Ramadhan D., Watanabe R., Mizuguchi K. Optimizing Multi-Task Learning with Evolutionary Relatedness Metrics for Enhanced QSAR-Based Natural Product Activity Prediction ACS Omega2025 https://doi.org/10.1021/acsomega.5c05094
Kitatani Y.N., Kobiyama K., Igarashi Y., Aoshi T., Nakatsu N., Tripathi L.P., Ito J., Persson J.N., Kosugi Y., Osorio R.S.A., Nagao C., Temizoz B., Kuroda E., Standley D.M., Kiyono H., Nakanishi K., Uematsu S., Hamaguchi I., Yasutomi Y., Kunisawa J., Yamasaki S., Coban C., Yamada H., Mizuguchi K., Ishii K.J. An adjuvant database for preclinical evaluation of vaccines and immunotherapeutics Cell Chemical Biology2025 https://doi.org/10.1016/j.chembiol.202507005
Hu Y., Mizuguchi K., Hashimoto K. Unveiling unique expression patterns of D20S16 satellite DNA in human embryonic development Scientific Reports2025, 15(1) https://doi.org/10.1038/s41598-025-11753-w
Yoshimura E., Hamada Y., Hatamoto Y., Nakagata T., Nanri H., Nakayama Y., Iwasaka C., Hayashi T., Suzuki I., Ando T., Takata K.I., Tanaka S., Ono R., Araki M., Kawashima H., Chen Y.A., Park J., Hosomi K., Mizuguchi K., Kunisawa J., Miyachi M. Effect of short-term dietary intervention on fecal serotonin, gut microbiome-derived tryptophanase, and energy absorption in a randomized crossover trial: an exploratory analysis Gut Microbes2025, 17(1) https://doi.org/10.1080/19490976.2025.2514137
Chen Y.A., Kawashima H., Park J., Mohsen A., Hosomi K., Nakagata T., Murakami H., Nanri H., Miyachi M., Kunisawa J., Mizuguchi K. NIBN Japan Microbiome Database, a database for exploring the correlations between human microbiome and health Scientific Reports2025, 15(1) https://doi.org/10.1038/s41598-025-04339-z
Nojima Y., Mizuguchi K. Identification of the differences in molecular networks between idiopathic pulmonary fibrosis and lung squamous cell carcinoma using machine learning Computational Biology and Chemistry2025 https://doi.org/10.1016/j.compbiolchem.2025.108560
Song J., Ui A., Mizuguchi K., Watanabe R. A Novel Method for Endometrial Cancer Patient Stratification Considering ARID1A Protein Expression and Activity with Effective Use of Multi-omics Data Computational and Structural Biotechnology Journal2025 https://doi.org/10.1016/j.csbj.2025年06月01日5
Ardiansah B., Farhan A., Nurhasanah N.S., Nasution M.A.F., Salleh N.M., Mizuguchi K., Cahyana A.H., Mardiana L. Dual antioxidant and cytotoxic activities of novel 1,2,3-triazole-decorated unsymmetrical monocarbonyl curcumin analogs Case Studies in Chemical and Environmental Engineering2025, 11101031-101031 https://doi.org/10.1016/j.cscee.2024.101031
Permadi E.E., Watanabe R., Mizuguchi K. Improving the accuracy of prediction models for small datasets of Cytochrome P450 inhibition with deep learning Journal of Cheminformatics2025, 17(1) https://doi.org/10.1186/s13321-025-01015-2
Wang Q., Wang Z., Mizuguchi K., Takao T. Biological age prediction using a DNN model based on pathways of steroidogenesis Science Advances2025, 11(11) https://doi.org/10.1126/sciadv.adt2624
Doi M., Inoue R., Hosomi K., Park J., Yumioka H., Syauki A.Y., Kageyama S., Sakaue H., Tanabe K., Mizuguchi K., Kunisawa J., Irie Y. Effects of Malted Rice Amazake Consumption on Nutritional Status and Gut Microbiome in Older Patients and Residents of an Integrated Facility for Medical and Long-Term Care Journal of Nutrition in Gerontology and Geriatrics2025, 1-23 https://doi.org/10.1080/21551197.2024.2431283
Ito S., Koyama T., Matsumoto S., Kojima R., Okamoto Y., Kuroda M., Kawashima H., Watanabe R., Yonezawa T., Sumiyoshi T., Ikeda K., Mizuguchi K., Iwata H., Okuno Y. Improving ADME Prediction with Multitask Graph Neural Networks and Assessing Explainability in Lead Optimization 2025 https://doi.org/10.26434/chemrxiv-2025-ls77r
Kanno S.I., Kobayashi T., Watanabe R., Kurimasa A., Tanaka K., Yasui A., Ui A. Armadillo domain of ARID1A directly interacts with DNA-PKcs to couple chromatin remodeling with nonhomologous end joining (NHEJ) pathway. Nucleic acids research2025, 53(5) https://doi.org/10.1093/nar/gkaf150
Bekker G.J., Nagao C., Shirota M., Nakamura T., Katayama T., Kihara D., Kinoshita K., Kurisu G. Protein Data Bank Japan: Improved tools for sequence-oriented analysis of protein structures. Protein science : a publication of the Protein Society2025, 34(3), e70052 https://doi.org/10.1002/pro.70052
