Advanced Medical Science(Cooperating field)Systems Biology


We are developing and practicing a methodology of data driven science that analyzes disease in a bird's-eye view from a systematic point of view using mathematical modeling by statistical science and information science and comprehensive biological information. In recent years, with the development of advanced measurement instruments including next generation sequencers, it is now possible to acquire so-called omics data such as genome, epigenome, transcriptome, proteome, and metabolome for large-scale clinical samples. This will accelerate the development of breakthrough molecular targeted therapeutic drugs, diagnostic agents and preventive methods in the medical field, and it is greatly expected that research on complicated diseases such as cancer will progress greatly. However, there is a big gap between expectation and reality. In other words, while comprehensive genome-wide information accumulates like floods, it is a reality that we cannot hope for a significant leap in information accumulation and data analysis by the previous approach.
By fusing data-driven science using statistical science, information science, computational science and experimental verification by molecular biology, we have developed a system biological methodology that exceeds the limits confronted by previous studies. This will promote systemic integrated understanding of molecular pathologies of complicated diseases such as cancer and mental disorders and ultimately provide highly accurate diagnostic methods, therapeutic methods and preventive measures reflecting differences in cancer personality and individual system.

Research Projects

  1. Development of a statistical modeling method to capture life phenomena in a bird's-eye view from data In today's life science, there is a necessity for data-driven research to extract meaningful information from comprehensive and systematically acquired large-scale biological information and comprehensively understand life phenomena as a system as a system It was. We are developing a system biological methodology, grasping the problems occurring in medical research and their discovery and solution in the discussion with the front line researchers in the field, analyzing vast amounts of omics data appropriately and overlooking the life phenomena.
  2. Development of analysis method of object-oriented data The development of mass spectrometry and image analysis, including the next generation sequencer, has caused enormous and heterogeneous big data to be accumulated in the field of biomedical sciences, and their analysis technology base is a challenge. Meanwhile, in the field of statistical science, in addition to numerical matrix type data in conventional multivariate analysis, object-oriented data analysis is emphasizing importance, in which each observation value is represented by various kinds of objects such as histogram, function, tree structure, and image. In our laboratory, we are building a foundation for object-oriented data analysis to capture the ecological system of extremely complicated cancer by making full use of the wide variety of cancer data.

Faculty Members

