Depeng Wang

7.1k total citations · 4 hit papers
46 papers, 2.8k citations indexed

About

Depeng Wang is a scholar working on Molecular Biology, Genetics and Ecology. According to data from OpenAlex, Depeng Wang has authored 46 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 8 papers in Genetics and 7 papers in Ecology. Recurrent topics in Depeng Wang's work include Genomics and Phylogenetic Studies (8 papers), RNA modifications and cancer (8 papers) and Chromosomal and Genetic Variations (5 papers). Depeng Wang is often cited by papers focused on Genomics and Phylogenetic Studies (8 papers), RNA modifications and cancer (8 papers) and Chromosomal and Genetic Variations (5 papers). Depeng Wang collaborates with scholars based in China, United States and Denmark. Depeng Wang's co-authors include Chuan‐Le Xiao, Fan Liang, Guoliang Yu, Kai Wang, Feng Luo, Fang Li, Yingfeng Zheng, Shuang Xie, Qian Liu and Jianxin Wang and has published in prestigious journals such as Nature Communications, Molecular Cell and Bioinformatics.

In The Last Decade

Depeng Wang

45 papers receiving 2.8k citations

Hit Papers

Immune cell profiling of COVID-19 patients in the recover... 2018 2026 2020 2023 2020 2018 2021 2024 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Depeng Wang China 25 1.7k 544 453 359 228 46 2.8k
Chuan‐Le Xiao China 25 2.2k 1.2× 540 1.0× 474 1.0× 283 0.8× 265 1.2× 57 3.2k
Alan Bridge Switzerland 23 3.1k 1.8× 400 0.7× 297 0.7× 458 1.3× 341 1.5× 44 4.1k
Lu Yu United Kingdom 36 3.1k 1.8× 956 1.8× 417 0.9× 387 1.1× 378 1.7× 127 4.9k
Jingwen Bai China 5 2.7k 1.6× 349 0.6× 188 0.4× 336 0.9× 472 2.1× 6 4.4k
Shengbo Wang United Kingdom 5 2.7k 1.6× 306 0.6× 189 0.4× 336 0.9× 472 2.1× 6 4.3k
Suresh Hewapathirana United Kingdom 2 2.7k 1.5× 307 0.6× 188 0.4× 335 0.9× 472 2.1× 6 4.3k
Chakradhar Bandla United Kingdom 4 2.7k 1.6× 306 0.6× 188 0.4× 336 0.9× 472 2.1× 6 4.3k
Deepti J Kundu United Kingdom 6 2.7k 1.6× 306 0.6× 188 0.4× 335 0.9× 473 2.1× 9 4.4k
Selvakumar Kamatchinathan United Kingdom 3 2.7k 1.5× 306 0.6× 188 0.4× 335 0.9× 472 2.1× 5 4.3k
James J. Cai United States 32 1.7k 1.0× 442 0.8× 1.1k 2.4× 463 1.3× 231 1.0× 112 3.7k

Countries citing papers authored by Depeng Wang

Since Specialization
Citations

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

Fields of papers citing papers by Depeng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Depeng Wang