Bekker G.J., Nagao C., Shirota M., Nakamura T., Katayama T., Kihara D., Kinoshita K., Kurisu G. Protein Data Bank Japan: Computational Resources for Analysis of Protein Structures. Journal of molecular biology2025, 169013-169013 https://doi.org/10.1016/j.jmb.2025.169013
2024
Inoue R., Hosomi K., Park J., Sakaue H., Yumioka H., Kamitani H., Kinugasa Y., Harano K., Syauki A.Y., Doi M., Kageyama S., Yamamoto K., Mizuguchi K., Kunisawa J., Irie Y. Clinical Phenotypes Associated with the Gut Microbiome in Older Japanese People with Care Needs in a Nursing Home Nutrients2024, 16(22), 3839-3839 https://doi.org/10.3390/nu16223839
Maruyama S., Matsuoka T., Hosomi K., Park J., Murakami H., Miyachi M., Kawashima H., Mizuguchi K., Kobayashi T., Ooka T., Yamagata Z., Kunisawa J. High barley intake in non-obese individuals is associated with high natto consumption and abundance of butyrate-producing bacteria in the gut: a cross-sectional study Frontiers in Nutrition2024, 11 https://doi.org/10.3389/fnut.2024.1434150
Kageyama S., Inoue R., Hosomi K., Park J., Yumioka H., Doi M., Miyake M., Nagashio Y., Shibuya Y., Oka N., Akazawa H., Kanzaki S., Mizuguchi K., Kunisawa J., Irie Y. Association Between Gut Microbiome Composition and Physical Characteristics in Patients with Severe Motor and Intellectual Disabilities: Perspectives from Microbial Diversity Nutrients2024, 16(20), 3546-3546 https://doi.org/10.3390/nu16203546
Osorio R.S.A., Kosugi Y., Persson J.T.N., Mizuguchi K., Kitatani Y.N. A modern multi-omics data exploration experience with Panomicon Bioinformatics Advances2024 https://doi.org/10.1093/bioadv/vbae147
Shoji H., Hirano H., Nojima Y., Gunji D., Shinkura A., Muraoka S., Abe Y., Narumi R., Nagao C., Aoki M., Obama K., Honda K., Mizuguchi K., Tomonaga T., Saito Y., Yoshikawa T., Kato K., Boku N., Adachi J. Phosphoproteomic subtyping of gastric cancer reveals dynamic transformation with chemotherapy and guides targeted cancer treatment Cell Reports2024, 114774-114774 https://doi.org/10.1016/j.celrep.2024.114774
Sato H., Taketomi Y., Murase R., Park J., Hosomi K., Sanada T.J., Mizuguchi K., Arita M., Kunisawa J., Murakami M. Group X phospholipase A2 links colonic lipid homeostasis to systemic metabolism via host-microbiota interaction Cell Reports2024, 43(10), 114752-114752 https://doi.org/10.1016/j.celrep.2024.114752
Kuroda M., Kasahara Y., Hirose M., Yamaguma H., Oda M., Nagao C., Mizuguchi K. Construction of a Tm-Value Prediction Model and Molecular Dynamics Study of AmNA-Containing Gapmer Antisense Oligonucleotide Molecular Therapy - Nucleic Acids2024, 102272-102272 https://doi.org/10.1016/j.omtn.2024.102272
Uchida M., Park J., Fujie S., Hosomi K., Horii N., Watanabe K., Sanada K., Shinohara Y., Mizuguchi K., Kunisawa J., Iemitsu M., Miyachi M. Effect of resistance training and chicken meat on muscle strength and mass and the gut microbiome of older women: A randomized controlled trial Physiological Reports2024, 12(12) https://doi.org/10.14814/phy2.16100
Enomoto T., Shirai Y., Takeda Y., Edahiro R., Shichino S., Nakayama M., Itoh M.T., Noda Y., Adachi Y., Kawasaki T., Koba T., Futami Y., Yaga M., Hosono Y., Yoshimura H., Amiya S., Hara R., Yamamoto M., Nakatsubo D., Suga Y., Naito M., Masuhiro K., Hirata H., Iwahori K., Nagatomo I., Miyake K., Koyama S., Fukushima K., Shiroyama T., Naito Y., Futami S., Kitatani Y.N., Nojima S., Yanagawa M., Shintani Y., Itoh M.N., Mizuguchi K., Adachi J., Tomonaga T., Inoue Y., Kumanogoh A. SFTPB in serum extracellular vesicles as a biomarker of progressive pulmonary fibrosis JCI Insight2024, 9(11) https://doi.org/10.1172/jci.insight.177937
Yoshimura H., Takeda Y., Shirai Y., Yamamoto M., Nakatsubo D., Amiya S., Enomoto T., Hara R., Adachi Y., Edahiro R., Yaga M., Masuhiro K., Koba T., Takahashi M.I., Nakayama M., Takata S., Hosono Y., Obata S., Nishide M., Hata A., Yanagawa M., Namba S., Iwata M., Hamano M., Hirata H., Koyama S., Iwahori K., Nagatomo I., Suga Y., Miyake K., Shiroyama T., Fukushima K., Futami S., Naito Y., Kawasaki T., Mizuguchi K., Kawashima Y., Yamanishi Y., Adachi J., Itoh M.N., Ueki S., Kumanogoh A. Galectin-10 in serum extracellular vesicles reflects asthma pathophysiology Journal of Allergy and Clinical Immunology2024 https://doi.org/10.1016/j.jaci.2023年12月03日0
