Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDYoshihiro Yamanishi
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2022
[j44]Ryohei Eguchi
, Momoko Hamano, Michio Iwata, Toru Nakamura, Shinya Oki, Yoshihiro Yamanishi:
TRANSDIRE: data-driven direct reprogramming by a pioneer factor-guided trans-omics approach. Bioinform. 38(10): 2839-2846 (2022)- [j43]Zhaonan Zou, Michio Iwata, Yoshihiro Yamanishi, Shinya Oki:
Epigenetic landscape of drug responses revealed through large-scale ChIP-seq data analyses. BMC Bioinform. 23(1): 51 (2022) - [j42]Kazuma Kaitoh, Yoshihiro Yamanishi:
Scaffold-Retained Structure Generator to Exhaustively Create Molecules in an Arbitrary Chemical Space. J. Chem. Inf. Model. 62(9): 2212-2225 (2022) - [c13]Chen Li, Chikashige Yamanaka, Kazuma Kaitoh, Yoshihiro Yamanishi:
Transformer-based Objective-reinforced Generative Adversarial Network to Generate Desired Molecules. IJCAI 2022: 3884-3890 - 2021
- [j41]Francois Berenger, Ashutosh Kumar, Kam Y. J. Zhang, Yoshihiro Yamanishi:
Lean-Docking: Exploiting Ligands' Predicted Docking Scores to Accelerate Molecular Docking. J. Chem. Inf. Model. 61(5): 2341-2352 (2021) - [j40]Kazuma Kaitoh, Yoshihiro Yamanishi:
TRIOMPHE: Transcriptome-Based Inference and Generation of Molecules with Desired Phenotypes by Machine Learning. J. Chem. Inf. Model. 61(9): 4303-4320 (2021) - 2020
- [j39]Midori Iida, Michio Iwata, Yoshihiro Yamanishi:
Network-based characterization of disease-disease relationships in terms of drugs and therapeutic targets. Bioinform. 36(Supplement-1): i516-i524 (2020) - [j38]Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima:
Dual graph convolutional neural network for predicting chemical networks. BMC Bioinform. 21-S(3): 94 (2020) - [j37]Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh:
Space-Efficient Feature Maps for String Alignment Kernels. Data Sci. Eng. 5(2): 168-179 (2020) - [j36]Francois Berenger, Yoshihiro Yamanishi:
Ranking Molecules with Vanishing Kernels and a Single Parameter: Active Applicability Domain Included. J. Chem. Inf. Model. 60(9): 4376-4387 (2020)
2010 – 2019
- 2019
- [j35]Michio Iwata, Longhao Yuan, Qibin Zhao, Yasuo Tabei, Francois Berenger, Ryusuke Sawada, Sayaka Akiyoshi, Momoko Hamano, Yoshihiro Yamanishi:
Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm. Bioinform. 35(14): i191-i199 (2019) - [j34]Yasuo Tabei, Masaaki Kotera, Ryusuke Sawada, Yoshihiro Yamanishi:
Network-based characterization of drug-protein interaction signatures with a space-efficient approach. BMC Syst. Biol. 13-S(2): 39:1-39:15 (2019) - [j33]Francois Berenger, Kam Y. J. Zhang, Yoshihiro Yamanishi:
Chemoinformatics and structural bioinformatics in OCaml. J. Cheminformatics 11(1): 10:1-10:13 (2019) - [j32]Francois Berenger, Yoshihiro Yamanishi:
A Distance-Based Boolean Applicability Domain for Classification of High Throughput Screening Data. J. Chem. Inf. Model. 59(1): 463-476 (2019) - [j31]Yoshihiro Yamanishi, Yasubumi Sakakibara, Yi-Ping Phoebe Chen:
Guest Editorial for the 16th Asia Pacific Bioinformatics Conference. IEEE ACM Trans. Comput. Biol. Bioinform. 16(1): 1-2 (2019) - [c12]Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh:
Space-Efficient Feature Maps for String Alignment Kernels. ICDM 2019: 1312-1317 - 2018
- [i3]Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh:
Scalable Alignment Kernels via Space-Efficient Feature Maps. CoRR abs/1802.06382 (2018) - [i2]Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima:
Dual Convolutional Neural Network for Graph of Graphs Link Prediction. CoRR abs/1810.02080 (2018) - 2016
- [j30]Yasuo Tabei, Yoshihiro Yamanishi, Masaaki Kotera:
Simultaneous prediction of enzyme orthologs from chemical transformation patterns for de novo metabolic pathway reconstruction. Bioinform. 32(12): 278-287 (2016) - [c11]Yasuo Tabei, Hiroto Saigo, Yoshihiro Yamanishi, Simon J. Puglisi:
Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices. KDD 2016: 1875-1884 - [i1]Yasuo Tabei, Hiroto Saigo, Yoshihiro Yamanishi, Simon J. Puglisi:
Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices. CoRR abs/1606.05031 (2016) - 2015
- [j29]Yoshihiro Yamanishi, Yasuo Tabei, Masaaki Kotera:
Metabolome-scale de novo pathway reconstruction using regioisomer-sensitive graph alignments. Bioinform. 31(12): 161-170 (2015) - [j28]Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Yoshihiro Yamanishi:
Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data. J. Chem. Inf. Model. 55(2): 446-459 (2015) - [j27]Zheng Shao, Yuya Hirayama, Yoshihiro Yamanishi, Hiroto Saigo:
Mining Discriminative Patterns from Graph Data with Multiple Labels and Its Application to Quantitative Structure-Activity Relationship (QSAR) Models. J. Chem. Inf. Model. 55(12): 2519-2527 (2015) - [j26]Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Masaaki Kotera, Yoshihiro Yamanishi:
Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles. J. Chem. Inf. Model. 55(12): 2705-2716 (2015) - [j25]Ryusuke Sawada, Hiroaki Iwata, Sayaka Mizutani, Yoshihiro Yamanishi:
Target-Based Drug Repositioning Using Large-Scale Chemical-Protein Interactome Data. J. Chem. Inf. Model. 55(12): 2717-2730 (2015) - 2014
- [j24]Masaaki Kotera, Yasuo Tabei, Yoshihiro Yamanishi, Ai Muto, Yuki Moriya, Toshiaki Tokimatsu, Susumu Goto:
Metabolome-scale prediction of intermediate compounds in multistep metabolic pathways with a recursive supervised approach. Bioinform. 30(12): 165-174 (2014) - [j23]Yoshihiro Yamanishi, Masaaki Kotera, Yuki Moriya, Ryusuke Sawada, Minoru Kanehisa, Susumu Goto:
DINIES: drug-target interaction network inference engine based on supervised analysis. Nucleic Acids Res. 42(Webserver-Issue): 39-45 (2014) - 2013
- [j22]Masaaki Kotera, Yasuo Tabei, Yoshihiro Yamanishi, Toshiaki Tokimatsu, Susumu Goto:
Supervised de novo reconstruction of metabolic pathways from metabolome-scale compound sets. Bioinform. 29(13): 135-144 (2013) - [j21]Hiroaki Iwata, Sayaka Mizutani, Yasuo Tabei, Masaaki Kotera, Susumu Goto, Yoshihiro Yamanishi:
Inferring protein domains associated with drug side effects based on drug-target interaction network. BMC Syst. Biol. 7(S-6): S18 (2013) - [j20]Masaaki Kotera, Yasuo Tabei, Yoshihiro Yamanishi, Yuki Moriya, Toshiaki Tokimatsu, Minoru Kanehisa, Susumu Goto:
KCF-S: KEGG Chemical Function and Substructure for improved interpretability and prediction in chemical bioinformatics. BMC Syst. Biol. 7(S-6): S2 (2013) - [j19]Yasuo Tabei, Yoshihiro Yamanishi:
Scalable prediction of compound-protein interactions using minwise hashing. BMC Syst. Biol. 7(S-6): S3 (2013) - [j18]Akihiro Nakaya, Toshiaki Katayama, Masumi Itoh, Kazushi Hiranuka, Shuichi Kawashima, Yuki Moriya, Shujiro Okuda, Michihiro Tanaka, Toshiaki Tokimatsu, Yoshihiro Yamanishi, Akiyasu C. Yoshizawa, Minoru Kanehisa, Susumu Goto:
KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters. Nucleic Acids Res. 41(Database-Issue): 353-357 (2013) - [c10]Yasuo Tabei, Akihiro Kishimoto, Masaaki Kotera, Yoshihiro Yamanishi:
Succinct interval-splitting tree for scalable similarity search of compound-protein pairs with property constraints. KDD 2013: 176-184 - 2012
- [j17]Yasuo Tabei, Edouard Pauwels, Véronique Stoven, Kazuhiro Takemoto, Yoshihiro Yamanishi:
Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers. Bioinform. 28(18): 487-494 (2012) - [j16]Sayaka Mizutani, Edouard Pauwels, Véronique Stoven, Susumu Goto, Yoshihiro Yamanishi:
Relating drug-protein interaction network with drug side effects. Bioinform. 28(18): 522-528 (2012) - [j15]Masataka Takarabe, Masaaki Kotera, Yosuke Nishimura, Susumu Goto, Yoshihiro Yamanishi:
Drug target prediction using adverse event report systems: a pharmacogenomic approach. Bioinform. 28(18): 611-618 (2012) - [j14]Yoshihiro Yamanishi, Edouard Pauwels, Masaaki Kotera:
Drug Side-Effect Prediction Based on the Integration of Chemical and Biological Spaces. J. Chem. Inf. Model. 52(12): 3284-3292 (2012) - [j13]Masaaki Kotera, Yoshihiro Yamanishi, Yuki Moriya, Minoru Kanehisa, Susumu Goto:
GENIES: gene network inference engine based on supervised analysis. Nucleic Acids Res. 40(Web-Server-Issue): 162-167 (2012) - 2011
