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Items: 33

1.

A comparison of machine learning classifiers for dementia with Lewy bodies using miRNA expression data.

Shigemizu D, Akiyama S, Asanomi Y, Boroevich KA, Sharma A, Tsunoda T, Sakurai T, Ozaki K, Ochiya T, Niida S.

BMC Med Genomics. 2019 Oct 30;12(1):150. doi: 10.1186/s12920-019-0607-3.

2.

DeepInsight: A methodology to transform a non-image data to an image for convolution neural network architecture.

Sharma A, Vans E, Shigemizu D, Boroevich KA, Tsunoda T.

Sci Rep. 2019 Aug 6;9(1):11399. doi: 10.1038/s41598-019-47765-6.

3.

Risk prediction models for dementia constructed by supervised principal component analysis using miRNA expression data.

Shigemizu D, Akiyama S, Asanomi Y, Boroevich KA, Sharma A, Tsunoda T, Matsukuma K, Ichikawa M, Sudo H, Takizawa S, Sakurai T, Ozaki K, Ochiya T, Niida S.

Commun Biol. 2019 Feb 25;2:77. doi: 10.1038/s42003-019-0324-7. eCollection 2019.

4.

An integrative machine learning approach for prediction of toxicity-related drug safety.

Lysenko A, Sharma A, Boroevich KA, Tsunoda T.

Life Sci Alliance. 2018 Nov 28;1(6):e201800098. doi: 10.26508/lsa.201800098. eCollection 2018 Dec.

5.

Integrated analysis of human genetic association study and mouse transcriptome suggests LBH and SHF genes as novel susceptible genes for amyloid-β accumulation in Alzheimer's disease.

Yamaguchi-Kabata Y, Morihara T, Ohara T, Ninomiya T, Takahashi A, Akatsu H, Hashizume Y, Hayashi N, Shigemizu D, Boroevich KA, Ikeda M, Kubo M, Takeda M, Tsunoda T.

Hum Genet. 2018 Jul;137(6-7):521-533. doi: 10.1007/s00439-018-1906-z. Epub 2018 Jul 13.

6.

Publisher Correction: IMSindel: An accurate intermediate-size indel detection tool incorporating de novo assembly and gapped global-local alignment with split read analysis.

Shigemizu D, Miya F, Akiyama S, Okuda S, Boroevich KA, Fujimoto A, Nakagawa H, Ozaki K, Niida S, Kanemura Y, Okamoto N, Saitoh S, Kato M, Yamasaki M, Matsunaga T, Mutai H, Kosaki K, Tsunoda T.

Sci Rep. 2018 Jul 4;8(1):10367. doi: 10.1038/s41598-018-28698-y.

7.

A novel homozygous missense mutation in the SH3-binding motif of STAMBP causing microcephaly-capillary malformation syndrome.

Hori I, Miya F, Negishi Y, Hattori A, Ando N, Boroevich KA, Okamoto N, Kato M, Tsunoda T, Yamasaki M, Kanemura Y, Kosaki K, Saitoh S.

J Hum Genet. 2018 Sep;63(9):957-963. doi: 10.1038/s10038-018-0482-3. Epub 2018 Jun 15.

PMID:
29907875
8.

Empirical Bayes Estimation of Semi-parametric Hierarchical Mixture Models for Unbiased Characterization of Polygenic Disease Architectures.

Nishino J, Kochi Y, Shigemizu D, Kato M, Ikari K, Ochi H, Noma H, Matsui K, Morizono T, Boroevich KA, Tsunoda T, Matsui S.

Front Genet. 2018 Apr 24;9:115. doi: 10.3389/fgene.2018.00115. eCollection 2018.

9.

IMSindel: An accurate intermediate-size indel detection tool incorporating de novo assembly and gapped global-local alignment with split read analysis.

Shigemizu D, Miya F, Akiyama S, Okuda S, Boroevich KA, Fujimoto A, Nakagawa H, Ozaki K, Niida S, Kanemura Y, Okamoto N, Saitoh S, Kato M, Yamasaki M, Matsunaga T, Mutai H, Kosaki K, Tsunoda T.

Sci Rep. 2018 Apr 4;8(1):5608. doi: 10.1038/s41598-018-23978-z. Erratum in: Sci Rep. 2018 Jul 4;8(1):10367.