Teppei Shimamura Designated Associate Professor Systems Biology
Hideko Kawakubo Designated Associate Professor Systems Biology
Hyunha Nam Designated Associate Professor Systems Biology
Ko Abe Designated Associate Professor Systems Biology


  • 2019
    1. Kidoya H, Muramatsu F, Shimamura T, Jia W, Satoh T, Hayashi Y, Naito H, Kunisaki Y, Arai F, Seki M, Suzuki Y, Osawa T, Akira S, Takakura N. Regnase-1-mediated post-transcriptional regulation is essential for hematopoietic stem and progenitor cell homeostasis. Nat Commun, in press (2019)
    2. Shimamura T, Matsui Y, Kajino T, Ito S, Takahashi T, Miyano S. GIMLET: Identifying biological modulators in context-specific gene regulation using local energy statistics. Lecture Notes in Bioinformatics, in press (2019)
    3. Matsui Y, Miyano S, Shimamura T. Tumor subclonal progression model for cancer hallmark acquisition. Lecture Notes in Bioinformatics, in press (2019)
    4. Abe K, Hirayama H, Ohno K, Shimamura T. ENIGMA: An Enterotype-Like Unigram Mixture Model for Microbial Association Analysis. BMC Genomics, in press (2019)
    5. Kawakubo H, Matsui Y, Kushima I, Ozaki N, Shimamura T. Bioinformatics. A Network of Networks Approach for Modeling Interconnected Brain Tissue-Specific Networks. Bioinformatics, in press (2019)
  • 2018
    1. Abe K, Hirayama M, Ohno K, Shimamura T. A latent allocation model for the analysis of microbial composition and disease. BMC Bioinformatics, 19(Suppl 19):519 (2018)
    2. Kushima I, Aleksic B, Nakatochi M, Shimamura T, Okada T, Uno Y, Morikawa M, Ishizuka K, Shiino T, Kimura H, Arioka Y, Yoshimi A, Takasaki Y, Yu Y, Nakamura Y, Yamamoto M, Iidaka T, Iritani S, Inada T, Ogawa N, Shishido E, Torii Y, Kawano N, Omura Y, Yoshikawa T, Uchiyama T, Yamamoto T, Ikeda M, Hashimoto R, Yamamori H, Yasuda Y, Someya T, Watanabe Y, Egawa J, Nunokawa A, Itokawa M, Arai M, Miyashita M, Kobori A, Suzuki M, Takahashi T, Usami M, Kodaira M, Watanabe K, Sasaki T, Kuwabara H, Tochigi M, Nishimura F, Yamasue H, Eriguchi Y, Benner S, Kojima M, Yassin W, Munesue T, Yokoyama S, Kimura R, Funabiki Y, Kosaka H, Ishitobi M, Ohmori T, Numata S, Yoshikawa T, Toyota T, Yamakawa K, Suzuki T, Inoue Y, Nakaoka K, Goto YI, Inagaki M, Hashimoto N, Kusumi I, Son S, Murai T, Ikegame T, Okada N, Kasai K, Kunimoto S, Mori D, Iwata N, Ozaki N. Comparative Analyses of Copy-Number Variation in Autism Spectrum Disorder and Schizophrenia Reveal Etiological Overlap and Biological Insights. Cell Rep, 24(11):2838-2856(2018)
    3. Saito T, Niida A, Uchi R, Hirata H, Komatsu H, Sakimura S, Hayashi S, Nambara S, Kuroda Y, Ito S, Eguchi H, Masuda T, Sugimachi K, Tobo T, Nishida H, Daa T, Chiba K, Shiraishi Y, Yoshizato T, Kodama M, Okimoto T, Mizukami K, Ogawa R, Okamoto K, Shuto M, Fukuda K, Matsui Y, Shimamura T, Hasegawa T, Doki Y, Nagayama S, Yamada K, Kato M, Shibata T, Mori M, Aburatani H, Murakami K, Suzuki Y, Ogawa S, Miyano S, Mimori K. A temporal shift of the evolutionary principle shaping intratumor heterogeneity in colorectal cancer. Nat Commun, 9(1):2884 (2018)
