Jide Tian

6.0k total citations · 1 hit paper
85 papers, 5.0k citations indexed

About

Jide Tian is a scholar working on Genetics, Immunology and Surgery. According to data from OpenAlex, Jide Tian has authored 85 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Genetics, 28 papers in Immunology and 23 papers in Surgery. Recurrent topics in Jide Tian's work include Diabetes and associated disorders (27 papers), Immune Cell Function and Interaction (25 papers) and Pancreatic function and diabetes (23 papers). Jide Tian is often cited by papers focused on Diabetes and associated disorders (27 papers), Immune Cell Function and Interaction (25 papers) and Pancreatic function and diabetes (23 papers). Jide Tian collaborates with scholars based in United States, China and Poland. Jide Tian's co-authors include Daniel L. Kaufman, Hoa Dang, Mark A. Atkinson, Michael Clare‐Salzler, Thomas G. Forsthuber, Paul Lehmann, Yuxin Lu, Yihua Zhang, Allan J. Tobin and P. Lehmann and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Jide Tian

82 papers receiving 4.9k citations

Hit Papers

Spontaneous loss of T-cell tolerance to glutamic acid dec... 1993 2026 2004 2015 1993 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jide Tian United States 37 2.0k 1.8k 1.3k 1.1k 894 85 5.0k
Laurent Audoly United States 38 796 0.4× 949 0.5× 352 0.3× 1.8k 1.6× 409 0.5× 69 5.9k
Yumi Imai United States 39 567 0.3× 426 0.2× 937 0.7× 1.7k 1.5× 890 1.0× 109 4.4k
K. Leahy United States 27 1.4k 0.7× 655 0.4× 536 0.4× 1.7k 1.5× 137 0.2× 63 6.4k
Antonio Castrillo Spain 44 377 0.2× 3.8k 2.1× 2.8k 2.1× 4.0k 3.5× 450 0.5× 92 9.0k
Subbiah Pugazhenthi United States 32 450 0.2× 350 0.2× 548 0.4× 1.8k 1.6× 596 0.7× 82 4.0k
C. Bruce Verchere Canada 50 2.2k 1.1× 943 0.5× 4.0k 3.0× 2.6k 2.3× 2.1k 2.3× 163 7.7k
Luca Parente Italy 35 341 0.2× 1.0k 0.6× 469 0.4× 1.8k 1.6× 329 0.4× 93 4.4k
Luciano Pirola France 34 359 0.2× 965 0.5× 508 0.4× 3.6k 3.2× 465 0.5× 77 6.4k
Enrique Sáez United States 38 469 0.2× 480 0.3× 1.3k 1.0× 3.7k 3.3× 445 0.5× 71 6.1k
Takuya Noguchi Japan 40 292 0.1× 1.0k 0.6× 490 0.4× 3.8k 3.4× 233 0.3× 135 6.1k

Countries citing papers authored by Jide Tian

Since Specialization
Citations

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

Fields of papers citing papers by Jide Tian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jide Tian