Saqib U., Demaree I.S., Obukhov A.G., Baig M.S., Khan M.S., Altwaijry N., Nasution M.A.F., Mizuguchi K., Hajela K. Structural and accessibility studies highlight the differential binding of clemizole to TRPC5 and TRPC6 Journal of Biomolecular Structure and Dynamics2024 https://doi.org/10.1080/07391102.2024.2306198
Tomoto M., Mineharu Y., Sato N., Tamada Y., Itoh M.N., Kuroda M., Adachi J., Takeda Y., Mizuguchi K., Kumanogoh A., Kitatani Y.N., Okuno Y. Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information Scientific Reports2024, 14(1) https://doi.org/10.1038/s41598-023-50905-8
Nagao C., Okuda H., Bekker G.J., Noguchi A., Takahashi T., Koizumi A., Youssefian S., Tezuka T., Akioka S. Familial Episodic Pain Syndrome: A Japanese Family Harboring the Novel Variant c.2431C>T (p.Leu811Phe) in SCN11A. Biochemical genetics2024 https://doi.org/10.1007/s10528-024-10888-1
2023
Gou Y., Re S., Mizuguchi K., Nagao C. Impact of Hydrogen Bonding on P-Glycoprotein Efflux Transport as Revealed by Evaluation of a De Novo Prediction Model ACS Medicinal Chemistry Letters2023 https://doi.org/10.1021/acsmedchemlett.3c00376
Koyama K., Hashimoto K., Nagao C., Mizuguchi K. Attention network for predicting T-cell receptor–peptide binding can associate attention with interpretable protein structural properties Frontiers in Bioinformatics2023, 3 https://doi.org/10.3389/fbinf.2023.1274599
Iwasaka C., Nanri H., Nakagata T., Ohno H., Tanisawa K., Konishi K., Murakami H., Hosomi K., Park J., Yamada Y., Ono R., Mizuguchi K., Kunisawa J., Miyachi M. Association of skeletal muscle function, quantity, and quality with gut microbiota in Japanese adults: A cross-sectional study. Geriatrics & gerontology international2023 https://doi.org/10.1111/ggi.14751
Yoshimura E., Hamada Y., Hatamoto Y., Nakagata T., Nanri H., Nakayama Y., Hayashi T., Suzuki I., Ando T., Ishikawa‐takata K., Tanaka S., Ono R., Park J., Hosomi K., Mizuguchi K., Kunisawa J., Miyachi M. Effects of energy loads on energy and nutrient absorption rates and gut microbiome in humans: A randomized crossover trial Obesity2023 https://doi.org/10.1002/oby.23935
Kageyama S., Inoue R., Park J., Hosomi K., Yumioka H., Suka T., Teramoto K., Syauki A.Y., Doi M., Sakaue H., Miyake M., Mizuguchi K., Kunisawa J., Irie Y. Changes in Fecal Gut Microbiome of Home Healthcare Patients with Disabilities through Consumption of Malted Rice Amazake Physiological Genomics2023 https://doi.org/10.1152/physiolgenomics.00062.2023
Park J., Bushita H., Nakano A., Hara A., Ueno H.M., Ozato N., Hosomi K., Kawashima H., Chen Y.A., Mohsen A., Ohno H., Konishi K., Tanisawa K., Nanri H., Murakami H., Miyachi M., Kunisawa J., Mizuguchi K., Araki M. Ramen Consumption and Gut Microbiota Diversity in Japanese Women: Cross-Sectional Data from the NEXIS Cohort Study Microorganisms2023, 11(8), 1892-1892 https://doi.org/10.3390/microorganisms11081892
Akazawa, N.; Nakamura, M.; Eda, N.; Murakami, H.; Nakagata, T.; Nanri, H.; Park, J.;
Hosomi, K.; Mizuguchi, K.; Kunisawa, J.; Miyachi, M.; Hoshikawa, M. Gut microbiota alternation with training periodization and physical fitness in
Japanese elite athletes Frontiers in Sports and Active Living2023, 5 https://doi.org/10.3389/fspor.2023.1219345
Kawashima, H.; Watanabe, R.; Esaki, T.; Kuroda, M.; Nagao, C.; Kitatani, Y.N.; Ohashi,
R.; Komura, H.; Mizuguchi, K. DruMAP: A Novel Drug Metabolism and Pharmacokinetics Analysis Platform Journal of Medicinal Chemistry2023 https://doi.org/10.1021/acs.jmedchem.3c00481
Alarabi, A.B.; Mohsen, A.; Taleb, Z.B.; Mizuguchi, K.; Alshbool, F.Z.; Khasawneh,
F.T. Predicting thrombotic cardiovascular outcomes induced by waterpipe-associated
chemicals using comparative toxicogenomic database: Genes, phenotypes, and
pathways Life Sciences2023, 323121694-121694 https://doi.org/10.1016/j.lfs.2023.121694
Martin, ; Watanabe, R.; Hashimoto, K.; Higashisaka, K.; Haga, Y.; Tsutsumi, Y.;
Mizuguchi, K. Evidence-Based Prediction of Cellular Toxicity for Amorphous Silica
Nanoparticles ACS Nano2023 https://doi.org/10.1021/acsnano.2c11968
Maruyama, S.; Matsuoka, T.; Hosomi, K.; Park, J.; Nishimura, M.; Murakami, H.; Konishi,
K.; Miyachi, M.; Kawashima, H.; Mizuguchi, K.; Kobayashi, T.; Ooka, T.; Yamagata, Z.;
Kunisawa, J. Characteristic Gut Bacteria in High Barley Consuming Japanese Individuals without
