Sachi Maeda

457 citations
25 papers · 186 · h-index 9

Impact in

    • Glioma Diagnosis and Treatment
    • Virus-based gene therapy research
    • Cancer Genomics and Diagnostics
    • MicroRNA in disease regulation

Papers in

    • Glioma Diagnosis and Treatment 16
    • Virus-based gene therapy research 2
    • Epigenetics and DNA Methylation 4
    • RNA Research and Splicing 2

Sachi Maeda

21 papers receiving 183 citations

Peers

Sachi Maeda
Comparison fields: 5 of 45
  • Genetics 68
  • Cancer Research 50
  • Structural Biology 3
  • Oncology 43
  • Developmental Neuroscience 6
Replace Denise Herpai with:
Denise Herpai United States
Takashi Tsujiuchi Japan
Susan Clenton United Kingdom
Landon J. Hansen United States
Ainhoa Hernández Spain
Brock Armstrong United States
Gilbert Youssef United States
Michaël H. Meel Netherlands
Valerio Ortenzi Italy
Sachi Maeda relative to Denise Herpai United States Denise Herpai's profile →
Citations per field
00.5×1.5×
Denise Herpai · 1×
Citations per year

Countries citing papers authored by Sachi Maeda

Since Specialization
Citations

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

Fields of papers citing papers by Sachi Maeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sachi Maeda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sachi Maeda Line = papers co-authored together Sachi Maeda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202246
2 202137
3 202115
4 201813
5 201812
6 20239
7 20219
8 20199
9 20238
10 20236
11 20194
12 20223
13 20243
14 20233
15 20202
16 20232
17 20231
18 20241
19 20251
20 20251

About Sachi Maeda

Sachi Maeda is a scholar working on Genetics, Molecular Biology, Cancer Research, Neurology and Radiology, Nuclear Medicine and Imaging, having authored 25 papers that have together received 186 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (16 papers), Neuroblastoma Research and Treatments (4 papers), Epigenetics and DNA Methylation (4 papers), MicroRNA in disease regulation (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Virus-based gene therapy research (2 papers), Cerebrospinal fluid and hydrocephalus (2 papers) and RNA Research and Splicing (2 papers). The work is most often cited by research in Genetics (68 citations), Cancer Research (50 citations), Structural Biology (3 citations), Oncology (43 citations) and Developmental Neuroscience (6 citations). Sachi Maeda has collaborated with scholars based in Japan, United States and Chile. Frequent co-authors include Atsushi Natsume, Junya Yamaguchi, Kazuya Motomura, Fumiharu Ohka, Kosuke Aoki, Akira Kato, Masaki Hirano, Toshihiko Wakabayashi, Akane Yamamichi and Yukinari Kato. Their work appears in journals such as Brain Tumor Pathology, Acta Neuropathologica Communications, Neuro-Oncology, Cancer Science and iScience.

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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