Jianping Hua

2.1k total citations
54 papers, 1.5k citations indexed

About

Jianping Hua is a scholar working on Molecular Biology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jianping Hua has authored 54 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 12 papers in Artificial Intelligence and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jianping Hua's work include Gene expression and cancer classification (27 papers), Bioinformatics and Genomic Networks (14 papers) and Advanced Data Compression Techniques (8 papers). Jianping Hua is often cited by papers focused on Gene expression and cancer classification (27 papers), Bioinformatics and Genomic Networks (14 papers) and Advanced Data Compression Techniques (8 papers). Jianping Hua collaborates with scholars based in United States, China and Canada. Jianping Hua's co-authors include Edward R. Dougherty, Chao Sima, Waibhav Tembe, Michael Bittner, Zixiang Xiong, Blaise Hanczar, John N. Weinstein, James Lowey, Marcel Brun and Edward Suh and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Jianping Hua

52 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jianping Hua United States	19	593	437	301	118	114	54	1.5k
Justin Bedő Australia	14	384 0.6×	457 1.0×	236 0.8×	42 0.4×	112 1.0×	29	1.5k
Alexandros Kalousis Switzerland	20	569 1.0×	712 1.6×	398 1.3×	84 0.7×	65 0.6×	49	1.6k
Nigel Duffy United States	7	1.2k 2.0×	920 2.1×	363 1.2×	68 0.6×	141 1.2×	14	2.3k
André Elisseeff Germany	15	496 0.8×	981 2.2×	474 1.6×	163 1.4×	149 1.3×	25	1.9k
Sören Sonnenburg Germany	17	818 1.4×	900 2.1×	831 2.8×	153 1.3×	160 1.4×	20	2.4k
Kun Zhang United States	22	559 0.9×	647 1.5×	184 0.6×	94 0.8×	80 0.7×	114	1.9k
Alex Gammerman United Kingdom	23	511 0.9×	1.2k 2.7×	376 1.2×	150 1.3×	153 1.3×	80	2.5k
David Bednarski United States	8	1.4k 2.4×	539 1.2×	282 0.9×	44 0.4×	120 1.1×	9	2.2k
Luis Rueda Canada	19	509 0.9×	289 0.7×	106 0.4×	90 0.8×	108 0.9×	122	1.1k
Vı́ctor Robles Spain	15	579 1.0×	691 1.6×	297 1.0×	49 0.4×	173 1.5×	41	1.6k

Countries citing papers authored by Jianping Hua

Since Specialization

Citations

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

Fields of papers citing papers by Jianping Hua

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianping Hua

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Datta, Aniruddha, Chao Sima, Jianping Hua, et al.. (2022). Anti-tumor effects of cryptotanshinone (C19H20O3) in human osteosarcoma cell lines. Biomedicine & Pharmacotherapy. 150. 112993–112993. 10 indexed citations

Datta, Aniruddha, et al.. (2021). Targeting oncogenic mutations in colorectal cancer using cryptotanshinone. PLoS ONE. 16(2). e0247190–e0247190. 11 indexed citations

Bittner, Michael, et al.. (2021). Comprehensive live-cell imaging analysis of cryptotanshinone and synergistic drug-screening effects in various human and canine cancer cell lines. PLoS ONE. 16(2). e0236074–e0236074. 2 indexed citations

Fisch, Kathleen M., Jianping Hua, Ganqiang Liu, et al.. (2019). DNA methylation changes associated with Parkinson’s disease progression: outcomes from the first longitudinal genome-wide methylation analysis in blood. Epigenetics. 14(4). 365–382. 54 indexed citations

Hua, Jianping, et al.. (2018). A Bayesian approach to determine the composition of heterogeneous cancer tissue. BMC Bioinformatics. 19(S3). 90–90. 5 indexed citations

Datta, Aniruddha, et al.. (2018). An in-silico study examining the induction of apoptosis by Cryptotanshinone in metastatic melanoma cell lines. BMC Cancer. 18(1). 855–855. 14 indexed citations

Zollanvari, Amin, Jianping Hua, & Edward R. Dougherty. (2013). Analytical study of performance of linear discriminant analysis in stochastic settings. Pattern Recognition. 46(11). 3017–3029. 9 indexed citations

Li, Xiangfang, Lijun Qian, Jianping Hua, Michael Bittner, & Edward R. Dougherty. (2012). Assessing the efficacy of molecularly targeted agents on cell line-based platforms by using system identification. BMC Genomics. 13(S6). S11–S11. 10 indexed citations

Sima, Chao, Jianping Hua, & Sungwon Jung. (2009). Inference of Gene Regulatory Networks Using Time-Series Data: A Survey. Current Genomics. 10(6). 416–429. 69 indexed citations

10.

Dougherty, Edward R., Jianping Hua, & Chao Sima. (2009). Performance of Feature Selection Methods. Current Genomics. 10(6). 365–374. 27 indexed citations

11.

Choudhary, Ashish, Jianping Hua, Michael Bittner, & Edward R. Dougherty. (2008). THE EFFECT OF POPULATION CONTEXTS ON CLASSIFIER PERFORMANCE. Journal of Biological Systems. 16(4). 495–517.

12.

Hua, Jianping, Waibhav Tembe, & Edward R. Dougherty. (2008). Feature selection in the classification of high-dimension data. 1–2. 15 indexed citations

13.

Dougherty, Edward R., Jianping Hua, & Michael Bittner. (2007). Validation of Computational Methods in Genomics. Current Genomics. 8(1). 1–19. 27 indexed citations

14.

Hanczar, Blaise, Jianping Hua, & Edward R. Dougherty. (2007). Decorrelation of the True and Estimated Classifier Errors in High-Dimensional Settings. SHILAP Revista de lepidopterología. 2007. 1–12. 42 indexed citations

15.

Hua, Jianping, et al.. (2007). Quantification of the Impact of Feature Selection on the Variance of Cross-Validation Error Estimation. PubMed. 2007. 1–11. 19 indexed citations

16.

Hua, Jianping, Yoganand Balagurunathan, Yidong Chen, et al.. (2006). Normalization Benefits Microarray-Based Classification. PubMed. 2006. 1–13. 16 indexed citations

17.

Hua, Jianping, James Lowey, Zixiang Xiong, & Edward R. Dougherty. (2006). Noise-injected neural networks show promise for use on small-sample expression data. BMC Bioinformatics. 7(1). 274–274. 15 indexed citations

18.

Hua, Jianping, David W. Craig, Marcel Brun, et al.. (2006). SNiPer-HD: improved genotype calling accuracy by an expectation-maximization algorithm for high-density SNP arrays. Bioinformatics. 23(1). 57–63. 29 indexed citations

19.

Hua, Jianping, Yoganand Balagurunathan, Yidong Chen, et al.. (2006). Effect of normalization on microarray-based classification. 7–8.

20.

Xiong, Zixiang, Xiaolin Wu, Samuel Cheng, & Jianping Hua. (2003). Lossy-to-lossless compression of medical volumetric data using three-dimensional integer wavelet transforms. IEEE Transactions on Medical Imaging. 22(3). 459–470. 103 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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