Hypertension Microorganisms2023 https://doi.org/10.3390/microorganisms11051246
Nojima, Y.; Aoki, M.; Re, S.; Hirano, H.; Abe, Y.; Narumi, R.; Muraoka, S.; Shoji, H.;
Honda, K.; Tomonaga, T.; Mizuguchi, K.; Boku, N.; Adachi, J. Integration of pharmacoproteomic and computational approaches reveals the cellular
signal transduction pathways affected by apatinib in gastric cancer cell
lines Computational and Structural Biotechnology Journal2023 https://doi.org/10.1016/j.csbj.202303006
Ikeda, K.; Maezawa, Y.; Yonezawa, T.; Shimizu, Y.; Tashiro, T.; Kanai, S.; Sugaya, N.;
Masuda, Y.; Inoue, N.; Niimi, T.; Masuya, K.; Mizuguchi, K.; Furuya, T.; Osawa, M. DLiP-PPI library: An integrated chemical database of small-to-medium-sized molecules
targeting protein–protein interactions Frontiers in Chemistry2023, 10 https://doi.org/10.3389/fchem.2022.1090643
Komura H., Watanabe R., Mizuguchi K. The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery Pharmaceutics2023, 15(11), 2619-2619 https://doi.org/10.3390/pharmaceutics15112619
2022
Watanabe, R.; Kawata, T.; Ueda, S.; Shinbo, T.; Higashimori, M.; Kitatani, Y.N.;
Mizuguchi, K. Prediction of the Contribution Ratio of a Target Metabolic Enzyme to Clearance from
Chemical Structure Information Molecular Pharmaceutics2022 https://doi.org/10.1021/acs.molpharmaceut.2c00698
Sawane, K.; Hosomi, K.; Park, J.; Ookoshi, K.; Nanri, H.; Nakagata, T.; Chen, Y.A.;
Mohsen, A.; Kawashima, H.; Mizuguchi, K.; Miyachi, M.; Kunisawa, J. Identification of Human Gut Microbiome Associated with Enterolignan
Production Microorganisms2022, 10(11), 2169-2169 https://doi.org/10.3390/microorganisms10112169
Hosoe, Y.; Miyanoiri, Y.; Re, S.; Ochi, S.; Asahina, Y.; Kawakami, T.; Kuroda, M.;
Mizuguchi, K.; Oda, M. Structural dynamics of the N‐terminal SH2 domain of PI3K in its free and CD28‐bound
states The FEBS Journal2022, 290(9), 2366-2378 https://doi.org/10.1111/febs.16666
Hosomi, K.; Saito, M.; Park, J.; Murakami, H.; Shibata, N.; Ando, M.; Nagatake, T.;
Konishi, K.; Ohno, H.; Tanisawa, K.; Mohsen, A.; Chen, Y.A.; Kawashima, H.; Kitatani,
Y.N.; Oka, Y.; Shimizu, H.; Furuta, M.; Tojima, Y.; Sawane, K.; Saika, A.; Kondo, S.;
Yonejima, Y.; Takeyama, H.; Matsutani, A.; Mizuguchi, K.; Miyachi, M.; Kunisawa,
J. Oral administration of Blautia wexlerae ameliorates obesity and type 2 diabetes via
metabolic remodeling of the gut microbiota Nature Communications2022, 13(1), 4477-4477 https://doi.org/10.1038/s41467-022-32015-7
Gupta, S.; Vundavilli, H.; Osorio, R.S.A.; Itoh, M.N.; Mohsen, A.; Datta, A.; Mizuguchi,
K.; Tripathi, L.P. Integrative Network Modeling Highlights the Crucial Roles of Rho-GDI Signaling
Pathway in the Progression of Non-Small Cell Lung Cancer. IEEE journal of biomedical and health informatics2022, PP https://doi.org/10.1109/JBHI.2022.3190038
Mohsen, A.; Chen, Y.A.; Osorio, R.S.A.; Higuchi, C.; Mizuguchi, K. Snaq: A Dynamic Snakemake Pipeline for Microbiome Data Analysis With QIIME2 Frontiers in Bioinformatics2022, 2893933-893933 https://doi.org/10.3389/fbinf.2022.893933
Park, J.; Hosomi, K.; Kawashima, H.; Chen, Y.A.; Mohsen, A.; Ohno, H.; Konishi, K.;
Tanisawa, K.; Kifushi, M.; Kogawa, M.; Takeyama, H.; Murakami, H.; Kubota, T.; Miyachi,
M.; Kunisawa, J.; Mizuguchi, K. Dietary Vitamin B1 Intake Influences Gut Microbial Community and the Consequent
Production of Short-Chain Fatty Acids. Nutrients2022, 14(10) https://doi.org/10.3390/nu14102078
Alarabi, A.B.; Mohsen, A.; Mizuguchi, K.; Alshbool, F.Z.; Khasawneh, F.T. Co-expression analysis to identify key modules and hub genes associated with COVID-19
in platelets BMC Medical Genomics2022, 15(1) https://doi.org/10.1186/s12920-022-01222-y
Ikubo, Y.; Sanada, T.J.; Hosomi, K.; Park, J.; Naito, A.; Shoji, H.; Misawa, T.; Suda,
R.; Sekine, A.; Sugiura, T.; Shigeta, A.; Nanri, H.; Sakao, S.; Tanabe, N.; Mizuguchi,
K.; Kunisawa, J.; Suzuki, T.; Tatsumi, K. Altered gut microbiota and its association with inflammation in patients with chronic
thromboembolic pulmonary hypertension: a single-center observational study in
Japan BMC Pulmonary Medicine2022, 22(1) https://doi.org/10.1186/s12890-022-01932-0
Kitatani, Y.N.; Itoh, M.N.; Takeda, Y.; Kuroda, M.; Hirata, H.; Miyake, K.; Shiroyama,
T.; Shirai, Y.; Noda, Y.; Adachi, Y.; Enomoto, T.; Amiya, S.; Adachi, J.; Narumi, R.;