    4. Komura K, Yoshikawa Y, Shimamura T, Chakraborty G, Gerke TA, Hinohara K, Chadalavada K, Jeong SH, Armenia J, Du SY, Mazzu YZ, Taniguchi K, Ibuki N, Meyer CA, Nanjangud GJ, Inamoto T, Lee GM, Mucci LA, Azuma H, Sweeney CJ, Kantoff PW. ATR inhibition controls aggressive prostate tumors deficient in Y-linked histone demethylase KDM5D. J Clin Invest, 128(7):2979-2995 (2018)
    5. Takeda M, Kanki Y, Masumoto H, Funakoshi S, Hatani T, Fukushima H, Izumi-Taguchi A, Matsui Y, Shimamura T, Yoshida Y, Yamashita JK. Identification of Cardiomyocyte-Fated Progenitors from Human-Induced Pluripotent Stem Cells Marked with CD82. Cell Rep, 22(2):546-556 (2018)
    6. Terai H, Kitajima S, Potter DS, Matsui Y, Quiceno LG, Chen T, Kim TJ, Rusan M, Thai TC, Piccioni F, Donovan KA, Kwiatkowski N, Hinohara K, Wei G, Gray NS, Fischer ES, Wong KK, Shimamura T, Letai A, Hammerman PS, Barbie DA. ER stress signaling promotes the survival of cancer 'persister cells' tolerant to EGFR tyrosine kinase inhibitors. Cancer Res, 78(4):1044-1057 (2018)
    7. Isobe T, Seki M, Yoshida K, Sekiguchi M, Shiozawa Y, Shiraishi Y, Kimura S, Yoshida M, Inoue Y, Yokoyama A, Kakiuchi N, Suzuki H, Kataoka K, Sato Y, Kawai T, Chiba K, Tanaka H, Shimamura T, Kato M, Iguchi A, Hama A, Taguchi T, Akiyama M, Fujimura J, Inoue A, Ito T, Deguchi T, Kiyotani C, Iehara T, Hosoi H, Oka A, Sanada M, Tanaka Y, Hata K, Miyano S, Ogawa S, Takita J. Integrated molecular characterization of the lethal pediatric cancer pancreatoblastoma. Cancer Res, 78(4):865-876 (2018)
    8. Park H, Shimamura T, Imoto S, Miyano S. Adaptive NetworkProfiler for Identifying Cancer Characteristic-Specific Gene Regulatory Networks. J Comput Biol, 25(2):130-145 (2018)
    9. Aoki K, Nakamura H, Suzuki H, Matsuo K, Kataoka K, Shimamura T, Motomura K, Ohka F, Shiina S, Yamamoto T, Nagata Y, Yoshizato T, Mizoguchi M, Abe T, Momii Y, Muragaki Y, Watanabe R, Ito I, Sanada M, Yajima H, Morita N, Takeuchi I, Miyano S, Wakabayashi T, Ogawa S, Natsume A. Prognostic relevance of genetic alterations in diffuse lower-grade gliomas. Neuro Oncol, 20(1):66-77 (2018)
    10. Taniguchi R, Muramatsu H, Okuno Y, Suzuki K, Obu S, Nakatochi M, Shimamura T, Takahashi Y, Horikoshi Y, Watanabe K, Kojima S. Comprehensive genetic analysis of donor cell derived leukemia with KMT2A rearrangement. Pediatr Blood Cancer, 65(2) (2018)
  • 2017
    1. Takahashi Y, Sugimachi K, Yamamoto K, Niida A, Shimamura T, Sato T, Watanabe M, Tanaka J, Kudo S, Sugihara K, Hase K, Kusunoki M, Yamada K, Shimada Y, Moriya Y, Suzuki Y, Miyano S, Mori M, Mimori K. Japanese genome-wide association study identifies a significant colorectal cancer susceptibility locus at chromosome 10p14. Cancer Sci, 108(11):2239-2247 (2017)
    2. Tsubota S, Kishida S, Shimamura T, Ohira M, Yamashita S, Cao D, Kiyonari S, Ushijima T, Kadomatsu K. PRC2-Mediated Transcriptomic Alterations at the Embryonic Stage Govern Tumorigenesis and Clinical Outcome in MYCN-Driven Neuroblastoma. Cancer Res, 77(19):5259-5271 (2017)
    3. Seki M, Kimura S, Isobe T, Yoshida K, Ueno H, Nakajima-Takagi Y, Wang C, Lin L, Kon A, Suzuki H, Shiozawa Y, Kataoka K, Fujii Y, Shiraishi Y, Chiba K, Tanaka H, Shimamura T, Masuda K, Kawamoto H, Ohki K, Kato M, Arakawa Y, Koh K, Hanada R, Moritake H, Akiyama M, Kobayashi R, Deguchi T, Hashii Y, Imamura T, Sato A, Kiyokawa N, Oka A, Hayashi Y, Takagi M, Manabe A, Ohara A, Horibe K, Sanada M, Iwama A, Mano H, Miyano S, Ogawa S, Takita J. Recurrent SPI1 (PU.1) fusions in high-risk pediatric T cell acute lymphoblastic leukemia. Nat Genet, 49(8):1274-1281 (2017)