10.

A novel genetic syndrome with STARD9 mutation and abnormal spindle morphology.

Okamoto N, Tsuchiya Y, Miya F, Tsunoda T, Yamashita K, Boroevich KA, Kato M, Saitoh S, Yamasaki M, Kanemura Y, Kosaki K, Kitagawa D.

Am J Med Genet A. 2017 Oct;173(10):2690-2696. doi: 10.1002/ajmg.a.38391. Epub 2017 Aug 4.

PMID:
28777490
11.

Structural Basis and Genotype-Phenotype Correlations of INSR Mutations Causing Severe Insulin Resistance.

Hosoe J, Kadowaki H, Miya F, Aizu K, Kawamura T, Miyata I, Satomura K, Ito T, Hara K, Tanaka M, Ishiura H, Tsuji S, Suzuki K, Takakura M, Boroevich KA, Tsunoda T, Yamauchi T, Shojima N, Kadowaki T.

Diabetes. 2017 Oct;66(10):2713-2723. doi: 10.2337/db17-0301. Epub 2017 Aug 1.

12.

Arete - candidate gene prioritization using biological network topology with additional evidence types.

Lysenko A, Boroevich KA, Tsunoda T.

BioData Min. 2017 Jul 6;10:22. doi: 10.1186/s13040-017-0141-9. eCollection 2017.

13.

The prediction models for postoperative overall survival and disease-free survival in patients with breast cancer.

Shigemizu D, Iwase T, Yoshimoto M, Suzuki Y, Miya F, Boroevich KA, Katagiri T, Zembutsu H, Tsunoda T.

Cancer Med. 2017 Jul;6(7):1627-1638. doi: 10.1002/cam4.1092. Epub 2017 May 24.

14.

Whole genome sequencing discriminates hepatocellular carcinoma with intrahepatic metastasis from multi-centric tumors.

Furuta M, Ueno M, Fujimoto A, Hayami S, Yasukawa S, Kojima F, Arihiro K, Kawakami Y, Wardell CP, Shiraishi Y, Tanaka H, Nakano K, Maejima K, Sasaki-Oku A, Tokunaga N, Boroevich KA, Abe T, Aikata H, Ohdan H, Gotoh K, Kubo M, Tsunoda T, Miyano S, Chayama K, Yamaue H, Nakagawa H.

J Hepatol. 2017 Feb;66(2):363-373. doi: 10.1016/j.jhep.2016.09.021. Epub 2016 Oct 11.

PMID:
27742377
15.

Stepwise iterative maximum likelihood clustering approach.

Sharma A, Shigemizu D, Boroevich KA, López Y, Kamatani Y, Kubo M, Tsunoda T.

BMC Bioinformatics. 2016 Aug 24;17(1):319. doi: 10.1186/s12859-016-1184-5.

16.

Erratum: Whole-genome mutational landscape and characterization of noncoding and structural mutations in liver cancer.

Fujimoto A, Furuta M, Totoki Y, Tsunoda T, Kato M, Shiraishi Y, Tanaka H, Taniguchi H, Kawakami Y, Ueno M, Gotoh K, Ariizumi S, Wardell CP, Hayami S, Nakamura T, Aikata H, Arihiro K, Boroevich KA, Abe T, Nakano K, Maejima K, Sasaki-Oku A, Ohsawa A, Shibuya T, Nakamura H, Hama N, Hosoda F, Arai Y, Ohashi S, Urushidate T, Nagae G, Yamamoto S, Ueda H, Tatsuno K, Ojima H, Hiraoka N, Okusaka T, Kubo M, Marubashi S, Yamada T, Hirano S, Yamamoto M, Ohdan H, Shimada K, Ishikawa O, Yamaue H, Chayama K, Miyano S, Aburatani H, Shibata T, Nakagawa H.

Nat Genet. 2016 May 27;48(6):700. doi: 10.1038/ng0616-700a. No abstract available.

PMID:
27230686
17.

Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes.

Fujimoto A, Okada Y, Boroevich KA, Tsunoda T, Taniguchi H, Nakagawa H.

Sci Rep. 2016 May 26;6:26483. doi: 10.1038/srep26483.

18.

