Bing Leng

87 papers receiving 788 citations

Peers

Bing Leng
Comparison fields: 5 of 127
  • Biological Psychiatry 18
  • Molecular Medicine 30
  • Applied Microbiology and Biotechnology 9
  • Computer Networks and Communications 113
  • Neurology 56
Replace Boxun Zhang with:
Boxun Zhang China
Jin-Il Kim South Korea
Xijun Chen China
Ying Ye China
Manish Sharma India
Junlin Zhang China
Jichang Li China
Qimin Zhang China
Martin Novotný Czechia
Hyun-Seok Kim South Korea
Bing Leng relative to Boxun Zhang China Boxun Zhang's profile →
Citations per field
00.5×
Boxun Zhang · 1×
Citations per year

Countries citing papers authored by Bing Leng

Since Specialization
Citations

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

Fields of papers citing papers by Bing Leng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bing Leng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bing Leng Line = papers co-authored together Bing Leng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022106
2 201650
3 202246
4 201440
5 202031
6 202231
7 202128
8 202227
9 201926
10 201723
11 201522
12 202119
13 199717
14 202217
15 202216
16 199616
17 201715
18 199414
19 201513
20 202311

About Bing Leng

Bing Leng is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Molecular Biology, Information Systems and Artificial Intelligence, having authored 91 papers that have together received 813 indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (7 papers), Antibiotics Pharmacokinetics and Efficacy (6 papers), Obstructive Sleep Apnea Research (6 papers), Software-Defined Networks and 5G (6 papers), Network Security and Intrusion Detection (5 papers), Data Mining Algorithms and Applications (4 papers), Cooperative Communication and Network Coding (4 papers) and Pneumocystis jirovecii pneumonia detection and treatment (4 papers). The work is most often cited by research in Biological Psychiatry (18 citations), Molecular Medicine (30 citations), Applied Microbiology and Biotechnology (9 citations), Computer Networks and Communications (113 citations) and Neurology (56 citations). Bing Leng has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Xike Gao, Hairong Sun, Liusheng Huang, Dong Ruan, Kwong Ming Tse, Jinbiao Zhang, Yongsheng Li, Lina Fu, Hongli Xu and Wei‐Min Shen. Their work appears in journals such as Frontiers in Pharmacology, Chinese Chemical Letters, Journal of Alzheimer s Disease, Biomedical Signal Processing and Control and Bell Labs Technical Journal.

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.

Explore authors with similar magnitude of impact