    4. Kondo A, Nonaka A, Shimamura T, Yamamoto S, Yoshida T, Kodama T, Aburatani H, Osawa T. Long Noncoding RNA JHDM1D-AS1 Promotes Tumor Growth by Regulating Angiogenesis in Response to Nutrient Starvation. Mol Cell Biol, 37(11) (2017)
    5. Matsui Y, Niida A, Uchi R, Mimori K, Miyano S, Shimamura T. phyC: Clustering cancer evolutionary trees. PLoS Comput Biol. 13(5):e1005509 (2017)
    6. Kanki Y, Nakaki R, Shimamura T, Matsunaga T, Yamamizu K, Katayama S, Suehiro JI, Osawa T, Aburatani H, Kodama T, Wada Y, Yamashita JK, Minami T. Dynamically and epigenetically coordinated GATA/ETS/SOX transcription factor expression is indispensable for endothelial cell differentiation. Nucleic Acids Res, 45(8):4344-4358 (2017)
    7. Kondo A, Yamamoto S, Nakaki R, Shimamura T, Hamakubo T, Sakai J, Kodama T, Yoshida T, Aburatani H, Osawa T. Extracellular Acidic pH Activates the Sterol Regulatory Element-Binding Protein 2 to Promote Tumor Progression. Cell Rep, 18(9):2228-2242 (2017)
    8. Kushima I, Aleksic B, Nakatochi M, Shimamura T, Shiino T, Yoshimi A, Kimura H, Takasaki Y, Wang C, Xing J, Ishizuka K, Oya-Ito T, Nakamura Y, Arioka Y, Maeda T, Yamamoto M, Yoshida M, Noma H, Hamada S, Morikawa M, Uno Y, Okada T, Iidaka T, Iritani S, Yamamoto T, Miyashita M, Kobori A, Arai M, Itokawa M, Cheng MC, Chuang YA, Chen CH, Suzuki M, Takahashi T, Hashimoto R, Yamamori H, Yasuda Y, Watanabe Y, Nunokawa A, Someya T, Ikeda M, Toyota T, Yoshikawa T, Numata S, Ohmori T, Kunimoto S, Mori D, Iwata N, Ozaki N. High-resolution copy number variation analysis of schizophrenia in Japan. Mol Psychiatry, 22(3):430-440 (2017)
    9. Tominaga K, Shimamura T, Kimura N, Murayama T, Matsubara D, Kanauchi H, Niida A, Shimizu S, Nishioka K, Tsuji EI, Yano M, Sugano S, Shimono Y, Ishii H, Saya H, Mori M, Akashi K, Tada KI, Ogawa T, Tojo A, Miyano S, Gotoh N. Addiction to the IGF2-ID1-IGF2 circuit for maintenance of the breast cancer stem-like cells. Oncogene, 36(9):1276-1286 (2017)
  • 2016
    1. Sugimachi K, Matsumura T, Shimamura T, Hirata H, Uchi R, Ueda M, Sakimura S, Iguchi T, Eguchi H, Masuda T, Morita K, Takenaka K, Maehara Y, Mori M, Mimori K. Aberrant Methylation of FOXE1 Contributes to a Poor Prognosis for Patients with Colorectal Cancer. Ann Surg Oncol, 23(12):3948-3955 (2016)
    2. Matsui Y, Mizuta M, Ito S, Miyano S, Shimamura T. D3M: detection of differential distributions of methylation levels. Bioinformatics. 32(15):2248-55 (2016)
    3. Nakaoka HJ, Hara T, Yoshino S, Kanamori A, Matsui Y, Shimamura T, Sato H, Murakami Y, Seiki M, Sakamoto T. NECAB3 Promotes Activation of Hypoxia-inducible factor-1 during Normoxia and Enhances Tumourigenicity of Cancer Cells. Sci Rep, 6:22784 (2016)
