Qi Dai

2.1k citations
98 papers · 1.4k indexed · 1 hit paper · h-index 23
Topics
Machine Learning in Bioinformatics (58 papers)RNA and protein synthesis mechanisms (33 papers)Genomics and Phylogenetic Studies (32 papers)
Partner nations
ChinaUnited StatesJapan

In The Last Decade

Qi Dai

86 papers receiving 1.4k citations

Hit Papers

Efficient assembly of nanopore reads via highly accurate ...2021202620222024202150100150200

Peers

Qi Dai
Comparison fields: 5 of 120
  • Molecular Biology 1.2k
  • Plant Science 176
  • Cancer Research 132
  • Computational Theory and Mathematics 114
  • Artificial Intelligence 91
Replace Kuo-Bin Li with:
Kuo-Bin Li Singapore
Jishou Ruan China
Andrea Pierleoni Italy
Andrew Yates United Kingdom
Harald Vöhringer Germany
Bindu Nanduri United States
Julie Nixon United States
Nadav Brandes Israel
Andy Perkins United States
Osbaldo Reséndis-Antonio Mexico
Qi Dai relative to Kuo-Bin Li Singapore Kuo-Bin Li's profile →
Citations per field
00.5×11.7×
Kuo-Bin Li · 1×
Citations per year

Countries citing papers authored by Qi Dai

Since Specialization
Citations

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

Fields of papers citing papers by Qi Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qi Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Qi Dai. A scholar is included among the top collaborators of Qi Dai 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 Qi Dai. Qi Dai 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
#WorkIndexed citations
1 0
2 0
3 0
4 3
5 0
6 0
7 2
8 3
9 24
10
A multi-granularity ensemble classification algorithm for imbalanced data
0
11 19
12 7
13 13
14 28
15 14
16
An Intefrated Semi-Random Forests Based Approach to Gene Selection for Glioma Classification
3
17 6
18 39
19 11
20 36

About Qi Dai

Qi Dai is a scholar working on Molecular Biology, Virology and Computational Theory and Mathematics, having authored 98 papers that have together received 1.4k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (58 papers), RNA and protein synthesis mechanisms (33 papers) and Genomics and Phylogenetic Studies (32 papers). The work is most often cited by research in Molecular Biology (1.2k citations), Cancer Research (132 citations) and Computational Theory and Mathematics (114 citations). Qi Dai has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Pingan He, Tianming Wang, Yuhua Yao, Xuying Nan, Lei Chen, Xiaoqing Liu, Yanchun Yang, Yaozhou Zhang, Xiaoqing Liu and Xiaoqing Liu. Their work appears in journals such as Nature Communications, Bioinformatics and PLoS ONE.

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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