Pak-Sin Chu

547 citations
17 papers · 473 · h-index 10

Impact in

Papers in

Pak-Sin Chu

17 papers receiving 449 citations

Peers

Pak-Sin Chu
Comparison fields: 5 of 66
  • Food Science 243
  • Animal Science and Zoology 114
  • Insect Science 104
  • Analytical Chemistry 80
  • Pharmacology 117
Replace Carolin S. Stachel with:
Carolin S. Stachel Germany
Tomasz Śniegocki Poland
M.I.N. Silveira Portugal
Stanisław Semeniuk Poland
Ivan Pecorelli Italy
G. Stoev Bulgaria
Ádám Tölgyesi United States
Maki Kanda Japan
Edward Malone Ireland
G. W. Stubbings United Kingdom
Pak-Sin Chu relative to Carolin S. Stachel Germany Carolin S. Stachel's profile →
Citations per field
00.5×1.5×2.0×
Carolin S. Stachel · 1×
Citations per year

Countries citing papers authored by Pak-Sin Chu

Since Specialization
Citations

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

Fields of papers citing papers by Pak-Sin Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pak-Sin Chu. 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 Pak-Sin Chu. The network helps show where Pak-Sin Chu may publish in the future.

Co-authors

The 16 scholars most cited alongside Pak-Sin Chu, 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 Pak-Sin Chu Line = papers co-authored together Pak-Sin Chu links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2008132
2 200757
3 200756
4 200550
5 200844
6 200239
7 200614
8 199313
9 199512
10 200012
11 20009
12 20168
13 20078
14 19987
15 20124
16 19914
17 20154

About Pak-Sin Chu

Pak-Sin Chu is a scholar working on Food Science, Pharmacology, Molecular Biology, Animal Science and Zoology and Endocrinology, Diabetes and Metabolism, having authored 17 papers that have together received 473 indexed citations. Recurring topics across this work include Pesticide Residue Analysis and Safety (7 papers), Antibiotics Pharmacokinetics and Efficacy (6 papers), Hormonal and reproductive studies (4 papers), Analytical Chemistry and Chromatography (3 papers), Coccidia and coccidiosis research (2 papers), Analytical Methods in Pharmaceuticals (2 papers), Bee Products Chemical Analysis (2 papers) and Plant Toxicity and Pharmacological Properties (2 papers). The work is most often cited by research in Food Science (243 citations), Animal Science and Zoology (114 citations), Insect Science (104 citations), Analytical Chemistry (80 citations) and Pharmacology (117 citations). Pak-Sin Chu has collaborated with scholars based in United States. Frequent co-authors include Jeffery S. Pettis, Anthony D. Williams, Mark F. Feldlaufer, Badar Shaikh, Steven M. Plakas, Ann Abraham, Kathleen R. El Said, Renate Reimschuessel, D.J. Donoghue and Thomas A. Brandt. Their work appears in journals such as Journal of Agricultural and Food Chemistry, Aquaculture, Journal of AOAC International, Journal of Chromatography B and Journal of Chromatography B Biomedical Sciences and Applications.

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.

Explore authors with similar magnitude of impact