Wanida Sukketsiri

69 total papers · 806 total citations
57 papers, 569 citations indexed

About

Wanida Sukketsiri is a scholar working on Molecular Biology, Complementary and alternative medicine and Rehabilitation. According to data from OpenAlex, Wanida Sukketsiri has authored 57 papers receiving a total of 569 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 9 papers in Complementary and alternative medicine and 8 papers in Rehabilitation. Recurrent topics in Wanida Sukketsiri's work include Protein Hydrolysis and Bioactive Peptides (7 papers), Wound Healing and Treatments (7 papers) and Medicinal Plants and Neuroprotection (6 papers). Wanida Sukketsiri is often cited by papers focused on Protein Hydrolysis and Bioactive Peptides (7 papers), Wound Healing and Treatments (7 papers) and Medicinal Plants and Neuroprotection (6 papers). Wanida Sukketsiri collaborates with scholars based in Thailand, Japan and Canada. Wanida Sukketsiri's co-authors include Supita Tanasawet, Pilaiwanwadee Hutamekalin, Pennapa Chonpathompikunlert, Lalita Chotphruethipong, Soottawat Benjakul, Varomyalin Tipmanee, Rotimi E. Aluko, Mayuree H. Tantisira, Wanwimol Klaypradit and Morakot Sroyraya and has published in prestigious journals such as RSC Advances, Journal of the Science of Food and Agriculture and LWT.

In The Last Decade

Wanida Sukketsiri

51 papers receiving 555 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Wanida Sukketsiri	205	78	77	68	61	57	569
Vadivelan Ramachandran	198 1.0×	69 0.9×	91 1.2×	57 0.8×	114 1.9×	55	663
Ekta Yadav	137 0.7×	56 0.7×	67 0.9×	32 0.5×	90 1.5×	48	598
G Blazsó	253 1.2×	87 1.1×	45 0.6×	58 0.9×	122 2.0×	41	619
Mohammad Amjad Hossain	282 1.4×	54 0.7×	63 0.8×	68 1.0×	77 1.3×	38	593
Rana Arslan	118 0.6×	90 1.2×	75 1.0×	61 0.9×	178 2.9×	40	541
Mahdieh Eftekhari	170 0.8×	95 1.2×	66 0.9×	34 0.5×	171 2.8×	50	562
Darízy Flávia Silva	146 0.7×	69 0.9×	40 0.5×	40 0.6×	63 1.0×	37	497
Çiğdem Yücel	181 0.9×	80 1.0×	60 0.8×	88 1.3×	119 2.0×	39	623
Sina Andalib	181 0.9×	51 0.7×	49 0.6×	39 0.6×	50 0.8×	47	653
Flávia Nathiely Silveira Fachel	146 0.7×	82 1.1×	41 0.5×	65 1.0×	55 0.9×	36	525

Countries citing papers authored by Wanida Sukketsiri

Since Specialization

Citations

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

Fields of papers citing papers by Wanida Sukketsiri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wanida Sukketsiri

This figure shows the co-authorship network connecting the top 25 collaborators of Wanida Sukketsiri. A scholar is included among the top collaborators of Wanida Sukketsiri 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 Wanida Sukketsiri. Wanida Sukketsiri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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