Win Darmanto

53 papers receiving 512 citations

Peers

Win Darmanto
Comparison fields: 5 of 93
  • Drug Discovery 2
  • Pharmacology 60
  • Plant Science 194
  • Complementary and alternative medicine 32
  • Biochemistry 16
Replace Zahra Hashemi with:
Zahra Hashemi Iran
Parth Thakor India
Hanady S. Al‐Shmgani Iraq
Naghmeh Hadidi Iran
Mydhili Govindarasu India
Chul-Soon Yong South Korea
Ibrahim Abdel Aziz Ibrahim Saudi Arabia
Kaushik Kumar Bharadwaj India
Hany G. Attia Saudi Arabia
S. R. Patil India
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Citations per year

Countries citing papers authored by Win Darmanto

Since Specialization
Citations

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

Fields of papers citing papers by Win Darmanto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201967
2 202053
3 202035
4 202034
5 201928
6 202026
7 201926
8 201724
9 201923
10 201819
11 202117
12 200016
13 201916
14 202114
15 200013
16 202010
17
Anticancer activity of okra raw polysaccharides extracts against human liver cancer cells
20199
18 20229
19 20188
20 20208

About Win Darmanto

Win Darmanto is a scholar working on Plant Science, Molecular Biology, General Health Professions, Aquatic Science and Pediatrics, Perinatology and Child Health, having authored 64 papers that have together received 528 indexed citations. Recurring topics across this work include Medicinal Plant Research (11 papers), Agricultural Practices and Plant Genetics (7 papers), Diverse Scientific Research Studies (6 papers), Natural Antidiabetic Agents Studies (4 papers), Aquatic life and conservation (4 papers), Plant Virus Research Studies (3 papers), Effects and risks of endocrine disrupting chemicals (3 papers) and Carbon and Quantum Dots Applications (3 papers). The work is most often cited by research in Drug Discovery (2 citations), Pharmacology (60 citations), Plant Science (194 citations), Complementary and alternative medicine (32 citations) and Biochemistry (16 citations). Win Darmanto has collaborated with scholars based in Indonesia, Taiwan and Japan. Frequent co-authors include Ruey‐an Doong, Dwi Winarni, Suhailah Hayaza, Sri Puji Astuti Wahyuningsih, Raden Joko Kuncoroningrat Susilo, Saikhu Akhmad Husen, Hai Linh Tran, Nguyễn Thị Ngọc Ánh, Adita Ayu Permanasari and Hunsa Punnapayak. Their work appears in journals such as Agronomy, Nanomaterials, Electrochimica Acta, Advances in Pharmacological Sciences and Advances in Pharmacological and Pharmaceutical Sciences.

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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