- [j12]Edouard Pauwels, Véronique Stoven, Yoshihiro Yamanishi:
Predicting drug side-effect profiles: a chemical fragment-based approach. BMC Bioinform. 12: 169 (2011) - [j11]Yoshihiro Yamanishi, Edouard Pauwels, Hiroto Saigo, Véronique Stoven:
Extracting Sets of Chemical Substructures and Protein Domains Governing Drug-Target Interactions. J. Chem. Inf. Model. 51(5): 1183-1194 (2011) - 2010
- [j10]Yoshihiro Yamanishi, Masaaki Kotera, Minoru Kanehisa, Susumu Goto:
Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework. Bioinform. 26(12): 246-254 (2010) - [j9]Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda:
Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel. IEICE Trans. Inf. Syst. 93-D(10): 2672-2679 (2010)
2000 – 2009
- 2009
- [j8]Yoshihiro Yamanishi, Masahiro Hattori, Masaaki Kotera, Susumu Goto, Minoru Kanehisa:
E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs. Bioinform. 25(12) (2009) - [j7]Kevin Bleakley, Yoshihiro Yamanishi:
Supervised prediction of drug-target interactions using bipartite local models. Bioinform. 25(18): 2397-2403 (2009) - [j6]Hisashi Kashima, Yoshihiro Yamanishi, Tsuyoshi Kato, Masashi Sugiyama, Koji Tsuda:
Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach. Bioinform. 25(22): 2962-2968 (2009) - [c9]Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda:
On Pairwise Kernels: An Efficient Alternative and Generalization Analysis. PAKDD 2009: 1030-1037 - [c8]Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda:
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. SDM 2009: 1100-1111 - 2008
- [j5]Minoru Kanehisa, Michihiro Araki, Susumu Goto, Masahiro Hattori, Mika Hirakawa, Masumi Itoh, Toshiaki Katayama, Shuichi Kawashima, Shujiro Okuda, Toshiaki Tokimatsu, Yoshihiro Yamanishi:
KEGG for linking genomes to life and the environment. Nucleic Acids Res. 36(Database-Issue): 480-484 (2008) - [c7]Yoshihiro Yamanishi, Michihiro Araki, Alex Gutteridge, Wataru Honda, Minoru Kanehisa:
Prediction of drug-target interaction networks from the integration of chemical and genomic spaces. ISMB 2008: 232-240 - [c6]Yoshihiro Yamanishi:
Supervised Bipartite Graph Inference. NIPS 2008: 1841-1848 - 2007
- [j4]Yoshihiro Yamanishi, Francis R. Bach, Jean-Philippe Vert:
Glycan classification with tree kernels. Bioinform. 23(10): 1211-1216 (2007) - [c5]Tetsuya Sato, Yoshihiro Yamanishi, Katsuhisa Horimoto, Minoru Kanehisa, Hiroyuki Toh:
Inference of Protein-Protein Interactions by Using Co-evolutionary Information. AB 2007: 322-333 - 2006
- [j3]Tetsuya Sato, Yoshihiro Yamanishi, Katsuhisa Horimoto, Minoru Kanehisa, Hiroyuki Toh:
Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions. Bioinform. 22(20): 2488-2492 (2006) - 2005
- [j2]Tetsuya Sato, Yoshihiro Yamanishi, Minoru Kanehisa, Hiroyuki Toh:
The inference of protein-protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships. Bioinform. 21(17): 3482-3489 (2005) - [j1]Yoshihiro Yamanishi, Yutaka Tanaka:
Sensitivity analysis in functional principal component analysis. Comput. Stat. 20(2): 311-326 (2005) - [c4]Yoshihiro Yamanishi, Jean-Philippe Vert, Minoru Kanehisa:
Supervised enzyme network inference from the integration of genomic data and chemical information. ISMB (Supplement of Bioinformatics) 2005: 468-477 - 2004
- [c3]Yoshihiro Yamanishi, Jean-Philippe Vert, Minoru Kanehisa:
Protein network inference from multiple genomic data: a supervised approach. ISMB/ECCB (Supplement of Bioinformatics) 2004: 363-370 - [c2]Jean-Philippe Vert, Yoshihiro Yamanishi:
Supervised Graph Inference. NIPS 2004: 1433-1440 - 2003
- [c1]Yoshihiro Yamanishi, Jean-Philippe Vert, Akihiro Nakaya, Minoru Kanehisa:
Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis. ISMB (Supplement of Bioinformatics) 2003: 323-330
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
load content from web.archive.org
Privacy notice: By enabling the option above, your browser will contact the API of web.archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2023-05-12 21:02 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
