroyuki Honda, Analysis of organic solvent tolerance in Escherichia coli using gene expression profiles from DNA microarrays, Journal of Bioscience and Bioengineering, 95, 4, 379-383, 2003.04.
43. Tetsuya Ando, Miyuki Suguro, Taizo Hanai, Takeshi Kobayashi, Hiroyuki Honda and Masato Seto, Fuzzy neural network applied to gene expression profiling for prognosis of diffuse large B-cell lymphoma, Japanese Journal of Cancer Research, 93, 12, 1207-1212, 2002.12.
44. Shuta Tomida, Taizo Hanai, Hiroyuki Honda and Takeshi Kobayashi, Gene expression analysis using fuzzy ART model, Bioinformatics, 18, 8, 1073-1083, 2002.08.
45. Shuta Tomida, Taizo Hanai, Naoki Koma, Hiroyuki Honda and Takeshi Kobayashi, ANN predictive model for allergic disease using SNPs data, Journal of Bioscience and Bioengineering, 93, 5, 470-478, 2002.05.
46. Toshiaki Imanishi, Taizo Hanai, Ichiro Aoyagi, Jun Uemura, Katsuhiro Araki, Hiroshi Yoshimoto, Takeshi Harima, Hiroyuki Honda and Takeshi Kobayashi, Software sensing for glucose concentration in industrial antibiotic fed-batch culture using fuzzy neural network, Biotechnology and Bioprocess Engineering, 7, 5, 175-180, 2002.05.
47. Hideki Noguchi, Ryuji Kato, Taizo Hanai, Yukari Matsubara, Hiroyuki Honda and Takeshi Kobayashi, Hidden Markov model-based prediction of antigenic peptides that interact with MHC class II molecules, Journal of Bioscience and Bioengineering, 94, 3, 264-270, 2002.03.
48. Osamu Tominaga, Fumio Ito, Taizo Hanai, Hiroyuki Honda and Takeshi Kobayashi, Modeling of consumer’s preference on regular coffee samples and its application to product design, Food Science and Technology Research, 8, 3, 281-285, 2002.03.
49. Osamu Tominaga, Fumio Ito, Taizo Hanai, Hiroyuki Honda and Takeshi Kobayashi, Determination of blending ratio of roasted coffee bean by information technology, Journal of Chemical Engineering of Japan, 35, 2, 137-143, 2002.02.
50. Osamu Tominaga, Fumio Ito, Taizo Hanai, Hiroyuki Honda and Takeshi Kobayashi, Sensory modeling of coffee with a fuzzy neural network, Journal of Food Science, 67, 1, 363-368, 2002.01.
51. Shuta Tomida, Taizo Hanai, Hiroyuki Honda, Takeshi Kobayashi, Gene Expression Analysis Using Fuzzy ART Model, Genome Informatics, 12,245-246, 2001.12.
52. Tatsuya Ando, Taizo Hanai, Hiroyuki Honda, Takeshi Kobayashi, Prognostic prediction of lymphoma by gene expression profile using FNN, Genome Informatics, 12,247-248, 2001.12.
53. Kazumi Hakamada, Taizo Hanai, Hiroyuki Honda, Takeshi Kobayashi, Identifying genetic network using experimental time series data by Boolean algorithm, Genome Informatics, 12,272-273, 2001.12.
54. Eiji Nagamori, Hiroyuki Honda, Taizo Hanai, Katsuyuki Nakanishi, Naotsugu Hata, Takeshi Masuda and Takeshi Kobayashi, Prediction of occurrence of Heterocapsa circularisquama red tide by means of fuzzy neural network, Journal of Chemical Engineering Japan, 34, 8, 998-1005, 2001.08.
55. Hiroki Yoshikawa, Taizo Hanai, Shuta Tomita, Hiroyuki Honda and Takeshi Kobayashi, Determination of operating conditions in activated sludge process using Fuzzy Neural Network and Genetic Algorithm, Journal of Chemical Engineering of Japan, 34, 8, 1033-1039, 2001.08.
56. Shin Hibino, Taizo Hanai, Erika Nagata, Michitaka Matsubara, Kazutoshi Fukagawa, Tatsuaki Shirataki, Hiroyuki Honda and Takeshi Kobayashi, Fuzzy neural network model for assessment of Alzheimer-type dementia, Journal of Chemical Engineering of Japan, 34, 7, 936-942, 2001.07.
57. Shuta Tomita, Taizo Hanai, Hiroyuki Honda and Takeshi Kobayashi, Construction of COD simulation model for activated sludge process by recursive fuzzy neural network, Journal of Chemical Engineering of Japan, 34, 3, 369-375, 2001.03.
58. Hideki Noguchi, Taizo Hanai, Hiroyuki Honda, Takeshi Kobayashi, Fuzzy Neural Network-Based Prediction of the Motif for MHC Class II Binding Peptides, Journal of Bioscience and Bioengineering, 92, 3, 227-231, 2001.03.
