Tohoku University Tohoku Medical Megabank Organization (Kengo Kinoshita)
2022.08.12

1.   Iemura Kenji, Anzawa Hayato, Funayama Ryo, et al. High levels of chromosomal instability facilitate the tumor growth and sphere formation. Cancer Science. 2022; 113 (8): 2727-2737. doi:10.1111/cas.15457  
2.   Hishinuma Eiji, Narita Yoko, Obuchi Kai, et al. Importance of Rare DPYD Genetic Polymorphisms for 5-Fluorouracil Therapy in the Japanese Population. Frontiers in Pharmacology. 2022; 13 : . doi:10.3389/fphar.2022.930470  
3.   Ohneda Kinuko, Hiratsuka Masahiro, Kawame Hiroshi, et al. A Pilot Study for Return of Individual Pharmacogenomic Results to Population-Based Cohort Study Participants. JMA Journal. 2022; 5 (2): . doi:10.31662/jmaj.2021-0156  
4.   Sugawara Junichi, Ishikuro Mami, Obara Taku, et al. Maternal Baseline Characteristics and Perinatal Outcomes: The Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. Journal of epidemiology. 2022; 32 (2): 69-79. doi:10.2188/jea.JE20200338  
5.   Goto Atsushi, Suzuki Shiori, Katagiri Ryoko, et al. Public Access to Summary Statistics for Genome-wide Association Studies of Body Mass Index, Weight, and Height Among Healthy Japanese Individuals: The Japanese Consortium of Genetic Epidemiology Studies. Journal of Epidemiology. 2022; 32 (2): JE20210459. doi:10.2188/jea.JE20210459  
6.   Kawame Hiroshi, Fukushima Akimune, Fuse Nobuo, et al. The return of individual genomic results to research participants: design and pilot study of Tohoku Medical Megabank Project. Journal of Human Genetics. 2022; 67 (1): 9-17. doi:10.1038/s10038-021-00952-8  
7.   Fuse Nobuo, Sakurai Miyuki, Motoike Ikuko N., et al. Genome-wide Association Study of Axial Length in Population-based Cohorts in Japan. Ophthalmology Science. 2022; 2 (1): 100113. doi:10.1016/j.xops.2022.100113  
8.   Obayashi Takeshi, Hibara Himiko, Kagaya Yuki, et al. ATTED-II v11: A Plant Gene Coexpression Database Using a Sample Balancing Technique by Subagging of Principal Components. Plant and Cell Physiology. 2022; 63 (6): 869-881. doi:10.1093/pcp/pcac041  
9.   Okazaki Keito, Anzawa Hayato, Katsuoka Fumiki, et al. CEBPB is required for NRF2-mediated drug resistance in NRF2-activated non-small cell lung cancer cells. The Journal of Biochemistry. 2022; 171 (5): 567-578. doi:10.1093/jb/mvac013  
10.   Zempo Hirofumi, Kim Su-Jeong, Fuku Noriyuki, et al. A pro-diabetogenic mtDNA polymorphism in the mitochondrial-derived peptide, MOTS-c. Aging. 2021; 13 (2): 1692-1717. doi:10.18632/aging.202529  
11.   Uchida Yasuo, Higuchi Tomoya, Shirota Matsuyuki, et al. Identification and Validation of Combination Plasma Biomarker of Afamin, Fibronectin and Sex Hormone-Binding Globulin to Predict Pre-eclampsia. Biological and Pharmaceutical Bulletin. 2021; 44 (6): 804-815. doi:10.1248/bpb.b20-01043  
12.   Suzuki Shiori, Goto Atsushi, Nakatochi Masahiro, et al. Body mass index and colorectal cancer risk: A Mendelian randomization study. Cancer Science. 2021; 112 (4): 1579-1588. doi:10.1111/cas.14824  
13.   Omori Satoshi, Tsugita Misato, Hoshikawa Yasuto, et al. Tim4 recognizes carbon nanotubes and mediates phagocytosis leading to granuloma formation. Cell Reports. 2021; 34 (6): 108734. doi:10.1016/j.celrep.2021.108734  
14.   Yamada Mitsuhiro, Motoike Ikuko N., Kojima Kaname, et al. Genetic loci for lung function in Japanese adults with adjustment for exhaled nitric oxide levels as airway inflammation indicator. Communications Biology. 2021; 4 (1): 1288. doi:10.1038/s42003-021-02813-8  
