Morihiro Hayashida

1.8k total citations
62 papers, 1.3k citations indexed

About

Morihiro Hayashida is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Morihiro Hayashida has authored 62 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 10 papers in Artificial Intelligence and 10 papers in Computational Theory and Mathematics. Recurrent topics in Morihiro Hayashida's work include Bioinformatics and Genomic Networks (25 papers), Machine Learning in Bioinformatics (19 papers) and Protein Structure and Dynamics (17 papers). Morihiro Hayashida is often cited by papers focused on Bioinformatics and Genomic Networks (25 papers), Machine Learning in Bioinformatics (19 papers) and Protein Structure and Dynamics (17 papers). Morihiro Hayashida collaborates with scholars based in Japan, China and Australia. Morihiro Hayashida's co-authors include Tatsuya Akutsu, Wai‐Ki Ching, Michael K. Ng, Jiangning Song, Trevor Lithgow, Jiawei Wang, Jose C. Nacher, André Leier, Tatiana T. Marquez‐Lago and Mayumi Kamada and has published in prestigious journals such as Bioinformatics, PLoS ONE and Scientific Reports.

In The Last Decade

Morihiro Hayashida

61 papers receiving 1.2k citations

Peers

Morihiro Hayashida

CTM

GENET

ENDOC

Marie-France Sagot France

Zhirong Sun China

Pedro T. Monteiro Portugal

Alfonso Rodríguez‐Patón Spain

Alain Schenkel Switzerland

Peng Ni China

Renzhi Cao United States

André Leier United States

Vincent Schächter France

Kyungsook Han South Korea

Marie-France Sagot France

Morihiro Hayashida

1.0k ×1.0

97 ×0.4

CTM

176 ×1.7

GENET

206 ×2.7

51 ×0.7

ENDOC

Citations per year, relative to Morihiro Hayashida Morihiro Hayashida (= 1×) peers Marie-France Sagot

Countries citing papers authored by Morihiro Hayashida

Since Specialization

Citations

This map shows the geographic impact of Morihiro Hayashida's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Morihiro Hayashida with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Morihiro Hayashida more than expected).

Fields of papers citing papers by Morihiro Hayashida

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Morihiro Hayashida. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Morihiro Hayashida. The network helps show where Morihiro Hayashida may publish in the future.

Co-authorship network of co-authors of Morihiro Hayashida

This figure shows the co-authorship network connecting the top 25 collaborators of Morihiro Hayashida. A scholar is included among the top collaborators of Morihiro Hayashida based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Morihiro Hayashida. Morihiro Hayashida is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Hayashida, Morihiro, et al.. (2019). Optimal string clustering based on a Laplace-like mixture and EM algorithm on a set of strings. Journal of Computer and System Sciences. 106. 94–128. 1 indexed citations

Nakajima, Natsu, Morihiro Hayashida, Jesper Jansson, Osamu Maruyama, & Tatsuya Akutsu. (2018). Determining the minimum number of protein-protein interactions required to support known protein complexes. PLoS ONE. 13(4). e0195545–e0195545. 10 indexed citations

Hayashida, Morihiro, et al.. (2018). ncRNA-disease association prediction based on sequence information and tripartite network. BMC Systems Biology. 12(S1). 37–37. 14 indexed citations

An, Yi, Jiawei Wang, Chen Li, et al.. (2017). SecretEPDB: a comprehensive web-based resource for secreted effector proteins of the bacterial types III, IV and VI secretion systems. Scientific Reports. 7(1). 41031–41031. 39 indexed citations

Hayashida, Morihiro, et al.. (2016). Maximum margin classifier working in a set of strings. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 472(2187). 20150551–20150551. 2 indexed citations

Hayashida, Morihiro, et al.. (2016). Enumeration method for tree-like chemical compounds with benzene rings and naphthalene rings by breadth-first search order. BMC Bioinformatics. 17(1). 113–113. 3 indexed citations

Bao, Yu, Morihiro Hayashida, & Tatsuya Akutsu. (2016). LBSizeCleav: improved support vector machine (SVM)-based prediction of Dicer cleavage sites using loop/bulge length. BMC Bioinformatics. 17(1). 487–487. 14 indexed citations

Kamada, Mayumi, et al.. (2014). Prediction of Protein-Protein Interaction Strength Using Domain Features with Supervised Regression. The Scientific World JOURNAL. 2014. 1–7. 10 indexed citations

Hayashida, Morihiro, et al.. (2014). Proteome compression via protein domain compositions. Methods. 67(3). 380–385. 6 indexed citations

10.

Kamada, Mayumi, et al.. (2013). Inferring Strengths of Protein-Protein Interactions Using Support Vector Regression. 2013(1). 1–4. 2 indexed citations

11.

Hayashida, Morihiro, et al.. (2013). Prediction of Heterodimeric Protein Complexes from Weighted Protein-Protein Interaction Networks Using Novel Features and Kernel Functions. PLoS ONE. 8(6). e65265–e65265. 10 indexed citations

12.

Hayashida, Morihiro, Mayumi Kamada, Jiangning Song, & Tatsuya Akutsu. (2011). Conditional random field approach to prediction of protein-protein interactions using domain information. BMC Systems Biology. 5(Suppl 1). S8–S8. 31 indexed citations

13.

Hayashida, Morihiro & Tatsuya Akutsu. (2010). Comparing biological networks via graph compression. BMC Systems Biology. 4(S2). S13–S13. 15 indexed citations

14.

Zhao, Yang, Morihiro Hayashida, & Tatsuya Akutsu. (2010). Integer programming-based method for grammar-based tree compression and its application to pattern extraction of glycan tree structures. BMC Bioinformatics. 11(S11). S4–S4. 7 indexed citations

15.

Hayashida, Morihiro, Takeyuki Tamura, Tatsuya Akutsu, Shuqin Zhang, & Wai‐Ki Ching. (2008). Algorithms and Complexity Analyses for Control of Singleton Attractors in Boolean Networks. PubMed. 2008. 1–16. 7 indexed citations

16.

Nacher, Jose C., Morihiro Hayashida, & Tatsuya Akutsu. (2008). Emergence of scale-free distribution in protein–protein interaction networks based on random selection of interacting domain pairs. Biosystems. 95(2). 155–159. 15 indexed citations

17.

Zhang, Shuqin, Morihiro Hayashida, Tatsuya Akutsu, Wai‐Ki Ching, & Michael K. Ng. (2007). Algorithms for Finding Small Attractors in Boolean Networks. PubMed. 2007. 1–13. 60 indexed citations

18.

Akutsu, Tatsuya, Morihiro Hayashida, Wai‐Ki Ching, & Michael K. Ng. (2006). Control of Boolean networks: Hardness results and algorithms for tree structured networks. Journal of Theoretical Biology. 244(4). 670–679. 448 indexed citations

19.

Hayashida, Morihiro, Nobuhisa Ueda, & Tatsuya Akutsu. (2003). Inferring strengths of protein-protein interactions from experimental data using linear programming. Bioinformatics. 19(suppl_2). ii58–ii65. 17 indexed citations

20.

Hayashida, Morihiro, et al.. (1993). Synthesis and Evaluation of (Piperidinomethylene)bis(phosphonic acid) Derivatives as Anti-osteoporosis Agents.. Chemical and Pharmaceutical Bulletin. 41(11). 1971–1986. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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