Shigeki Kajihara

957 total citations
21 papers, 712 citations indexed

About

Shigeki Kajihara is a scholar working on Molecular Biology, Spectroscopy and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Shigeki Kajihara has authored 21 papers receiving a total of 712 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 13 papers in Spectroscopy and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Shigeki Kajihara's work include Mass Spectrometry Techniques and Applications (11 papers), Metabolomics and Mass Spectrometry Studies (9 papers) and Advanced Proteomics Techniques and Applications (9 papers). Shigeki Kajihara is often cited by papers focused on Mass Spectrometry Techniques and Applications (11 papers), Metabolomics and Mass Spectrometry Studies (9 papers) and Advanced Proteomics Techniques and Applications (9 papers). Shigeki Kajihara collaborates with scholars based in Japan and United States. Shigeki Kajihara's co-authors include Mitsutoshi Setou, Hiroki Nakanishi, Ryo Taguchi, Mitsuo Kawato, Taku Yoshioka, Kenji Doya, Masa-aki Sato, Naokazu Goda, Keisuke Toyama and Nobuhiro Zaima and has published in prestigious journals such as Bioinformatics, PLoS ONE and NeuroImage.

In The Last Decade

Shigeki Kajihara

21 papers receiving 690 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shigeki Kajihara Japan 12 347 243 151 117 48 21 712
Àngel Moreno‐Torres Spain 13 203 0.6× 108 0.4× 32 0.2× 425 3.6× 43 0.9× 19 740
Christophe Ladroue United Kingdom 13 361 1.0× 102 0.4× 30 0.2× 120 1.0× 32 0.7× 19 737
Ruimin Wang China 11 140 0.4× 41 0.2× 83 0.5× 36 0.3× 26 0.5× 42 415
Liang Zhou China 13 89 0.3× 37 0.2× 41 0.3× 43 0.4× 24 0.5× 73 579
Kenichi Kamijo Japan 13 114 0.3× 64 0.3× 131 0.9× 49 0.4× 16 0.3× 32 432
Gordon B. Scarth Canada 9 77 0.2× 27 0.1× 102 0.7× 194 1.7× 24 0.5× 15 406
Shanzhuo Zhang China 9 272 0.8× 23 0.1× 60 0.4× 57 0.5× 16 0.3× 14 656
L. Vanhamme Belgium 7 83 0.2× 57 0.2× 28 0.2× 301 2.6× 46 1.0× 13 481
Walid M. Abdelmoula United States 17 464 1.3× 388 1.6× 26 0.2× 91 0.8× 1 0.0× 23 806
J. de Certaines France 17 236 0.7× 112 0.5× 18 0.1× 663 5.7× 5 0.1× 60 1.2k

Countries citing papers authored by Shigeki Kajihara

Since Specialization
Citations

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

Fields of papers citing papers by Shigeki Kajihara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shigeki Kajihara

