Yingfang Tian

2.8k total citations
67 papers, 2.1k citations indexed

About

Yingfang Tian is a scholar working on Molecular Biology, Cancer Research and Neurology. According to data from OpenAlex, Yingfang Tian has authored 67 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 13 papers in Cancer Research and 12 papers in Neurology. Recurrent topics in Yingfang Tian's work include Autism Spectrum Disorder Research (11 papers), MicroRNA in disease regulation (10 papers) and Cancer-related molecular mechanisms research (8 papers). Yingfang Tian is often cited by papers focused on Autism Spectrum Disorder Research (11 papers), MicroRNA in disease regulation (10 papers) and Cancer-related molecular mechanisms research (8 papers). Yingfang Tian collaborates with scholars based in China, United States and Netherlands. Yingfang Tian's co-authors include Glen C. Jickling, Frank R. Sharp, Boryana Stamova, Bradley P. Ander, Xinhua Zhan, Huichun Xu, Renée J. Turner, Dazhi Liu, Piero Verro and Edward C. Jauch and has published in prestigious journals such as Journal of Neuroscience, Neurology and Stroke.

In The Last Decade

Yingfang Tian

65 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yingfang Tian China 26 1.1k 711 374 300 250 67 2.1k
Dayun Feng China 26 772 0.7× 245 0.3× 302 0.8× 225 0.8× 230 0.9× 77 1.8k
Dianshuai Gao China 25 856 0.8× 361 0.5× 205 0.5× 112 0.4× 189 0.8× 125 1.8k
Christian Barbato Italy 26 1.1k 0.9× 453 0.6× 171 0.5× 136 0.5× 172 0.7× 79 1.9k
Julie A. Ellison United States 18 1.2k 1.1× 258 0.4× 785 2.1× 212 0.7× 232 0.9× 24 2.9k
Vera Chesnokova United States 28 630 0.6× 268 0.4× 225 0.6× 237 0.8× 101 0.4× 64 2.3k
John B. Redell United States 24 1.3k 1.2× 360 0.5× 260 0.7× 592 2.0× 786 3.1× 57 2.4k
Marcelo Páez-Pereda Germany 35 1.4k 1.2× 459 0.6× 96 0.3× 388 1.3× 158 0.6× 85 3.8k
Boris Sabirzhanov United States 24 830 0.7× 261 0.4× 560 1.5× 422 1.4× 438 1.8× 39 2.2k
Gabriella Schiera Italy 21 843 0.7× 267 0.4× 374 1.0× 86 0.3× 110 0.4× 52 1.7k
Akiko Satoh United States 14 762 0.7× 156 0.2× 130 0.3× 687 2.3× 246 1.0× 21 2.9k

Countries citing papers authored by Yingfang Tian

Since Specialization
Citations

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

Fields of papers citing papers by Yingfang Tian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yingfang Tian

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

All Works

20 of 20 papers shown
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Diao, Zhijun, Yao Li, Chunling Wei, et al.. (2021). Involvement of Midbrain Dopamine Neuron Activity in Negative Reinforcement Learning in Mice. Molecular Neurobiology. 58(11). 5667–5681. 4 indexed citations
4.
Li, Yao, Zhijun Diao, Chunling Wei, et al.. (2021). Stress Controllability Modulates Basal Activity of Dopamine Neurons in the Substantia Nigra Compacta. eNeuro. 8(3). ENEURO.0044–21.2021. 4 indexed citations
5.
Tian, Yingfang, Xinlin Chen, Meimei Shi, et al.. (2019). Angiogenic Gene Profiles in Laser-Microdissected Microvessels and Neurons from Ischemic Penumbra of Rat Brain. Journal of Molecular Neuroscience. 67(4). 643–653. 2 indexed citations
6.
Zhang, Ruoxin, et al.. (2018). RNA-Seq data on prefrontal cortex in valproic acid model of autism and control rats. Data in Brief. 18. 787–789. 2 indexed citations
7.
Zhang, Junfeng, Lili Shi, Li Zhang, et al.. (2016). MicroRNA-25 Negatively Regulates Cerebral Ischemia/Reperfusion Injury-Induced Cell Apoptosis Through Fas/FasL Pathway. Journal of Molecular Neuroscience. 58(4). 507–516. 71 indexed citations
8.
Matikainen‐Ankney, Bridget A., Nebojsa Kezunovic, Roxana Mesias, et al.. (2016). Altered Development of Synapse Structure and Function in Striatum Caused by Parkinson's Disease-Linked LRRK2-G2019S Mutation. Journal of Neuroscience. 36(27). 7128–7141. 81 indexed citations
9.
Wang, Li, Zhaorong Li, Qing Gao, et al.. (2014). miR-99a and -99b inhibit cervical cancer cell proliferation and invasion by targeting mTOR signaling pathway. Medical Oncology. 31(5). 934–934. 68 indexed citations
10.
Apperson, Michelle, Yingfang Tian, Boryana Stamova, et al.. (2013). Genome wide differences of gene expression associated with HLA-DRB1 genotype in multiple sclerosis: A pilot study. Journal of Neuroimmunology. 257(1-2). 90–96. 4 indexed citations
11.
Tian, Yingfang, Boryana Stamova, Glen C. Jickling, et al.. (2012). Y Chromosome Gene Expression in the Blood of Male Patients With Ischemic Stroke Compared With Male Controls. Gender Medicine. 9(2). 68–75.e3. 25 indexed citations
12.
Chen, Xinlin, et al.. (2011). Selection of housekeeping genes for normalization of RT-PCR in hypoxic neural stem cells of rat in vitro. Molecular Biology Reports. 39(1). 569–576. 29 indexed citations
13.
Stamova, Boryana, Yingfang Tian, Glen C. Jickling, et al.. (2011). The X-Chromosome Has a Different Pattern of Gene Expression in Women Compared With Men With Ischemic Stroke. Stroke. 43(2). 326–334. 46 indexed citations
14.
Sharp, Frank R., Glen C. Jickling, Boryana Stamova, et al.. (2011). Molecular markers and mechanisms of stroke: RNA studies of blood in animals and humans. Journal of Cerebral Blood Flow & Metabolism. 31(7). 1513–1531. 53 indexed citations
15.
Sharp, Frank R., Glen C. Jickling, Boryana Stamova, et al.. (2011). RNA Expression Profiles From Blood for the Diagnosis of Stroke and Its Causes. Journal of Child Neurology. 26(9). 1131–1136. 7 indexed citations
16.
Xu, Huichun, Boryana Stamova, Glen C. Jickling, et al.. (2010). Distinctive RNA Expression Profiles in Blood Associated With White Matter Hyperintensities in Brain. Stroke. 41(12). 2744–2749. 35 indexed citations
17.
Zhang, Pengbo, et al.. (2006). Effects of ketamine-midazolam anesthesia on the expression of NMDA and AMPA receptor subunit in the peri-infarction of rat brain. Chinese Medical Journal. 119(18). 1555–1562. 10 indexed citations
18.
Zhao, Jianjun, Yong Liu, Xinlin Chen, et al.. (2006). [Effect of citicoline on spatial learning and memory of rats after focal cerebral ischemia].. PubMed. 26(2). 174–6. 9 indexed citations
19.
Zhang, Pengbo, Yong Liu, Jie Li, et al.. (2004). [Effects of ketamine-midazolam anesthesia on focal cerebral ischemic injury in rats].. PubMed. 24(12). 1337–41. 3 indexed citations
20.
Zhu, Bofeng, et al.. (2002). [Genetic polymorphism of 9 STR loci in Han nation population in Shandong Province].. PubMed. 24(6). 620–5. 1 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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