Su-Pin Koo

616 total citations
8 papers, 505 citations indexed

About

Su-Pin Koo is a scholar working on Molecular Biology, Microbiology and Genetics. According to data from OpenAlex, Su-Pin Koo has authored 8 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Microbiology and 3 papers in Genetics. Recurrent topics in Su-Pin Koo's work include Antimicrobial Peptides and Activities (6 papers), Biochemical and Structural Characterization (5 papers) and Venomous Animal Envenomation and Studies (3 papers). Su-Pin Koo is often cited by papers focused on Antimicrobial Peptides and Activities (6 papers), Biochemical and Structural Characterization (5 papers) and Venomous Animal Envenomation and Studies (3 papers). Su-Pin Koo collaborates with scholars based in United States, Australia and India. Su-Pin Koo's co-authors include Michael R. Yeaman, Arnold S. Bayer, Paul M. Sullam, Hans‐Georg Sahl, Richard A. Proctor, Jyotsna Chandra, Archana Varma, Neville Firth, Melissa H. Brown and Rajendra Prasad and has published in prestigious journals such as Journal of Clinical Investigation, Infection and Immunity and Journal of Food Engineering.

In The Last Decade

Su-Pin Koo

8 papers receiving 496 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Su-Pin Koo United States	8	256	237	158	93	68	8	505
Kristi L. Strandberg United States	14	118 0.5×	179 0.8×	212 1.3×	60 0.6×	135 2.0×	16	632
Mingsong Kang Canada	10	142 0.6×	344 1.5×	173 1.1×	64 0.7×	98 1.4×	25	587
Alberto Licci Italy	15	411 1.6×	349 1.5×	96 0.6×	29 0.3×	146 2.1×	20	608
Carolyn R. Schaeffer United States	9	140 0.5×	526 2.2×	404 2.6×	42 0.5×	36 0.5×	12	689
Martin Schlag Germany	10	218 0.9×	572 2.4×	360 2.3×	60 0.6×	56 0.8×	10	860
Huagang Peng China	14	125 0.5×	352 1.5×	275 1.7×	40 0.4×	47 0.7×	31	613
Julia Garbe Sweden	7	108 0.4×	315 1.3×	72 0.5×	104 1.1×	42 0.6×	8	552
Joseph J. Dajcs United States	15	62 0.2×	216 0.9×	183 1.2×	117 1.3×	40 0.6×	24	622
Brian M. Gray United States	8	91 0.4×	350 1.5×	214 1.4×	23 0.2×	90 1.3×	15	608
Giuseppina D’Amato Italy	17	428 1.7×	339 1.4×	107 0.7×	23 0.2×	173 2.5×	21	635

Countries citing papers authored by Su-Pin Koo

Since Specialization

Citations

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

Fields of papers citing papers by Su-Pin Koo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Su-Pin Koo. 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 Su-Pin Koo. The network helps show where Su-Pin Koo may publish in the future.

Co-authorship network of co-authors of Su-Pin Koo

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

All Works

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8 of 8 papers shown

Koo, Su-Pin, Arnold S. Bayer, & Michael R. Yeaman. (2001). Diversity in Antistaphylococcal Mechanisms among Membrane-Targeting Antimicrobial Peptides. Infection and Immunity. 69(8). 4916–4922. 43 indexed citations

Bayer, Arnold S., Rajendra Prasad, Jyotsna Chandra, et al.. (2000). In Vitro Resistance of Staphylococcus aureus to Thrombin-Induced Platelet Microbicidal Protein Is Associated with Alterations in Cytoplasmic Membrane Fluidity. Infection and Immunity. 68(6). 3548–3553. 127 indexed citations

Koo, Su-Pin, Arnold S. Bayer, Bruce L. Kagan, & Michael R. Yeaman. (1999). Membrane Permeabilization by Thrombin-Induced Platelet Microbicidal Protein 1 Is Modulated by Transmembrane Voltage Polarity and Magnitude. Infection and Immunity. 67(5). 2475–2481. 20 indexed citations

Yeaman, Michael R., et al.. (1998). Platelet microbicidal proteins and neutrophil defensin disrupt the Staphylococcus aureus cytoplasmic membrane by distinct mechanisms of action.. Journal of Clinical Investigation. 101(1). 178–187. 159 indexed citations

Koo, Su-Pin, Michael R. Yeaman, Cynthia C. Nast, & Arnold S. Bayer. (1997). The cytoplasmic membrane is a primary target for the staphylocidal action of thrombin-induced platelet microbicidal protein. Infection and Immunity. 65(11). 4795–4800. 35 indexed citations

Koo, Su-Pin, Arnold S. Bayer, Hans‐Georg Sahl, Richard A. Proctor, & Michael R. Yeaman. (1996). Staphylocidal action of thrombin-induced platelet microbicidal protein is not solely dependent on transmembrane potential. Infection and Immunity. 64(3). 1070–1074. 63 indexed citations

Koo, Su-Pin, Michael R. Yeaman, & Arnold S. Bayer. (1996). Staphylocidal action of thrombin-induced platelet microbicidal protein is influenced by microenvironment and target cell growth phase. Infection and Immunity. 64(9). 3758–3764. 34 indexed citations

Booth, Ian R., et al.. (1994). Mechanisms controlling compatible solute accumulation: A consideration of the genetics and physiology of bacterial osmoregulation. Journal of Food Engineering. 22(1-4). 381–397. 24 indexed citations

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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