Bing Bai

1.7k total citations · 1 hit paper
17 papers, 1.0k citations indexed

About

Bing Bai is a scholar working on Molecular Biology, Spectroscopy and Genetics. According to data from OpenAlex, Bing Bai has authored 17 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 6 papers in Spectroscopy and 2 papers in Genetics. Recurrent topics in Bing Bai's work include Advanced Proteomics Techniques and Applications (6 papers), Metabolomics and Mass Spectrometry Studies (5 papers) and RNA Research and Splicing (5 papers). Bing Bai is often cited by papers focused on Advanced Proteomics Techniques and Applications (6 papers), Metabolomics and Mass Spectrometry Studies (5 papers) and RNA Research and Splicing (5 papers). Bing Bai collaborates with scholars based in China, United States and Belgium. Bing Bai's co-authors include Junmin Peng, Haiyan Tan, James Messing, Hong Joo Kim, Kyung‐Ha Lee, Richard W. Kriwacki, Brian D. Freibaum, Nam Chul Kim, Amandine Molliex and J. Paul Taylor and has published in prestigious journals such as Cell, Chemical Communications and Brain Research.

In The Last Decade

Bing Bai

16 papers receiving 1.0k citations

Hit Papers

align trajectories

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.

C9orf72 Dipeptide Repeats Impair the Assembly, Dynamics, and Function of Membrane-Less Organelles

2016 510 citations Kyung‐Ha Lee, Peipei Zhang et al. Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bing Bai China	10	789	289	164	134	121	17	1.0k
Sebastian Hogl Germany	11	347 0.4×	147 0.5×	87 0.5×	303 2.3×	39 0.3×	14	784
Xiang Yin China	17	350 0.4×	134 0.5×	48 0.3×	90 0.7×	38 0.3×	35	688
Luke McAlary Australia	18	568 0.7×	569 2.0×	256 1.6×	186 1.4×	22 0.2×	41	1.0k
Jennifer J. Marden United States	11	358 0.5×	235 0.8×	111 0.7×	132 1.0×	15 0.1×	15	732
Daniel C. Berwick United Kingdom	16	853 1.1×	433 1.5×	26 0.2×	237 1.8×	24 0.2×	18	1.4k
Timothy P. Kegelman United States	14	490 0.6×	72 0.2×	71 0.4×	66 0.5×	22 0.2×	28	983
Michael Hedvat United States	10	465 0.6×	71 0.2×	76 0.5×	64 0.5×	19 0.2×	16	953
Ji-Hoon Cho United States	11	585 0.7×	447 1.5×	16 0.1×	388 2.9×	136 1.1×	21	1.4k
Ruth F. Deighton United Kingdom	11	380 0.5×	31 0.1×	73 0.4×	86 0.6×	52 0.4×	14	519
Caterina Peggion Italy	15	543 0.7×	186 0.6×	77 0.5×	178 1.3×	6 0.0×	34	735

Countries citing papers authored by Bing Bai

Since Specialization

Citations

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

Fields of papers citing papers by Bing Bai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bing Bai

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

All Works

Sort: Min cites: Since: Top N: Style:

17 of 17 papers shown

Bai, Bing, et al.. (2025). CRISPR-based SNP detection technologies advance from classical methods to cutting-edge innovations. Chemical Communications. 61(71). 13345–13358.

Bai, Bing, et al.. (2024). Benchmark N-glycoproteomics study of common differential tissue and serum N-glycoproteins of patients with hepatocellular carcinoma. Analytica Chimica Acta. 1322. 343066–343066. 2 indexed citations

Zheng, Pengfei, et al.. (2024). Insights from the neural guidance factor Netrin-1 into neurodegeneration and other diseases. Frontiers in Molecular Neuroscience. 17. 1379726–1379726. 5 indexed citations

Yao, Bing, Qinglin Zhang, Zhou Yang, et al.. (2022). CircEZH2/miR-133b/IGF2BP2 aggravates colorectal cancer progression via enhancing the stability of m6A-modified CREB1 mRNA. Molecular Cancer. 21(1). 140–140. 98 indexed citations

Bai, Bing, et al.. (2022). Structure-Specific N-Glycoproteomics Characterization of NIST Monoclonal Antibody Reference Material 8671. Journal of Proteome Research. 21(5). 1276–1284. 6 indexed citations

Wang, Yanyan, et al.. (2020). Effects of U1 Small Nuclear Ribonucleoprotein Inhibition on the Expression of Genes Involved in Alzheimer’s Disease. ACS Omega. 5(39). 25306–25311. 3 indexed citations

Bentea, Eduard, Erica A. K. DePasquale, Sinead M. O’Donovan, et al.. (2019). Kinase network dysregulation in a human induced pluripotent stem cell model of DISC1 schizophrenia. Molecular Omics. 15(3). 173–188. 28 indexed citations

Dey, Kaushik, Hong Wang, Mingming Niu, et al.. (2019). Deep undepleted human serum proteome profiling toward biomarker discovery for Alzheimer’s disease. Clinical Proteomics. 16(1). 16–16. 103 indexed citations

Bai, Bing. (2018). U1 snRNP Alteration and Neuronal Cell Cycle Reentry in Alzheimer Disease. Frontiers in Aging Neuroscience. 10. 75–75. 23 indexed citations

10.

Bai, Bing, Sen Wang, Yuxin Chen, et al.. (2018). Effects of RNA Splicing Inhibitors on Amyloid Precursor Protein Expression. ACS Omega. 3(3). 2798–2803. 2 indexed citations

11.

Bai, Bing, Haiyan Tan, & Junmin Peng. (2017). Quantitative Phosphoproteomic Analysis of Brain Tissues. Methods in molecular biology. 1598. 199–211. 5 indexed citations

12.

Lee, Kyung‐Ha, Peipei Zhang, Hong Joo Kim, et al.. (2016). C9orf72 Dipeptide Repeats Impair the Assembly, Dynamics, and Function of Membrane-Less Organelles. Cell. 167(3). 774–788.e17. 510 indexed citations breakdown →

13.

Bai, Bing, Haiyan Tan, Vishwajeeth Pagala, et al.. (2016). Deep Profiling of Proteome and Phosphoproteome by Isobaric Labeling, Extensive Liquid Chromatography, and Mass Spectrometry. Methods in enzymology on CD-ROM/Methods in enzymology. 585. 377–395. 81 indexed citations

14.

Wang, Peng, Yonggang Cao, Ruxia Liu, et al.. (2016). Baicalin alleviates ischemia-induced memory impairment by inhibiting the phosphorylation of CaMKII in hippocampus. Brain Research. 1642. 95–103. 47 indexed citations

15.

Tan, Haiyan, Zhiping Wu, Hong Wang, et al.. (2014). Refined phosphopeptide enrichment by phosphate additive and the analysis of human brain phosphoproteome. PROTEOMICS. 15(2-3). 500–507. 38 indexed citations

16.

Bai, Bing, Ping‐Chung Chen, Chadwick M. Hales, et al.. (2014). Integrated Approaches for Analyzing U1-70K Cleavage in Alzheimer’s Disease. Journal of Proteome Research. 13(11). 4526–4534. 31 indexed citations

17.

Wang, Hong, Yanling Yang, Yuxin Li, et al.. (2014). Systematic Optimization of Long Gradient Chromatography Mass Spectrometry for Deep Analysis of Brain Proteome. Journal of Proteome Research. 14(2). 829–838. 63 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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