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Items: 1 to 20 of 25

1.

SiBIC: A Tool for Generating a Network of Biclusters Captured by Maximal Frequent Itemset Mining.

Takahashi KI, duVerle DA, Yotsukura S, Takigawa I, Mamitsuka H.

Methods Mol Biol. 2018;1807:95-111. doi: 10.1007/978-1-4939-8561-6_8.

PMID:
30030806
2.

Obesity Suppresses Cell-Competition-Mediated Apical Elimination of RasV12-Transformed Cells from Epithelial Tissues.

Sasaki A, Nagatake T, Egami R, Gu G, Takigawa I, Ikeda W, Nakatani T, Kunisawa J, Fujita Y.

Cell Rep. 2018 Apr 24;23(4):974-982. doi: 10.1016/j.celrep.2018.03.104.

3.

Genomic copy number variation analysis in multiple system atrophy.

Hama Y, Katsu M, Takigawa I, Yabe I, Matsushima M, Takahashi I, Katayama T, Utsumi J, Sasaki H.

Mol Brain. 2017 Nov 29;10(1):54. doi: 10.1186/s13041-017-0335-6.

4.

Machine learning reveals orbital interaction in materials.

Lam Pham T, Kino H, Terakura K, Miyake T, Tsuda K, Takigawa I, Chi Dam H.

Sci Technol Adv Mater. 2017 Oct 26;18(1):756-765. doi: 10.1080/14686996.2017.1378060. eCollection 2017.

5.

Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code.

Yotsukura S, Karasuyama M, Takigawa I, Mamitsuka H.

Brief Bioinform. 2017 Jul 1;18(4):619-633. doi: 10.1093/bib/bbw040.

PMID:
27197545
6.

Generalized Sparse Learning of Linear Models Over the Complete Subgraph Feature Set.

Takigawa I, Mamitsuka H.

IEEE Trans Pattern Anal Mach Intell. 2017 Mar;39(3):617-624. doi: 10.1109/TPAMI.2016.2567399. Epub 2016 May 12.

PMID:
27187949
7.

Predictions of Cleavability of Calpain Proteolysis by Quantitative Structure-Activity Relationship Analysis Using Newly Determined Cleavage Sites and Catalytic Efficiencies of an Oligopeptide Array.

Shinkai-Ouchi F, Koyama S, Ono Y, Hata S, Ojima K, Shindo M, duVerle D, Ueno M, Kitamura F, Doi N, Takigawa I, Mamitsuka H, Sorimachi H.

Mol Cell Proteomics. 2016 Apr;15(4):1262-80. doi: 10.1074/mcp.M115.053413. Epub 2016 Jan 21.

8.

The cell competition-based high-throughput screening identifies small compounds that promote the elimination of RasV12-transformed cells from epithelia.

Yamauchi H, Matsumaru T, Morita T, Ishikawa S, Maenaka K, Takigawa I, Semba K, Kon S, Fujita Y.

Sci Rep. 2015 Oct 20;5:15336. doi: 10.1038/srep15336.

9.

MED26 regulates the transcription of snRNA genes through the recruitment of little elongation complex.

Takahashi H, Takigawa I, Watanabe M, Anwar D, Shibata M, Tomomori-Sato C, Sato S, Ranjan A, Seidel CW, Tsukiyama T, Mizushima W, Hayashi M, Ohkawa Y, Conaway JW, Conaway RC, Hatakeyama S.

Nat Commun. 2015 Jan 9;6:5941. doi: 10.1038/ncomms6941.

10.

Ribosomes in a stacked array: elucidation of the step in translation elongation at which they are stalled during S-adenosyl-L-methionine-induced translation arrest of CGS1 mRNA.

Yamashita Y, Kadokura Y, Sotta N, Fujiwara T, Takigawa I, Satake A, Onouchi H, Naito S.

J Biol Chem. 2014 May 2;289(18):12693-704. doi: 10.1074/jbc.M113.526616. Epub 2014 Mar 20.

11.

SiBIC: a web server for generating gene set networks based on biclusters obtained by maximal frequent itemset mining.

Takahashi K, Takigawa I, Mamitsuka H.

PLoS One. 2013 Dec 30;8(12):e82890. doi: 10.1371/journal.pone.0082890. eCollection 2013.

12.

Similarity-based machine learning methods for predicting drug-target interactions: a brief review.

Ding H, Takigawa I, Mamitsuka H, Zhu S.

Brief Bioinform. 2014 Sep;15(5):734-47. doi: 10.1093/bib/bbt056. Epub 2013 Aug 11. Review.

PMID:
23933754
13.

An in silico model for interpreting polypharmacology in drug-target networks.

Takigawa I, Tsuda K, Mamitsuka H.

Methods Mol Biol. 2013;993:67-80. doi: 10.1007/978-1-62703-342-8_5.

PMID:
23568464
14.

Identifying pathways of coordinated gene expression.

Hancock T, Takigawa I, Mamitsuka H.

Methods Mol Biol. 2013;939:69-85. doi: 10.1007/978-1-62703-107-3_7.

PMID:
23192542
15.

Graph mining: procedure, application to drug discovery and recent advances.

Takigawa I, Mamitsuka H.

Drug Discov Today. 2013 Jan;18(1-2):50-7. doi: 10.1016/j.drudis.2012.07.016. Epub 2012 Aug 5. Review.

PMID:
22889967
16.

Identifying neighborhoods of coordinated gene expression and metabolite profiles.

Hancock T, Wicker N, Takigawa I, Mamitsuka H.

PLoS One. 2012;7(2):e31345. doi: 10.1371/journal.pone.0031345. Epub 2012 Feb 15.

17.

ROS-DET: robust detector of switching mechanisms in gene expression.

Kayano M, Takigawa I, Shiga M, Tsuda K, Mamitsuka H.

Nucleic Acids Res. 2011 Jun;39(11):e74. doi: 10.1093/nar/gkr130. Epub 2011 Apr 1.

18.

Mining significant substructure pairs for interpreting polypharmacology in drug-target network.

Takigawa I, Tsuda K, Mamitsuka H.

PLoS One. 2011 Feb 23;6(2):e16999. doi: 10.1371/journal.pone.0016999.

19.

Mining metabolic pathways through gene expression.

Hancock T, Takigawa I, Mamitsuka H.

Bioinformatics. 2010 Sep 1;26(17):2128-35. doi: 10.1093/bioinformatics/btq344. Epub 2010 Jun 29.

20.

On the performance of methods for finding a switching mechanism in gene expression.

Kayano M, Takigawa I, Shiga M, Tsuda K, Mamitsuka H.

Genome Inform. 2010;24:69-83.

PMID:
22081590

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