Su Datt Lam

2.1k total citations · 1 hit paper
42 papers, 1.1k citations indexed

About

Su Datt Lam is a scholar working on Molecular Biology, Infectious Diseases and Plant Science. According to data from OpenAlex, Su Datt Lam has authored 42 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 7 papers in Infectious Diseases and 6 papers in Plant Science. Recurrent topics in Su Datt Lam's work include Genomics and Phylogenetic Studies (7 papers), RNA and protein synthesis mechanisms (6 papers) and Protein Structure and Dynamics (5 papers). Su Datt Lam is often cited by papers focused on Genomics and Phylogenetic Studies (7 papers), RNA and protein synthesis mechanisms (6 papers) and Protein Structure and Dynamics (5 papers). Su Datt Lam collaborates with scholars based in Malaysia, United Kingdom and India. Su Datt Lam's co-authors include Christine Orengo, Ian Sillitoe, Jonathan Lees, Natalie L. Dawson, Neeladri Sen, Paul Ashford, Vaishali Waman, Nicola Bordin, Clemens Rauer and David Lee and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and PLoS ONE.

In The Last Decade

Su Datt Lam

37 papers receiving 1.1k citations

Hit Papers

CATH: increased structural coverage of functional space 2020 2026 2022 2024 2020 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Su Datt Lam Malaysia 17 618 192 159 137 75 42 1.1k
Ragothaman M. Yennamalli India 16 578 0.9× 135 0.7× 114 0.7× 67 0.5× 26 0.3× 63 1.1k
Jasmine Kaur India 17 466 0.8× 145 0.8× 71 0.4× 61 0.4× 63 0.8× 84 1.2k
Magdalena Zalacaín United States 23 905 1.5× 181 0.9× 103 0.6× 65 0.5× 48 0.6× 40 1.4k
Xia Wu China 24 1.0k 1.6× 216 1.1× 369 2.3× 62 0.5× 65 0.9× 97 1.7k
Ed T. Buurman United States 23 1.1k 1.7× 532 2.8× 235 1.5× 84 0.6× 42 0.6× 46 1.8k
Sergio Lociuro Switzerland 18 547 0.9× 225 1.2× 51 0.3× 52 0.4× 96 1.3× 37 1.3k
L. Moynié United Kingdom 15 516 0.8× 92 0.5× 94 0.6× 99 0.7× 74 1.0× 25 1.0k
Dana Braff United States 6 1.4k 2.3× 298 1.6× 73 0.5× 66 0.5× 81 1.1× 7 2.0k
Nelson C. Soares United Arab Emirates 22 1.2k 1.9× 293 1.5× 191 1.2× 56 0.4× 261 3.5× 100 2.1k
Maarten Vercruysse United States 8 500 0.8× 100 0.5× 85 0.5× 56 0.4× 96 1.3× 12 957

Countries citing papers authored by Su Datt Lam

Since Specialization
Citations

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

Fields of papers citing papers by Su Datt Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Su Datt Lam. 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 Datt Lam. The network helps show where Su Datt Lam may publish in the future.

Co-authorship network of co-authors of Su Datt Lam

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

All Works

20 of 20 papers shown
1.
Salim, Emil, et al.. (2025). Bioactive glycosides: insights into antimalarial advances. Chemistry Letters. 54(2). 2 indexed citations
2.
Sen, Neeladri, et al.. (2025). Review of protein structure-based analyses that illuminate plant stress mechanisms. Computational and Structural Biotechnology Journal. 27. 3155–3166.
3.
Waman, Vaishali, Paul Ashford, Su Datt Lam, et al.. (2024). Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics. Scientific Reports. 14(1). 14208–14208. 1 indexed citations
4.
Khoo, Shing Ching, et al.. (2024). Potential of Synbiotics and Probiotics as Chemopreventive Agent. Probiotics and Antimicrobial Proteins. 16(6). 2085–2101. 5 indexed citations
5.
6.
Bordin, Nicola, Ian Sillitoe, Clemens Rauer, et al.. (2023). AlphaFold2 reveals commonalities and novelties in protein structure space for 21 model organisms. Communications Biology. 6(1). 160–160. 44 indexed citations
8.
Tan, Cedric, Su Datt Lam, Damien Richard, et al.. (2022). Transmission of SARS-CoV-2 from humans to animals and potential host adaptation. Nature Communications. 13(1). 2988–2988. 75 indexed citations
9.
Harun, Sarahani, et al.. (2022). Identification of Potential Genes Encoding Protein Transporters in Arabidopsis thaliana Glucosinolate (GSL) Metabolism. Life. 12(3). 326–326. 3 indexed citations
10.
Lam, Su Datt, Vaishali Waman, Franca Fraternali, Christine Orengo, & Jonathan Lees. (2022). Structural and energetic analyses of SARS-CoV-2 N-terminal domain characterise sugar binding pockets and suggest putative impacts of variants on COVID-19 transmission. Computational and Structural Biotechnology Journal. 20. 6302–6316. 2 indexed citations
11.
Akbar, Rahmad, et al.. (2022). Machine learning and molecular simulation ascertain antimicrobial peptide against Klebsiella pneumoniae from public database. Computational Biology and Chemistry. 102. 107800–107800. 15 indexed citations
12.
Lam, Su Datt, M. Madan Babu, Jonathan Lees, & Christine Orengo. (2021). Biological impact of mutually exclusive exon switching. PLoS Computational Biology. 17(3). e1008708–e1008708. 16 indexed citations
13.
Ling, Nyuk, Su Datt Lam, Aziz Ahmad, et al.. (2021). Integration of environmental metabolomics and physiological approach for evaluation of saline pollution to rice plant. Environmental Pollution. 286. 117214–117214. 12 indexed citations
14.
Lam, Su Datt, Yafeng Yang, Wilson Thau Lym Yong, et al.. (2021). Omics technologies used in pesticide residue detection and mitigation in crop. Journal of Hazardous Materials. 420. 126624–126624. 34 indexed citations
15.
Lam, Su Datt, Nicola Bordin, Vaishali Waman, et al.. (2020). SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals. Scientific Reports. 10(1). 16471–16471. 80 indexed citations
16.
Ling, Nyuk, et al.. (2018). Susceptibility and tolerance of rice crop to salt threat: Physiological and metabolic inspections. PLoS ONE. 13(2). e0192732–e0192732. 72 indexed citations
17.
Lewis, Tony E., Ian Sillitoe, Natalie L. Dawson, et al.. (2017). Gene3D: Extensive prediction of globular domains in proteins. Nucleic Acids Research. 46(D1). D435–D439. 124 indexed citations
18.
Lam, Su Datt, Natalie L. Dawson, Sayoni Das, et al.. (2015). Gene3D: expanding the utility of domain assignments. Nucleic Acids Research. 44(D1). D404–D409. 45 indexed citations
19.
Lam, Su Datt, Jean LeRiche, A. J. Coldman, et al.. (1999). Sex-Related Differences in Bronchial Epithelial Changes Associated With Tobacco Smoking. JNCI Journal of the National Cancer Institute. 91(8). 691–696. 70 indexed citations
20.
Goh, K. T., et al.. (1990). Person-to-person transmission of cholera in a psychiatric hospital. Journal of Infection. 20(3). 193–200. 42 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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