Ju Han

669 total citations
23 papers, 482 citations indexed

About

Ju Han is a scholar working on Biophysics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Ju Han has authored 23 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Biophysics, 12 papers in Molecular Biology and 9 papers in Artificial Intelligence. Recurrent topics in Ju Han's work include Cell Image Analysis Techniques (12 papers), AI in cancer detection (8 papers) and Gene expression and cancer classification (7 papers). Ju Han is often cited by papers focused on Cell Image Analysis Techniques (12 papers), AI in cancer detection (8 papers) and Gene expression and cancer classification (7 papers). Ju Han collaborates with scholars based in United States, China and Australia. Ju Han's co-authors include Hang Chang, Bahram Parvin, Joe W. Gray, Paul T. Spellman, Mary Helen Barcellos‐Hoff, Qing Yang, Björn Rydberg, Alexander D. Borowsky, Bahram Parvin and Gerald Fontenay and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Image Processing.

In The Last Decade

Ju Han

21 papers receiving 471 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ju Han United States	13	229	220	150	104	86	23	482
Tokiya Abe Japan	15	166 0.7×	150 0.7×	96 0.6×	94 0.9×	89 1.0×	49	645
Daniel Heim Germany	10	253 1.1×	159 0.7×	115 0.8×	125 1.2×	142 1.7×	17	578
Wiem Lassoued United States	9	321 1.4×	308 1.4×	245 1.6×	262 2.5×	120 1.4×	14	886
Lauri Goodell United States	16	183 0.8×	137 0.6×	71 0.5×	220 2.1×	81 0.9×	26	620
Deborah Thompson United States	11	233 1.0×	131 0.6×	60 0.4×	83 0.8×	109 1.3×	30	469
Isabel Vallcorba Spain	8	130 0.6×	172 0.8×	227 1.5×	143 1.4×	33 0.4×	17	566
Sharath R. Cholleti United States	11	157 0.7×	193 0.9×	43 0.3×	136 1.3×	98 1.1×	20	573
Mikhail Teverovskiy United States	8	318 1.4×	195 0.9×	77 0.5×	76 0.7×	109 1.3×	13	459
Monjoy Saha India	10	371 1.6×	172 0.8×	91 0.6×	57 0.5×	269 3.1×	18	559
Maria Gabrani Switzerland	12	254 1.1×	164 0.7×	55 0.4×	54 0.5×	195 2.3×	39	469

Countries citing papers authored by Ju Han

Since Specialization

Citations

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

Fields of papers citing papers by Ju Han

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ju Han

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

Cheng, Qingsu, Gerald Fontenay, Hang Chang, et al.. (2016). Stiffness of the microenvironment upregulates ERBB2 expression in 3D cultures of MCF10A within the range of mammographic density. Scientific Reports. 6(1). 28987–28987. 17 indexed citations

Fontenay, Gerald, et al.. (2016). BioSig3D: High Content Screening of Three-Dimensional Cell Culture Models. PLoS ONE. 11(3). e0148379–e0148379. 17 indexed citations

Han, Ju, Gerald Fontenay, Yunfu Wang, Jian‐Hua Mao, & Hang Chang. (2016). Phenotypic characterization of breast invasive carcinoma via transferable tissue morphometric patterns learned from glioblastoma multiforme. PubMed. 113. 1025–1028.

Dong, Fengyun, Ju Han, Xiaocui Chen, et al.. (2016). Dihydroartemisinin transiently activates the JNK/SAPK signaling pathway in endothelial cells. Oncology Letters. 12(6). 4699–4704. 13 indexed citations

Han, Ju, Yunfu Wang, Weidong Cai, et al.. (2016). Integrative Analysis of Cellular Morphometric Context Reveals Clinically Relevant Signatures in Lower Grade Glioma. Lecture notes in computer science. 9900. 72–80. 6 indexed citations

Zhong, Cheng, Ju Han, Alexander D. Borowsky, et al.. (2016). When machine vision meets histology: A comparative evaluation of model architecture for classification of histology sections. Medical Image Analysis. 35. 530–543. 17 indexed citations

Han, Ju, Hang Chang, Orsi Giricz, et al.. (2015). Text S1 - Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture. Figshare. 44 indexed citations

Becker-Weimann, Sabine, Gaofeng Xiong, Saori Furuta, et al.. (2013). NFkB disrupts tissue polarity in 3D by preventing integration of microenvironmental signals. Oncotarget. 4(11). 2010–2020. 38 indexed citations

Chang, Hang, Ju Han, Alexander D. Borowsky, et al.. (2012). Invariant Delineation of Nuclear Architecture in Glioblastoma Multiforme for Clinical and Molecular Association. IEEE Transactions on Medical Imaging. 32(4). 670–682. 73 indexed citations

10.

Nath, Sangeeta, Virginia A. Spencer, Ju Han, et al.. (2012). Identification of Fluorescent Compounds with Non-Specific Binding Property via High Throughput Live Cell Microscopy. PLoS ONE. 7(1). e28802–e28802. 8 indexed citations

11.

Zhang, Kai, et al.. (2012). Inference of Causal Networks from Time-Varying Transcriptome Data via Sparse Coding. PLoS ONE. 7(8). e42306–e42306. 3 indexed citations

12.

Chang, Hang, et al.. (2012). Multireference Level Set for the Characterization of Nuclear Morphology in Glioblastoma Multiforme. IEEE Transactions on Biomedical Engineering. 59(12). 3460–3467. 14 indexed citations

13.

Han, Ju, Hang Chang, Gerald Fontenay, et al.. (2012). Molecular bases of morphometric composition in Glioblastoma multiforme. 56. 1631–1634. 4 indexed citations

14.

Le, Quoc V., Ju Han, Joe W. Gray, et al.. (2012). Learning invariant features of tumor signatures. 9. 302–305. 22 indexed citations

15.

Chang, Hang, Gerald Fontenay, Ju Han, et al.. (2011). Morphometic analysis of TCGA glioblastoma multiforme. BMC Bioinformatics. 12(1). 484–484. 41 indexed citations

16.

Han, Ju, Hang Chang, Kai Zhang, et al.. (2011). Comparison of sparse coding and kernel methods for histopathological classification of gliobastoma multiforme. PubMed. 14. 711–714. 21 indexed citations

17.

Han, Ju, et al.. (2010). Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture. PLoS Computational Biology. 6(2). e1000684–e1000684. 1 indexed citations

18.

Zheng, Chun-Hou, Ping Zhang, Lei Zhang, Xinxin Liu, & Ju Han. (2009). Gene expression data classification based on non-negative matrix factorization. 9. 3542–3547. 2 indexed citations

19.

Han, Ju, Hang Chang, Kumari L. Andarawewa, et al.. (2008). Multidimensional Profiling of Cell Surface Proteins and Nuclear Markers. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 7(1). 80–90. 14 indexed citations

20.

Parvin, Bahram, Qing Yang, Ju Han, et al.. (2007). Iterative Voting for Inference of Structural Saliency and Characterization of Subcellular Events. IEEE Transactions on Image Processing. 16(3). 615–623. 123 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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