Muraoka, S.; Tomonaga, T.; Kurohashi, S.; Cheng, F.; Tanaka, R.; Yada, S.; Aramaki, E.;
Wakamiya, S.; Chen, Y.A.; Higuchi, C.; Nojima, Y.; Fujiwara, T.; Nagao, C.; Matsumura,
Y.; Mizuguchi, K.; Kumanogoh, A.; Ueda, N. Data-driven patient stratification and drug target discovery by using medical
information and serum proteome data of idiopathic pulmonary fibrosis
patients 2022 https://doi.org/10.21203/rs.3.rs-405195/v2
Maruyama, S.; Matsuoka, T.; Hosomi, K.; Park, J.; Nishimura, M.; Murakami, H.; Konishi,
K.; Miyachi, M.; Kawashima, H.; Mizuguchi, K.; Kobayashi, T.; Ooka, T.; Yamagata, Z.;
Kunisawa, J. Classification of the Occurrence of Dyslipidemia Based on Gut Bacteria Related to
Barley Intake Frontiers in Nutrition2022, 9 https://doi.org/10.3389/fnut.2022.812469
Tsuji, T.; Hashiguchi, K.; Yoshida, M.; Ikeda, T.; Koga, Y.; Honda, Y.; Tanaka, T.; Re,
S.; Mizuguchi, K.; Takahashi, D.; Yazaki, R.; Ohshima, T. α-Amino acid and peptide synthesis using catalytic cross-dehydrogenative
coupling Nature Synthesis2022, 1(4), 304-312 https://doi.org/10.1038/s44160-022-00037-0
Hirano, H.; Abe, Y.; Nojima, Y.; Aoki, M.; Shoji, H.; Isoyama, J.; Honda, K.; Boku, N.;
Mizuguchi, K.; Tomonaga, T.; Adachi, J. Temporal dynamics from phosphoproteomics using endoscopic biopsy specimens provides
new therapeutic targets in stage IV gastric cancer Scientific Reports2022, 12(1) https://doi.org/10.1038/s41598-022-08430-7
Matsuoka, T.; Hosomi, K.; Park, J.; Goto, Y.; Nishimura, M.; Maruyama, S.; Murakami, H.;
Konishi, K.; Miyachi, M.; Kawashima, H.; Mizuguchi, K.; Kobayashi, T.; Yokomichi, H.;
Kunisawa, J.; Yamagata, Z. Relationships between barley consumption and gut microbiome characteristics in a
healthy Japanese population: a cross-sectional study BMC Nutrition2022, 8(1), 23-23 https://doi.org/10.1186/s40795-022-00500-3
Otoshi, T.; Nagano, T.; Park, J.; Hosomi, K.; Yamashita, T.; Tachihara, M.; Tabata, T.;
Sekiya, R.; Tanaka, Y.; Kobayashi, K.; Mizuguchi, K.; Itoh, T.; Maniwa, Y.; Kunisawa,
J.; Nishimura, Y. The Gut Microbiome as a Biomarker of Cancer Progression Among Female Never-smokers
With Lung Adenocarcinoma Anticancer Research2022, 42(3), 1589-1598 https://doi.org/10.21873/anticanres.15633
Miki, Y.; Taketomi, Y.; Kidoguchi, Y.; Yamamoto, K.; Muramatsu, K.; Nishito, Y.; Park,
J.; Hosomi, K.; Mizuguchi, K.; Kunisawa, J.; Soga, T.; Boilard, E.; Gowda, S.G.B.;
Ikeda, K.; Arita, M.; Murakami, M. Group IIA secreted phospholipase A2 controls skin carcinogenesis and psoriasis by
shaping the gut microbiota JCI Insight2022, 7(2) https://doi.org/10.1172/jci.insight.152611
Yamane, D.; Onitsuka, S.; Re, S.; Isogai, H.; Hamada, R.; Hiramoto, T.; Kawanishi, E.;
Mizuguchi, K.; Shindo, N.; Ojida, A. Selective covalent targeting of SARS-CoV-2 main protease by enantiopure
chlorofluoroacetamide Chemical Science2022, 13(10), 3027-3034 https://doi.org/10.1039/d1sc06596c
Arakawa, M.; Tabata, K.; Ishida, K.; Kobayashi, M.; Arai, A.; Ishikawa, T.; Suzuki, R.;
Takeuchi, H.; Tripathi, L.P.; Mizuguchi, K.; Morita, E. Flavivirus recruits the valosin-containing protein (VCP)/NPL4 complex to induce
stress granule disassembly for efficient viral genome replication Journal of Biological Chemistry2022, 101597-101597 https://doi.org/10.1016/j.jbc.2022.101597
Takano, J.; Ito, S.; Dong, Y.; Sharif, J.; Takagi, Y.N.; Umeyama, T.; Han, Y.W.; Isono,
K.; Kondo, T.; Iizuka, Y.; Miyai, T.; Koseki, Y.; Ikegaya, M.; Sakihara, M.; Nakayama,
M.; Ohara, O.; Hasegawa, Y.; Hashimoto, K.; Arner, E.; Klose, R.J.; Iwama, A.; Koseki,
H.; Ikawa, T. PCGF1-PRC1 links chromatin repression with DNA replication during hematopoietic cell
lineage commitment Nature Communications2022, 13(1), 7159-7159 https://doi.org/10.1038/s41467-022-34856-8
Pascarella, G.; Hon, C.C.; Hashimoto, K.; Busch, A.; Luginbühl, J.; Parr, C.; Yip, W.H.;
Abe, K.; Kratz, A.; Bonetti, A.; Agostini, F.; Severin, J.; Murayama, S.; Suzuki, Y.;
Gustincich, S.; Frith, M.; Carninci, P. Recombination of repeat elements generates somatic complexity in human
genomes. Cell2022, 185(16), 3025-3040 https://doi.org/10.1016/j.cell.2022年06月03日2
Vuoristo, S.; Bhagat, S.; Granskog, C.H.; Yoshihara, M.; Gawriyski, L.; Jouhilahti,
E.M.; Ranga, V.; Tamirat, M.; Huhtala, M.; Kirjanov, I.; Nykänen, S.; Krjutškov, K.;
Damdimopoulos, A.; Weltner, J.; Hashimoto, K.; Recher, G.; Ezer, S.; Paluoja, P.;
