Shan Goh

1.5k total citations
38 papers, 1.2k citations indexed

About

Shan Goh is a scholar working on Ecology, Infectious Diseases and Molecular Biology. According to data from OpenAlex, Shan Goh has authored 38 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Ecology, 14 papers in Infectious Diseases and 14 papers in Molecular Biology. Recurrent topics in Shan Goh's work include Bacteriophages and microbial interactions (15 papers), Clostridium difficile and Clostridium perfringens research (10 papers) and Bacterial Genetics and Biotechnology (9 papers). Shan Goh is often cited by papers focused on Bacteriophages and microbial interactions (15 papers), Clostridium difficile and Clostridium perfringens research (10 papers) and Bacterial Genetics and Biotechnology (9 papers). Shan Goh collaborates with scholars based in United Kingdom, Sweden and Australia. Shan Goh's co-authors include Liam Good, Barbara J. Chang, Thomas V. Riley, Lynne V. McFarland, Tobias Allander, James E. M. Stach, Cecilia Lindau, Annika Tiveljung‐Lindell, Metehan Özen and Ener Çağrı Dinleyici and has published in prestigious journals such as Nature, PLoS ONE and Applied and Environmental Microbiology.

In The Last Decade

Shan Goh

37 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shan Goh United Kingdom 20 460 428 396 177 156 38 1.2k
Caroline Corless United Kingdom 11 241 0.5× 246 0.6× 95 0.2× 52 0.3× 44 0.3× 19 1.2k
Mohamad S. Hakim Indonesia 15 186 0.4× 332 0.8× 49 0.1× 51 0.3× 52 0.3× 47 894
Christoph Jans Switzerland 18 434 0.9× 145 0.3× 54 0.1× 21 0.1× 42 0.3× 43 1.0k
Gemma L. Kay United Kingdom 16 456 1.0× 281 0.7× 144 0.4× 34 0.2× 97 0.6× 34 1.2k
Elena N. Ilina Russia 23 613 1.3× 531 1.2× 287 0.7× 23 0.1× 111 0.7× 141 1.8k
Ching‐Hao Teng Taiwan 20 349 0.8× 107 0.3× 93 0.2× 27 0.2× 165 1.1× 50 1.0k
Mimi Healy United States 11 192 0.4× 768 1.8× 98 0.2× 53 0.3× 12 0.1× 19 1.3k
Zeaur Rahim Bangladesh 23 311 0.7× 1.0k 2.4× 96 0.2× 30 0.2× 32 0.2× 63 1.7k
Christoph Schoen Germany 26 845 1.8× 292 0.7× 203 0.5× 125 0.7× 322 2.1× 63 1.9k
Cheon‐Kwon Yoo South Korea 20 350 0.8× 585 1.4× 142 0.4× 45 0.3× 107 0.7× 55 1.2k

Countries citing papers authored by Shan Goh

Since Specialization
Citations

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

Fields of papers citing papers by Shan Goh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shan Goh. 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 Shan Goh. The network helps show where Shan Goh may publish in the future.

