Gung‐Wei Chirn

4.9k total citations
29 papers, 1.0k citations indexed

About

Gung‐Wei Chirn is a scholar working on Molecular Biology, Artificial Intelligence and Cancer Research. According to data from OpenAlex, Gung‐Wei Chirn has authored 29 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 6 papers in Artificial Intelligence and 6 papers in Cancer Research. Recurrent topics in Gung‐Wei Chirn's work include RNA and protein synthesis mechanisms (6 papers), Algorithms and Data Compression (6 papers) and Cancer Genomics and Diagnostics (5 papers). Gung‐Wei Chirn is often cited by papers focused on RNA and protein synthesis mechanisms (6 papers), Algorithms and Data Compression (6 papers) and Cancer Genomics and Diagnostics (5 papers). Gung‐Wei Chirn collaborates with scholars based in United States, China and Canada. Gung‐Wei Chirn's co-authors include Nelson C. Lau, Yuliya A. Sytnikova, Kaizhong Zhang, Mark Labow, Thomas G. Marr, Dennis Shasha, Bruce A. Shapiro, Daniel M. Kemp, Andreas Bender and Timothy J. Mitchison 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

Gung‐Wei Chirn

29 papers receiving 1.0k citations

Peers

Countries citing papers authored by Gung‐Wei Chirn

Since Specialization

Citations

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

Fields of papers citing papers by Gung‐Wei Chirn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gung‐Wei Chirn. 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 Gung‐Wei Chirn. The network helps show where Gung‐Wei Chirn may publish in the future.

