Fa‐Yun Che

581 total citations
10 papers, 483 citations indexed

About

Fa‐Yun Che is a scholar working on Molecular Biology, Spectroscopy and Cellular and Molecular Neuroscience. According to data from OpenAlex, Fa‐Yun Che has authored 10 papers receiving a total of 483 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Spectroscopy and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Fa‐Yun Che's work include Advanced Proteomics Techniques and Applications (4 papers), Mass Spectrometry Techniques and Applications (4 papers) and Neuropeptides and Animal Physiology (3 papers). Fa‐Yun Che is often cited by papers focused on Advanced Proteomics Techniques and Applications (4 papers), Mass Spectrometry Techniques and Applications (4 papers) and Neuropeptides and Animal Physiology (3 papers). Fa‐Yun Che collaborates with scholars based in United States and China. Fa‐Yun Che's co-authors include Lloyd D. Fricker, Hui Pan, Jihyeon Lim, Yun Feng, Bonnie Peng, John E. Pintar, Lakshmi A. Devi, Hui‐Lin Pan, Yimei Qian and Nino Mzhavia and has published in prestigious journals such as Biochemical Journal, Journal of Neurochemistry and PROTEOMICS.

In The Last Decade

Fa‐Yun Che

9 papers receiving 473 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fa‐Yun Che United States	7	321	205	175	61	46	10	483
Julia S. Gelman United States	7	240 0.7×	76 0.4×	56 0.3×	19 0.3×	81 1.8×	8	330
Jan Daniel Rudolph Germany	9	369 1.1×	266 1.3×	80 0.5×	92 1.5×	36 0.8×	10	649
Silvia Detro‐Dassen Germany	9	323 1.0×	28 0.1×	177 1.0×	15 0.2×	28 0.6×	11	454
Marito Hayashi United States	14	322 1.0×	25 0.1×	93 0.5×	39 0.6×	23 0.5×	20	565
Eugénie Goupil Canada	13	330 1.0×	17 0.1×	153 0.9×	50 0.8×	19 0.4×	17	503
Arja Kuusinen Finland	9	419 1.3×	61 0.3×	327 1.9×	21 0.3×	11 0.2×	10	509
Chantal Maertens Belgium	13	554 1.7×	18 0.1×	238 1.4×	10 0.2×	31 0.7×	13	704
Yasunori Sugiyama Japan	15	398 1.2×	38 0.2×	62 0.4×	78 1.3×	28 0.6×	38	578
Benoît Lectez Spain	15	405 1.3×	14 0.1×	114 0.7×	102 1.7×	68 1.5×	20	653
Line Vedel Denmark	9	332 1.0×	14 0.1×	136 0.8×	22 0.4×	18 0.4×	11	404

Countries citing papers authored by Fa‐Yun Che

Since Specialization

Citations

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

Fields of papers citing papers by Fa‐Yun Che

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fa‐Yun Che. 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 Fa‐Yun Che. The network helps show where Fa‐Yun Che may publish in the future.

Co-authorship network of co-authors of Fa‐Yun Che

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

All Works

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10 of 10 papers shown

Che, Fa‐Yun, et al.. (2011). Photo‐assisted peptide enrichment in protein complex cross‐linking analysis of a model homodimeric protein using mass spectrometry. PROTEOMICS. 11(20). 4109–4115. 3 indexed citations

Fricker, Lloyd D., Jihyeon Lim, Hui Pan, & Fa‐Yun Che. (2006). Peptidomics: Identification and quantification of endogenous peptides in neuroendocrine tissues. Mass Spectrometry Reviews. 25(2). 327–344. 174 indexed citations

Pan, Hui‐Lin, Fa‐Yun Che, Bonnie Peng, et al.. (2006). The role of prohormone convertase‐2 in hypothalamic neuropeptide processing: a quantitative neuropeptidomic study. Journal of Neurochemistry. 98(6). 1763–1777. 69 indexed citations

Che, Fa‐Yun, et al.. (2005). Relative quantitation of peptides in wild‐type and Cpe^fat/fat mouse pituitary using stable isotopic tags and mass spectrometry. Journal of Mass Spectrometry. 40(2). 227–237. 64 indexed citations

Che, Fa‐Yun & Lloyd D. Fricker. (2005). Quantitative peptidomics of mouse pituitary: comparison of different stable isotopic tags. Journal of Mass Spectrometry. 40(2). 238–249. 92 indexed citations

Che, Fa‐Yun, Quan Yuan, Elena Kalinina, & Lloyd D. Fricker. (2004). Examination of the rate of peptide biosynthesis in neuroendocrine cell lines using a stable isotopic label and mass spectrometry. Journal of Neurochemistry. 90(3). 585–594. 10 indexed citations

Mzhavia, Nino, Yimei Qian, Yun Feng, et al.. (2002). Processing of proSAAS in neuroendocrine cell lines. Biochemical Journal. 361(1). 67–67. 42 indexed citations

Mzhavia, Nino, Yimei Qian, Yun Feng, et al.. (2001). Processing of proSAAS in neuroendocrine cell lines. Biochemical Journal. 361(1). 67–76. 27 indexed citations

Che, Fa‐Yun & Qi‐Chang Xia. (2000). Thiophosphorylation and Fluorescent Labeling of Substrate Peptide of Protein Kinase.. PubMed. 32(1). 69–73. 1 indexed citations

10.

Gao, Xiang, et al.. (1999). Potential GM-CSF Antagonists Selected from a Peptide Phage Display Library.. PubMed. 31(4). 463–465. 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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