15.   Kumondai Masaki, Gutiérrez Rico Evelyn Marie, Hishinuma Eiji, et al. Functional Characterization of 40 CYP3A4 Variants by Assessing Midazolam 1′-Hydroxylation and Testosterone 6 β -Hydroxylation. Drug Metabolism and Disposition. 2021; 49 (3): 212-220. doi:10.1124/dmd.120.000261  
16.   Shiihara Masahiro, Ishikawa Tomohiko, Saiki Yuriko, et al. Development of a system combining comprehensive genotyping and organoid cultures for identifying and testing genotype-oriented personalised medicine for pancreatobiliary cancers. European Journal of Cancer. 2021; 148 : 239-250. doi:10.1016/j.ejca.2021.01.047  
17.   Saito Sakae, Aoki Yuichi, Tamahara Toru, et al. Oral Microbiome Analysis in Prospective Genome Cohort Studies of the Tohoku Medical Megabank Project. Frontiers in Cellular and Infection Microbiology. 2021; 10 : . doi:10.3389/fcimb.2020.604596  
18.   Ogishima Soichi, Nagaie Satoshi, Mizuno Satoshi, et al. dbTMM: an integrated database of large-scale cohort, genome and clinical data for the Tohoku Medical Megabank Project. Human Genome Variation. 2021; 8 (1): 44. doi:10.1038/s41439-021-00175-5  
19.   Nagaoka Shinichi, Yamaguchi-Kabata Yumi, Shiga Naomi, et al. Estimation of the carrier frequencies and proportions of potential patients by detecting causative gene variants associated with autosomal recessive bone dysplasia using a whole-genome reference panel of Japanese individuals. Human Genome Variation. 2021; 8 (1): 2. doi:10.1038/s41439-020-00133-7  
20.   Hozawa Atsushi, Tanno Kozo, Nakaya Naoki, et al. Study profile of the tohoku medical megabank community-based cohort study. Journal of Epidemiology. 2021; 31 (1): 65-76. doi:10.2188/jea.JE20190271  
21.   Shido Kosuke, Kojima Kaname, Shirota Matsuyuki, et al. GWAS Identified IL4R and the Major Histocompatibility Complex Region as the Associated Loci of Total Serum IgE Levels in 9,260 Japanese Individuals. Journal of Investigative Dermatology. 2021; 141 (11): 2749-2752. doi:10.1016/j.jid.2021.02.762  
22.   Kumondai Masaki, Ito Akio, Gutiérrez Rico Evelyn Marie, et al. Functional Assessment of 12 Rare Allelic CYP2C9 Variants Identified in a Population of 4773 Japanese Individuals. Journal of Personalized Medicine. 2021; 11 (2): 94. doi:10.3390/jpm11020094  
23.   Kumondai Masaki, Gutiérrez Rico Evelyn, Hishinuma Eiji, et al. Functional Characterization of 21 Rare Allelic CYP1A2 Variants Identified in a Population of 4773 Japanese Individuals by Assessing Phenacetin O-Deethylation. Journal of Personalized Medicine. 2021; 11 (8): 690. doi:10.3390/jpm11080690  
24.   Saigusa Daisuke, Hishinuma Eiji, Matsukawa Naomi, et al. Comparison of Kit-Based Metabolomics with Other Methodologies in a Large Cohort, towards Establishing Reference Values. Metabolites. 2021; 11 (10): 652. doi:10.3390/metabo11100652  
25.   Otsuki Akihito, Okamura Yasunobu, Aoki Yuichi, et al. Identification of Dominant Transcripts in Oxidative Stress Response by a Full-Length Transcriptome Analysis. Molecular and Cellular Biology. 2021; 41 (2): . doi:10.1128/MCB.00472-20  
26.   Takayama Jun, Tadaka Shu, Yano Kenji, et al. Construction and integration of three de novo Japanese human genome assemblies toward a population-specific reference. Nature Communications. 2021; 12 (1): 226. doi:10.1038/s41467-020-20146-8  
27.   Tadaka Shu, Hishinuma Eiji, Komaki Shohei, et al. jMorp updates in 2020: large enhancement of multi-omics data resources on the general Japanese population. Nucleic Acids Research. 2021; 49 (D1): D536-D544. doi:10.1093/nar/gkaa1034  