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

All Works

20 of 20 papers shown
1.
2.
Noda, A., Arisa Ito, Kyoko Hashimoto, et al.. (2020). Fake metabolomics chromatogram generation for facilitating deep learning of peak-picking neural networks. Journal of Bioscience and Bioengineering. 131(2). 207–212. 3 indexed citations
3.
Sato, Masaya, Shigeki Kajihara, Ryosuke Tateishi, et al.. (2019). Machine-learning Approach for the Development of a Novel Predictive Model for the Diagnosis of Hepatocellular Carcinoma. Scientific Reports. 9(1). 7704–7704. 92 indexed citations
4.
Kawaguchi‐Sakita, Nobuko, Masahiro Kawashima, Masahiro Sugimoto, et al.. (2015). Serum immunoglobulin G Fc region N-glycosylation profiling by matrix-assisted laser desorption/ionization mass spectrometry can distinguish breast cancer patients from cancer-free controls. Biochemical and Biophysical Research Communications. 469(4). 1140–1145. 36 indexed citations
5.
Nakayama, Kenji, Takahiro Inoue, Sadanori Sekiya, et al.. (2014). The C-Terminal Fragment of Prostate-Specific Antigen, a 2331 Da Peptide, as a New Urinary Pathognomonic Biomarker Candidate for Diagnosing Prostate Cancer. PLoS ONE. 9(9). e107234–e107234. 12 indexed citations
6.
Aoshima, Ken, Kentaro Takahashi, Takayuki Kimura, et al.. (2014). A simple peak detection and label-free quantitation algorithm for chromatography-mass spectrometry. BMC Bioinformatics. 15(1). 376–376. 12 indexed citations
7.
Kajihara, Shigeki, et al.. (2014). Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry. Mass Spectrometry. 3(1). A0030–A0030. 3 indexed citations
8.
Tanaka, Satoshi, Akiyasu C. Yoshizawa, Yoshihiro Yamada, et al.. (2014). Mass++: A Visualization and Analysis Tool for Mass Spectrometry. Journal of Proteome Research. 13(8). 3846–3853. 35 indexed citations
9.
Yoshizawa, Akiyasu C., Yuko Fukuyama, Shigeki Kajihara, Hiroki Kuyama, & Kōichi Tanaka. (2014). Computational Survey of Sequence Specificity for Protein Terminal Tags Covering Nine Organisms and Its Application to Protein Identification. Journal of Proteome Research. 14(2). 756–767. 1 indexed citations
10.
Tanaka, Satoshi, et al.. (2014). Signal Processing Algorithm Development for Mass++ (Ver. 2): Platform Software for Mass Spectrometry. 7(0). 24–29. 5 indexed citations
11.
12.
Saito, Yûsuke, Takahiro Hayasaka, Kenji Onoue, et al.. (2011). Pharmacokinetic Analysis Using a High Spatial-Resolution Mass Microscope. Journal of the Mass Spectrometry Society of Japan. 59(4). 79–84. 3 indexed citations
13.
Kubo, Akiko, Mitsuyo Ohmura, Masatoshi Wakui, et al.. (2011). Semi-quantitative analyses of metabolic systems of human colon cancer metastatic xenografts in livers of superimmunodeficient NOG mice. Analytical and Bioanalytical Chemistry. 400(7). 1895–1904. 49 indexed citations
14.
Hayasaka, Takahiro, Naoko Goto‐Inoue, Masaru Ushijima, et al.. (2011). Development of imaging mass spectrometry (IMS) dataset extractor software, IMS convolution. Analytical and Bioanalytical Chemistry. 401(1). 183–193. 18 indexed citations
15.
Wang, Hong, Chee‐Hong Wong, Alice Chin, et al.. (2011). Integrated mass spectrometry–based analysis of plasma glycoproteins and their glycan modifications. Nature Protocols. 6(3). 253–269. 35 indexed citations
16.
Roy, Michael C., Hiroki Nakanishi, Setsuko Nakanishi, et al.. (2010). Salamander retina phospholipids and their localization by MALDI imaging mass spectrometry at cellular size resolution. Journal of Lipid Research. 52(3). 463–470. 35 indexed citations
17.
Sugiura, Yuki, Yoshiyuki Konishi, Nobuhiro Zaima, et al.. (2009). Visualization of the cell-selective distribution of PUFA-containing phosphatidylcholines in mouse brain by imaging mass spectrometry. Journal of Lipid Research. 50(9). 1776–1788. 165 indexed citations
18.
Sato, Masa-aki, Taku Yoshioka, Shigeki Kajihara, et al.. (2004). Hierarchical Bayesian estimation for MEG inverse problem. NeuroImage. 23(3). 806–826. 178 indexed citations
19.
Kajihara, Shigeki, et al.. (2000). Moving Mesh Method for Reconstructing Some Spread Sources in the Brain. Brain Topography. 12(4). 283–292. 2 indexed citations
20.
Kajihara, Shigeki, et al.. (1996). Influence of head model in biomagnetic source localization. Brain Topography. 8(3). 337–340. 7 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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