Satoshi Niijima

668 total citations
19 papers, 505 citations indexed

About

Satoshi Niijima is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Satoshi Niijima has authored 19 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Satoshi Niijima's work include Computational Drug Discovery Methods (7 papers), Bioinformatics and Genomic Networks (6 papers) and Gene expression and cancer classification (5 papers). Satoshi Niijima is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Bioinformatics and Genomic Networks (6 papers) and Gene expression and cancer classification (5 papers). Satoshi Niijima collaborates with scholars based in Japan. Satoshi Niijima's co-authors include Yasushi Okuno, Hiroaki Yabuuchi, Satoru Kuhara, Akira Shiraishi, Ryo Kunimoto, Akiko Tamon, Gozoh Tsujimoto, Yusuke Okuno, Chenchen Feng and Takatsugu Hirokawa and has published in prestigious journals such as Nucleic Acids Research, BMC Bioinformatics and BMC Genomics.

In The Last Decade

Satoshi Niijima

19 papers receiving 487 citations

Peers

Satoshi Niijima

CTM

PHARM

CMN

Yankang Jing United States

Zhining Wen China

Vladimir Chupakhin Russia

Sabina Podlewska Poland

Michele Fratello Finland

Murat Can Çobanoğlu United States

Wenqi Qiu China

Ziheng Hu United States

Qi Huang China

Zhaorong Li China

Yankang Jing United States

Satoshi Niijima

217 ×0.6

231 ×0.9

CTM

56 ×0.8

PHARM

35 ×0.9

15 ×0.4

CMN

Citations per year, relative to Satoshi Niijima Satoshi Niijima (= 1×) peers Yankang Jing

Countries citing papers authored by Satoshi Niijima

Since Specialization

Citations

This map shows the geographic impact of Satoshi Niijima'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 Satoshi Niijima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Satoshi Niijima more than expected).

Fields of papers citing papers by Satoshi Niijima

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Satoshi Niijima. 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 Satoshi Niijima. The network helps show where Satoshi Niijima may publish in the future.

Co-authorship network of co-authors of Satoshi Niijima

This figure shows the co-authorship network connecting the top 25 collaborators of Satoshi Niijima. A scholar is included among the top collaborators of Satoshi Niijima 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 Satoshi Niijima. Satoshi Niijima is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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19 of 19 papers shown

Shima, Daisuke, Takahide Kohro, Satoshi Hoshide, et al.. (2020). Validation of novel identification algorithms for major adverse cardiovascular events in a Japanese claims database. Journal of Clinical Hypertension. 23(3). 646–655. 14 indexed citations

Niijima, Satoshi, Tsukasa Ohmori, & Kazuomi Kario. (2018). Differential impact of diabetes mellitus on antiplatelet effects of prasugrel and clopidogrel. Thrombosis Journal. 16(1). 5–5. 3 indexed citations

Shima, Daisuke, Yoko Fujimoto, Takahide Kohro, et al.. (2018). Validation of Algorithms to Identify Acute Myocardial Infarction, Ischemic Stroke, and Hemorrhagic Stroke Cases from Japanese Claims Database. Value in Health. 21. S95–S95. 1 indexed citations

Imaizumi, Yuki, Katsumi Eguchi, Satoshi Niijima, et al.. (2016). Electron Microscopy of Contact Between a Monocyte and a Multinucleated Giant Cell in Cardiac Sarcoidosis. Canadian Journal of Cardiology. 32(12). 1577.e19–1577.e20. 1 indexed citations

Niijima, Satoshi, Michiaki Nagai, Satoshi Hoshide, et al.. (2016). Long sleep duration: a nonconventional indicator of arterial stiffness in Japanese at high risk of cardiovascular disease: the J-HOP study. Journal of the American Society of Hypertension. 10(5). 429–437. 22 indexed citations

Brown, J., Satoshi Niijima, & Yasushi Okuno. (2013). CompoundProtein Interaction Prediction Within Chemogenomics: Theoretical Concepts, Practical Usage, and Future Directions. Molecular Informatics. 32(11-12). 906–921. 14 indexed citations

Shiraishi, Akira, Satoshi Niijima, J.B. Brown, Masahiko Nakatsui, & Yasushi Okuno. (2013). Chemical Genomics Approach for GPCR–Ligand Interaction Prediction and Extraction of Ligand Binding Determinants. Journal of Chemical Information and Modeling. 53(6). 1253–1262. 17 indexed citations

Niijima, Satoshi, Akira Shiraishi, & Yasushi Okuno. (2012). Dissecting Kinase Profiling Data to Predict Activity and Understand Cross-Reactivity of Kinase Inhibitors. Journal of Chemical Information and Modeling. 52(4). 901–912. 40 indexed citations

Brown, J.B., Satoshi Niijima, Akira Shiraishi, Masahiko Nakatsui, & Yasushi Okuno. (2012). Chemogenomic approach to comprehensive predictions of ligand-target interactions: A comparative study. 2. 136–142. 4 indexed citations

10.

Yabuuchi, Hiroaki, Satoshi Niijima, Hiromu Takematsu, et al.. (2011). Analysis of multiple compound–protein interactions reveals novel bioactive molecules. Molecular Systems Biology. 7(1). 472–472. 118 indexed citations

11.

Sakaeda, Toshiyuki, et al.. (2011). Platinum Agent-Induced Hypersensitivity Reactions: Data Mining of the Public Version of the FDA Adverse Event Reporting System, AERS. International Journal of Medical Sciences. 8(4). 332–338. 37 indexed citations

12.

Niijima, Satoshi, Hiroaki Yabuuchi, & Yasushi Okuno. (2010). Cross-Target View to Feature Selection: Identification of Molecular Interaction Features in Ligand−Target Space. Journal of Chemical Information and Modeling. 51(1). 15–24. 19 indexed citations

13.

Feng, Chunlai, Michihiro Araki, Ryo Kunimoto, et al.. (2009). GEM-TREND: a web tool for gene expression data mining toward relevant network discovery. BMC Genomics. 10(1). 411–411. 23 indexed citations

14.

Niijima, Satoshi & Yasushi Okuno. (2009). Laplacian Linear Discriminant Analysis Approach to Unsupervised Feature Selection. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 6(4). 605–614. 45 indexed citations

15.

Okuno, Yusuke, Akiko Tamon, Hiroaki Yabuuchi, et al.. (2007). GLIDA: GPCR ligand database for chemical genomics drug discovery database and tools update. Nucleic Acids Research. 36(Database). D907–D912. 108 indexed citations

16.

Niijima, Satoshi & Satoru Kuhara. (2006). Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE. BMC Bioinformatics. 7(1). 543–543. 30 indexed citations

17.

Niijima, Satoshi & Satoru Kuhara. (2006). Gene subset selection in kernel-induced feature space. Pattern Recognition Letters. 27(16). 1884–1892. 6 indexed citations

18.

Niijima, Satoshi & Satoru Kuhara. (2005). MULTICLASS MOLECULAR CANCER CLASSIFICATION BY KERNEL SUBSPACE METHODS WITH EFFECTIVE KERNEL PARAMETER SELECTION. Journal of Bioinformatics and Computational Biology. 3(5). 1071–1088. 2 indexed citations

19.

Niijima, Satoshi & Shoogo Ueno. (2002). MEG source estimation using the fourth order MUSIC method. IEICE Transactions on Information and Systems. 167–174. 1 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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