28.   Tokunaga Hideki, Iida Keita, Hozawa Atsushi, et al. Novel candidates of pathogenic variants of the BRCA1 and BRCA2 genes from a dataset of 3,552 Japanese whole genomes (3.5KJPNv2). PLOS ONE. 2021; 16 (1): e0236907. doi:10.1371/journal.pone.0236907  
29.   Kojima Kaname, Shido Kosuke, Tamiya Gen, et al. Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks. Scientific Reports. 2021; 11 (1): 1213. doi:10.1038/s41598-020-79995-4  
30.   Sakurai-Yageta Mika, Kumada Kazuki, Gocho Chinatsu, et al. Japonica Array NEO with increased genome-wide coverage and abundant disease risk SNPs. The Journal of Biochemistry. 2021; 170 (3): 399-410. doi:10.1093/jb/mvab060  
31.   Hishinuma Eiji, Shimada Muneaki, Matsukawa Naomi, et al. Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer. Toxins. 2021; 13 (7): 461. doi:10.3390/toxins13070461  
32.   Shigemizu Daichi, Mitsumori Risa, Akiyama Shintaro, et al. Ethnic and trans-ethnic genome-wide association studies identify new loci influencing Japanese Alzheimer’s disease risk. Translational Psychiatry. 2021; 11 (1): 151. doi:10.1038/s41398-021-01272-3  
33.   Ishikawa Tomohiko, Ogawa Takenori, Nakanome Ayako, et al. Whole exome sequencing and establishment of an organoid culture of the carcinoma showing thymus-like differentiation (CASTLE) of the parotid gland. Virchows Archiv. 2021; 478 (6): 1149-1159. doi:10.1007/s00428-020-02981-8  
34.   Anzawa Hayato, Yamagata Hitoshi, Kinoshita Kengo. Theoretical characterisation of strand cross-correlation in ChIP-seq. BMC Bioinformatics. 2020; 21 (1): 417. doi:10.1186/s12859-020-03729-6  
35.   Saigusa Daisuke, Motoike Ikuko N., Saito Sakae, et al. Impacts of NRF2 activation in non–small‐cell lung cancer cell lines on extracellular metabolites. Cancer Science. 2020; 111 (2): 667-678. doi:10.1111/cas.14278  
36.   Koshiba Seizo, Motoike Ikuko N., Saigusa Daisuke, et al. Identification of critical genetic variants associated with metabolic phenotypes of the Japanese population. Communications Biology. 2020; 3 (1): 662. doi:10.1038/s42003-020-01383-5  
37.   Ishida Noriko, Aoki Yuichi, Katsuoka Fumiki, et al. Landscape of electrophilic and inflammatory stress-mediated gene regulation in human lymphoblastoid cell lines. Free Radical Biology and Medicine. 2020; 161 : 71-83. doi:10.1016/j.freeradbiomed.2020.09.023  
38.   Kuriyama Shinichi, Metoki Hirohito, Kikuya Masahiro, et al. Cohort Profile: Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study): rationale, progress and perspective. International Journal of Epidemiology. 2020; 49 (1): 18-19m. doi:10.1093/ije/dyz169  
39.   Shirota Matsuyuki, Saigusa Daisuke, Yamashita Riu, et al. Longitudinal plasma amino acid profiling with maternal genomic background throughout human pregnancy. Medical Mass Spectrometry. 2020; 4 (1): 36-49. doi:10.24508/mms.2020.06.001  
40.   Kagaya Yuki, Minei Ryuhei, Duong Ha T T, et al. Metagenome Sequences from the Environment of Diseased Otter Clams, Lutraria rhynchaena, from a Farm in Vietnam. Microbiology Resource Announcements. 2020; 9 (2): . doi:10.1128/MRA.01068-19  
41.   Okazaki Keito, Anzawa Hayato, Liu Zun, et al. Enhancer remodeling promotes tumor-initiating activity in NRF2-activated non-small cell lung cancers. Nature Communications. 2020; 11 (1): 5911. doi:10.1038/s41467-020-19593-0  
42.   Lin Yingsong, Nakatochi Masahiro, Hosono Yasuyuki, et al. Genome-wide association meta-analysis identifies GP2 gene risk variants for pancreatic cancer. Nature Communications. 2020; 11 (1): 3175. doi:10.1038/s41467-020-16711-w  