    4. Uchi R, Takahashi Y, Niida A, Shimamura T, Hirata H, Sugimachi K, Sawada G, Iwaya T, Kurashige J, Shinden Y, Iguchi T, Eguchi H, Chiba K, Shiraishi Y, Nagae G, Yoshida K, Nagata Y, Haeno H, Yamamoto H, Ishii H, Doki Y, Iinuma H, Sasaki S, Nagayama S, Yamada K, Yachida S, Kato M, Shibata T, Oki E, Saeki H, Shirabe K, Oda Y, Maehara Y, Komune S, Mori M, Suzuki Y, Yamamoto K, Aburatani H, Ogawa S, Miyano S, Mimori K. Integrated Multiregional Analysis Proposing a New Model of Colorectal Cancer Evolution. PLoS Genet, 12(2):e1005778 (2016)
    5. Sawada G, Niida A, Uchi R, Hirata H, Shimamura T, Suzuki Y, Shiraishi Y, Chiba K, Imoto S, Takahashi Y, Iwaya T, Sudo T, Hayashi T, Takai H, Kawasaki Y, Matsukawa T, Eguchi H, Sugimachi K, Tanaka F, Suzuki H, Yamamoto K, Ishii H, Shimizu M, Yamazaki H, Yamazaki M, Tachimori Y, Kajiyama Y, Natsugoe S, Fujita H, Mafune K, Tanaka Y, Kelsell DP, Scott CA, Tsuji S, Yachida S, Shibata T, Sugano S, Doki Y, Akiyama T, Aburatani H, Ogawa S, Miyano S, Mori M, Mimori K. Genomic Landscape of Esophageal Squamous Cell Carcinoma in a Japanese Population. Gastroenterology. 150(5):1171-82 (2016)
    6. Hasegawa T, Niida A, Mori T, Shimamura T, Yamaguchi R, Miyano S, Akutsu T, Imoto S. A likelihood-free filtering method via approximate Bayesian computation in evaluating biological simulation models. Computational Statistics and Data Analysis, 94:63-74 (2016)
  • 2015
    1. Sawada G, Niida A, Hirata H, Komatsu H, Uchi R, Shimamura T, Takahashi Y, Kurashige J, Matsumura T, Ueo H, Takano Y, Ueda M, Sakimura S, Shinden Y, Eguchi H, Sudo T, Sugimachi K, Yamasaki M, Tanaka F, Tachimori Y, Kajiyama Y, Natsugoe S, Fujita H, Tanaka Y, Calin G, Miyano S, Doki Y, Mori M, Mimori K. An Integrative Analysis to Identify Driver Genes in Esophageal Squamous Cell Carcinoma. PLoS One, 10(10):e0139808 (2015)
    2. Kataoka K, Nagata Y, Kitanaka A, Shiraishi Y, Shimamura T, Yasunaga J, Totoki Y, Chiba K, Sato-Otsubo A, Nagae G, Ishii R, Muto S, Kotani S, Watatani Y, Takeda J, Sanada M, Tanaka H, Suzuki H, Sato Y, Shiozawa Y, Yoshizato T, Yoshida K, Makishima H, Iwanaga M, Ma G, Nosaka K, Hishizawa M, Itonaga H, Imaizumi Y, Munakata W, Ogasawara H, Sato T, Sasai K, Muramoto K, Penova M, Kawaguchi T, Nakamura H, Hama N, Shide K, Kubuki Y, Hidaka T, Kameda T, Nakamaki T, Ishiyama K, Miyawaki S, Yoon SS, Tobinai K, Miyazaki Y, Takaori-Kondo A, Matsuda F, Takeuchi K, Nureki O, Aburatani H, Watanabe T, Shibata T, Matsuoka M, Miyano S, Shimoda K, Ogawa S. Integrated molecular analysis of adult T cell leukemia/lymphoma. Nat Genet. 47:1304-15 (2015)
    3. Nakata A, Yoshida R, Yamaguchi R, Yamauchi M, Tamada Y, Fujita A, Shimamura T, Imoto S, Higuchi T, Nomura M, Kimura T, Nokihara H, Higashiyama M, Kondoh K, Nishihara H, Tojo A, Yano S, Miyano S, Gotoh N. Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs. Sci Rep, 5:13076 (2015)
    4. Seki M, Nishimura R, Yoshida K, Shimamura T, Shiraishi Y, Sato Y, Kato M, Chiba K, Tanaka H, Hoshino N, Nagae G, Shiozawa Y, Okuno Y, Hosoi H, Tanaka Y, Okita H, Miyachi M, Souzaki R, Taguchi T, Koh K, Hanada R, Kato K, Nomura Y, Akiyama M, Oka A, Igarashi T, Miyano S, Aburatani H, Hayashi Y, Ogawa S, Takita J. Integrated genetic and epigenetic analysis defines novel molecular subgroups in rhabdomyosarcoma. Nat Commun. 6:7557 (2015)
    5. Hasegawa T, Mori T, Yamaguchi R, Shimamura T, Miyano S, Imoto S, Akutsu T. Genomic data assimilation using a higher moment filtering technique for restoration of gene regulatory networks. BMC Syst Biol, 9:14 (2015)
