Pauline C. Ng
- Molecular Biology top 0.5%
- Genetics top 0.1%
- Cancer Research top 1%
- Oncology top 5%
- Immunology top 5%
- Co-authors
- Steven HenikoffP. Naresh KumarJing HuGeorg SchneiderSwarnaseetha AdusumalliRobert VaserMile ŠikićSamuel Lévy
- Topics
- RNA and protein synthesis mechanisms (9 papers)Genomics and Rare Diseases (8 papers)Genomics and Phylogenetic Studies (8 papers)
- Partner nations
- United StatesSingaporeEstonia
In The Last Decade
Pauline C. Ng
23 papers receiving 12.3k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Molecular Biology 7.3k
- Genetics 5.2k
- Cancer Research 1.4k
- Oncology 873
- Immunology 791
Countries citing papers authored by Pauline C. Ng
This map shows the geographic impact of Pauline C. Ng'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 Pauline C. Ng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pauline C. Ng more than expected).
Fields of papers citing papers by Pauline C. Ng
This network shows the impact of papers produced by Pauline C. Ng. 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 Pauline C. Ng. The network helps show where Pauline C. Ng may publish in the future.
Co-authorship network of co-authors of Pauline C. Ng
This figure shows the co-authorship network connecting the top 25 collaborators of Pauline C. Ng. A scholar is included among the top collaborators of Pauline C. Ng 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 Pauline C. Ng. Pauline C. Ng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 75 | |
| 2 | 8 | |
| 3 | 9 | |
| 4 | SIFT missense predictions for genomesbreakdown → | 873 |
| 5 | 109 | |
| 6 | 87 | |
| 7 | SIFT web server: predicting effects of amino acid substitutions on proteinsbreakdown → | 1608 |
| 8 | 200 | |
| 9 | 437 | |
| 10 | Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithmbreakdown → | 4718 |
| 11 | 222 | |
| 12 | 10 | |
| 13 | 190 | |
| 14 | 74 | |
| 15 | 83 | |
| 16 | Predicting the Effects of Amino Acid Substitutions on Protein Functionbreakdown → | 727 |
| 17 | Accounting for Human Polymorphisms Predicted to Affect Protein Functionbreakdown → | 547 |
| 18 | Predicting Deleterious Amino Acid Substitutionsbreakdown → | 1943 |
| 19 | 108 | |
| 20 | 12 |
About Pauline C. Ng
Pauline C. Ng is a scholar working on Horticulture, Genetics and Molecular Biology, having authored 23 papers that have together received 12.5k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (9 papers), Genomics and Rare Diseases (8 papers) and Genomics and Phylogenetic Studies (8 papers). The work is most often cited by research in Genetics (5.2k citations), Molecular Biology (7.3k citations) and Cancer Research (1.4k citations). Pauline C. Ng has collaborated with scholars based in United States, Singapore and Estonia. Frequent co-authors include Steven Henikoff, P. Naresh Kumar, Jing Hu, Georg Schneider, Swarnaseetha Adusumalli, Robert Vaser, Mile Šikić, Samuel Lévy, Sarah S. Murray and Ewen F. Kirkness. Their work appears in journals such as Nature, Nucleic Acids Research and Bioinformatics.
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.