Chao Dai

78 papers receiving 2.9k citations

Chao Dai's Hit Papers

HiChIP: efficient and sensitive analysis of protein-directed genome architecture 2016 · 685 citations
6850+3+6Years since publication200400600

Peers

Chao Dai
Comparison fields: 5 of 146
  • Water Science and Technology 412
  • Ocean Engineering 350
  • Molecular Biology 1.5k
  • Global and Planetary Change 315
  • Industrial and Manufacturing Engineering 123
Replace Li Zeng with:
Li Zeng China
Xiaoling Sun China
Günther Fischer Germany
Yongbo Liu China
Tingxi Liu China
Magnus Persson Sweden
Bai Zhang China
Agnès Bégué France
Iain Brown United Kingdom
Huili Chen China
Chao Dai relative to Li Zeng China Li Zeng's profile →
Citations per field
00.5×2.9×
Li Zeng · 1×
Citations per year

Countries citing papers authored by Chao Dai

Since Specialization
Citations

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

Fields of papers citing papers by Chao Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chao Dai, 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 Chao Dai Line = papers co-authored together Chao Dai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1
HiChIP: efficient and sensitive analysis of protein-directed genome architecture
Hit paper breakdown →
2016685
2 2010220
3 2012219
4 2015172
5 2016133
6 2014126
7 201199
8 201888
9 201882
10 201365
11 201961
12 201854
13 201443
14 201338
15 201635
16 201735
17 201233
18 201932
19 201531
20 201629

About Chao Dai

Chao Dai is a scholar working on Ocean Engineering, Water Science and Technology, Molecular Biology, Global and Planetary Change and Management Science and Operations Research, having authored 85 papers that have together received 2.9k indexed citations. Recurring topics across this work include Water resources management and optimization (28 papers), Hydrology and Watershed Management Studies (16 papers), Water-Energy-Food Nexus Studies (12 papers), Genomics and Chromatin Dynamics (8 papers), Climate variability and models (5 papers), Water Systems and Optimization (5 papers), Flood Risk Assessment and Management (5 papers) and Optimization and Mathematical Programming (5 papers). The work is most often cited by research in Water Science and Technology (412 citations), Ocean Engineering (350 citations), Molecular Biology (1.5k citations), Global and Planetary Change (315 citations) and Industrial and Manufacturing Engineering (123 citations). Chao Dai has collaborated with scholars based in China, Singapore and Canada. Frequent co-authors include William J. Greenleaf, Maxwell R. Mumbach, Howard Y. Chang, Paul A. Khavari, Ryan A. Flynn, Adam J. Rubin, Xianghong Jasmine Zhou, Xiaosheng Qin, Yanpeng Cai and Guohe Huang. Their work appears in journals such as Journal of Hydrology, Ecological Indicators, Energy, Nucleic Acids Research and Ecological Engineering.

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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