Paloviita, P.; Takegami, Y.; Kanemaru, A.; Lundin, K.; Airenne, T.T.; Otonkoski, T.;
Tapanainen, J.S.; Kawaji, H.; Murakawa, Y.; Bürglin, T.R.; Varjosalo, M.; Johnson, M.S.;
Tuuri, T.; Katayama, S.; Kere, J. DUX4 is a multifunctional factor priming human embryonic genome activation. iScience2022, 25(4), 104137-104137 https://doi.org/10.1016/j.isci.2022.104137
Kuroda, M.; Watanabe, R.; Esaki, T.; Kawashima, H.; Ohashi, R.; Sato, T.; Honma, T.;
Komura, H.; Mizuguchi, K. Utilizing public and private sector data to build better machine learning models for
the prediction of pharmacokinetic parameters. Drug discovery today2022, 103339-103339 https://doi.org/10.1016/j.drudis.2022.103339
2021
Kageyama, S.; Inoue, R.; Hosomi, K.; Park, J.; Yumioka, H.; Suka, T.; Kurohashi, Y.;
Teramoto, K.; Syauki, A.Y.; Doi, M.; Sakaue, H.; Mizuguchi, K.; Kunisawa, J.; Irie,
Y. Effects of Malted Rice Amazake on Constipation Symptoms and Gut Microbiota in
Children and Adults with Severe Motor and Intellectual Disabilities: A Pilot
Study Nutrients2021, 13(12), 4466-4466 https://doi.org/10.3390/nu13124466
Park, J.; Kato, K.; Murakami, H.; Hosomi, K.; Tanisawa, K.; Nakagata, T.; Ohno, H.;
Konishi, K.; Kawashima, H.; Chen, Y.A.; Mohsen, A.; Xiao, J.Z.; Odamaki, T.; Kunisawa,
J.; Mizuguchi, K.; Miyachi, M. Comprehensive analysis of gut microbiota of a healthy population and covariates
affecting microbial variation in two large Japanese cohorts BMC Microbiology2021, 21(1), 151-151 https://doi.org/10.1186/s12866-021-02215-0
Ueta, M.; Hosomi, K.; Park, J.; Mizuguchi, K.; Sotozono, C.; Kinoshita, S.; Kunisawa,
J. Categorization of the Ocular Microbiome in Japanese Stevens–Johnson Syndrome Patients
With Severe Ocular Complications Frontiers in Cellular and Infection Microbiology2021,
11741654-741654 https://doi.org/10.3389/fcimb.2021.741654
Mohsen, A.; Tripathi, L.P.; Mizuguchi, K. Deep Learning Prediction of Adverse Drug Reactions in Drug Discovery Using Open
TG–GATEs and FAERS Databases Frontiers in Drug Discovery2021, 1 https://doi.org/10.3389/fddsv.2021.768792
Kitatani, Y.N.; Mizuguchi, K.; Ueda, N. Subset-binding: A novel algorithm to detect paired itemsets from heterogeneous data
including biological datasets 2021 https://doi.org/10.21203/rs.3.rs-405195/v1
Lee, J.; Mohsen, A.; Banerjee, A.; Mccullough, L.D.; Mizuguchi, K.; Shimaoka, M.;
Kiyono, H.; Park, E.J. Distinct Age-Specific miRegulome Profiling of Isolated Small and Large Intestinal
Epithelial Cells in Mice International Journal of Molecular Sciences2021, 22(7),
3544-3544 https://doi.org/10.3390/ijms22073544
Matsumoto, N.; Park, J.; Tomizawa, R.; Kawashima, H.; Hosomi, K.; Mizuguchi, K.; Honda,
C.; Ozaki, R.; Iwatani, Y.; Watanabe, M.; Kunisawa, J. Relationship between Nutrient Intake and Human Gut Microbiota in Monozygotic
Twins Medicina2021, 57(3), 275-275 https://doi.org/10.3390/medicina57030275
Vundavilli, H.; P.tripathi, L.; Datta, A.; Mizuguchi, K. Network Modeling and Inference of Peroxisome Proliferator-Activated Receptor Pathway
in High fat diet-linked Obesity. Journal of theoretical biology2021, 110647-110647 https://doi.org/10.1016/j.jtbi.2021.110647
Watanabe, R.; Esaki, T.; Ohashi, R.; Kuroda, M.; Kawashima, H.; Komura, H.; Kitatani,
Y.N.; Mizuguchi, K. Development of an In Silico Prediction Model for P-glycoprotein Efflux Potential in
Brain Capillary Endothelial Cells toward the Prediction of Brain
Penetration Journal of Medicinal Chemistry2021 https://doi.org/10.1021/acs.jmedchem.0c02011
Re, S.; Mizuguchi, K. Glycan Cluster Shielding and Antibody Epitopes on Lassa Virus Envelop
Protein The Journal of Physical Chemistry B2021, 125(8), 2089-2097 https://doi.org/10.1021/acs.jpcb.0c11516
Abugessaisa, I.; Ramilowski, J.A.; Lizio, M.; Severin, J.; Hasegawa, A.; Harshbarger,
J.; Kondo, A.; Noguchi, S.; Yip, C.W.; Ooi, J.L.C.; Tagami, M.; Hori, F.; Agrawal, S.;
Hon, C.C.; Cardon, M.; Ikeda, S.; Ono, H.; Bono, H.; Kato, M.; Hashimoto, K.; Bonetti,
A.; Kato, M.; Kobayashi, N.; Shin, J.; Hoon, M.D.; Hayashizaki, Y.; Carninci, P.;
Kawaji, H.; Kasukawa, T. FANTOM enters 20th year: expansion of transcriptomic atlases and functional
annotation of non-coding RNAs. Nucleic acids research2021, 49(D1), D892-D898 https://doi.org/10.1093/nar/gkaa1054
2020
Tripathi, L.P.; Itoh, M.N.; Takeda, Y.; Tsujino, K.; Kondo, Y.; Kumanogoh, A.;
