Liam Good

5.8k total citations
98 papers, 4.5k citations indexed

About

Liam Good is a scholar working on Molecular Biology, Ecology and Genetics. According to data from OpenAlex, Liam Good has authored 98 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Molecular Biology, 32 papers in Ecology and 24 papers in Genetics. Recurrent topics in Liam Good's work include RNA and protein synthesis mechanisms (36 papers), Bacteriophages and microbial interactions (32 papers) and Bacterial Genetics and Biotechnology (22 papers). Liam Good is often cited by papers focused on RNA and protein synthesis mechanisms (36 papers), Bacteriophages and microbial interactions (32 papers) and Bacterial Genetics and Biotechnology (22 papers). Liam Good collaborates with scholars based in United Kingdom, Sweden and Canada. Liam Good's co-authors include Peter E. Nielsen, James E. M. Stach, Rikard Dryselius, Satish Kumar Awasthi, Nor Fadhilah Kamaruzzaman, Natalia Nekhotiaeva, Shan Goh, Ola Larsson, Ross N. Nazar and Claes Wahlestedt and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Liam Good

98 papers receiving 4.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liam Good United Kingdom 38 3.1k 1.0k 679 542 532 98 4.5k
Paolo Landini Italy 35 2.6k 0.8× 698 0.7× 1.3k 1.9× 238 0.4× 447 0.8× 77 3.8k
Gee W. Lau United States 36 2.7k 0.9× 413 0.4× 649 1.0× 725 1.3× 975 1.8× 87 4.6k
Yufeng Yao China 33 2.7k 0.9× 401 0.4× 410 0.6× 793 1.5× 542 1.0× 107 4.5k
Sophie de Bentzmann France 34 2.0k 0.6× 280 0.3× 572 0.8× 349 0.6× 623 1.2× 69 3.5k
Jozef Anné Belgium 44 2.8k 0.9× 810 0.8× 1.3k 2.0× 193 0.4× 172 0.3× 185 5.6k
Mamoru Hyodo Japan 39 4.4k 1.4× 299 0.3× 1.1k 1.6× 456 0.8× 437 0.8× 88 7.8k
Hitoshi Komatsuzawa Japan 45 3.1k 1.0× 602 0.6× 878 1.3× 1.4k 2.6× 454 0.9× 165 5.9k
Stefan Schild Austria 30 1.7k 0.5× 590 0.6× 419 0.6× 1.1k 2.1× 586 1.1× 62 3.9k
Yun‐Jaie Choi South Korea 37 2.3k 0.7× 319 0.3× 616 0.9× 159 0.3× 194 0.4× 112 4.2k
Pedro Garcı́a Spain 38 2.0k 0.6× 1.8k 1.7× 644 0.9× 999 1.8× 275 0.5× 131 4.6k

Countries citing papers authored by Liam Good

Since Specialization
Citations

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

Fields of papers citing papers by Liam Good

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liam Good

This figure shows the co-authorship network connecting the top 25 collaborators of Liam Good. A scholar is included among the top collaborators of Liam Good 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 Liam Good. Liam Good 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.
Good, Liam, et al.. (2023). Fungal cell barriers and organelles are disrupted by polyhexamethylene biguanide (PHMB). Scientific Reports. 13(1). 2790–2790. 11 indexed citations
2.
Good, Liam, et al.. (2020). Doxycycline induces Hok toxin killing in host E. coli. PLoS ONE. 15(7). e0235633–e0235633. 2 indexed citations
3.
Tsui, Janice, et al.. (2019). Polyhexamethylene Biguanide:Polyurethane Blend Nanofibrous Membranes for Wound Infection Control. Polymers. 11(5). 915–915. 35 indexed citations
4.
Kamaruzzaman, Nor Fadhilah, Sharon L. Kendall, & Liam Good. (2016). Targeting the hard to reach: challenges and novel strategies in the treatment of intracellular bacterial infections. British Journal of Pharmacology. 174(14). 2225–2236. 150 indexed citations
5.
Josse, Andrea R., Valentina Gburcik, Hannah Crossland, et al.. (2016). Biomarkers of browning of white adipose tissue and their regulation during exercise- and diet-induced weight loss,. American Journal of Clinical Nutrition. 104(3). 557–565. 51 indexed citations
6.
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
7.
Goh, Shan, et al.. (2014). Species-Selective Killing of Bacteria by Antimicrobial Peptide-PNAs. PLoS ONE. 9(2). e89082–e89082. 67 indexed citations
8.
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
9.
Mbugi, Erasto V., Bugwesa Z. Katale, Sharon L. Kendall, et al.. (2012). Tuberculosis cross-species transmission in Tanzania: Towards a One-Health concept. Onderstepoort Journal of Veterinary Research. 79(2). 501–501. 17 indexed citations
10.
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
11.
Good, Liam & James E. M. Stach. (2011). Synthetic RNA Silencing in Bacteria ? Antimicrobial Discovery and Resistance Breaking. Frontiers in Microbiology. 2. 185–185. 36 indexed citations
12.
Stach, James E. M., et al.. (2010). Genetic Evidence for Inhibition of Bacterial Division Protein FtsZ by Berberine. PLoS ONE. 5(10). e13745–e13745. 156 indexed citations
13.
Nikravesh, Abbas, Majid Sadeghizadeh, Mehrdad Behmanesh, & Liam Good. (2009). CELLULAR MORPHOLOGY AND IMMUNOLOGIC PROPERTIES OF ESCHERICHIA COLI TREATED WITH ANTIMICROBIAL ANTISENSE PEPTIDE NUCLEIC ACID. Iranian journal of pathology. 4(1). 13–18. 1 indexed citations
14.
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
15.
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
16.
Nakashima, Nobutaka, Tomohiro Tamura, & Liam Good. (2006). Paired termini stabilize antisense RNAs and enhance conditional gene silencing in Escherichia coli. Nucleic Acids Research. 34(20). e138–e138. 95 indexed citations
17.
Rajarao, Gunaratna Kuttuva, Natalia Nekhotiaeva, & Liam Good. (2002). Peptide-mediated delivery of green fluorescent protein into yeasts and bacteria. FEMS Microbiology Letters. 215(2). 267–272. 29 indexed citations
18.
Good, Liam, et al.. (1999). Peptide Nucleic Acid (PNA) Antisense Effects inEscherichia coli. Current Issues in Molecular Biology. 2 indexed citations
19.
Good, Liam & Peter E. Nielsen. (1997). Progress in Developing PNA as a Gene-Targeted Drug. Antisense and Nucleic Acid Drug Development. 7(4). 431–437. 87 indexed citations
20.
Elela, Sherif Abou, et al.. (1994). Inhibition of protein synthesis by an efficiently expressed mutation in the yeast 5.8S ribosomal RNA. Nucleic Acids Research. 22(4). 686–693. 23 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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