Y. Sun

1.1k total citations · 1 hit paper
16 papers, 929 citations indexed

About

Y. Sun is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Y. Sun has authored 16 papers receiving a total of 929 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 5 papers in Pulmonary and Respiratory Medicine and 4 papers in Molecular Biology. Recurrent topics in Y. Sun's work include Cancer Treatment and Pharmacology (5 papers), Colorectal Cancer Treatments and Studies (3 papers) and Cancer Genomics and Diagnostics (3 papers). Y. Sun is often cited by papers focused on Cancer Treatment and Pharmacology (5 papers), Colorectal Cancer Treatments and Studies (3 papers) and Cancer Genomics and Diagnostics (3 papers). Y. Sun collaborates with scholars based in United States, Australia and Spain. Y. Sun's co-authors include George Stearns, Sidney V. Suggs, Babru Samal, Jeffrey Crawford, L. Schwartzberg, Mark N. Stein, John Stephenson, Jesse McGreivy, Qing Zhao and Lian‐He Yang and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Clinical Oncology and Molecular and Cellular Biology.

In The Last Decade

Y. Sun

14 papers receiving 897 citations

Hit Papers

Cloning and characterization of the cDNA encoding a novel... 1994 2026 2004 2015 1994 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Cloning and characterization of the cDNA encoding a novel human pre-B-cell colony-enhancing factor.
    1994 857 citations Babru Samal, Y. Sun et al. Molecular and Cellular Biology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Y. Sun United States 6 532 294 201 198 176 16 929
Mara Gallí United States 9 329 0.6× 145 0.5× 273 1.4× 438 2.2× 344 2.0× 12 1.0k
Li Qin Zhang United States 13 164 0.3× 91 0.3× 211 1.0× 99 0.5× 124 0.7× 23 555
Kiyomi Saito Japan 13 390 0.7× 302 1.0× 177 0.9× 47 0.2× 24 0.1× 19 766
Michael W. Stoner United States 14 115 0.2× 355 1.2× 314 1.6× 43 0.2× 71 0.4× 28 858
Lingdi Wang China 16 171 0.3× 92 0.3× 366 1.8× 75 0.4× 23 0.1× 24 742
Eduardo Martínez‐Ansó Spain 13 240 0.5× 118 0.4× 275 1.4× 242 1.2× 11 0.1× 21 866
Yuanji Ma China 11 260 0.5× 86 0.3× 112 0.6× 47 0.2× 44 0.3× 37 531
Yuri Shimoda Japan 7 218 0.4× 184 0.6× 386 1.9× 47 0.2× 30 0.2× 10 708
Vjekoslav Zaninovic United States 9 300 0.6× 64 0.2× 222 1.1× 607 3.1× 8 0.0× 13 1.5k
Bernadette Chen United States 18 83 0.2× 227 0.8× 191 1.0× 20 0.1× 8 0.0× 39 782

Countries citing papers authored by Y. Sun

Since Specialization
Citations

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

Fields of papers citing papers by Y. Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Y. Sun

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

All Works

16 of 16 papers shown
1.
Zhang, Xiangyu, Y. Sun, Na Yu, et al.. (2025). Data-Driven Discovery of Polar Organic Cocrystals: Integration of Machine Learning and Automated Screening. Journal of the American Chemical Society. 147(49). 45523–45535.
2.
Wang, Xiaojian, et al.. (2025). Non-Destructive Detection of External Defects in Potatoes Using Hyperspectral Imaging and Machine Learning. Agriculture. 15(6). 573–573. 4 indexed citations
3.
Wang, Shou‐Yu, et al.. (2024). The decision‐making process of palliative care among male caregivers of chronically ill patients‐A grounded theory study. International Journal of Nursing Practice. 30(5). e13280–e13280. 1 indexed citations
4.
Sun, Y., et al.. (2023). Registered nurses' perceptions and experience of working in aged care: A qualitative approach. Nursing Open. 11(1). e2060–e2060. 2 indexed citations
5.
Köck, Kathleen, Jason M. Gow, Michelle Horner, et al.. (2014). Preclinical development ofAMG139, a human antibody specifically targetingIL‐23. British Journal of Pharmacology. 172(1). 159–172. 25 indexed citations
6.
Eatock, Martin, J. Szántó, Niall C. Tebbutt, et al.. (2011). Randomized, double-blind, placebo-controlled phase II study of AMG 386 in combination with cisplatin and capecitabine (CX) in patients (pts) with metastatic gastroesophageal adenocarcinoma.. Journal of Clinical Oncology. 29(4_suppl). 66–66. 2 indexed citations
7.
8.
9.
Bruno, René, Jianfeng Lü, Y. Sun, & Laurent Claret. (2009). Simulation of survival with first- and second-line non-small cell lung cancer (NSCLC) therapy using a public domain drug-disease modeling framework. Journal of Clinical Oncology. 27(15_suppl). 8087–8087. 1 indexed citations
10.
Lu, Jinying, Laurent Claret, Liviawati Sutjandra, et al.. (2009). Population pharmacokinetic (PK)/pharmacodynamic (PD) modeling and simulations for exposure‐;tumor response relationships: Motesanib in a phase II thyroid cancer (TC) trial. Journal of Clinical Oncology. 27(15_suppl). e14528–e14528. 1 indexed citations
11.
Boer, Richard de, Peter A. Kaufman, Shane White, et al.. (2009). Primary Analysis of a Phase 1b Combination Study of Motesanib (AMG 706) with Paclitaxel or Docetaxel for the Treatment of Locally Recurrent, Unresectable or Metastatic Breast Cancer.. Cancer Research. 69(24_Supplement). 205–205. 4 indexed citations
12.
Price, Timothy, et al.. (2007). Safety and pharmacokinetics (PK) of AMG 706 in combination with gemcitabine for the treatment of patients (pts) with solid tumors. Journal of Clinical Oncology. 25(18_suppl). 14005–14005. 5 indexed citations
13.
Crawford, Jeffrey, John Stephenson, Gregory A. Otterson, et al.. (2007). Safety and pharmacokinetics (PK) of AMG 706 in combination with panitumumab and gemcitabine-cisplatin in patients (pts) with advanced cancer. Journal of Clinical Oncology. 25(18_suppl). 14057–14057. 7 indexed citations
14.
Crawford, Jeffrey, Howard A. Burris, Mark N. Stein, et al.. (2006). Safety and pharmacokinetics (PK) of AMG 706, panitumumab, and gemcitabine/cisplatin (GC) for the treatment of advanced solid malignancies. Journal of Clinical Oncology. 24(18_suppl). 13005–13005. 9 indexed citations
15.
Gavva, Narender R., Lana Klionsky, Yusheng Qu, et al.. (2004). Receptors and channels. Journal of Pain. 5(3). S6–S6. 1 indexed citations
16.
Samal, Babru, et al.. (1994). Cloning and characterization of the cDNA encoding a novel human pre-B-cell colony-enhancing factor.. Molecular and Cellular Biology. 14(2). 1431–1437. 857 indexed citations breakdown →

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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