Co-authorship network of co-authors of Gung‐Wei Chirn

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Comprehensive genomic profiling of different subtypes of nasopharyngeal carcinoma reveals similarities and differences to guide targeted therapy 2017 ·Cancer ·Siraj M. Ali, Ming Yao, Jicheng Yao, (unknown), Yu‐Wei Cheng, Alexa B. Schrock, Gung‐Wei Chirn, Hui Chen, Shuo Mu, Laurie M. Gay, Julia A. Elvin, James Suh, Vincent A. Miller, Philip J. Stephens, Jeffrey S. Ross, Kai Wang	36
2	Analytical and clinical validation of a next-generation sequencing-based circulating tumor DNA (ctDNA) assay assures its clinical application 2017 ·Annals of Oncology ·(unknown), Shuo Mu, (unknown), (unknown), Hu Zhang, Jian Hu, Gung‐Wei Chirn, Hyo Jeong Kang, (unknown), Meng Yao	3
3	The landscape of kinase fusions in 445 Chinese NSCLC patients 2017 ·Annals of Oncology ·(unknown), (unknown), (unknown), Tao Shou, Yunfei Shi, Qisen Guo, Yue Shang, Jian Hu, (unknown), Lei Dai, (unknown), Gung‐Wei Chirn, Kai Wang, Ming Yao	1
4	XenopusPiwi proteins interact with a broad proportion of the oocyte transcriptome 2016 ·RNA ·James A. Toombs, Yuliya A. Sytnikova, Gung‐Wei Chirn, (unknown), Nelson C. Lau, Michael D. Blower	11
5	Unique transposon landscapes are pervasive acrossDrosophila melanogastergenomes 2015 ·Nucleic Acids Research ·Reazur Rahman, Gung‐Wei Chirn, Abhay Kanodia, Yuliya A. Sytnikova, Björn Brembs, Casey Bergman, Nelson C. Lau	82
6	Transposable element dynamics and PIWI regulation impacts lncRNA and gene expression diversity in Drosophila ovarian cell cultures 2014 ·Genome Research ·Yuliya A. Sytnikova, Reazur Rahman, Gung‐Wei Chirn, Josef P. Clark, Nelson C. Lau	43
7	The capacity of target silencing by Drosophila PIWI and piRNAs 2014 ·RNA ·(unknown), Josef P. Clark, Yuliya A. Sytnikova, Gung‐Wei Chirn, Nelson C. Lau	74
8	Small RNA Library Construction from Minute Biological Samples 2013 ·Methods in molecular biology ·Jessica Matts, Yuliya A. Sytnikova, Gung‐Wei Chirn, Gabor L. Igloi, Nelson C. Lau	9
9	Possible Formation of Mitochondrial-RNA Containing Chimeric or Trimeric RNA Implies a Post-Transcriptional and Post-Splicing Mechanism for RNA Fusion 2013 ·PLoS ONE ·Wei Yang, Jianmin Wu, (unknown), (unknown), Haihong Shen, Gung‐Wei Chirn, Jianhua Zhou, (unknown), (unknown), D. Joshua Liao	26
10	Holo-TFIID controls the magnitude of a transcription burst and fine-tuning of transcription 2013 ·Proceedings of the National Academy of Sciences ·Katie L. Pennington, Sharon K. Marr, Gung‐Wei Chirn, Michael T. Marr	19
11	Single nucleotide in the MTF-1 binding site can determine metal-specific transcription activation 2012 ·Proceedings of the National Academy of Sciences ·(unknown), Gung‐Wei Chirn, Michael T. Marr	48
12	Uncovering mechanisms of transcriptional regulations by systematic mining of cis regulatory elements with gene expression profiles 2008 ·BioData Mining ·Qicheng Ma, Gung‐Wei Chirn, Joseph D. Szustakowski, (unknown), Penelope A. Kosinski, Daniel M. Kemp, Nanguneri Nirmala	13
13	From proteomics to systems biology of bacterial pathogens: Approaches, tools, and applications 2007 ·PROTEOMICS ·Uwe Plikat, Hans Voshol, (unknown), Brigitte Wiedmann, Piroska Dévay, D. Müller, Urs Wirth, Joseph D. Szustakowski, Gung‐Wei Chirn, Bruno Inverardi, Xiaoling Puyang, Kara D. Brown, Heather D. Kamp, Sjouke Hoving, (unknown), (unknown), Ron Peterson, (unknown), Jan van Oostrum, Manuel C. Peitsch	15
14	Integrating high-content screening and ligand-target prediction to identify mechanism of action 2007 ·Nature Chemical Biology ·Daniel Young, Andreas Bender, J.D. Hoyt, Elizabeth McWhinnie, Gung‐Wei Chirn, (unknown), John A. Tallarico, Mark Labow, Jeremy L. Jenkins, Timothy J. Mitchison, Feng Yan	266
15	Multiple Retropseudogenes from Pluripotent Cell-specific Gene Expression Indicates a Potential Signature for Novel Gene Identification 2005 ·Journal of Biological Chemistry ·(unknown), Gung‐Wei Chirn, (unknown), Daniel M. Kemp	98
16	Development of comprehensive functional genomic screens to identify novel mediators of osteoarthritis 2005 ·Osteoarthritis and Cartilage ·Sherif Daouti, (unknown), Sujatha Nagulapalli, F Buxton, (unknown), Gung‐Wei Chirn, Dale L. Bodian, Chi Song, Mark Labow, Martin Lotz, Joseph Quintavalla, (unknown)	40
17	HIV protease genotype and viral sensitivity to HIV protease inhibitors following saquinavir therapy 1998 ·AIDS ·Charles Craig, Esther Race, (unknown), Lynne Whittaker, (unknown), (unknown), (unknown), (unknown), Gung‐Wei Chirn, I. B. R. Duncan, Nick Cammack	52
18	A Visualization Tool for Pattern Matching and Discovery in Scientific Databases. 1996 ·Software Engineering and Knowledge Engineering ·(unknown), Jason Tsong-Li Wang, Gung‐Wei Chirn, (unknown), (unknown), (unknown)	2
19	Pattern discovery in sequence databases: algorithms and applications to dna/protein classification 1996 ·Experimental & Molecular Medicine ·(unknown), Gung‐Wei Chirn	3
20	Discovering active motifs in sets of related protein sequences and using them for classification 1994 ·Nucleic Acids Research ·(unknown), Thomas G. Marr, Dennis Shasha, Bruce A. Shapiro, Gung‐Wei Chirn	31

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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