Whole-genome mutational landscape and characterization of noncoding and structural mutations in liver cancer.

Fujimoto A, Furuta M, Totoki Y, Tsunoda T, Kato M, Shiraishi Y, Tanaka H, Taniguchi H, Kawakami Y, Ueno M, Gotoh K, Ariizumi S, Wardell CP, Hayami S, Nakamura T, Aikata H, Arihiro K, Boroevich KA, Abe T, Nakano K, Maejima K, Sasaki-Oku A, Ohsawa A, Shibuya T, Nakamura H, Hama N, Hosoda F, Arai Y, Ohashi S, Urushidate T, Nagae G, Yamamoto S, Ueda H, Tatsuno K, Ojima H, Hiraoka N, Okusaka T, Kubo M, Marubashi S, Yamada T, Hirano S, Yamamoto M, Ohdan H, Shimada K, Ishikawa O, Yamaue H, Chayama K, Miyano S, Aburatani H, Shibata T, Nakagawa H.

Nat Genet. 2016 May;48(5):500-9. doi: 10.1038/ng.3547. Epub 2016 Apr 11. Erratum in: Nat Genet. 2016 May 27;48(6):700.

PMID:
27064257
19.

Hierarchical Maximum Likelihood Clustering Approach.

Sharma A, Boroevich KA, Shigemizu D, Kamatani Y, Kubo M, Tsunoda T.

IEEE Trans Biomed Eng. 2017 Jan;64(1):112-122. doi: 10.1109/TBME.2016.2542212. Epub 2016 Mar 24.

PMID:
27046867
20.

Gene expression profiling of DBA/2J mice cochleae treated with l-methionine and valproic acid.

Miya F, Mutai H, Fujii M, Boroevich KA, Matsunaga T, Tsunoda T.

Genom Data. 2015 Jul 2;5:323-5. doi: 10.1016/j.gdata.2015.06.022. eCollection 2015 Sep.

21.

Performance comparison of four commercial human whole-exome capture platforms.

Shigemizu D, Momozawa Y, Abe T, Morizono T, Boroevich KA, Takata S, Ashikawa K, Kubo M, Tsunoda T.

Sci Rep. 2015 Aug 3;5:12742. doi: 10.1038/srep12742.

22.

A combination of targeted enrichment methodologies for whole-exome sequencing reveals novel pathogenic mutations.

Miya F, Kato M, Shiohama T, Okamoto N, Saitoh S, Yamasaki M, Shigemizu D, Abe T, Morizono T, Boroevich KA, Kosaki K, Kanemura Y, Tsunoda T.

Sci Rep. 2015 Mar 19;5:9331. doi: 10.1038/srep09331.

23.

Whole-genome mutational landscape of liver cancers displaying biliary phenotype reveals hepatitis impact and molecular diversity.

Fujimoto A, Furuta M, Shiraishi Y, Gotoh K, Kawakami Y, Arihiro K, Nakamura T, Ueno M, Ariizumi S, Nguyen HH, Shigemizu D, Abe T, Boroevich KA, Nakano K, Sasaki A, Kitada R, Maejima K, Yamamoto Y, Tanaka H, Shibuya T, Shibata T, Ojima H, Shimada K, Hayami S, Shigekawa Y, Aikata H, Ohdan H, Marubashi S, Yamada T, Kubo M, Hirano S, Ishikawa O, Yamamoto M, Yamaue H, Chayama K, Miyano S, Tsunoda T, Nakagawa H.

Nat Commun. 2015 Jan 30;6:6120. doi: 10.1038/ncomms7120.

PMID:
25636086
24.

Integrated analysis of whole genome and transcriptome sequencing reveals diverse transcriptomic aberrations driven by somatic genomic changes in liver cancers.

Shiraishi Y, Fujimoto A, Furuta M, Tanaka H, Chiba K, Boroevich KA, Abe T, Kawakami Y, Ueno M, Gotoh K, Ariizumi S, Shibuya T, Nakano K, Sasaki A, Maejima K, Kitada R, Hayami S, Shigekawa Y, Marubashi S, Yamada T, Kubo M, Ishikawa O, Aikata H, Arihiro K, Ohdan H, Yamamoto M, Yamaue H, Chayama K, Tsunoda T, Miyano S, Nakagawa H.

