Makiko Suwa

2.6k total citations
60 papers, 1.7k citations indexed

About

Makiko Suwa is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Nutrition and Dietetics. According to data from OpenAlex, Makiko Suwa has authored 60 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Molecular Biology, 11 papers in Cellular and Molecular Neuroscience and 4 papers in Nutrition and Dietetics. Recurrent topics in Makiko Suwa's work include Machine Learning in Bioinformatics (32 papers), RNA and protein synthesis mechanisms (30 papers) and Protein Structure and Dynamics (12 papers). Makiko Suwa is often cited by papers focused on Machine Learning in Bioinformatics (32 papers), RNA and protein synthesis mechanisms (30 papers) and Protein Structure and Dynamics (12 papers). Makiko Suwa collaborates with scholars based in Japan, United Kingdom and India. Makiko Suwa's co-authors include M. Michael Gromiha, Kazushige Touhara, Sayako Katada, Yuki Oka, Takatsugu Hirokawa, Yukiteru Ono, Shandar Ahmad, Ryohei Yamaoka, Tatsuro Nakagawa and Masayo Omura and has published in prestigious journals such as Nucleic Acids Research, Neuron and Journal of Neuroscience.

In The Last Decade

Makiko Suwa

57 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Makiko Suwa Japan 22 992 556 372 276 192 60 1.7k
Jean‐Claude Pernollet France 30 767 0.8× 677 1.2× 210 0.6× 195 0.7× 405 2.1× 56 2.3k
Orna Man Israel 11 1.4k 1.4× 338 0.6× 458 1.2× 418 1.5× 297 1.5× 12 2.3k
Stefan Kubick Germany 28 1.7k 1.7× 475 0.9× 388 1.0× 327 1.2× 258 1.3× 79 2.4k
Fred F. Damberger Switzerland 27 1.9k 1.9× 681 1.2× 112 0.3× 212 0.8× 355 1.8× 41 2.7k
Marc Fivaz Singapore 25 1.5k 1.5× 532 1.0× 531 1.4× 86 0.3× 157 0.8× 46 2.7k
J Claude Pernollet France 15 265 0.3× 226 0.4× 214 0.6× 183 0.7× 156 0.8× 22 812
Xiangshu Jin United States 24 2.0k 2.0× 397 0.7× 418 1.1× 170 0.6× 209 1.1× 29 2.9k
Lukáš Žı́dek Czechia 23 1.0k 1.1× 134 0.2× 84 0.2× 54 0.2× 138 0.7× 59 1.5k
Shigeki Takeda Japan 24 1.1k 1.1× 327 0.6× 41 0.1× 135 0.5× 195 1.0× 71 1.6k
Jessica Siltberg-Liberles United States 14 474 0.5× 359 0.6× 138 0.4× 122 0.4× 47 0.2× 27 870

Countries citing papers authored by Makiko Suwa

Since Specialization
Citations

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

Fields of papers citing papers by Makiko Suwa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Makiko Suwa

