Keith Tan

927 total citations
9 papers, 713 citations indexed

About

Keith Tan is a scholar working on Molecular Biology, Endocrine and Autonomic Systems and Physiology. According to data from OpenAlex, Keith Tan has authored 9 papers receiving a total of 713 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Endocrine and Autonomic Systems and 3 papers in Physiology. Recurrent topics in Keith Tan's work include Biochemical Analysis and Sensing Techniques (3 papers), Sleep and Wakefulness Research (2 papers) and Regulation of Appetite and Obesity (2 papers). Keith Tan is often cited by papers focused on Biochemical Analysis and Sensing Techniques (3 papers), Sleep and Wakefulness Research (2 papers) and Regulation of Appetite and Obesity (2 papers). Keith Tan collaborates with scholars based in United States, Canada and United Kingdom. Keith Tan's co-authors include Jeffrey M. Friedman, Zachary A. Knight, Sarah F. Schmidt, Kıvanç Birsoy, Robert W. Wysocki, Jennifer L. Garrison, Ana B. Emiliano, Mats I. Ekstrand, Katherine L. B. Borden and Abdellatif Amri and has published in prestigious journals such as Cell, Journal of Biological Chemistry and The Journal of Cell Biology.

In The Last Decade

Keith Tan

9 papers receiving 706 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Keith Tan United States	9	356	178	131	95	93	9	713
Robert W. Wysocki United States	6	338 0.9×	132 0.7×	144 1.1×	82 0.9×	74 0.8×	7	1.2k
Varinder Gill Canada	9	168 0.5×	127 0.7×	51 0.4×	177 1.9×	32 0.3×	12	961
Tomoyuki Fujiyama Japan	13	265 0.7×	161 0.9×	36 0.3×	99 1.0×	46 0.5×	19	671
Kento Tominaga Japan	11	332 0.9×	296 1.7×	84 0.6×	225 2.4×	13 0.1×	28	873
Maria N. Pavlova United States	15	566 1.6×	90 0.5×	82 0.6×	163 1.7×	12 0.1×	26	928
Enrico Bastianelli Belgium	12	537 1.5×	72 0.4×	36 0.3×	349 3.7×	86 0.9×	25	898
Gemini Skariah United States	11	313 0.9×	202 1.1×	24 0.2×	120 1.3×	38 0.4×	12	878
Nicola Romanò United Kingdom	15	271 0.8×	111 0.6×	64 0.5×	98 1.0×	10 0.1×	34	804
Yuriko Ban Japan	13	255 0.7×	102 0.6×	58 0.4×	91 1.0×	13 0.1×	22	887
Heping Yu United States	19	376 1.1×	40 0.2×	38 0.3×	48 0.5×	75 0.8×	37	909

Countries citing papers authored by Keith Tan

Since Specialization

Citations

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

Fields of papers citing papers by Keith Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keith Tan

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

All Works

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9 of 9 papers shown

Schneeberger, Marc, Keith Tan, Alexander R. Nectow, et al.. (2018). Functional analysis reveals differential effects of glutamate and MCH neuropeptide in MCH neurons. Molecular Metabolism. 13. 83–89. 32 indexed citations

Tan, Keith, Zachary A. Knight, & Jeffrey M. Friedman. (2014). Ablation of AgRP neurons impairs adaption to restricted feeding. Molecular Metabolism. 3(7). 694–704. 58 indexed citations

Knight, Zachary A., Sarah F. Schmidt, Kıvanç Birsoy, Keith Tan, & Jeffrey M. Friedman. (2014). A critical role for mTORC1 in erythropoiesis and anemia. eLife. 3. e01913–e01913. 67 indexed citations

Li, Zhiying, Giovanni Ceccarini, Michael Eisenstein, Keith Tan, & Jeffrey M. Friedman. (2013). Phenotypic effects of an induced mutation of the ObRa isoform of the leptin receptor. Molecular Metabolism. 2(4). 364–375. 45 indexed citations

Knight, Zachary A., Keith Tan, Kıvanç Birsoy, et al.. (2012). Molecular Profiling of Activated Neurons by Phosphorylated Ribosome Capture. Cell. 151(5). 1126–1137. 231 indexed citations

Tan, Keith, Biljana Čuljković, Abdellatif Amri, & Katherine L. B. Borden. (2008). Ribavirin targets eIF4E dependent Akt survival signaling. Biochemical and Biophysical Research Communications. 375(3). 341–345. 45 indexed citations

Čuljković, Biljana, Keith Tan, Slobodanka Orolicki, et al.. (2008). The eIF4E RNA regulon promotes the Akt signaling pathway. The Journal of Cell Biology. 181(1). 51–63. 81 indexed citations

Barrett, Angela N., Samantha Santangelo, Keith Tan, et al.. (2007). Breast cancer associated transcriptional repressor PLU‐1/JARID1B interacts directly with histone deacetylases. International Journal of Cancer. 121(2). 265–275. 79 indexed citations

Tan, Keith, Anthony Shaw, Bente Kühn Madsen, et al.. (2003). Human PLU-1 Has Transcriptional Repression Properties and Interacts with the Developmental Transcription Factors BF-1 and PAX9. Journal of Biological Chemistry. 278(23). 20507–20513. 75 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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