Tabei Y - Search Results

1

Metabolome-scale prediction of intermediate compounds in multistep metabolic pathways with a recursive supervised approach.

Kotera M, Tabei Y, Yamanishi Y, Muto A, Moriya Y, Tokimatsu T, Goto S. Kotera M, et al. Among authors: tabei y. Bioinformatics. 2014 Jun 15;30(12):i165-74. doi: 10.1093/bioinformatics/btu265. Bioinformatics. 2014. PMID: 24931980 Free PMC article.

2

Supervised de novo reconstruction of metabolic pathways from metabolome-scale compound sets.

Kotera M, Tabei Y, Yamanishi Y, Tokimatsu T, Goto S. Kotera M, et al. Among authors: tabei y. Bioinformatics. 2013 Jul 1;29(13):i135-44. doi: 10.1093/bioinformatics/btt244. Bioinformatics. 2013. PMID: 23812977 Free PMC article.

3

Metabolome-scale de novo pathway reconstruction using regioisomer-sensitive graph alignments.

Yamanishi Y, Tabei Y, Kotera M. Yamanishi Y, et al. Among authors: tabei y. Bioinformatics. 2015 Jun 15;31(12):i161-70. doi: 10.1093/bioinformatics/btv224. Bioinformatics. 2015. PMID: 26072478 Free PMC article.

4

Simultaneous prediction of enzyme orthologs from chemical transformation patterns for de novo metabolic pathway reconstruction.

Tabei Y, Yamanishi Y, Kotera M. Tabei Y, et al. Bioinformatics. 2016 Jun 15;32(12):i278-i287. doi: 10.1093/bioinformatics/btw260. Bioinformatics. 2016. PMID: 27307627 Free PMC article.

5

Network-based characterization of drug-protein interaction signatures with a space-efficient approach.

Tabei Y, Kotera M, Sawada R, Yamanishi Y. Tabei Y, et al. BMC Syst Biol. 2019 Apr 5;13(Suppl 2):39. doi: 10.1186/s12918-019-0691-1. BMC Syst Biol. 2019. PMID: 30953486 Free PMC article.

6

KCF-S: KEGG Chemical Function and Substructure for improved interpretability and prediction in chemical bioinformatics.

Kotera M, Tabei Y, Yamanishi Y, Moriya Y, Tokimatsu T, Kanehisa M, Goto S. Kotera M, et al. Among authors: tabei y. BMC Syst Biol. 2013;7 Suppl 6(Suppl 6):S2. doi: 10.1186/1752-0509-7-S6-S2. Epub 2013 Dec 13. BMC Syst Biol. 2013. PMID: 24564846 Free PMC article.

7

Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers.

Tabei Y, Pauwels E, Stoven V, Takemoto K, Yamanishi Y. Tabei Y, et al. Bioinformatics. 2012 Sep 15;28(18):i487-i494. doi: 10.1093/bioinformatics/bts412. Bioinformatics. 2012. PMID: 22962471 Free PMC article.

8

Scalable prediction of compound-protein interactions using minwise hashing.

Tabei Y, Yamanishi Y. Tabei Y, et al. BMC Syst Biol. 2013;7 Suppl 6(Suppl 6):S3. doi: 10.1186/1752-0509-7-S6-S3. Epub 2013 Dec 13. BMC Syst Biol. 2013. PMID: 24564870 Free PMC article.

9

Predicting inhibitory and activatory drug targets by chemically and genetically perturbed transcriptome signatures.

Sawada R, Iwata M, Tabei Y, Yamato H, Yamanishi Y. Sawada R, et al. Among authors: tabei y. Sci Rep. 2018 Jan 9;8(1):156. doi: 10.1038/s41598-017-18315-9. Sci Rep. 2018. PMID: 29317676 Free PMC article.

10

Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm.

Iwata M, Yuan L, Zhao Q, Tabei Y, Berenger F, Sawada R, Akiyoshi S, Hamano M, Yamanishi Y. Iwata M, et al. Among authors: tabei y. Bioinformatics. 2019 Jul 15;35(14):i191-i199. doi: 10.1093/bioinformatics/btz313. Bioinformatics. 2019. PMID: 31510663 Free PMC article.

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