43.   Kojima Kaname, Tadaka Shu, Katsuoka Fumiki, et al. A genotype imputation method for de-identified haplotype reference information by using recurrent neural network. PLOS Computational Biology. 2020; 16 (10): e1008207. doi:10.1371/journal.pcbi.1008207  
44.   Wagata Maiko, Ishikuro Mami, Obara Taku, et al. Low birth weight and abnormal pre-pregnancy body mass index were at higher risk for hypertensive disorders of pregnancy. Pregnancy Hypertension. 2020; 22 : 119-125. doi:10.1016/j.preghy.2020.08.001  
45.   Amano Ryota, Karashima Akihiro, Motoike Ikuko, et al. Consistency index of daily activity pattern and its correlations with subjective ratings of QOL. Sleep and Biological Rhythms. 2020; 18 (4): 297-304. doi:10.1007/s41105-020-00271-z  
46.   Tsuboi Akito, Matsui Hiroyuki, Shiraishi Naru, et al. Design and Progress of Oral Health Examinations in the Tohoku Medical Megabank Project. The Tohoku Journal of Experimental Medicine. 2020; 251 (2): 97-115. doi:10.1620/tjem.251.97  
47.   Takahashi Yuta, Ueki Masao, Yamada Makoto, et al. Improved metabolomic data-based prediction of depressive symptoms using nonlinear machine learning with feature selection. Translational Psychiatry. 2020; 10 (1): 157. doi:10.1038/s41398-020-0831-9  
48.   Takahashi Yuta, Ueki Masao, Tamiya Gen, et al. Machine learning for effectively avoiding overfitting is a crucial strategy for the genetic prediction of polygenic psychiatric phenotypes. Translational Psychiatry. 2020; 10 (1): 294. doi:10.1038/s41398-020-00957-5  
49.   Sugawara Junichi, Ochi Daisuke, Yamashita Riu, et al. Maternity Log study: a longitudinal lifelog monitoring and multiomics analysis for the early prediction of complicated pregnancy. BMJ Open. 2019; 9 (2): e025939. doi:10.1136/bmjopen-2018-025939  
50.   Mori Minako, Hira Asuka, Yoshida Kenichi, et al. Pathogenic mutations identified by a multimodality approach in 117 Japanese Fanconi anemia patients. Haematologica. 2019; 104 (10): 1962-1973. doi:10.3324/haematol.2018.207241  
51.   Yamaguchi-Kabata Yumi, Yasuda Jun, Uruno Akira, et al. Estimating carrier frequencies of newborn screening disorders using a whole-genome reference panel of 3552 Japanese individuals. Human Genetics. 2019; 138 (4): 389-409. doi:10.1007/s00439-019-01998-7  
52.   Tadaka Shu, Katsuoka Fumiki, Ueki Masao, et al. 3.5KJPNv2: an allele frequency panel of 3552 Japanese individuals including the X chromosome. Human Genome Variation. 2019; 6 (1): 28. doi:10.1038/s41439-019-0059-5  
53.   Nagasaki Masao, Kuroki Yoko, Shibata Tomoko F., et al. Construction of JRG (Japanese reference genome) with single-molecule real-time sequencing. Human Genome Variation. 2019; 6 (1): 27. doi:10.1038/s41439-019-0057-7  
54.   Sato Tomonori, Kawasaki Yoshihide, Maekawa Masamitsu, et al. Value of global metabolomics in association with diagnosis and clinicopathological factors of renal cell carcinoma. International Journal of Cancer. 2019; 145 (2): 484-493. doi:10.1002/ijc.32115  
55.   Sakurai Rieko, Ueki Masao, Makino Satoshi, et al. Outlier detection for questionnaire data in biobanks. International Journal of Epidemiology. 2019; 48 (4): 1305-1315. doi:10.1093/ije/dyz012  
56.   Fuse Nobuo, Sakurai-Yageta Mika, Katsuoka Fumiki, et al. Establishment of Integrated Biobank for Precision Medicine and Personalized Healthcare: The Tohoku Medical Megabank Project. JMA Journal. 2019; 2 (2): 113-122. doi:10.31662/jmaj.2019-0014  
