Yaosen Min

507 total citations · 1 hit paper
8 papers, 155 citations indexed

About

Yaosen Min is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Yaosen Min has authored 8 papers receiving a total of 155 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computational Theory and Mathematics, 4 papers in Molecular Biology and 4 papers in Materials Chemistry. Recurrent topics in Yaosen Min's work include Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (4 papers) and Machine Learning in Materials Science (4 papers). Yaosen Min is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (4 papers) and Machine Learning in Materials Science (4 papers). Yaosen Min collaborates with scholars based in China, Sweden and Germany. Yaosen Min's co-authors include Han Li, Jianyang Zeng, Dacheng Ma, Dan Zhao, Ruotian Zhang, Yingheng Wang, Shuxin Zheng, He Zhang, Ziheng Lu and Tie‐Yan Liu and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Advanced Science.

In The Last Decade

Yaosen Min

7 papers receiving 150 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.

Predicting equilibrium distributions for molecular systems with deep learning

2024 59 citations Shuxin Zheng, Yu Shi et al. Nature Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yaosen Min China	5	94	79	67	10	6	8	155
Ilia Igashov United Kingdom	4	128 1.4×	80 1.0×	60 0.9×	5 0.5×	22 3.7×	5	202
Junsu Ko South Korea	6	145 1.5×	151 1.9×	93 1.4×	14 1.4×	7 1.2×	9	217
Alejandro Varela‐Rial Spain	6	114 1.2×	109 1.4×	76 1.1×	6 0.6×	6 1.0×	8	183
Austin Clyde United States	7	74 0.8×	75 0.9×	32 0.5×	16 1.6×	11 1.8×	11	149
Soojung Yang South Korea	2	93 1.0×	119 1.5×	58 0.9×	10 1.0×	5 0.8×	3	142
Arne Schneuing United Kingdom	4	119 1.3×	75 0.9×	49 0.7×	5 0.5×	24 4.0×	4	195
Jeff Guo Sweden	7	107 1.1×	133 1.7×	126 1.9×	6 0.6×	7 1.2×	10	233
Fusong Ju China	7	153 1.6×	39 0.5×	55 0.8×	7 0.7×	7 1.2×	17	191
Linbu Liao China	7	211 2.2×	107 1.4×	41 0.6×	6 0.6×	9 1.5×	10	250
Michael Caldera Austria	7	106 1.1×	45 0.6×	29 0.4×	4 0.4×	7 1.2×	10	187

Countries citing papers authored by Yaosen Min

Since Specialization

Citations

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

Fields of papers citing papers by Yaosen Min

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaosen Min

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

8 of 8 papers shown

1.

Min, Yaosen, Jingwei Yi, Shuai Cheng Li, et al.. (2025). Controlling risks of AI in chemical science with agents. SHILAP Revista de lepidopterología. 1(1). 15002–15002.

2.

Min, Yaosen, Wei Ye, Xiaoting Wang, et al.. (2024). From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph‐Based Deep Learning. Advanced Science. 11(40). e2405404–e2405404. 13 indexed citations

3.

Zheng, Shuxin, Yu Shi, Ziheng Lu, et al.. (2024). Predicting equilibrium distributions for molecular systems with deep learning. Nature Machine Intelligence. 6(5). 558–567. 59 indexed citations breakdown →

4.

Li, Han, Ruotian Zhang, Yaosen Min, et al.. (2023). A knowledge-guided pre-training framework for improving molecular representation learning. Nature Communications. 14(1). 7568–7568. 61 indexed citations

5.

Wang, Yingheng, Xin Chen, Yaosen Min, & Ji Wu. (2021). MolCloze: A Unified Cloze-style Self-supervised Molecular Structure Learning Model for Chemical Property Prediction. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2896–2903. 3 indexed citations

6.

Wang, Yingheng, et al.. (2021). Molecular Graph Contrastive Learning with Parameterized Explainable Augmentations. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 1558–1563. 9 indexed citations

7.

Min, Yaosen, et al.. (2018). Learning Protein Structural Fingerprints under the Label-Free Supervision of Domain Knowledge. 69–74. 3 indexed citations

8.

Min, Yaosen, et al.. (2017). External oxidant-free cross-coupling of arylcopper and alkynylcopper reagents leading to arylalkyne. RSC Advances. 7(45). 28308–28312. 7 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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