Hongjin Wen

1.9k total citations · 1 hit paper
6 papers, 1.5k citations indexed

About

Hongjin Wen is a scholar working on Pharmacology, Physiology and Molecular Biology. According to data from OpenAlex, Hongjin Wen has authored 6 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Pharmacology, 3 papers in Physiology and 2 papers in Molecular Biology. Recurrent topics in Hongjin Wen's work include Cholinesterase and Neurodegenerative Diseases (3 papers), Alzheimer's disease research and treatments (3 papers) and Computational Drug Discovery Methods (2 papers). Hongjin Wen is often cited by papers focused on Cholinesterase and Neurodegenerative Diseases (3 papers), Alzheimer's disease research and treatments (3 papers) and Computational Drug Discovery Methods (2 papers). Hongjin Wen collaborates with scholars based in United States. Hongjin Wen's co-authors include Philip C. Wong, Donald L. Price, Huaibin Cai, David Borchelt, Yanshu Wang, Diane B. McCarthy, Fiona M. Laird, Hsueh‐Cheng Chiang, Mohamed H. Farah and Hey‐Kyoung Lee and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Neuroscience and Nature Neuroscience.

In The Last Decade

Hongjin Wen

6 papers receiving 1.5k citations

Hit Papers

1 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.

BACE1 is the major β-secretase for generation of Aβ peptides by neurons

2001 868 citations Huaibin Cai, Yanshu Wang et al. Nature Neuroscience profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hongjin Wen United States	5	1.1k	588	506	355	291	6	1.5k
Nancy C. Stratman United States	10	1.1k 1.0×	693 1.2×	474 0.9×	353 1.0×	279 1.0×	14	1.5k
Luisa Onstead United States	13	1.1k 0.9×	500 0.9×	333 0.7×	207 0.6×	249 0.9×	14	1.3k
Vicki Olm United States	8	1.2k 1.0×	704 1.2×	291 0.6×	177 0.5×	395 1.4×	8	1.7k
Paul Denis United States	5	1.3k 1.1×	742 1.3×	532 1.1×	399 1.1×	231 0.8×	6	1.6k
Elizabeth Brigham United States	14	1.1k 0.9×	652 1.1×	297 0.6×	213 0.6×	240 0.8×	22	1.6k
Hahn-Jun Lee Japan	10	1.2k 1.1×	706 1.2×	351 0.7×	163 0.5×	448 1.5×	13	1.7k
Holger Cynis Germany	24	1.3k 1.1×	965 1.6×	316 0.6×	308 0.9×	359 1.2×	47	2.0k
Raphaëlle Pardossi‐Piquard France	19	1.3k 1.1×	837 1.4×	369 0.7×	179 0.5×	348 1.2×	29	1.7k
Lawrence M. Refolo United States	10	1.3k 1.2×	757 1.3×	398 0.8×	251 0.7×	419 1.4×	13	1.6k
Mary E. Shuck United States	9	1.1k 1.0×	1.0k 1.8×	471 0.9×	358 1.0×	294 1.0×	11	1.8k

Countries citing papers authored by Hongjin Wen

Since Specialization

Citations

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

Fields of papers citing papers by Hongjin Wen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongjin Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Hongjin Wen. A scholar is included among the top collaborators of Hongjin Wen 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 Hongjin Wen. Hongjin Wen 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:

6 of 6 papers shown

1.

Li, Tong, Hongjin Wen, Cory Brayton, et al.. (2007). Moderate Reduction of γ-Secretase Attenuates Amyloid Burden and Limits Mechanism-Based Liabilities. Journal of Neuroscience. 27(40). 10849–10859. 59 indexed citations

2.

Li, Tong, Hongjin Wen, Cory Brayton, et al.. (2007). Epidermal Growth Factor Receptor and Notch Pathways Participate in the Tumor Suppressor Function of γ-Secretase. Journal of Biological Chemistry. 282(44). 32264–32273. 74 indexed citations

3.

Laird, Fiona M., Huaibin Cai, Alena Savonenko, et al.. (2005). BACE1, a Major Determinant of Selective Vulnerability of the Brain to Amyloid-β Amyloidogenesis, is Essential for Cognitive, Emotional, and Synaptic Functions. Journal of Neuroscience. 25(50). 11693–11709. 431 indexed citations

4.

Cai, Huaibin, Xian Lin, Chengsong Xie, et al.. (2005). Loss ofALS2Function Is Insufficient to Trigger Motor Neuron Degeneration in Knock-Out Mice But Predisposes Neurons to Oxidative Stress. Journal of Neuroscience. 25(33). 7567–7574. 101 indexed citations

5.

Li, Tong, et al.. (2004). O3-05-08 Characterization of γ-secretase complex: analysis of APH-1B deficient mice. Neurobiology of Aging. 25. S63–S63. 1 indexed citations

6.

Cai, Huaibin, Yanshu Wang, Diane B. McCarthy, et al.. (2001). BACE1 is the major β-secretase for generation of Aβ peptides by neurons. Nature Neuroscience. 4(3). 233–234. 868 indexed citations breakdown →

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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