57.   Kiniwa Yukiko, Yasuda Jun, Saito Sakae, et al. Identification of genetic alterations in extramammary Paget disease using whole exome analysis. Journal of Dermatological Science. 2019; 94 (1): 229-235. doi:10.1016/j.jdermsci.2019.03.006  
58.   Mizuguchi Takeshi, Suzuki Takeshi, Abe Chihiro, et al. A 12-kb structural variation in progressive myoclonic epilepsy was newly identified by long-read whole-genome sequencing. Journal of Human Genetics. 2019; 64 (5): 359-368. doi:10.1038/s10038-019-0569-5  
59.   Obayashi Takeshi, Kagaya Yuki, Aoki Yuichi, et al. COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference. Nucleic Acids Research. 2019; 47 (D1): D55-D62. doi:10.1093/nar/gky1155  
60.   Yasuda Jun, Kinoshita Kengo, Katsuoka Fumiki, et al. Genome analyses for the Tohoku Medical Megabank Project towards establishment of personalized healthcare. The Journal of Biochemistry. 2019; 165 (2): 139-158. doi:10.1093/jb/mvy096  
61.   Mimori Takahiro, Yasuda Jun, Kuroki Yoko, et al. Construction of full-length Japanese reference panel of class I HLA genes with single-molecule, real-time sequencing. The Pharmacogenomics Journal. 2019; 19 (2): 136-146. doi:10.1038/s41397-017-0010-4  
62.   Yamada Kazunori D., Kinoshita Kengo. De novo profile generation based on sequence context specificity with the long short-term memory network. BMC Bioinformatics. 2018; 19 (1): 272. doi:10.1186/s12859-018-2284-1  
63.   Okamura Yasunobu, Kinoshita Kengo. Matataki: an ultrafast mRNA quantification method for large-scale reanalysis of RNA-Seq data. BMC Bioinformatics. 2018; 19 (1): 266. doi:10.1186/s12859-018-2279-y  
64.   Yasuda Jun, Katsuoka Fumiki, Danjoh Inaho, et al. Regional genetic differences among Japanese populations and performance of genotype imputation using whole-genome reference panel of the Tohoku Medical Megabank Project. BMC Genomics. 2018; 19 (1): 551. doi:10.1186/s12864-018-4942-0  
65.   Koshiba Seizo, Motoike Ikuko, Saigusa Daisuke, et al. Omics research project on prospective cohort studies from the Tohoku Medical Megabank Project. Genes to Cells. 2018; 23 (6): 406-417. doi:10.1111/gtc.12588  
66.   Yamaguchi-Kabata Yumi, Yasuda Jun, Tanabe Osamu, et al. Evaluation of reported pathogenic variants and their frequencies in a Japanese population based on a whole-genome reference panel of 2049 individuals. Journal of Human Genetics. 2018; 63 (2): 213-230. doi:10.1038/s10038-017-0347-1  
67.   Doi Kent, Nishida Osamu, Shigematsu Takashi, et al. The Japanese Clinical Practice Guideline for acute kidney injury 2016. Journal of Intensive Care. 2018; 6 (1): 48. doi:10.1186/s40560-018-0308-6  
68.   Kondo Hiroko X, Yoshida Norio, Shirota Matsuyuki, Kinoshita Kengo. Molecular Mechanism of Depolarization-Dependent Inactivation in W366F Mutant of Kv1.2. Journal of Physical Chemistry B. 2018; 122 (48): 10825-10833. doi:10.1021/acs.jpcb.8b09446  
69.   Iwaki Masayo, Takeshita Kohei, Kondo Hiroko X, et al. Zn2+-Binding to the Voltage-Gated Proton Channel Hv1/VSOP. Journal of Physical Chemistry B. 2018; 122 (39): 9076-9080. doi:10.1021/acs.jpcb.8b04890  
70.   Tadaka Shu, Saigusa Daisuke, Motoike Ikuko N., et al. jMorp: Japanese Multi Omics Reference Panel. Nucleic Acids Research. 2018; 46 (D1): D551-D557. doi:10.1093/nar/gkx978  
71.   Obayashi Takeshi, Aoki Yuichi, Tadaka Shu, et al. ATTED-II in 2018: A Plant Coexpression Database Based on Investigation of the Statistical Property of the Mutual Rank Index. Plant and Cell Physiology. 2018; 59 (1): e3-e3. doi:10.1093/pcp/pcx191  
