D-Index & Metrics Best Publications

Hiroshi Mamitsuka

Kyoto University
Japan

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 34 Citations 5,063 205 World Ranking 8140 National Ranking 129

Overview

What is he best known for?

The fields of study Hiroshi Mamitsuka is best known for:

Gene
Enzyme
Bioinformatics

Hiroshi Mamitsuka works mostly in the field of Semantic similarity, limiting it down to concerns involving Information retrieval and, occasionally, Search engine indexing. He performs multidisciplinary studies into Search engine indexing and Information retrieval in his work. His research on Artificial intelligence frequently links to adjacent areas such as Pattern recognition (psychology). As part of his studies on Pattern recognition (psychology), Hiroshi Mamitsuka frequently links adjacent subjects like Artificial intelligence. With his scientific publications, his incorporates both Computational biology and Gene. His multidisciplinary approach integrates Gene and Computational biology in his work. He performs multidisciplinary study in Data mining and Feature selection in his work. By researching both Feature selection and Data mining, he produces research that crosses academic boundaries. His research is interdisciplinary, bridging the disciplines of Ranking (information retrieval) and Machine learning.

His most cited work include:

Similarity-based machine learning methods for predicting drug–target interactions: a brief review (286 citations)
Predicting peptides that bind to MHC molecules using supervised learning of hidden markov models (164 citations)
DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank (107 citations)

What are the main themes of his work throughout his whole career to date

Hiroshi Mamitsuka conducts interdisciplinary study in the fields of Artificial intelligence and Information retrieval through his works. His study on Machine learning is mostly dedicated to connecting different topics, such as Markov chain. Markov chain is closely attributed to Machine learning in his work. Hiroshi Mamitsuka integrates several fields in his works, including Computational biology and Bioinformatics. Hiroshi Mamitsuka merges Bioinformatics with Computational biology in his research. He undertakes multidisciplinary studies into Data mining and Cluster analysis in his work. He performs integrative study on Cluster analysis and Data mining. Genetics is closely attributed to Gene expression in his study. Gene expression connects with themes related to Genetics in his study.

Hiroshi Mamitsuka most often published in these fields:

Artificial intelligence (71.43%)
Machine learning (43.81%)
Computational biology (40.95%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Query Learning Strategies Using Boosting and Bagging

Naoki Abe;Hiroshi Mamitsuka.
international conference on machine learning (1998)

506 Citations

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

Hao Ding;Ichigaku Takigawa;Hiroshi Mamitsuka;Shanfeng Zhu.
Briefings in Bioinformatics (2014)

340 Citations

Collaborative matrix factorization with multiple similarities for predicting drug-target interactions

Xiaodong Zheng;Hao Ding;Hiroshi Mamitsuka;Shanfeng Zhu.
knowledge discovery and data mining (2013)

269 Citations

Predicting Peptides That Bind to MHC Molecules Using Supervised Learning of Hidden Markov Models

Hiroshi Mamitsuka.
Proteins (1998)

242 Citations

Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools

Lianming Zhang;Keiko Udaka;Hiroshi Mamitsuka;Shanfeng Zhu.
Briefings in Bioinformatics (2012)

132 Citations

Selecting features in microarray classification using ROC curves

Hiroshi Mamitsuka.
Pattern Recognition (2006)

125 Citations

A spectral clustering approach to optimally combining numericalvectors with a modular network

Motoki Shiga;Ichigaku Takigawa;Hiroshi Mamitsuka.
knowledge discovery and data mining (2007)

125 Citations

Multiple Graph Label Propagation by Sparse Integration

Masayuki Karasuyama;Hiroshi Mamitsuka.
IEEE Transactions on Neural Networks (2013)

122 Citations

A probabilistic model for mining implicit ‘chemical compound–gene’ relations from literature

Shanfeng Zhu;Yasushi Okuno;Gozoh Tsujimoto;Hiroshi Mamitsuka.
Bioinformatics (2005)

117 Citations

KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains

Kiyoko F. Aoki;Atsuko Yamaguchi;Nobuhisa Ueda;Tatsuya Akutsu.
Nucleic Acids Research (2004)

116 Citations

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Frequent Co-Authors

External Links

Personal Website for Hiroshi Mamitsuka