59. Shin Hibino, Taizo Hanai, Erika Nagata, Michitaka Matsubara, Fukagawa Kazutoshi, Tatsuaki Shirataki, Hiroyuki Honda and Takeshi Kobayashi: Construction of a diagnostic assistant system of dementia severity using electroencephalography by fuzzy neural networks; a study using EEG under the state of resting and loading a linguistic task, Clinical Electroencephalography, 43(2), 109-114(2001) (in Japanese).
60. Shuta Tomida, Taizo Hanai, Hiroyuki Honda, Takeshi Kobayashi, Gene Expression Analysis Using Fuzzy ART Model, Genome Informatics, 11, 394-395, 2000.12.
61. Shin Hibino, Taizo Hanai, Ken-ichi Kawai, Hiroyuki Honda and Takeshi Kobayashi : Construction of a diagnostic assistant system in electromyography using an expert system, Clinical Electroencephalography, 42(3), 177-181(2000) (in Japanese).
62. Hideki Noguchi, Taizo Hanai, Hiroyuki Honda, Takeshi Kobayashi, Prediction of MHC Class II-Peptide Interaction Using Fuzzy Neural Network, Genome Informatics, 10, 259-260, 1999.12.
63. Hiroyuki Honda, Takeshi Ito, Junko Yamada, Taizo Hanai, Makoto Matsuoka and Takeshi Kobayashi, Selection of embryogenic sugarcane callus by image analysis, Journal of Bioscience and Bioengineering, 87, 5, 700-702, 1999.05.
64. Hideki Noguchi, Taizo Hanai, Wataru Takahashi, Tomohiko Ichii, Mitsuru Tanikawa, Susumu Masuoka, Hiroyuki Honda and Takeshi Kobayashi : Model construction for quality of beer and brewing process using FNN, Kagaku Kougaku Ronbunshu, 25(5), 695-701(1999) (in Japanese).
65. Taizo Hanai, Eiji Ohkusu, Toshihiko Ohki, Hiroyuki Honda, Hisao Tohoyama, Takahiro Muramatsu, Takeshi Kobayashi, An application of artificial neural network and genetic algorithm to koji making process, Journal of Bioscience and Bioengineering, 87, 4, 507-512, 1999.04.
66. Taizo Hanai, Hiroyuki Honda and Takeshi Kobayashi : Application of knowledge information engineering for sake mashing process, Kagaku Kougaku Ronbunshu, 25(2), 163-168(1999)(in Japanese).
67. Shin Hibino, Taizo Hanai, Michitaka Matsubara, Kazutoshi Fukagawa, Tatsuaki Shirataki, Hiroyuki Honda and Takeshi Kobayashi : Assessment of aphasia using artificial neural networks, Japanese Journal of Medical Electronics and Biological Engineering, 37(2), 140-145(1999) (in Japanese).
68. Taizo Hanai, Shin Hibino, Erika Nagata, Michitaka Matsubara, Kazutoshi Fukagawa, Tatsuaki Shirataki, Hiroyuki Honda and Takeshi Kobayashi : Assessment of senile dementia of Alzheimer type using artificial neural networks, Japanese Journal of Medical Electronics and Biological Engineering, 37(2), 178-183(1999) (in Japanese).
69. Shuta Tomita, Taizo Hanai, Masanori Ueda, Hiryuki Honda, Takeshi Kobayashi, Construction of COD simulation model for activated sludge process by fuzzy neural network, Journal of Bioscience and Bioengineering, 88, 2, 215-220, 1999.02.
70. Taizo Hanai, Naoyasu Ueda, Hiroyuki Honda, Hisao Tohyama and Takeshi Kobayashi : Decision of optimal temperature course in mashing process using GA-FNN for quality control of ginjo sake, Seibustu-kogaku Kaishi, 76(8), 331-337(1998)(in Japanese).
71. Taizo Hanai, Kazunori Ando, Hideki Noguchi, Hiroyuki Honda, Chiyo Takai, Junko Kawaide and Takeshi Kobayashi : A new selection system for the exterior tile using 2 step FNN models, Kagaku Kougaku Ronbunshu, 24(5), 716-721(1998)(in Japanese).
72. Taizo Hanai, Kazunori Ando, Hideki Noguchi, Hiroyuki Honda, Chiyo Takai, Takeshi Furuhashi, Yoshiki Uchikawa and Takeshi Kobayashi : Modeling of sensory evaluation for interior tiles using fuzzy neural network, Kagaku Kougaku Ronbunshu, 24(1), 18-23(1998)(in Japanese).
73. Hiroyuki Honda, Taizo Hanai, Akemi Katayama, Hisao Tohyama, Takeshi Kobayashi, Temperature control of Ginjo sake brewing process by automatic fuzzy modeling using fuzzy neural networks, Journal of Fermentation and Bioengineering, 85, 1, 107-112, 1998.01.