Leyi Wei

11.5k total citations · 4 hit papers
199 papers, 8.6k citations indexed

About

Leyi Wei is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Leyi Wei has authored 199 papers receiving a total of 8.6k indexed citations (citations by other indexed papers that have themselves been cited), including 147 papers in Molecular Biology, 34 papers in Computational Theory and Mathematics and 23 papers in Artificial Intelligence. Recurrent topics in Leyi Wei's work include Machine Learning in Bioinformatics (94 papers), RNA and protein synthesis mechanisms (50 papers) and Computational Drug Discovery Methods (34 papers). Leyi Wei is often cited by papers focused on Machine Learning in Bioinformatics (94 papers), RNA and protein synthesis mechanisms (50 papers) and Computational Drug Discovery Methods (34 papers). Leyi Wei collaborates with scholars based in China, Macao and Japan. Leyi Wei's co-authors include Ran Su, Quan Zou, Pengwei Xing, Balachandran Manavalan, Jijun Tang, Shaherin Basith, Gwang Lee, Qiangguo Jin, Tae Hwan Shin and Zhaopeng Meng and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Leyi Wei

177 papers receiving 8.5k 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.

DUNet: A deformable network for retinal vessel segmentation

2019 584 citations Qiangguo Jin, Leyi Wei et al. profile →
Gene2vec: gene subsequence embedding for prediction of mammalian N⁶-methyladenosine sites from mRNA

2018 428 citations Quan Zou, Pengwei Xing et al. profile →
ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides

2018 369 citations Leyi Wei, Chen Zhou et al. Bioinformatics profile →
DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis

2023 104 citations Ruheng Wang, Junru Jin et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Leyi Wei China	48	6.8k	1.2k	870	756	751	199	8.6k
Ran Su China	38	3.5k 0.5×	676 0.6×	499 0.6×	370 0.5×	731 1.0×	105	5.5k
Jiangning Song Australia	57	8.0k 1.2×	1.0k 0.8×	725 0.8×	523 0.7×	412 0.5×	329	10.3k
Hong‐Bin Shen China	65	12.5k 1.8×	2.0k 1.6×	282 0.3×	1.0k 1.3×	787 1.0×	280	15.0k
Jijun Tang China	42	4.7k 0.7×	976 0.8×	238 0.3×	441 0.6×	503 0.7×	231	5.8k
Wei Chen China	72	15.5k 2.3×	1.3k 1.1×	771 0.9×	1.8k 2.3×	395 0.5×	483	18.4k
Lei Chen China	48	5.4k 0.8×	1.4k 1.2×	67 0.1×	1.2k 1.5×	455 0.6×	338	8.1k
Fei Guo China	38	3.7k 0.6×	820 0.7×	178 0.2×	697 0.9×	357 0.5×	278	5.3k
Tao Huang China	50	6.0k 0.9×	1.0k 0.9×	93 0.1×	1.5k 1.9×	410 0.5×	395	8.7k
Tatsuya Akutsu Japan	48	7.4k 1.1×	1.4k 1.1×	246 0.3×	390 0.5×	884 1.2×	378	9.2k
Bin Liu China	50	7.7k 1.1×	807 0.7×	417 0.5×	1.2k 1.6×	428 0.6×	165	8.9k

Countries citing papers authored by Leyi Wei

Since Specialization

Citations

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

Fields of papers citing papers by Leyi Wei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leyi Wei

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

20 of 20 papers shown

Wei, Leyi, et al.. (2025). Abductive multi-instance multi-label learning for periodontal disease classification with prior domain knowledge. Medical Image Analysis. 101. 103452–103452. 1 indexed citations

Jin, Junru, Leyi Wei, Hua Shi, et al.. (2025). MCAMEF-BERT: an efficient deep learning method for RNA N7-methylguanosine site prediction via multi-branch feature integration. Briefings in Bioinformatics. 26(5).

