Yichen Guo

921 total citations · 1 hit paper
10 papers, 711 citations indexed

About

Yichen Guo is a scholar working on Molecular Biology, Microbiology and Cell Biology. According to data from OpenAlex, Yichen Guo has authored 10 papers receiving a total of 711 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 3 papers in Microbiology and 2 papers in Cell Biology. Recurrent topics in Yichen Guo's work include vaccines and immunoinformatics approaches (7 papers), Machine Learning in Bioinformatics (7 papers) and Antimicrobial Peptides and Activities (3 papers). Yichen Guo is often cited by papers focused on vaccines and immunoinformatics approaches (7 papers), Machine Learning in Bioinformatics (7 papers) and Antimicrobial Peptides and Activities (3 papers). Yichen Guo collaborates with scholars based in China, United States and Egypt. Yichen Guo's co-authors include Ivan Stamenkovic, Man‐Sun Sy, Ke Yan, Bin Liu, Hongwu Lv, M S Sy, Wei Peng, Hao Wu, Jie Wen and Yongyong Chen and has published in prestigious journals such as The Journal of Experimental Medicine, Bioinformatics and Analytical Biochemistry.

In The Last Decade

Yichen Guo

10 papers receiving 693 citations

Hit Papers

sAMPpred-GAT: prediction of antimicrobial peptide by grap... 2022 2026 2023 2024 2022 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yichen Guo China 9 579 291 168 137 70 10 711
Andreas Jäckel Germany 13 262 0.5× 214 0.7× 39 0.2× 16 0.1× 190 2.7× 28 649
Kamala Kesavan United States 10 520 0.9× 69 0.2× 29 0.2× 28 0.2× 126 1.8× 11 704
R. Hein Germany 10 290 0.5× 69 0.2× 97 0.6× 14 0.1× 189 2.7× 11 486
Suzanne Salvi Switzerland 15 410 0.7× 105 0.4× 48 0.3× 25 0.2× 220 3.1× 30 770
Timothy V. Updyke United States 7 286 0.5× 104 0.4× 71 0.4× 8 0.1× 69 1.0× 7 423
Kyle A. DiVito United States 16 508 0.9× 59 0.2× 43 0.3× 36 0.3× 273 3.9× 24 767
Stephanie C. Pero United States 18 633 1.1× 59 0.2× 50 0.3× 19 0.1× 284 4.1× 38 926
Maria Vias United Kingdom 10 593 1.0× 84 0.3× 27 0.2× 16 0.1× 220 3.1× 16 914
Thomas McGonigal United States 13 541 0.9× 126 0.4× 41 0.2× 8 0.1× 251 3.6× 16 796
Ju-Yu Hsu Taiwan 8 311 0.5× 168 0.6× 146 0.9× 5 0.0× 186 2.7× 11 605

Countries citing papers authored by Yichen Guo

Since Specialization
Citations

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

Fields of papers citing papers by Yichen Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yichen Guo

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

All Works

10 of 10 papers shown
1.
Yan, Ke, Yichen Guo, & Bin Liu. (2023). PreTP-2L: identification of therapeutic peptides and their types using two-layer ensemble learning framework. Bioinformatics. 39(4). 14 indexed citations
2.
Lv, Hongwu, Ke Yan, Yichen Guo, et al.. (2022). AMPpred-EL: An effective antimicrobial peptide prediction model based on ensemble learning. Computers in Biology and Medicine. 146. 105577–105577. 28 indexed citations
3.
Yan, Ke, Hongwu Lv, Yichen Guo, Wei Peng, & Bin Liu. (2022). sAMPpred-GAT: prediction of antimicrobial peptide by graph attention network and predicted peptide structure. Bioinformatics. 39(1). 138 indexed citations breakdown →
4.
Yan, Ke, Hongwu Lv, Yichen Guo, et al.. (2022). TPpred-ATMV: therapeutic peptide prediction by adaptive multi-view tensor learning model. Bioinformatics. 38(10). 2712–2718. 53 indexed citations
5.
Yan, Ke, Hongwu Lv, Jie Wen, et al.. (2022). PreTP-Stack: Prediction of Therapeutic Peptide Based on the Stacked Ensemble Learning. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(2). 1337–1344. 38 indexed citations
6.
Yan, Ke, Hongwu Lv, Jie Wen, Yichen Guo, & Bin Liu. (2021). TP-MV: Therapeutic Peptides Prediction by Multi-view Learning. Current Bioinformatics. 17(2). 174–183. 15 indexed citations
7.
Guo, Yichen, Ke Yan, Hongwu Lv, & Bin Liu. (2021). PreTP-EL: prediction of therapeutic peptides based on ensemble learning. Briefings in Bioinformatics. 22(6). 49 indexed citations
8.
Guo, Yichen, Ke Yan, Hao Wu, & Bin Liu. (2020). ReFold-MAP: Protein remote homology detection and fold recognition based on features extracted from profiles. Analytical Biochemistry. 611. 114013–114013. 4 indexed citations
9.
Sy, M S, Yichen Guo, & Ivan Stamenkovic. (1992). Inhibition of tumor growth in vivo with a soluble CD44-immunoglobulin fusion protein.. The Journal of Experimental Medicine. 176(2). 623–627. 99 indexed citations
10.
Sy, Man‐Sun, Yichen Guo, & Ivan Stamenkovic. (1991). Distinct effects of two CD44 isoforms on tumor growth in vivo.. The Journal of Experimental Medicine. 174(4). 859–866. 273 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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