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

All Works

20 of 20 papers shown
1.
Hu, Jiang, Zhuo Wang, Fan Liang, et al.. (2024). NextPolish2: A Repeat-aware Polishing Tool for Genomes Assembled Using HiFi Long Reads. Genomics Proteomics & Bioinformatics. 22(1). 31 indexed citations
2.
Hu, Jiang, Zhuo Wang, Zongyi Sun, et al.. (2024). NextDenovo: an efficient error correction and accurate assembly tool for noisy long reads. Genome biology. 25(1). 107–107. 154 indexed citations breakdown →
3.
Zhou, Zhongyun, et al.. (2024). Factors influencing seniors’ switching to m-government services: A mixed-methods study through the lens of push-pull-mooring framework. Information & Management. 61(3). 103928–103928. 10 indexed citations
4.
Zheng, Xiulin, Jie Li, Yixin Ouyang, et al.. (2024). Ecological linkages between top-down designed benzothiazole-degrading consortia and selection strength: From performance to community structure and functional genes. Water Research. 267. 122491–122491. 2 indexed citations
5.
Zhang, Yang, Depeng Wang, Xiaoliang Lin, et al.. (2022). Immune-Enhancing Activity of Compound Polysaccharide on the Inactivated Influenza Vaccine. SSRN Electronic Journal. 2 indexed citations
6.
Wang, Depeng, et al.. (2022). Immunohistochemical staining of LEF-1 is a useful marker for distinguishing WNT-activated medulloblastomas. Diagnostic Pathology. 17(1). 69–69. 5 indexed citations
7.
Chen, Ying, Fan Nie, Shuang Xie, et al.. (2021). Efficient assembly of nanopore reads via highly accurate and intact error correction. Nature Communications. 12(1). 60–60. 239 indexed citations breakdown →
8.
Geng, Chang, et al.. (2021). Sequence and Structure Characteristics of 22 Deletion Breakpoints in Intron 44 of the DMD Gene Based on Long-Read Sequencing. Frontiers in Genetics. 12. 638220–638220. 10 indexed citations
9.
Yan, Yi, Ke Wu, Jun Chen, et al.. (2021). Rapid Acquisition of High-Quality SARS-CoV-2 Genome via Amplicon-Oxford Nanopore Sequencing. Virologica Sinica. 36(5). 901–912. 16 indexed citations
11.
Fan, Xiaoying, Yuhan Liao, Pidong Li, et al.. (2020). Single-cell RNA-seq analysis of mouse preimplantation embryos by third-generation sequencing. PLoS Biology. 18(12). e3001017–e3001017. 58 indexed citations
12.
Ni, Peng, Neng Huang, Zhi Zhang, et al.. (2019). DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning. Bioinformatics. 35(22). 4586–4595. 166 indexed citations
13.
Dai, Yi, Pidong Li, Zhiqiang Wang, et al.. (2019). Single-molecule optical mapping enables quantitative measurement of D4Z4 repeats in facioscapulohumeral muscular dystrophy (FSHD). Journal of Medical Genetics. 57(2). 109–120. 47 indexed citations
14.
Xiao, Chuan‐Le, Song Zhu, Minghui He, et al.. (2018). N6-Methyladenine DNA Modification in the Human Genome. Molecular Cell. 71(2). 306–318.e7. 379 indexed citations breakdown →
15.
Liu, Qian, Peng Zhang, Depeng Wang, Weihong Gu, & Kai Wang. (2017). Interrogating the “unsequenceable” genomic trinucleotide repeat disorders by long-read sequencing. Genome Medicine. 9(1). 65–65. 59 indexed citations
16.
Ning, Guogui, Xu Cheng, Ping Luo, et al.. (2017). Hybrid sequencing and map finding (HySeMaFi): optional strategies for extensively deciphering gene splicing and expression in organisms without reference genome. Scientific Reports. 7(1). 43793–43793. 23 indexed citations
17.
Liu, Zhengwei, Yuping Liu, Jing Kuang, et al.. (2016). Construction of a high-density, high-quality genetic map of cultivated lotus (Nelumbo nucifera) using next-generation sequencing. BMC Genomics. 17(1). 466–466. 24 indexed citations
18.
Li, Hongge, Songchang Guo, Yongming Ren, et al.. (2013). VEGF 189 Expression Is Highly Related to Adaptation of the Plateau Pika ( Ochotona curzoniae ) Inhabiting High Altitudes. High Altitude Medicine & Biology. 14(4). 395–404. 19 indexed citations
19.
Liu, Dongbo, Jing Gong, Wenkui Dai, et al.. (2012). The Genome of Ganderma lucidum Provide Insights into Triterpense Biosynthesis and Wood Degradation. PLoS ONE. 7(5). e36146–e36146. 85 indexed citations
20.
Ren, Yongming, Songchang Guo, Long Cheng, et al.. (2008). The protein level of hypoxia‐inducible factor‐1α is increased in the plateau pika (Ochotona curzoniae) inhabiting high altitudes. Journal of Experimental Zoology Part A Ecological Genetics and Physiology. 311A(2). 134–141. 28 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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