72.   Takai-Igarashi Takako, Kinoshita Kengo, Nagasaki Masao, et al. Security controls in an integrated Biobank to protect privacy in data sharing: rationale and study design. BMC Medical Informatics and Decision Making. 2017; 17 (1): 100. doi:10.1186/s12911-017-0494-5  
73.   Tsugita Misato, Morimoto Nobuyuki, Tashiro Manabu, et al. SR-B1 Is a Silica Receptor that Mediates Canonical Inflammasome Activation. Cell Reports. 2017; 18 (5): 1298-1311. doi:10.1016/j.celrep.2017.01.004  
74.   Matsuura Kentaro, Sawai Hiromi, Ikeo Kazuho, et al. Genome-Wide Association Study Identifies TLL1 Variant Associated With Development of Hepatocellular Carcinoma After Eradication of Hepatitis C Virus Infection. Gastroenterology. 2017; 152 (6): 1383-1394. doi:10.1053/j.gastro.2017.01.041  
75.   Hachiya Tsuyoshi, Furukawa Ryohei, Shiwa Yuh, et al. Genome-wide identification of inter-individually variable DNA methylation sites improves the efficacy of epigenetic association studies. npj Genomic Medicine. 2017; 2 (1): 11. doi:10.1038/s41525-017-0016-5  
76.   Tadaka Shu, Kinoshita Kengo. NCMine: Core-peripheral based functional module detection using near-clique mining. Bioinformatics. 2016; 32 (22): btw488. doi:10.1093/bioinformatics/btw488  
77.   Yamada Kazunori D, Nishi Hafumi, Nakata Junichi, Kinoshita Kengo. Structural characterization of single nucleotide variants at ligand binding sites and enzyme active sites of human proteins. Biophysics and Physicobiology. 2016; 13 : 157-163. doi:10.2142/biophysico.13.0_157  
78.   Shirota Matsuyuki, Kinoshita Kengo. Discrepancies between human DNA, mRNA and protein reference sequences and their relation to single nucleotide variants in the human population. Database. 2016; 2016 : baw124. doi:10.1093/database/baw124  
79.   Kuriyama Shinichi, Yaegashi Nobuo, Nagami Fuji, et al. The Tohoku Medical Megabank Project: Design and Mission. Journal of Epidemiology. 2016; 26 (9): 493-511. doi:10.2188/jea.JE20150268  
80.   Murakami Yoichi, Omori Satoshi, Kinoshita Kengo. NLDB: a database for 3D protein–ligand interactions in enzymatic reactions. Journal of Structural and Functional Genomics. 2016; 17 (4): 101-110. doi:10.1007/s10969-016-9206-0  
81.   Gojobori Takashi, Ikeo Kazuho, Katayama Yukie, et al. VaProS: a database-integration approach for protein/genome information retrieval. Journal of Structural and Functional Genomics. 2016; 17 (4): 69-81. doi:10.1007/s10969-016-9211-3  
82.   Aoki Yuichi, Okamura Yasunobu, Ohta Hiroyuki, et al. ALCOdb: Gene Coexpression Database for Microalgae. Plant and Cell Physiology. 2016; 57 (1): e3-e3. doi:10.1093/pcp/pcv190  
83.   Aoki Yuichi, Okamura Yasunobu, Tadaka Shu, et al. ATTED-II in 2016: A Plant Coexpression Database Towards Lineage-Specific Coexpression. Plant and Cell Physiology. 2016; 57 (1): e5-e5. doi:10.1093/pcp/pcv165  
84.   Saigusa Daisuke, Okamura Yasunobu, Motoike Ikuko N., et al. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery. PLOS ONE. 2016; 11 (8): e0160555. doi:10.1371/journal.pone.0160555  
85.   Kasahara Kota, Kinoshita Kengo. IBiSA_Tools: A Computational Toolkit for Ion-Binding State Analysis in Molecular Dynamics Trajectories of Ion Channels. PLOS ONE. 2016; 11 (12): e0167524. doi:10.1371/journal.pone.0167524  
86.   Kasahara Kota, Shirota Matsuyuki, Kinoshita Kengo. Ion Concentration- and Voltage-Dependent Push and Pull Mechanisms of Potassium Channel Ion Conduction. PLOS ONE. 2016; 11 (3): e0150716. doi:10.1371/journal.pone.0150716  