Co-authorship network of co-authors of Shan Goh

This figure shows the co-authorship network connecting the top 25 collaborators of Shan Goh. A scholar is included among the top collaborators of Shan Goh 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 Shan Goh. Shan Goh 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.
2.
Goh, Shan & Jameel M. Inal. (2024). Membrane Vesicles of Clostridioides difficile and Other Clostridial Species. Advances in experimental medicine and biology. 1435. 315–327.
3.
Goh, Shan, Chiew Foan Chin, Christophe Wiart, et al.. (2024). Antibacterial potency of mid-polar extracts obtained from Malaysian plant Parkia speciosa against human pathogenic bacteria. Microbial Pathogenesis. 198. 107134–107134. 1 indexed citations
4.
Schuller, M., Rachel E. Butler, A. Ariza, et al.. (2021). Molecular basis for DarT ADP-ribosylation of a DNA base. Nature. 596(7873). 597–602. 50 indexed citations
5.
Goh, Shan, et al.. (2018). The Novel Phages phiCD5763 and phiCD2955 Represent Two Groups of Big Plasmidial Siphoviridae Phages of Clostridium difficile. Frontiers in Microbiology. 9. 26–26. 20 indexed citations
6.
McFarland, Lynne V. & Shan Goh. (2018). Are probiotics and prebiotics effective in the prevention of travellers’ diarrhea: A systematic review and meta-analysis. Travel Medicine and Infectious Disease. 27. 11–19. 50 indexed citations
7.
McFarland, Lynne V., Metehan Özen, Ener Çağrı Dinleyici, & Shan Goh. (2016). Comparison of pediatric and adult antibiotic-associated diarrhea andClostridium difficileinfections. World Journal of Gastroenterology. 22(11). 3078–3078. 107 indexed citations
8.
Goh, Shan, Anette Loeffler, D. H. Lloyd, Sean P. Nair, & Liam Good. (2015). Oxacillin sensitization of methicillin-resistant Staphylococcus aureus and methicillin-resistant Staphylococcus pseudintermedius by antisense peptide nucleic acids in vitro. BMC Microbiology. 15(1). 262–262. 38 indexed citations
9.
Goh, Shan, et al.. (2014). Species-Selective Killing of Bacteria by Antimicrobial Peptide-PNAs. PLoS ONE. 9(2). e89082–e89082. 67 indexed citations
10.
Goh, Shan, James E. M. Stach, & Liam Good. (2013). Antisense Effects of PNAs in Bacteria. Methods in molecular biology. 1050. 223–236. 12 indexed citations
11.
Liverani, Marco, Jeff Waage, Tony Barnett, et al.. (2013). Understanding and Managing Zoonotic Risk in the New Livestock Industries. Environmental Health Perspectives. 121(8). 873–877. 52 indexed citations
12.
Mitchell, John, Shan Goh, Quintin McKellar, & Declan J. McKeever. (2013). In vitro pharmacodynamics of gamithromycin against Mycoplasma mycoides subspecies mycoides Small Colony. The Veterinary Journal. 197(3). 806–811. 13 indexed citations
13.
Gustafsson, Britt, Shan Goh, G Giraud, et al.. (2012). KI, WU, and Merkel Cell Polyomavirus DNA was not Detected in Guthrie Cards of Children who Later Developed Acute Lymphoblastic Leukemia. Journal of Pediatric Hematology/Oncology. 34(5). 364–367. 15 indexed citations
14.
Nakashima, Nobutaka, Shan Goh, Liam Good, & Tomohiro Tamura. (2011). Multiple-Gene Silencing Using Antisense RNAs in Escherichia coli. Methods in molecular biology. 815. 307–319. 16 indexed citations
15.
Goh, Shan, Cecilia Lindau, Annika Tiveljung‐Lindell, & Tobias Allander. (2009). Merkel Cell Polyomavirus in Respiratory Tract Secretions. Emerging infectious diseases. 15(3). 489–491. 107 indexed citations
16.
Goh, Shan, et al.. (2009). Concurrent Growth Rate and Transcript Analyses Reveal Essential Gene Stringency in Escherichia coli. PLoS ONE. 4(6). e6061–e6061. 66 indexed citations
17.
Lindau, Cecilia, Annika Tiveljung‐Lindell, Shan Goh, Torbjörn Ramqvist, & Tobias Allander. (2008). A single-tube, real-time PCR assay for detection of the two newly characterized human KI and WU polyomaviruses. Journal of Clinical Virology. 44(1). 24–26. 24 indexed citations
18.
Goh, Shan & Liam Good. (2008). Plasmid selection in Escherichia coli using an endogenous essential gene marker. BMC Biotechnology. 8(1). 61–61. 50 indexed citations
19.
Nikravesh, Abbas, Rikard Dryselius, Omid R. Faridani, et al.. (2007). Antisense PNA Accumulates in Escherichia coli and Mediates a Long Post-antibiotic Effect. Molecular Therapy. 15(8). 1537–1542. 52 indexed citations
20.
Dryselius, Rikard, Abbas Nikravesh, Agné Kulyté, Shan Goh, & Liam Good. (2006). Variable coordination of cotranscribed genes in Escherichia coli following antisense repression.. BMC Microbiology. 6(1). 97–97. 20 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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