Mitsuo Iwadate

1.3k total citations
33 papers, 797 citations indexed

About

Mitsuo Iwadate is a scholar working on Molecular Biology, Materials Chemistry and Epidemiology. According to data from OpenAlex, Mitsuo Iwadate has authored 33 papers receiving a total of 797 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 8 papers in Materials Chemistry and 5 papers in Epidemiology. Recurrent topics in Mitsuo Iwadate's work include Protein Structure and Dynamics (10 papers), Enzyme Structure and Function (8 papers) and Machine Learning in Bioinformatics (6 papers). Mitsuo Iwadate is often cited by papers focused on Protein Structure and Dynamics (10 papers), Enzyme Structure and Function (8 papers) and Machine Learning in Bioinformatics (6 papers). Mitsuo Iwadate collaborates with scholars based in Japan, United Kingdom and Germany. Mitsuo Iwadate's co-authors include Michael P. Williamson, Hideaki Umeyama, Tetsuo Asakura, Y‐h. Taguchi, Makoto Demura, Tatsuya Yamaguchi, Hirofumi Arakawa, Koichi Matsuda, Yoji Sagiya and Yusuke Nakamura and has published in prestigious journals such as Scientific Reports, Biochemical and Biophysical Research Communications and European Journal of Biochemistry.

In The Last Decade

Mitsuo Iwadate

33 papers receiving 785 citations

Peers

Mitsuo Iwadate
Tetsuo Uno United States
James G. Bann United States
Holly Gratkowski United States
Tetsuo Uno United States
Mitsuo Iwadate
Citations per year, relative to Mitsuo Iwadate Mitsuo Iwadate (= 1×) peers Tetsuo Uno

Countries citing papers authored by Mitsuo Iwadate

Since Specialization
Citations

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

Fields of papers citing papers by Mitsuo Iwadate

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mitsuo Iwadate

This figure shows the co-authorship network connecting the top 25 collaborators of Mitsuo Iwadate. A scholar is included among the top collaborators of Mitsuo Iwadate 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 Mitsuo Iwadate. Mitsuo Iwadate 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.
Honda, Takashi, Masatoshi Ishigami, Yoji Ishizu, et al.. (2016). Core I97L mutation in conjunction with P79Q is associated with persistent low HBV DNA and HBs antigen clearance in patients with chronic hepatitis B. Clinical Microbiology and Infection. 23(6). 407.e1–407.e7. 5 indexed citations
2.
Taguchi, Y‐h., Mitsuo Iwadate, & Hideaki Umeyama. (2016). SFRP1 is a possible candidate for epigenetic therapy in non-small cell lung cancer. BMC Medical Genomics. 9(S1). 28–28. 27 indexed citations
3.
Umeyama, Hideaki, Mitsuo Iwadate, Toshihito Tanahashi, et al.. (2015). Development of novel hepatitis B virus capsid inhibitor using in silico screening. Biochemical and Biophysical Research Communications. 463(4). 1165–1175. 11 indexed citations
4.
Taguchi, Y‐h., Mitsuo Iwadate, & Hideaki Umeyama. (2015). Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease. BMC Bioinformatics. 16(1). 30 indexed citations
5.
Murakami, Yoshiki, Yoshihiko Yano, Toshihito Tanahashi, et al.. (2014). Discovering novel direct acting antiviral agents for HBV using in silico screening. Biochemical and Biophysical Research Communications. 456(1). 20–28. 10 indexed citations
6.
Umeyama, Hideaki, Mitsuo Iwadate, & Y‐h. Taguchi. (2014). TINAGL1 and B3GALNT1 are potential therapy target genes to suppress metastasis in non-small cell lung cancer. BMC Genomics. 15(S9). S2–S2. 41 indexed citations
8.
Iwadate, Mitsuo, et al.. (2013). Discrimination of symbiotic/parasitic bacterial type III secretion system effector protein using principal component analysis (ニューロコンピューティング). IEICE technical report. Speech. 113(111). 47–54. 1 indexed citations
9.
Umeyama, Hideaki, et al.. (2013). Bioinformatic Screening of Autoimmune Disease Genes and Protein Structure Prediction with FAMS for Drug Discovery. Protein and Peptide Letters. 21(8). 828–839. 21 indexed citations
10.
Terashi, Genki, Mayuko Takeda‐Shitaka, Kazuhiko Kanou, et al.. (2007). Fams-ace: A combined method to select the best model after remodeling all server models. Proteins Structure Function and Bioinformatics. 69(S8). 98–107. 17 indexed citations
11.
Terashi, Genki, Mayuko Takeda‐Shitaka, Kazuhiko Kanou, et al.. (2007). The SKE‐DOCK server and human teams based on a combined method of shape complementarity and free energy estimation. Proteins Structure Function and Bioinformatics. 69(4). 866–872. 18 indexed citations
12.
Takeda‐Shitaka, Mayuko, Genki Terashi, Daisuke Takaya, et al.. (2005). Protein structure prediction in CASP6 using CHIMERA and FAMS. Proteins Structure Function and Bioinformatics. 61(S7). 122–127. 10 indexed citations
13.
Komatsu, Katsuichiro, et al.. (2003). Evaluation of the third solvent clusters fitting procedure for the prediction of protein–protein interactions based on the results at the CAPRI blind docking study. Proteins Structure Function and Bioinformatics. 52(1). 15–18. 5 indexed citations
14.
Demura, Makoto, Mitsuo Iwadate, Anne S. Ulrich, et al.. (2001). Interaction of mastoparan with membranes studied by 1H‐NMR spectroscopy in detergent micelles and by solid‐state 2H‐NMR and 15N‐NMR spectroscopy in oriented lipid bilayers. European Journal of Biochemistry. 268(2). 302–309. 56 indexed citations
15.
Hori, Yumiko, Makoto Demura, Mitsuo Iwadate, et al.. (2001). Interaction of mastoparan with membranes studied by 1H-NMR spectroscopy in detergent micelles and by solid-state 2H-NMR and 15N-NMR spectroscopy in oriented lipid bilayers. European Journal of Biochemistry. 268(2). 302–309. 3 indexed citations
16.
Iwadate, Mitsuo, et al.. (2000). Structure determination of [Arg8]vasopressin methylenedithioether in dimethylsulfoxide using NMR. European Journal of Biochemistry. 267(14). 4504–4510. 5 indexed citations
17.
Ueki, Masaaki, et al.. (1999). Solid phase synthesis and biological activities of [Arg8]-vasopressin methylenedithioether. Bioorganic & Medicinal Chemistry Letters. 9(13). 1767–1772. 11 indexed citations
18.
Iwadate, Mitsuo, et al.. (1999). Structural analysis of silk with 13C NMR chemical shift contour plots. International Journal of Biological Macromolecules. 24(2-3). 167–171. 93 indexed citations
19.
Iwadate, Mitsuo, Tetsuo Asakura, & Michael P. Williamson. (1999). Cα and Cβ Carbon-13 Chemical Shifts in Proteins From an Empirical Database. Journal of Biomolecular NMR. 13(3). 199–211. 150 indexed citations
20.
Iwadate, Mitsuo, Tetsuo Asakura, & Michael P. Williamson. (1998). The structure of the melittin tetramer at different temperatures. European Journal of Biochemistry. 257(2). 479–487. 39 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026