Hsin‐ya Yang

829 total citations
23 papers, 450 citations indexed

About

Hsin‐ya Yang is a scholar working on Rehabilitation, Molecular Biology and Occupational Therapy. According to data from OpenAlex, Hsin‐ya Yang has authored 23 papers receiving a total of 450 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Rehabilitation, 9 papers in Molecular Biology and 5 papers in Occupational Therapy. Recurrent topics in Hsin‐ya Yang's work include Wound Healing and Treatments (11 papers), Planarian Biology and Electrostimulation (7 papers) and Diabetic Foot Ulcer Assessment and Management (5 papers). Hsin‐ya Yang is often cited by papers focused on Wound Healing and Treatments (11 papers), Planarian Biology and Electrostimulation (7 papers) and Diabetic Foot Ulcer Assessment and Management (5 papers). Hsin‐ya Yang collaborates with scholars based in United States, Switzerland and Canada. Hsin‐ya Yang's co-authors include Francis J. McNally, R. Rivkah Isseroff, Karen Perry McNally, Paul E. Mains, Valentin Lulevich, Gang-yu Liu, Edith Hümmler, Deborah L. Baines, Roch‐Philippe Charles and Marcella Gomez and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Cell Biology and PLoS ONE.

In The Last Decade

Hsin‐ya Yang

19 papers receiving 441 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hsin‐ya Yang United States	9	199	188	98	94	77	23	450
Hala Fahs United States	9	320 1.6×	332 1.8×	197 2.0×	15 0.2×	20 0.3×	17	639
Lucy Xu United States	7	279 1.4×	59 0.3×	81 0.8×	63 0.7×	7 0.1×	8	555
Sergio Juarez-Carreño Spain	5	135 0.7×	22 0.1×	26 0.3×	14 0.1×	20 0.3×	6	436
K. Azibi France	14	583 2.9×	158 0.8×	5 0.1×	44 0.5×	99 1.3×	18	770
Greg Vatcher Canada	9	212 1.1×	22 0.1×	96 1.0×	7 0.1×	18 0.2×	14	357
Daniel Yoon United States	9	106 0.5×	36 0.2×	4 0.0×	83 0.9×	21 0.3×	18	324
Ferenc Jeanplong New Zealand	12	568 2.9×	162 0.9×	16 0.2×	40 0.4×	3 0.0×	19	650
Rouhollah Fathi Iran	16	206 1.0×	28 0.1×	15 0.2×	20 0.2×	352 4.6×	58	619
Christine Yang Canada	9	165 0.8×	79 0.4×	10 0.1×	105 1.1×	26 0.3×	17	466
Gary Stinnett United States	4	168 0.8×	100 0.5×	10 0.1×	10 0.1×	14 0.2×	6	413

Countries citing papers authored by Hsin‐ya Yang

Since Specialization

Citations

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

Fields of papers citing papers by Hsin‐ya Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsin‐ya Yang. 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 Hsin‐ya Yang. The network helps show where Hsin‐ya Yang may publish in the future.

Co-authorship network of co-authors of Hsin‐ya Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Hsin‐ya Yang. A scholar is included among the top collaborators of Hsin‐ya Yang 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 Hsin‐ya Yang. Hsin‐ya Yang 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

Yang, Hsin‐ya, Moyasar A. Alhamo, Kan Zhu, et al.. (2025). A high-resolution temporal transcriptomic and imaging dataset of porcine wound healing. Scientific Data. 12(1). 1635–1635.

Yang, Hsin‐ya, et al.. (2025). Differences in thickness of dermal layers in cranio-caudal anatomic locations in porcine skin wounds: Implications for wound healing studies. Research in Veterinary Science. 186. 105572–105572.

Sun, Yaohui, Kan Zhu, Hsin‐ya Yang, et al.. (2024). A data-driven approach to establishing cell motility patterns as predictors of macrophage subtypes and their relation to cell morphology. PLoS ONE. 19(12). e0315023–e0315023.