Mizuguchi, K. Integrative Analysis Reveals Common and Unique Roles of Tetraspanins in Fibrosis and
Emphysema Frontiers in Genetics2020, 11585998-585998 https://doi.org/10.3389/fgene.2020.585998
Chen, Y.A.; Park, J.; Kitatani, Y.N.; Kawashima, H.; Mohsen, A.; Hosomi, K.; Tanisawa,
K.; Ohno, H.; Konishi, K.; Murakami, H.; Miyachi, M.; Kunisawa, J.; Mizuguchi, K. MANTA, an integrative database and analysis platform that relates microbiome and
phenotypic data PLOS ONE2020, 15(12), e0243609-e0243609 https://doi.org/10.1371/journal.pone.0243609
Afanasyeva, A.; Nagao, C.; Mizuguchi, K. Developing a Kinase-Specific Target Selection Method Using a Structure-Based Machine
Learning Approach Advances and Applications in Bioinformatics and Chemistry2020, Volume
1327-40 https://doi.org/10.2147/aabc.s278900
Nojima, Y.; Takeda, Y.; Maeda, Y.; Bamba, T.; Fukusaki, E.; Itoh, M.N.; Mizuguchi, K.;
Kumanogoh, A. Metabolomic analysis of fibrotic mice combined with public RNA-Seq human lung data
reveal potential diagnostic biomarker candidates for lung fibrosis. FEBS open bio2020, 10(11), 2427-2436 https://doi.org/10.1002/2211-5463.12982
Osorio, R.S.A.; Persson, J.T.N.; Nojima, Y.; Kosugi, Y.; Mizuguchi, K.; Kitatani,
Y.N. Panomicon: A web-based environment for interactive, visual analysis of multi-omics
data. Heliyon2020, 6(8), e04618-e04618 https://doi.org/10.1016/j.heliyon.2020.e04618
Saito, A.; Tsuchiya, D.; Sato, S.; Okamoto, A.; Murakami, Y.; Mizuguchi, K.; Toh, H.;
Nemoto, W. Update of the GRIP web service. Journal of receptor and signal transduction research2020, 40(4),
348-356 https://doi.org/10.1080/10799893.2020.1734821
Tabata, T.; Yamashita, T.; Hosomi, K.; Park, J.; Hayashi, T.; Yoshida, N.; Saito, Y.;
Fukuzawa, K.; Konishi, K.; Murakami, H.; Kawashima, H.; Mizuguchi, K.; Miyachi, M.;
Kunisawa, J.; Hirata, K.I. Gut microbial composition in patients with atrial fibrillation: effects of diet and
drugs. Heart and vessels2020, 36(1), 105-114 https://doi.org/10.1007/s00380-020-01669-y
Sanada, T.J.; Hosomi, K.; Shoji, H.; Park, J.; Naito, A.; Ikubo, Y.; Yanagisawa, A.;
Kobayashi, T.; Miwa, H.; Suda, R.; Sakao, S.; Mizuguchi, K.; Kunisawa, J.; Tanabe, N.;
Tatsumi, K. Gut microbiota modification suppresses the development of pulmonary arterial
hypertension in an SU5416/hypoxia rat model Pulmonary Circulation2020, 10(3),
204589402092914-204589402092914 https://doi.org/10.1177/2045894020929147
Tokunaga, M.; Miyamoto, Y.; Suzuki, T.; Otani, M.; Inuki, S.; Esaki, T.; Nagao, C.;
Mizuguchi, K.; Ohno, H.; Yoneda, Y.; Okamoto, T.; Oka, M.; Matsuura, Y. Novel anti-flavivirus drugs targeting the nucleolar distribution of core
protein. Virology2020, 54141-51 https://doi.org/10.1016/j.virol.2019年11月01日5
Kajihara, D.; Hon, C.C.; Abdullah, A.N.; Jr, J.W.; Moretti, A.I.S.; Poloni, J.F.;
Bonatto, D.; Hashimoto, K.; Carninci, P.; Laurindo, F.R.M. Analysis of splice variants of the human protein disulfide isomerase (P4HB)
gene. BMC genomics2020, 21(1), 766-766 https://doi.org/10.1186/s12864-020-07164-y
Taguchi, A.; Nagasaka, K.; Plessy, C.; Nakamura, H.; Kawata, Y.; Kato, S.; Hashimoto,
K.; Nagamatsu, T.; Oda, K.; Kukimoto, I.; Kawana, K.; Carninci, P.; Osuga, Y.; Fujii,
T. Use of Cap Analysis Gene Expression to detect human papillomavirus promoter activity
patterns at different disease stages. Scientific reports2020, 10(1), 17991-17991 https://doi.org/10.1038/s41598-020-75133-2
Komura, H.; Watanabe, R.; Kawashima, H.; Ohashi, R.; Kuroda, M.; Sato, T.; Honma, T.;
Mizuguchi, K. A public–private partnership to enrich the development of in silico predictive models
for pharmacokinetic and cardiotoxic properties Drug Discovery Today2020, 26(5), 1275-1283 https://doi.org/10.1016/j.drudis.2021年01月02日4
Esaki, T.; Kumazawa, K.; Takahashi, K.; Watanabe, R.; Masuda, T.; Watanabe, H.; Shimizu,
Y.; Okada, A.; Takimoto, S.; Shimada, T.; Ikeda, K. Open Innovation Platform using Cloud-based Applications and Collaborative Space: A
Case Study of Solubility Prediction Model Development Chem-Bio Informatics Journal2020, 20(0), 5-18 https://doi.org/10.1273/cbij.20.5
Afanasyeva, A.; Nagao, C.; Mizuguchi, K. Developing a Kinase-Specific Target Selection Method Using a Structure-Based Machine
Learning Approach Advances and Applications in Bioinformatics and Chemistry2020, Volume
