Wah-Seng See-Too

31 total papers · 419 total citations
23 papers, 306 citations indexed

About

Wah-Seng See-Too is a scholar working on Molecular Biology, Plant Science and Ecology. According to data from OpenAlex, Wah-Seng See-Too has authored 23 papers receiving a total of 306 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 9 papers in Plant Science and 8 papers in Ecology. Recurrent topics in Wah-Seng See-Too's work include Genomics and Phylogenetic Studies (14 papers), Microbial Community Ecology and Physiology (7 papers) and Plant-Microbe Interactions and Immunity (4 papers). Wah-Seng See-Too is often cited by papers focused on Genomics and Phylogenetic Studies (14 papers), Microbial Community Ecology and Physiology (7 papers) and Plant-Microbe Interactions and Immunity (4 papers). Wah-Seng See-Too collaborates with scholars based in Malaysia, United Kingdom and Singapore. Wah-Seng See-Too's co-authors include Kok‐Gan Chan, Wai‐Fong Yin, Peter Convey, Robson Ee, David A. Pearce, Munusamy Madhaiyan, Venkatakrishnan Sivaraj Saravanan, Hoi-Sen Yong, Sze‐Looi Song and Kek Heng Chua and has published in prestigious journals such as Scientific Reports, Frontiers in Microbiology and INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY.

In The Last Decade

Wah-Seng See-Too

23 papers receiving 305 citations

Author Peers

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

Author Last Decade Papers Cites
Wah-Seng See-Too 196 71 70 40 37 23 306
Leonardo Broetto 222 1.1× 25 0.4× 96 1.4× 25 0.6× 41 1.1× 17 344
Paula de Souza Santos 137 0.7× 41 0.6× 44 0.6× 33 0.8× 17 0.5× 26 341
Mariana Reyes‐Prieto 152 0.8× 52 0.7× 72 1.0× 26 0.7× 15 0.4× 20 304
Wentao Zheng 224 1.1× 69 1.0× 57 0.8× 70 1.8× 40 1.1× 18 305
Shailly Anand 168 0.9× 69 1.0× 44 0.6× 14 0.3× 28 0.8× 18 287
Assem Abolmaaty 154 0.8× 38 0.5× 65 0.9× 10 0.3× 70 1.9× 26 313
R. R. Azizbekyan 206 1.1× 92 1.3× 48 0.7× 24 0.6× 27 0.7× 26 302
Elena K. Perry 145 0.7× 35 0.5× 38 0.5× 15 0.4× 14 0.4× 11 277
Fernando A. Pagliai 146 0.7× 42 0.6× 166 2.4× 44 1.1× 11 0.3× 22 353
Arwa Al-Dilaimi 182 0.9× 45 0.6× 43 0.6× 12 0.3× 36 1.0× 17 362

Countries citing papers authored by Wah-Seng See-Too

Since Specialization
Citations

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

Fields of papers citing papers by Wah-Seng See-Too

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wah-Seng See-Too

This figure shows the co-authorship network connecting the top 25 collaborators of Wah-Seng See-Too. A scholar is included among the top collaborators of Wah-Seng See-Too 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 Wah-Seng See-Too. Wah-Seng See-Too 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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