Li, Na, Fei Gao, Yanling Wang, et al.. (2025). GICL: A Cross-Modal Drug Property Prediction Framework Based on Knowledge Enhancement of Large Language Models. Journal of Chemical Information and Modeling. 65(11). 5518–5527.

Wei, Leyi, et al.. (2024). Enhancing energy-efficient building design: a multi-agent-assisted MOEA/D approach for multi-objective optimization. Energy Informatics. 7(1). 4 indexed citations

Wang, Ruheng, et al.. (2024). NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection. Bioinformatics. 40(2). 11 indexed citations

Fang, Yitian, et al.. (2024). CELA-MFP: a contrast-enhanced and label-adaptive framework for multi-functional therapeutic peptides prediction. Briefings in Bioinformatics. 25(4). 6 indexed citations

Zhang, Wenyu, et al.. (2024). Therapeutic peptides identification via kernel risk sensitive loss-based k-nearest neighbor model and multi-Laplacian regularization. Briefings in Bioinformatics. 25(6). 1 indexed citations

Wang, Yu, et al.. (2023). MolCAP: Molecular Chemical reActivity Pretraining and prompted-finetuning enhanced molecular representation learning. Computers in Biology and Medicine. 167. 107666–107666. 3 indexed citations

Wang, Y., Chao Pang, Yuzhe Wang, et al.. (2023). Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks. Nature Communications. 14(1). 6155–6155. 75 indexed citations

10.

Wang, Ruheng, et al.. (2023). Multi-CGAN: Deep Generative Model-Based Multiproperty Antimicrobial Peptide Design. Journal of Chemical Information and Modeling. 64(1). 316–326. 18 indexed citations

11.

Wei, Lesong, Xiucai Ye, Kai Zhang, et al.. (2022). SiameseCPP: a sequence-based Siamese network to predict cell-penetrating peptides by contrastive learning. Briefings in Bioinformatics. 24(1). 37 indexed citations

12.

Wei, Lesong, Xiucai Ye, Tetsuya Sakurai, Zengchao Mu, & Leyi Wei. (2022). ToxIBTL: prediction of peptide toxicity based on information bottleneck and transfer learning. Bioinformatics. 38(6). 1514–1524. 111 indexed citations

13.

Wei, Leyi, Wenjia He, Adeel Malik, et al.. (2020). Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework. Briefings in Bioinformatics. 22(4). 118 indexed citations

14.

Wei, Leyi, Chen Zhou, Ran Su, & Quan Zou. (2019). PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning. Bioinformatics. 35(21). 4272–4280. 155 indexed citations

15.

Li, Fuyi, Tatiana T. Marquez‐Lago, André Leier, et al.. (2019). PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact. Briefings in Bioinformatics. 21(3). 1069–1079. 33 indexed citations

16.

Manavalan, Balachandran, Shaherin Basith, Tae Hwan Shin, et al.. (2019). 4mCpred-EL: An Ensemble Learning Framework for Identification of DNA N4-Methylcytosine Sites in the Mouse Genome. Cells. 8(11). 1332–1332. 83 indexed citations

17.

Su, Ran, et al.. (2019). Fusing convolutional neural network features with hand-crafted features for osteoporosis diagnoses. Neurocomputing. 385. 300–309. 48 indexed citations

18.

Wei, Leyi, et al.. (2018). ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides. Bioinformatics. 34(23). 4007–4016. 369 indexed citations breakdown →

19.

Wei, Leyi, Pengwei Xing, Jijun Tang, & Quan Zou. (2017). PhosPred-RF: A Novel Sequence-Based Predictor for Phosphorylation Sites Using Sequential Information Only. IEEE Transactions on NanoBioscience. 16(4). 240–247. 104 indexed citations

20.

Wei, Leyi, Pengwei Xing, Ran Su, et al.. (2017). CPPred-RF: A Sequence-based Predictor for Identifying Cell-Penetrating Peptides and Their Uptake Efficiency. Journal of Proteome Research. 16(5). 2044–2053. 176 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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