1327-40 https://doi.org/10.2147/AABC.S278900
2019
Mohsen, A.; Park, J.; Chen, Y.A.; Kawashima, H.; Mizuguchi, K. Impact of quality trimming on the efficiency of reads joining and diversity analysis
of Illumina paired-end reads in the context of QIIME1 and QIIME2 microbiome analysis
frameworks BMC Bioinformatics2019, 20(1), 581 https://doi.org/10.1186/s12859-019-3187-5
Allendes, R.S.; Tripathi, L.P.; Mizuguchi, K. CLINE: a web-tool for the comparison of biological dendrogram structures BMC Bioinformatics2019, 20(1), 528 https://doi.org/10.1186/s12859-019-3149-y
Miyake, K.; Sakane, A.; Tsuchiya, Y.; Sagawa, I.; Tomida, Y.; Kasahara, J.; Imoto, I.;
Watanabe, S.; Higo, D.; Mizuguchi, K.; Sasaki, T. Actin Cytoskeletal Reorganization Function of JRAB/MICAL-L2 Is Fine-tuned by
Intramolecular Interaction between First LIM Zinc Finger and C-terminal Coiled-coil
Domains Scientific Reports2019, 9(1), 12794-12794 https://doi.org/10.1038/s41598-019-49232-8
Watanabe, R.; Ohashi, R.; Esaki, T.; Kawashima, H.; Natsume, Y.; Nagao, C.; Mizuguchi,
K. Development of an in silico prediction system of human renal excretion and clearance
from chemical structure information incorporating fraction unbound in plasma as a
descriptor Scientific Reports2019, 9(1), 18782-18782 https://doi.org/10.1038/s41598-019-55325-1
Afanasyeva, A.; Nagao, C.; Mizuguchi, K. Prediction of the secondary structure of short DNA aptamers Biophysics and Physicobiology2019, 16(0), 287-294 https://doi.org/10.2142/biophysico.16.0_287
R§, W.; R§, O.; Esaki, T.; Taniguchi, T.; Torimoto, N.; Watanabe, T.; Ogasawara, Y.;
Takahashi, T.; Tsukimoto, M.; Mizuguchi, K. Development of Simplified in Vitro P-Glycoprotein Substrate Assay and in Silico
Prediction Models To Evaluate Transport Potential of P-Glycoprotein Mol. Pharmaceutics2019, 16(5), 1851-1863
Reviews
2025
Murakami K., Nguyen T.H.V., Nagao C., Mizuguchi K., Bitan G. Lysine-Targeting Inhibitors of Amyloidogenic Protein Aggregation: A Promise for Neurodegenerative Proteinopathies JACS Au2025 https://doi.org/10.1021/jacsau.5c00269
2024
Tripathi L.P., Osorio R.S.A., Murakami Y., Chen Y.A., Mizuguchi K. Network-Based Analysis for Biological Knowledge Discovery Reference Module in Life Sciences2024 https://doi.org/10.1016/b978-0-323-95502-7.00272-4
2023
Komura H., Watanabe R., Mizuguchi K. The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery Pharmaceutics2023, 15(11), 2619-2619 https://doi.org/10.3390/pharmaceutics15112619
2022
Murakami, Y.; Mizuguchi, K. Recent developments of sequence-based prediction of protein-protein
interactions. Biophysical reviews2022, 1-19 https://doi.org/10.1007/s12551-022-01038-1
Kuroda, M.; Watanabe, R.; Esaki, T.; Kawashima, H.; Ohashi, R.; Sato, T.; Honma, T.;
Komura, H.; Mizuguchi, K. Utilizing public and private sector data to build better machine learning models for
the prediction of pharmacokinetic parameters. Drug discovery today2022, 103339-103339 https://doi.org/10.1016/j.drudis.2022.103339
2021
Komura, H.; Watanabe, R.; Kawashima, H.; Ohashi, R.; Kuroda, M.; Sato, T.; Honma, T.;
Mizuguchi, K. A public–private partnership to enrich the development of in silico predictive models
for pharmacokinetic and cardiotoxic properties Drug Discovery Today2021 https://doi.org/10.1016/j.drudis.2021年01月02日4
2019
Chen, Y.A.; Tripathi, L.P.; Mizuguchi, K. Data Warehousing with TargetMine for Omics Data Analysis Methods in Molecular Biology2019, 35-64 https://doi.org/10.1007/978-1-4939-9442-7_3
Tripathi, L.P.; Chen, Y.A.; Mizuguchi, K.; Morita, E. Network-Based Analysis of Host-Pathogen Interactions Encyclopedia of Bioinformatics and Computational Biology2019, 932 https://doi.org/10.1016/b978-0-12-809633-8.20170-2
Tripathi, L.P.; Chen, Y.A.; Mizuguchi, K.; Murakami, Y. Network-Based Analysis for Biological Discovery Encyclopedia of Bioinformatics and Computational Biology2019, 283 https://doi.org/10.1016/b978-0-12-809633-8.20674-2
Tripathi, L.P.; Esaki, T.; Itoh, M.N.; Chen, Y.A.; Mizuguchi, K. Integrative Analysis of Multi-Omics Data Encyclopedia of Bioinformatics and Computational Biology2019, 194 https://doi.org/10.1016/b978-0-12-809633-8.20096-4
Books
2020
Afanasyeva, A.; Nagao, C.; Mizuguchi, K. Protein Interactions: Computational Methods, Analysis and Applications
World Scientific 2020 (DOI: 10.1142/11596) https://doi.org/10.1142/11596