Sun, Yaohui, Hsin‐ya Yang, Elham Aslankoohi, et al.. (2024). Deep learning classification for macrophage subtypes through cell migratory pattern analysis. Frontiers in Cell and Developmental Biology. 12. 1259037–1259037. 6 indexed citations

Mahajan, Shubham, et al.. (2023). WoundNet: A Domain-Adaptable Few-Shot Classification Framework for Wound Healing Assessment. 33. 1–5.

Nguyen, Tiffany, Cristián E. Hernández, Kan Zhu, et al.. (2023). A system for bioelectronic delivery of treatment directed toward wound healing. Scientific Reports. 13(1). 14766–14766. 8 indexed citations

Mehta, Abijeet Singh, Hsin‐ya Yang, Elham Aslankoohi, et al.. (2023). Quantifying innervation facilitated by deep learning in wound healing. Scientific Reports. 13(1). 16885–16885. 4 indexed citations

Yang, Hsin‐ya, Fernando A. Fierro, Daniel Yoon, et al.. (2022). Combination product of dermal matrix, preconditioned human mesenchymal stem cells and timolol promotes wound healing in the porcine wound model. Journal of Biomedical Materials Research Part B Applied Biomaterials. 110(7). 1615–1623. 6 indexed citations

Jafari, Mohammad, et al.. (2022). Automatic wound detection and size estimation using deep learning algorithms. PLoS Computational Biology. 18(3). e1009852–e1009852. 28 indexed citations

10.

Yoon, Daniel, et al.. (2022). Beta adrenergic receptor antagonist can modify Pseudomonas aeruginosa biofilm formation in vitro: Implications for chronic wounds. The FASEB Journal. 36(3). e22057–e22057. 10 indexed citations

11.

Jafari, Mohammad, Abijeet Singh Mehta, Yaohui Sun, et al.. (2022). A machine learning based model accurately predicts cellular response to electric fields in multiple cell types. Scientific Reports. 12(1). 9912–9912. 6 indexed citations

12.

Yang, Hsin‐ya, et al.. (2021). Alpha and beta adrenergic receptors modulate keratinocyte migration. PLoS ONE. 16(7). e0253139–e0253139. 10 indexed citations

13.

Yang, Hsin‐ya, et al.. (2021). Sling Training with Positive Reinforcement to Facilitate Porcine Wound Studies. SHILAP Revista de lepidopterología. 1(2). 100016–100016. 5 indexed citations

14.

Yang, Hsin‐ya, Fernando A. Fierro, Michelle So, et al.. (2020). Combination product of dermal matrix, human mesenchymal stem cells, and timolol promotes diabetic wound healing in mice. Stem Cells Translational Medicine. 9(11). 1353–1364. 42 indexed citations

15.

Yoon, Daniel, Hsin‐ya Yang, Saul Schaefer, et al.. (2020). Adverse effects of topical timolol: Safety concerns and implications for dermatologic use. Journal of the American Academy of Dermatology. 84(1). 199–200. 5 indexed citations

16.

Albrecht, Huguette, Hsin‐ya Yang, Maija Kiuru, et al.. (2018). The Beta 2 Adrenergic Receptor Antagonist Timolol Improves Healing of Combined Burn and Radiation Wounds. Radiation Research. 189(4). 441–445. 15 indexed citations

17.

Yang, Hsin‐ya, et al.. (2014). Utilizing Custom-designed Galvanotaxis Chambers to Study Directional Migration of Prostate Cells. Journal of Visualized Experiments. 5 indexed citations

18.

Yang, Hsin‐ya, Roch‐Philippe Charles, Edith Hümmler, Deborah L. Baines, & R. Rivkah Isseroff. (2013). The epithelial sodium channel mediates the directionality of galvanotaxis in human keratinocytes. Journal of Cell Science. 126(Pt 9). 1942–51. 54 indexed citations

19.

Lulevich, Valentin, Hsin‐ya Yang, R. Rivkah Isseroff, & Gang-yu Liu. (2010). Single cell mechanics of keratinocyte cells. Ultramicroscopy. 110(12). 1435–1442. 68 indexed citations

20.

Yang, Hsin‐ya, Karen Perry McNally, & Francis J. McNally. (2003). MEI-1/katanin is required for translocation of the meiosis I spindle to the oocyte cortex in C. elegans☆. Developmental Biology. 260(1). 245–259. 97 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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