Chia‐Ling Gau

1.4k total citations
16 papers, 942 citations indexed

About

Chia‐Ling Gau is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Chia‐Ling Gau has authored 16 papers receiving a total of 942 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 6 papers in Genetics and 5 papers in Oncology. Recurrent topics in Chia‐Ling Gau's work include Genomic variations and chromosomal abnormalities (4 papers), Cancer-related Molecular Pathways (4 papers) and Genomics and Rare Diseases (3 papers). Chia‐Ling Gau is often cited by papers focused on Genomic variations and chromosomal abnormalities (4 papers), Cancer-related Molecular Pathways (4 papers) and Genomics and Rare Diseases (3 papers). Chia‐Ling Gau collaborates with scholars based in United States, Saudi Arabia and Finland. Chia‐Ling Gau's co-authors include Fuyuhiko Tamanoi, Lea Guo, Holly LaDuca, Shuwei Li, Hironori Edamatsu, Tina Pesaran, Erik J. Uhlmann, David H. Gutmann, Elizabeth Chao and Virginia Speare and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Chia‐Ling Gau

16 papers receiving 929 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chia‐Ling Gau United States 13 532 342 217 205 184 16 942
Susanne Seitz Germany 19 717 1.3× 221 0.6× 131 0.6× 266 1.3× 213 1.2× 32 1.1k
S.A. Whitmore Australia 18 536 1.0× 255 0.7× 418 1.9× 73 0.4× 167 0.9× 26 1.3k
Jamel Chelly France 11 905 1.7× 162 0.5× 108 0.5× 154 0.8× 241 1.3× 14 1.2k
Christy J. Fryer United States 13 1.4k 2.7× 323 0.9× 127 0.6× 155 0.8× 211 1.1× 15 1.7k
Sei‐Ichi Matsui United States 17 733 1.4× 258 0.8× 63 0.3× 172 0.8× 147 0.8× 24 1.0k
Jean Kloss United States 14 645 1.2× 149 0.4× 64 0.3× 220 1.1× 178 1.0× 21 1.1k
Leonarda Ianzano Italy 21 696 1.3× 702 2.1× 69 0.3× 116 0.6× 120 0.7× 26 1.4k
Srikanth Jammulapati United States 6 598 1.1× 331 1.0× 82 0.4× 251 1.2× 445 2.4× 8 1.1k
Brenda K. Shell United States 10 1.0k 1.9× 159 0.5× 144 0.7× 265 1.3× 212 1.2× 10 1.2k
Esther Appeldoorn Netherlands 12 1.6k 3.0× 275 0.8× 84 0.4× 349 1.7× 201 1.1× 12 1.7k

Countries citing papers authored by Chia‐Ling Gau

Since Specialization
Citations

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

Fields of papers citing papers by Chia‐Ling Gau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chia‐Ling Gau. 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 Chia‐Ling Gau. The network helps show where Chia‐Ling Gau may publish in the future.

Co-authorship network of co-authors of Chia‐Ling Gau

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

All Works

16 of 16 papers shown
1.
Rana, Huma Q., Lily Hoang, Holly LaDuca, et al.. (2019). Genotype–phenotype associations among panel-based TP53+ subjects. Genetics in Medicine. 21(11). 2478–2484. 18 indexed citations
2.
Tian, Yuan, Tina Pesaran, Adam Chamberlin, et al.. (2019). REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification. Scientific Reports. 9(1). 12752–12752. 58 indexed citations
3.
Qian, Dajun, Shuwei Li, Yuan Tian, et al.. (2018). A Bayesian framework for efficient and accurate variant prediction. PLoS ONE. 13(9). e0203553–e0203553. 10 indexed citations
4.
Espenschied, Carin R., Holly LaDuca, Shuwei Li, et al.. (2017). Multigene Panel Testing Provides a New Perspective on Lynch Syndrome. Journal of Clinical Oncology. 35(22). 2568–2575. 104 indexed citations
5.
Millson, Alison, Tracey Lewis, Tina Pesaran, et al.. (2015). Processed Pseudogene Confounding Deletion/Duplication Assays for SMAD4. Journal of Molecular Diagnostics. 17(5). 576–582. 14 indexed citations
6.
LaDuca, Holly, Aaron J. Stuenkel, Jill S. Dolinsky, et al.. (2014). Utilization of multigene panels in hereditary cancer predisposition testing: analysis of more than 2,000 patients. Genetics in Medicine. 16(11). 830–837. 237 indexed citations
7.
Gau, Chia‐Ling, Holly LaDuca, Hong Lu, et al.. (2014). Abstract 14: Identification of probands with multiple mutations in cancer susceptibility genes using a multigene panel approach. Cancer Research. 74(23_Supplement). 14–14. 2 indexed citations
8.
Roberts, Jennifer, Stephanie Gandomi, Ira Lu, et al.. (2014). Clinical Report of a 17q12 Microdeletion with Additionally Unreported Clinical Features. SHILAP Revista de lepidopterología. 2014. 1–6. 13 indexed citations
9.
Gau, Chia‐Ling, Vincenzo Cerullo, Fides D. Lay, et al.. (2009). Short-term Correction of Arginase Deficiency in a Neonatal Murine Model With a Helper-dependent Adenoviral Vector. Molecular Therapy. 17(7). 1155–1163. 27 indexed citations
10.
Becker-Catania, Sara, Teresa Gregory, Yawei J. Yang, et al.. (2006). Loss of arginase I results in increased proliferation of neural stem cells. Journal of Neuroscience Research. 84(4). 735–746. 11 indexed citations
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13.
Gau, Chia‐Ling, Iara M.P. Machado, Erik J. Uhlmann, et al.. (2003). Identification of Dominant Negative Mutants of Rheb GTPase and Their Use to Implicate the Involvement of Human Rheb in the Activation of p70S6K. Journal of Biological Chemistry. 278(41). 39921–39930. 90 indexed citations
14.
Patel, Parthive H., Lea Guo, John M. Maris, et al.. (2003). DrosophilaRheb GTPase is required for cell cycle progression and cell growth. Journal of Cell Science. 116(17). 3601–3610. 126 indexed citations
15.
Pervin, Shehla, Rajan Singh, Chia‐Ling Gau, et al.. (2001). Potentiation of nitric oxide-induced apoptosis of MDA-MB-468 cells by farnesyltransferase inhibitor: implications in breast cancer.. PubMed. 61(12). 4701–6. 39 indexed citations
16.
Edamatsu, Hironori, Chia‐Ling Gau, Tetsuo Nemoto, Lea Guo, & Fuyuhiko Tamanoi. (2000). Cdk inhibitors, roscovitine and olomoucine, synergize with farnesyltransferase inhibitor (FTI) to induce efficient apoptosis of human cancer cell lines. Oncogene. 19(27). 3059–3068. 90 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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