Arthur Hsu

2.0k total citations
39 papers, 990 citations indexed

About

Arthur Hsu is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Arthur Hsu has authored 39 papers receiving a total of 990 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 8 papers in Artificial Intelligence and 6 papers in Genetics. Recurrent topics in Arthur Hsu's work include Neural Networks and Applications (6 papers), Genomics and Phylogenetic Studies (5 papers) and Machine Learning in Bioinformatics (3 papers). Arthur Hsu is often cited by papers focused on Neural Networks and Applications (6 papers), Genomics and Phylogenetic Studies (5 papers) and Machine Learning in Bioinformatics (3 papers). Arthur Hsu collaborates with scholars based in Australia, United States and Taiwan. Arthur Hsu's co-authors include Saman Halgamuge, Yehuda Bassok, Sen‐Lin Tang, Christopher M. Powers, Helen J. Hislop, Jacquelin Perry, Chon‐Kit Kenneth Chan, Houmin Yan, Ke Liu and Kym Pham and has published in prestigious journals such as Science, Bioinformatics and PLoS ONE.

In The Last Decade

Arthur Hsu

37 papers receiving 949 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Arthur Hsu Australia	17	296	208	149	147	117	39	990
Chung‐Ho Chen Taiwan	26	376 1.3×	252 1.2×	47 0.3×	167 1.1×	73 0.6×	239	2.7k
Seunggyun Ha South Korea	20	278 0.9×	135 0.6×	219 1.5×	158 1.1×	160 1.4×	82	1.7k
Yingjia Wang China	14	519 1.8×	49 0.2×	54 0.4×	59 0.4×	74 0.6×	50	931
Jiayuan Zhang China	19	788 2.7×	27 0.1×	181 1.2×	100 0.7×	103 0.9×	99	1.6k
Chao Ouyang China	16	139 0.5×	33 0.2×	166 1.1×	29 0.2×	46 0.4×	51	1.3k
Chun Zhao China	19	149 0.5×	70 0.3×	55 0.4×	13 0.1×	37 0.3×	107	1.4k
Junyan Xu China	18	552 1.9×	12 0.1×	73 0.5×	15 0.1×	263 2.2×	54	1.1k
David G. Robinson United States	15	223 0.8×	53 0.3×	14 0.1×	20 0.1×	35 0.3×	43	826

Countries citing papers authored by Arthur Hsu

Since Specialization

Citations

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

Fields of papers citing papers by Arthur Hsu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arthur Hsu

This figure shows the co-authorship network connecting the top 25 collaborators of Arthur Hsu. A scholar is included among the top collaborators of Arthur Hsu 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 Arthur Hsu. Arthur Hsu 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

Montellese, Christian, Matthew E. Ritchie, Monther Alhamdoosh, et al.. (2024). An optimized protocol for quality control of gene therapy vectors using nanopore direct RNA sequencing. Genome Research. 34(11). 1966–1975. 2 indexed citations

Jochum, Floriane, Martina Aida Ángeles, Vincent Balaya, et al.. (2023). Management of patients with advanced epithelial ovarian cancer: a European survey. Archives of Gynecology and Obstetrics. 308(2). 535–549. 2 indexed citations

Steinfort, Daniel, Kym Pham, Arthur Hsu, et al.. (2019). Sensitive molecular testing methods can demonstrate NSCLC driver mutations in malignant pleural effusion despite non-malignant cytology. Translational Lung Cancer Research. 8(4). 513–518. 9 indexed citations

Leong, Tracy L., Michael Christie, Kym Pham, et al.. (2017). Evaluating the Genomic Yield of a Single Endobronchial Ultrasound-guided Transbronchial Needle Aspiration in Lung Cancer: Meeting the Challenge of Doing More With Less. Clinical Lung Cancer. 18(6). e467–e472. 17 indexed citations

Grillet, Fanny, Luke Zappia, Ebba L. Lagerqvist, et al.. (2016). Circulating tumour cells from patients with colorectal cancer have cancer stem cell hallmarks in ex vivo culture. Gut. 66(10). 1802–1810. 159 indexed citations

Kondrashova, Olga, et al.. (2015). High-Throughput Amplicon-Based Copy Number Detection of 11 Genes in Formalin-Fixed Paraffin-Embedded Ovarian Tumour Samples by MLPA-Seq. PLoS ONE. 10(11). e0143006–e0143006. 20 indexed citations

Bennetts, Bruce, Arthur Hsu, Simon Mead, et al.. (2014). Quality standards for DNA sequence variation databases to improve clinical management under development in Australia. PubMed. 3(3). 54–57. 2 indexed citations

Wong, Emily, Anthony T. Papenfuss, Andreas Heger, et al.. (2011). Transcriptomic analysis supports similar functional roles for the two thymuses of the tammar wallaby. BMC Genomics. 12(1). 420–420. 16 indexed citations

Jap, Budi Thomas, et al.. (2011). Comparing two video-based techniques for driver fatigue detection: classification versus optical flow approach. Machine Vision and Applications. 22(4). 597–618. 23 indexed citations

10.

Whittington, Camilla M., Anthony T. Papenfuss, Devin P. Locke, et al.. (2010). Novel venom gene discovery in the platypus. Genome biology. 11(9). R95–R95. 48 indexed citations

11.

Murchison, Elizabeth P., Cesar Tovar, Arthur Hsu, et al.. (2009). The Tasmanian Devil Transcriptome Reveals Schwann Cell Origins of a Clonally Transmissible Cancer. Science. 327(5961). 84–87. 4 indexed citations

12.

Chan, Chon‐Kit Kenneth, Arthur Hsu, Saman Halgamuge, & Sen‐Lin Tang. (2008). Binning sequences using very sparse labels within a metagenome. BMC Bioinformatics. 9(1). 215–215. 59 indexed citations

13.

Chan, Chon‐Kit Kenneth, Arthur Hsu, Sen‐Lin Tang, & Saman Halgamuge. (2007). Using Growing Self‐Organising Maps to Improve the Binning Process in Environmental Whole‐Genome Shotgun Sequencing. BioMed Research International. 2008(1). 513701–513701. 48 indexed citations

14.

Karim, Azharul, Saman Halgamuge, Alan Jay Smith, & Arthur Hsu. (2006). Manufacturing Yield Improvement by Clustering. Lecture notes in computer science. 4234. 526–534. 1 indexed citations

15.

Asghar, Sohail, Damminda Alahakoon, & Arthur Hsu. (2004). Enhancing OLAP functionality using self-organizing neural networks. Neural, Parallel & Scientific Computations archive. 12(1). 1–20. 7 indexed citations

16.

Asghar, Sohail, Damminda Alahakoon, & Arthur Hsu. (2004). Enhancing OLAP functionality using neural networks.. 12(11). 1–20.

17.

Hsu, Arthur & Saman Halgamuge. (2003). Enhancement of topology preservation and hierarchical dynamic self-organising maps for data visualisation. International Journal of Approximate Reasoning. 32(2-3). 259–279. 27 indexed citations

18.

Preethichandra, D.M.G., Arthur Hsu, Damminda Alahakoon, & Saman Halgamuge. (2002). A modified dynamic self-organizing map algorithm for efficient hardware implementation. 2(1). 646–650. 1 indexed citations

19.

Hsu, Arthur, Damminda Alahakoon, Saman Halgamuge, & Bala Srinivasan. (2000). Automatic Clustering and Rule Extraction using a Dynamic SOM Tree. 3 indexed citations

20.

Hsu, Arthur & Ronald T. Wilcox. (2000). Stochastic Prediction in Multinomial Logit Models. Management Science. 46(8). 1137–1144. 11 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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