This figure shows the co-authorship network connecting the top 25 collaborators of Makiko Suwa. A scholar is included among the top collaborators of Makiko Suwa 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 Makiko Suwa. Makiko Suwa 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.
Sugihara, Minoru, Makiko Suwa, & Ana‐Nicoleta Bondar. (2014). Dynamics of bovine opsin bound to G-protein fragments. Journal of Structural Biology. 188(1). 79–86. 4 indexed citations
2.
Suwa, Makiko. (2013). Bioinformatics Tools for Predicting GPCR Gene Functions. Advances in experimental medicine and biology. 796. 205–224. 4 indexed citations
3.
Toda, Etsuko, Yuya Terashima, Kaori Esaki, et al.. (2013). Identification of a binding element for the cytoplasmic regulator FROUNT in the membrane-proximal C-terminal region of chemokine receptors CCR2 and CCR5. Biochemical Journal. 457(2). 313–322. 14 indexed citations
4.
Suwa, Makiko & Yukiteru Ono. (2009). A bioinformatics strategy to produce a project structure of spiral development. 2(4). 299–309. 3 indexed citations
5.
Hirokawa, Takatsugu, et al.. (2007). Identification of Glycosyltransferases Focusing on Golgi Transmembrane Region. Trends in Glycoscience and Glycotechnology. 19(105). 41–47. 3 indexed citations
6.
Gromiha, M. Michael & Makiko Suwa. (2007). Current Developments on β-Barrel Membrane Proteins: Sequence and Structure Analysis, Discrimination and Prediction. Current Protein and Peptide Science. 8(6). 580–599. 13 indexed citations
7.
Oka, Yuki, Sayako Katada, Masayo Omura, et al.. (2006). Odorant Receptor Map in the Mouse Olfactory Bulb: In Vivo Sensitivity and Specificity of Receptor-Defined Glomeruli. Neuron. 52(5). 857–869. 145 indexed citations
8.
Gromiha, M. Michael, Shandar Ahmad, & Makiko Suwa. (2005). TMBETA-NET: discrimination and prediction of membrane spanning  -strands in outer membrane proteins. Nucleic Acids Research. 33(Web Server). W164–W167. 39 indexed citations
9.
Nagasaki, Hideki, et al.. (2005). Species-specific variation of alternative splicing and transcriptional initiation in six eukaryotes. Gene. 364. 53–62. 74 indexed citations
10.
Gromiha, M. Michael & Makiko Suwa. (2005). Structural analysis of residues involving cation-π interactions in different folding types of membrane proteins. International Journal of Biological Macromolecules. 35(1-2). 55–62. 29 indexed citations
11.
Swindells, Mark B., et al.. (2004). GENIUS II: a high-throughput database system for linking ORFs in complete genomes to known protein three-dimensional structures. Bioinformatics. 20(4). 596–598. 2 indexed citations
12.
Nagasaki, Hideki, Makiko Suwa, & Osamu Gotoh. (2003). An Algorithm for Classification of Alternative Splicing and Transcriptional Initiation and Its Genome-Wide Application. Proceedings Genome Informatics Workshop/Genome informatics. 14. 424–425. 3 indexed citations
13.
Suwa, Makiko, Toshiyuki Sato, Yutaka Akiyama, et al.. (2000). Gene Discovery of G-Protein Coupled Receptors from Human Genome. Proceedings Genome Informatics Workshop/Genome informatics. 11. 410–411. 1 indexed citations
14.
Hirokawa, Takatsugu, et al.. (2000). A triangle lattice model that predicts transmembrane helix configuration using a polar jigsaw puzzle. Protein Engineering Design and Selection. 13(11). 771–778. 14 indexed citations
15.
Salamov, Asaf, Makiko Suwa, Christine Orengo, & Mark B. Swindells. (1999). Combining sensitive database searches with multiple intermediates to detect distant homologues. Protein Engineering Design and Selection. 12(2). 95–100. 45 indexed citations
16.
Salamov, Asaf, Makiko Suwa, Christine Orengo, & Mark B. Swindells. (1999). Genome analysis: Assigning protein coding regions to three‐dimensional structures. Protein Science. 8(4). 771–777. 26 indexed citations
17.
Ishikawa, Takashi, Shigeki Mitaku, Takao Terano, Makiko Suwa, & Takatsugu Hirokawa. (1996). Discovering Functional Sites of Amino Acid Sequences Using Sorted Variable Generalization. Proceedings Genome Informatics Workshop/Genome informatics. 7(7). 178–179.
18.
Ishikawa, Takashi, et al.. (1995). Building a knowledge-base for protein function prediction using multistrategy learning. Proceedings Genome Informatics Workshop/Genome informatics. 6. 39–48. 2 indexed citations
19.
Ishikawa, Takashi, et al.. (1994). Finding Functional Features of Proteins using Machine Learning Techniques. Proceedings Genome Informatics Workshop/Genome informatics. 5. 168–169. 1 indexed citations
20.
Suwa, Makiko, Shigeki Mitaku, & Y. KURODA. (1993). Theoretical Analysis of Amino Acid Sequence of Human Dystrophin. Biochemical and Biophysical Research Communications. 191(3). 782–789. 2 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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