This figure shows the co-authorship network connecting the top 25 collaborators of Jide Tian. A scholar is included among the top collaborators of Jide 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 Jide Tian. Jide 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
2.
Tian, Jide, et al.. (2024). Enhancing student engagement in online collaborative writing through a generative AI-based conversational agent. The Internet and Higher Education. 65. 100979–100979. 9 indexed citations
3.
Tian, Jide & Daniel L. Kaufman. (2023). The GABA and GABA-Receptor System in Inflammation, Anti-Tumor Immune Responses, and COVID-19. Biomedicines. 11(2). 254–254. 30 indexed citations
4.
Wu, Jianbing, Wei Yin, Zhangjian Huang, et al.. (2021). Design, Synthesis, and Biological Evaluation of Organic Nitrite (NO2) Donors as Potential Anticerebral Ischemia Agents. Journal of Medicinal Chemistry. 64(15). 10919–10933. 11 indexed citations
5.
Tian, Jide, Hoa Dang, Blake Middleton, & Daniel L. Kaufman. (2017). Clinically applicable GABA receptor positive allosteric modulators promote ß-cell replication. Scientific Reports. 7(1). 374–374. 23 indexed citations
8.
Tian, Jide, Hoa Dang, & Daniel L. Kaufman. (2011). Combining Antigen-Based Therapy with GABA Treatment Synergistically Prolongs Survival of Transplanted ß-Cells in Diabetic NOD Mice. PLoS ONE. 6(9). e25337–e25337. 41 indexed citations
9.
Tian, Jide, Jing Yong, Hoa Dang, & Daniel L. Kaufman. (2011). Oral GABA treatment downregulates inflammatory responses in a mouse model of rheumatoid arthritis. Autoimmunity. 44(6). 465–470. 88 indexed citations
10.
Escande‐Beillard, Nathalie, Lorraine Washburn, Dan Zekzer, et al.. (2009). Neurons Preferentially Respond to Self-MHC Class I Allele Products Regardless of Peptide Presented. The Journal of Immunology. 184(2). 816–823. 22 indexed citations
11.
Li, Yongqi, Hui Ji, Yihua Zhang, et al.. (2007). WB1106, a novel nitric oxide-releasing derivative of telmisartan, inhibits hypertension and improves glucose metabolism in rats. European Journal of Pharmacology. 577(1-3). 100–108. 21 indexed citations
12.
Tian, Jide, Dan Zekzer, Yuxin Lu, Hoa Dang, & Daniel L. Kaufman. (2006). B Cells Are Crucial for Determinant Spreading of T Cell Autoimmunity among β Cell Antigens in Diabetes-Prone Nonobese Diabetic Mice. The Journal of Immunology. 176(4). 2654–2661. 56 indexed citations
13.
Lu, Yuxin, Hoa Dang, Blake Middleton, et al.. (2006). Long-Term Monitoring of Transplanted Islets Using Positron Emission Tomography. Molecular Therapy. 14(6). 851–856. 29 indexed citations
14.
Olcott, Angelica, Jide Tian, Valerie Walker, et al.. (2005). Antigen-Based Therapies Using Ignored Determinants of β Cell Antigens Can More Effectively Inhibit Late-Stage Autoimmune Disease in Diabetes-Prone Mice. The Journal of Immunology. 175(3). 1991–1999. 27 indexed citations
15.
Tian, Jide, Yuxin Lu, Hanwei Zhang, et al.. (2004). γ-Aminobutyric Acid Inhibits T Cell Autoimmunity and the Development of Inflammatory Responses in a Mouse Type 1 Diabetes Model. The Journal of Immunology. 173(8). 5298–5304. 183 indexed citations
16.
Tian, Jide, Angelica Olcott, & Daniel L. Kaufman. (2002). Antigen-Based Immunotherapy Drives the Precocious Development of Autoimmunity. The Journal of Immunology. 169(11). 6564–6569. 20 indexed citations
17.
Tian, Jide, et al.. (2001). Lipopolysaccharide-Activated B Cells Down-Regulate Th1 Immunity and Prevent Autoimmune Diabetes in Nonobese Diabetic Mice. The Journal of Immunology. 167(2). 1081–1089. 328 indexed citations
18.
Tian, Jide, Mark A. Atkinson, Michael Clare‐Salzler, et al.. (1996). Nasal administration of glutamate decarboxylase (GAD65) peptides induces Th2 responses and prevents murine insulin-dependent diabetes.. The Journal of Experimental Medicine. 183(4). 1561–1567. 352 indexed citations
19.
Tian, Jide, P. Lehmann, & Daniel L. Kaufman. (1994). T cell cross-reactivity between coxsackievirus and glutamate decarboxylase is associated with a murine diabetes susceptibility allele.. The Journal of Experimental Medicine. 180(5). 1979–1984. 127 indexed citations
20.
Tian, Jide, et al.. (1993). Cloning and sequence analysis of a murine cDNA encoding glutamate decarboxylase (GAD65). Biochimica et Biophysica Acta (BBA) - Gene Structure and Expression. 1216(1). 157–160. 30 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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