    6. Suzuki H, Aoki K, Chiba K, Sato Y, Shiozawa Y, Shiraishi Y, Shimamura T, Niida A, Motomura K, Ohka F, Yamamoto T, Tanahashi K, Ranjit M, Wakabayashi T, Yoshizato T, Kataoka K, Yoshida K, Nagata Y, Sato-Otsubo A, Tanaka H, Sanada M, Kondo Y, Nakamura H, Mizoguchi M, Abe T, Muragaki Y, Watanabe R, Ito I, Miyano S, Natsume A, Ogawa S. Mutational landscape and clonal architecture in grade II and III gliomas. Nat Genet. 47:458-468 (2015)
    7. Ito H, Shiwaku H, Yoshida C, Homma H, Luo H, Chen X, Fujita K, Musante L, Fischer U, Frints SG, Romano C, Ikeuchi Y, Shimamura T, Imoto S, Miyano S, Muramatsu SI, Kawauchi T, Hoshino M, Sudol M, Arumughan A, Wanker EE, Rich T, Schwartz C, Matsuzaki F, Bonni A, Kalscheuer VM, Okazawa H. In utero gene therapy rescues microcephaly caused by Pqbp1-hypofunction in neural stem progenitor cells. Mol Psychiatry, 20(4):459-471 (2015)
  • 2014
    1. Park H, Shimamura T, Miyano S, Imoto S. Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker. PLoS One, 9(10):e108990(2014)
    2. Sawada G, Takahashi Y, Niida A, Shimamura T, Kurashige J, Matsumura T, Ueo H, Uchi R, Takano Y, Ueda M, Hirata H, Sakimura S, Shinden Y, Eguchi H, Sudo T, Sugimachi K, Miyano S, Doki Y, Mori M, Mimori K. Loss of CDCP1 expression promotes invasiveness and poor prognosis in esophageal squamous cell carcinoma. Ann Surg Oncol, 21:S640-647 (2014)
    3. Seki M, Yoshida K, Shiraishi Y, Shimamura T, Sato Y, Nishimura R, Okuno Y, Chiba K, Tanaka H, Kato K, Kato M, Hanada R, Nomura Y, Park MJ, Ishida T, Oka A, Igarashi T, Miyano S, Hayashi Y, Ogawa S, Takita J. Biallelic DICER1 mutations in sporadic pleuropulmonary blastoma. Cancer Res. 74:2742-9 (2014)
    4. Sugimachi K, Niida A, Yamamoto K, Shimamura T, Imoto S, Iinuma H, Shinden Y, Eguchi H, Sudo T, Watanabe M, Tanaka J, Kudo S, Hase K, Kusunoki M, Yamada K, Shimada Y, Sugihara K, Maehara Y, Miyano S, Mori M, Mimori K. Allelic imbalance at an 8q24 oncogenic SNP is involved in activating MYC in human colorectal cancer. Ann Surg Oncol, 21:S515-521 (2014)
    5. Barclay SS, Tamura T, Ito H, Fujita K, Tagawa K, Shimamura T, Katsuta A, Shiwaku H, Sone M, Imoto S, Miyano S, Okazawa H. Systems biology analysis of Drosophila in vivo screen data elucidates core networks for DNA damage repair in SCA1. Hum Mol Genet, 23(5):1345-1364 (2014)
  • 2013
    1. Kon A, Shih LY, Minamino M, Sanada M, Shiraishi Y, Nagata Y, Yoshida K, Okuno Y, Bando M, Nakato R, Ishikawa S, Sato-Otsubo A, Nagae G, Nishimoto A, Haferlach C, Nowak D, Sato Y, Alpermann T, Nagasaki M, Shimamura T, Tanaka H, Chiba K, Yamamoto R, Yamaguchi T, Otsu M, Obara N, Sakata-Yanagimoto M, Nakamaki T, Ishiyama K, Nolte F, Hofmann WK, Miyawaki S, Chiba S, Mori H, Nakauchi H, Koeffler HP, Aburatani H, Haferlach T, Shirahige K, Miyano S, Ogawa S. Recurrent mutations in multiple components of the cohesin complex in myeloid neoplasms. Nat Genet, 45(10): 1232-1237(2013)
    2. Sato Y, Yoshizato T, Shiraishi Y, Maekawa S, Okuno Y, Kamura T, Shimamura T, Sato-Otsubo A, Nagae G, Suzuki H, Nagata Y, Yoshida K, Kon A, Suzuki Y, Chiba K, Tanaka H, Niida A, Fujimoto A, Tsunoda T, Morikawa T, Maeda D, Kume H, Sugano S, Fukayama M, Aburatani H, Sanada M, Miyano S, Homma Y, Ogawa S. Integrated molecular analysis of clear-cell renal cell carcinoma. Nat Genet, 45(8): 860-867(2013)