PLoS One. 2014 Dec 19;9(12):e114263. doi: 10.1371/journal.pone.0114263. eCollection 2014.

25.

The construction of risk prediction models using GWAS data and its application to a type 2 diabetes prospective cohort.

Shigemizu D, Abe T, Morizono T, Johnson TA, Boroevich KA, Hirakawa Y, Ninomiya T, Kiyohara Y, Kubo M, Nakamura Y, Maeda S, Tsunoda T.

PLoS One. 2014 Mar 20;9(3):e92549. doi: 10.1371/journal.pone.0092549. eCollection 2014.

26.

A practical method to detect SNVs and indels from whole genome and exome sequencing data.

Shigemizu D, Fujimoto A, Akiyama S, Abe T, Nakano K, Boroevich KA, Yamamoto Y, Furuta M, Kubo M, Nakagawa H, Tsunoda T.

Sci Rep. 2013;3:2161. doi: 10.1038/srep02161.

27.

Whole-genome sequencing of liver cancers identifies etiological influences on mutation patterns and recurrent mutations in chromatin regulators.

Fujimoto A, Totoki Y, Abe T, Boroevich KA, Hosoda F, Nguyen HH, Aoki M, Hosono N, Kubo M, Miya F, Arai Y, Takahashi H, Shirakihara T, Nagasaki M, Shibuya T, Nakano K, Watanabe-Makino K, Tanaka H, Nakamura H, Kusuda J, Ojima H, Shimada K, Okusaka T, Ueno M, Shigekawa Y, Kawakami Y, Arihiro K, Ohdan H, Gotoh K, Ishikawa O, Ariizumi S, Yamamoto M, Yamada T, Chayama K, Kosuge T, Yamaue H, Kamatani N, Miyano S, Nakagama H, Nakamura Y, Tsunoda T, Shibata T, Nakagawa H.

Nat Genet. 2012 May 27;44(7):760-4. doi: 10.1038/ng.2291.

PMID:
22634756
28.

Whole-genome sequencing and comprehensive variant analysis of a Japanese individual using massively parallel sequencing.

Fujimoto A, Nakagawa H, Hosono N, Nakano K, Abe T, Boroevich KA, Nagasaki M, Yamaguchi R, Shibuya T, Kubo M, Miyano S, Nakamura Y, Tsunoda T.

Nat Genet. 2010 Nov;42(11):931-6. doi: 10.1038/ng.691. Epub 2010 Oct 24.

PMID:
20972442
29.

Genomic organization and evolution of the Atlantic salmon hemoglobin repertoire.

Quinn NL, Boroevich KA, Lubieniecki KP, Chow W, Davidson EA, Phillips RB, Koop BF, Davidson WS.

BMC Genomics. 2010 Oct 5;11:539. doi: 10.1186/1471-2164-11-539.

30.

Comparative genomics identifies candidate genes for infectious salmon anemia (ISA) resistance in Atlantic salmon (Salmo salar).

Li J, Boroevich KA, Koop BF, Davidson WS.

Mar Biotechnol (NY). 2011 Apr;13(2):232-41. doi: 10.1007/s10126-010-9284-0. Epub 2010 Apr 16.

31.

Assessing the feasibility of GS FLX Pyrosequencing for sequencing the Atlantic salmon genome.

Quinn NL, Levenkova N, Chow W, Bouffard P, Boroevich KA, Knight JR, Jarvie TP, Lubieniecki KP, Desany BA, Koop BF, Harkins TT, Davidson WS.

BMC Genomics. 2008 Aug 28;9:404. doi: 10.1186/1471-2164-9-404.

32.

Piecing together a ciliome.

Inglis PN, Boroevich KA, Leroux MR.

Trends Genet. 2006 Sep;22(9):491-500. Epub 2006 Jul 24. Review.

PMID:
16860433
33.

Functional genomics of the cilium, a sensory organelle.

Blacque OE, Perens EA, Boroevich KA, Inglis PN, Li C, Warner A, Khattra J, Holt RA, Ou G, Mah AK, McKay SJ, Huang P, Swoboda P, Jones SJ, Marra MA, Baillie DL, Moerman DG, Shaham S, Leroux MR.

Curr Biol. 2005 May 24;15(10):935-41.

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