Keng-See Chow

694 total citations
9 papers, 559 citations indexed

About

Keng-See Chow is a scholar working on Molecular Biology, Plant Science and Organic Chemistry. According to data from OpenAlex, Keng-See Chow has authored 9 papers receiving a total of 559 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Plant Science and 1 paper in Organic Chemistry. Recurrent topics in Keng-See Chow's work include Plant biochemistry and biosynthesis (3 papers), Porphyrin Metabolism and Disorders (1 paper) and Plant Gene Expression Analysis (1 paper). Keng-See Chow is often cited by papers focused on Plant biochemistry and biosynthesis (3 papers), Porphyrin Metabolism and Disorders (1 paper) and Plant Gene Expression Analysis (1 paper). Keng-See Chow collaborates with scholars based in Malaysia, Austria and United Kingdom. Keng-See Chow's co-authors include Kyung-Hwan Han, Jae‐Heung Ko, J. M. Roper, Alison G. Smith, Davinder Singh, Heimo Breiteneder, Birgit Wagner, Hoong Yeet Yeang, Jaemo Yang and Kyung‐Hwan Han and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Journal of Allergy and Clinical Immunology.

In The Last Decade

Keng-See Chow

9 papers receiving 537 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Keng-See Chow Malaysia	8	491	202	76	61	40	9	559
Rizhong Zeng China	13	322 0.7×	138 0.7×	45 0.6×	45 0.7×	37 0.9×	26	414
Longjun Dai China	11	269 0.5×	152 0.8×	40 0.5×	42 0.7×	20 0.5×	25	368
Boje Müller Germany	13	378 0.8×	243 1.2×	47 0.6×	23 0.4×	19 0.5×	27	552
Guijuan Kang China	9	248 0.5×	102 0.5×	40 0.5×	39 0.6×	23 0.6×	14	294
Jaemo Yang United States	9	491 1.0×	429 2.1×	43 0.6×	40 0.7×	16 0.4×	13	654
Nicole van Deenen Germany	13	627 1.3×	167 0.8×	127 1.7×	31 0.5×	44 1.1×	17	717
Zhiyi Nie China	9	239 0.5×	80 0.4×	44 0.6×	43 0.7×	27 0.7×	13	271
Cuifang Duan China	9	322 0.7×	192 1.0×	33 0.4×	37 0.6×	19 0.5×	12	384
Daniela Wahler Germany	6	323 0.7×	139 0.7×	84 1.1×	27 0.4×	14 0.3×	9	364
Rapepun Wititsuwannakul Thailand	17	633 1.3×	174 0.9×	54 0.7×	145 2.4×	66 1.6×	32	790

Countries citing papers authored by Keng-See Chow

Since Specialization

Citations

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

Fields of papers citing papers by Keng-See Chow

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keng-See Chow. 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 Keng-See Chow. The network helps show where Keng-See Chow may publish in the future.

Co-authorship network of co-authors of Keng-See Chow

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Matsui, Minami & Keng-See Chow. (2020). The Rubber Tree Genome. 9 indexed citations

2.

Isa, Mohd Noor Mat, Hoe‐Han Goh, Paul H. Dear, et al.. (2016). Perigone Lobe Transcriptome Analysis Provides Insights into Rafflesia cantleyi Flower Development. PLoS ONE. 11(12). e0167958–e0167958. 12 indexed citations

3.

Chow, Keng-See, et al.. (2014). RNA sequencing read depth requirement for optimal transcriptome coverage in Hevea brasiliensis. BMC Research Notes. 7(1). 28 indexed citations

4.

Chow, Keng-See, et al.. (2011). Metabolic routes affecting rubber biosynthesis in Hevea brasiliensis latex. Journal of Experimental Botany. 63(5). 1863–1871. 106 indexed citations

5.

Ko, Jae‐Heung, Keng-See Chow, & Kyung-Hwan Han. (2003). Transcriptome analysis reveals novel features of the molecular events occurring in the laticifers of Hevea brasiliensis (para rubber tree). Plant Molecular Biology. 53(4). 479–492. 131 indexed citations

6.

Sunderasan, E., et al.. (2002). Hev b 4 heavy peptide identified as latex cyanogenic glucosidase. Journal of Allergy and Clinical Immunology. 109(1). S333–S333. 1 indexed citations

7.

Bokma, Evert, et al.. (2001). Determination of cDNA and genomic DNA sequences of hevamine, a chitinase from the rubber tree Hevea brasiliensis. Plant Physiology and Biochemistry. 39(5). 367–376. 20 indexed citations

8.

Kang, Hunseung, Dong Ho Shin, Jaemo Yang, et al.. (1999). Isolation, Characterization, and Functional Analysis of a Novel cDNA Clone Encoding a Small Rubber Particle Protein from Hevea brasiliensis. Journal of Biological Chemistry. 274(24). 17132–17138. 169 indexed citations

9.

Chow, Keng-See, Davinder Singh, J. M. Roper, & Alison G. Smith. (1997). A Single Precursor Protein for Ferrochelatase-I fromArabidopsis Is Imported in Vitro into Both Chloroplasts and Mitochondria. Journal of Biological Chemistry. 272(44). 27565–27571. 83 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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