87.   Nishi Hafumi, Nakata Junichi, Kinoshita Kengo. Distribution of single‐nucleotide variants on protein–protein interaction sites and its relationship with minor allele frequency. Protein Science. 2016; 25 (2): 316-321. doi:10.1002/pro.2845  
88.   Kasahara Kota, Kinoshita Kengo. Landscape of protein-small ligand binding modes. Protein Science. 2016; 25 (9): 1659-1671. doi:10.1002/pro.2971  
89.   Fujiwara Yuichiro, Kondo Hiroko X., Shirota Matsuyuki, et al. Structural basis for the membrane association of ankyrinG via palmitoylation. Scientific Reports. 2016; 6 (1): 23981. doi:10.1038/srep23981  
90.   Koshiba Seizo, Motoike Ikuko, Kojima Kaname, et al. The structural origin of metabolic quantitative diversity. Scientific Reports. 2016; 6 (1): 31463. doi:10.1038/srep31463  
91.   Nagasaki Masao, Yasuda Jun, Katsuoka Fumiki, et al. Rare variant discovery by deep whole-genome sequencing of 1,070 Japanese individuals. Nature Communications. 2015; 6 (1): 8018. doi:10.1038/ncomms9018  
92.   Okamura Yasunobu, Aoki Yuichi, Obayashi Takeshi, et al. COXPRESdb in 2015: coexpression database for animal species by DNA-microarray and RNAseq-based expression data with multiple quality assessment systems. Nucleic Acids Research. 2015; 43 (D1): D82-D86. doi:10.1093/nar/gku1163  
93.   Okamura Yasunobu, Obayashi Takeshi, Kinoshita Kengo. Comparison of Gene Coexpression Profiles and Construction of Conserved Gene Networks to Find Functional Modules. PLOS ONE. 2015; 10 (7): e0132039. doi:10.1371/journal.pone.0132039  
94.   Kasahara Kota, Kinoshita Kengo. GIANT: pattern analysis of molecular interactions in 3D structures of protein–small ligand complexes. BMC Bioinformatics. 2014; 15 (1): 12. doi:10.1186/1471-2105-15-12  
95.   Motoike Ikuko N, Matsumoto Mitsuyo, Danjoh Inaho, et al. Validation of multiple single nucleotide variation calls by additional exome analysis with a semiconductor sequencer to supplement data of whole-genome sequencing of a human population. BMC Genomics. 2014; 15 (1): 673. doi:10.1186/1471-2164-15-673  
96.   Obayashi Takeshi, Okamura Yasunobu, Ito Satoshi, et al. ATTED-II in 2014: Evaluation of Gene Coexpression in Agriculturally Important Plants. Plant and Cell Physiology. 2014; 55 (1): e6-e6. doi:10.1093/pcp/pct178  
97.   Kasahara Kota, Shirota Matsuyuki, Kinoshita Kengo. Comprehensive classification and diversity assessment of atomic contacts in protein-small ligand interactions. Journal of Chemical Information and Modeling. 2013; 53 (1): 241-248. doi:10.1021/ci300377f  
98.   Kasahara Kota, Shirota Matsuyuki, Kinoshita Kengo. Ion Concentration-Dependent Ion Conduction Mechanism of a Voltage-Sensitive Potassium Channel. PLoS ONE. 2013; 8 (2): e56342. doi:10.1371/journal.pone.0056342  
99.   Shirota Matsuyuki, Kinoshita Kengo. Analyses of the general rule on residue pair frequencies in local amino acid sequences of soluble, ordered proteins. Protein Science. 2013; 22 (6): 725-733. doi:10.1002/pro.2255  
100.   布施 昇男、清水 愛、木村 雅恵、高野 良真、石 棟、宮澤 晃子、国松 志保、劉 孟林、渡邊 亮、安田 正幸、横山 悠、檜森 紀子、津田 聡、山本 耕太郎、中澤 徹、安田 純、勝岡 史城、小島 要、成相 直樹、松本 光代、元池 育子、長崎 正朗、木下 賢吾、五十嵐 和彦、山本 雅之、新堀 哲也、青木 洋子、松原 洋一、舟山 亮、長嶋 剛史、中山 啓子、眞島 行彦、舟山 智代、田中 光一、原田 高幸、阿部 春樹、福地 健郎、安田 典子、出田 秀尚、鄭 暁東、白石 敦、大橋 祐一、石田 誠夫、原 岳、金森 章. 緑内障のゲノム解析―次世代医療•個別化医療に向けて. 日本眼科学会雑誌. 2013; 118 ((3)): 216-240.  
101.   Obayashi Takeshi, Okamura Yasunobu, Ito Satoshi, et al. COXPRESdb: a database of comparative gene coexpression networks of eleven species for mammals. Nucleic Acids Research. 2012; 41 (D1): D1014-D1020. doi:10.1093/nar/gks1014