    3. Furuta M, Kozaki K, Tanimoto K, Tanaka S, Arii S, Shimamura T, Niida A, Miyano S, Inazawa J. The tumor-suppressive miR-497-195 cluster targets multiple cell-cycle regulators in hepatocellular carcinoma. PLoS One, 8(3): e60155(2013)
    4. Osawa T, Tsuchida R, Muramatsu M, Shimamura T, Wang F, Suehiro J, Kanki Y, Wada Y, Yuasa Y, Aburatani H, Miyano S, Minami T, Kodama T, Shibuya M. Inhibition of histone demethylase JMJD1A improves anti-angiogenic therapy and reduces tumor-associated macrophages. Cancer Res, 73(10): 3019-3028(2013)
    5. Yokobori T, Iinuma H, Shimamura T (equally contributed first author), Imoto S, Sugimachi K, Ishii H, Iwatsuki M, Ota D, Ohkuma M, Iwaya T, Nishida N, Kogo R, Sudo T, Tanaka F, Shibata K, Toh H, Sato T, Barnard GF, Fukagawa T, Yamamoto S, Nakanishi H, Sasaki S, Miyano S, Watanabe T, Kuwano H, Mimori K, Pantel K, Mori M. Plastin3 is a novel marker for circulating tumor cells undergoing the epithelial-mesenchymal transition and is associated with colorectal cancer prognosis. Cancer Res, 73(7): 2059-69(2013)
    6. Tamura T, Sone M, Nakamura Y, Shimamura T, Imoto S, Miyano S, Okazawa H. A restricted level of PQBP1 is needed for the best longevity of Drosophila. Neurobiol Aging, 34(1): 356.e11-20(2013)
  • 2012
    1. Yamauchi M, Yamaguchi R, Nakata A, Kohno T, Nagasaki M, Shimamura T, Imoto S, Saito A, Ueno K, Hatanaka Y, Yoshida R, Higuchi T, Nomura M, Beer DG, Yokota J, Miyano S, Gotoh N. Epidermal growth factor receptor tyrosine kinase defines critical prognostic genes of stage I lung adenocarcinoma. PLoS One, 7(9):e43923(2012)
    2. Niida A, Imoto S, Shimamura T, Miyano S. Statistical model-based testing to evaluate the recurrence of genomic aberrations. Bioinformatics, 28(12):i115-20(2012)
    3. Mimura I, Nangaku M, Kanki Y, Tsutsumi S, Inoue T, Kohro T, Yamamoto S, Fujita T, Shimamura T, Suehiro J, Taguchi A, Kobayashi M, Tanimura K, Inagaki T, Tanaka T, Hamakubo T, Sakai J, Aburatani H, Kodama T, Wada Y. Dynamic change of chromatin conformation in response to hypoxia enhances the expression of GLUT3 (SLC2A3) by cooperative interaction of hypoxia-inducible factor 1 and KDM3A. Molecular and Cellular Biology, 32(15):3018-32(2012)
    4. Kawano S, Shimamura T, Niida A, Imoto S, Yamaguchi R, Nagasaki M, Yoshida R, Print C, Miyano S. Identifying gene pathways associated with cancer characteristics via sparse statistical methods. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(4):966-72(2012)

Research Keywords

Bioinformatics、 Systems Biology、 Omics Analysis、 Gene Network-based Approach、 Statistical Modeling、 Data-driven Approach、 Next Generation Sequencer、 Statistical Analysis of Genome Data、 Statistical Analysis of Epigenome Data、 Statistical Analysis of Transcriptome Data、 Statistical Analysis of Proteome Data、 Statistical Analysis of Single-Cell Transcriptome Data、 Statistical Model of Cancer Evolutionary Tree、 Large-Scale Calculation Using Super-Computing、 Integrated System Understanding of Disease with Mathematical Modeling