Yas Hashimura

636 citations
16 papers · 455 · h-index 10

Impact in

Papers in

    • Pluripotent Stem Cells Research 9
    • Viral Infectious Diseases and Gene Expression in Insects 6
    • CRISPR and Genetic Engineering 4
    • 3D Printing in Biomedical Research 8
    • Innovative Microfluidic and Catalytic Techniques Innovation 2
    • Fluid Dynamics and Mixing 2

Yas Hashimura

16 papers receiving 432 citations

Peers

Yas Hashimura
Comparison fields: 5 of 55
  • Genetics 73
  • Developmental Neuroscience 26
  • Molecular Biology 352
  • Biomedical Engineering 214
  • Cancer Research 37
Replace Yao Fu with:
Yao Fu China
Marta M. Silva Portugal
Zhiying He China
Brent M. Bijonowski United States
Kai Cui China
Abhirath Parikh United States
Victoria L. Mascetti United Kingdom
Jianjie Jiang United States
Lívia Eiselleová Czechia
Yas Hashimura relative to Yao Fu China Yao Fu's profile →
Citations per field
00.5×1.6×
Yao Fu · 1×
Citations per year

Countries citing papers authored by Yas Hashimura

Since Specialization
Citations

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

Fields of papers citing papers by Yas Hashimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yas Hashimura, 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 Yas Hashimura Line = papers co-authored together Yas Hashimura links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201569
2 202163
3 201954
4 201948
5 202046
6 202035
7 202235
8 201835
9 202129
10 202010
11 20139
12 20228
13 20206
14 20204
15 20222
16 20152

About Yas Hashimura

Yas Hashimura is a scholar working on Molecular Biology, Biomedical Engineering, Genetics, Developmental Neuroscience and Surgery, having authored 16 papers that have together received 455 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (9 papers), 3D Printing in Biomedical Research (8 papers), Viral Infectious Diseases and Gene Expression in Insects (6 papers), CRISPR and Genetic Engineering (4 papers), Tissue Engineering and Regenerative Medicine (3 papers), Innovative Microfluidic and Catalytic Techniques Innovation (2 papers), Fluid Dynamics and Mixing (2 papers) and Mesenchymal stem cell research (2 papers). The work is most often cited by research in Genetics (73 citations), Developmental Neuroscience (26 citations), Molecular Biology (352 citations), Biomedical Engineering (214 citations) and Cancer Research (37 citations). Yas Hashimura has collaborated with scholars based in Portugal, Canada and United States. Frequent co-authors include Sunghoon Jung, Joaquim M. S. Cabral, Carlos A. V. Rodrigues, Brian Lee, Teresa Pereira Silva, Michael Scott Kallos, Tiffany Dang, Breanna S. Borys, Robin L. Wesselschmidt and Tiago G. Fernandes. Their work appears in journals such as Journal of Visualized Experiments, Biotechnology Journal, Stem Cell Research & Therapy, Cytotherapy and The Canadian Journal of Chemical Engineering.

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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