Ming Hao

117 papers receiving 5.0k citations

Ming Hao's Hit Papers

DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update) 2022 · 3.2k citations
3.2k0+1+2Years since publication10002.0k3.0k

Peers

Ming Hao
Comparison fields: 5 of 196
  • Cancer Research 621
  • Computational Theory and Mathematics 577
  • Molecular Biology 2.4k
  • Computer Vision and Pattern Recognition 560
  • Signal Processing 261
Replace Ming‐Tat Ko with:
Ming‐Tat Ko Taiwan
Yanda Li China
Doheon Lee South Korea
Siu‐Ming Yiu Hong Kong
Olli Yli‐Harja Finland
Dong Xu United States
Lei Chen China
Kenneth N. Ross United States
Jun Sese Japan
Fusheng Wang United States
Ming Hao relative to Ming‐Tat Ko Taiwan Ming‐Tat Ko's profile →
Citations per field
00.5×3.6×
Ming‐Tat Ko · 1×
Citations per year

Countries citing papers authored by Ming Hao

Since Specialization
Citations

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

Fields of papers citing papers by Ming Hao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 126 papers — load more, or switch the sort, to bring in the rest.

#Work
1
DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update)
Hit paper breakdown →
20223221
2 201796
3 201988
4 200986
5 201783
6 200968
7 200761
8 200258
9 201156
10 201456
11 201356
12 202252
13 201646
14 200638
15 201137
16 201737
17 201137
18 200734
19 200234
20 201232

About Ming Hao

Ming Hao is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology, Artificial Intelligence, Signal Processing and Computational Theory and Mathematics, having authored 126 papers that have together received 5.1k indexed citations. Recurring topics across this work include Data Visualization and Analytics (40 papers), Computational Drug Discovery Methods (17 papers), Time Series Analysis and Forecasting (16 papers), Video Analysis and Summarization (10 papers), Advanced Text Analysis Techniques (10 papers), Complex Network Analysis Techniques (10 papers), Data Management and Algorithms (8 papers) and Advanced Database Systems and Queries (7 papers). The work is most often cited by research in Cancer Research (621 citations), Computational Theory and Mathematics (577 citations), Molecular Biology (2.4k citations), Computer Vision and Pattern Recognition (560 citations) and Signal Processing (261 citations). Ming Hao has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Weizhong Chang, Tomozumi Imamichi, Xiaoli Jiao, Brad T. Sherman, H. Clifford Lane, Ju Qiu, Michael Baseler, Daniel A. Keim, Umeshwar Dayal and Stephen H. Bryant. Their work appears in journals such as International Journal of Molecular Sciences, Information Visualization, Blood, Analytica Chimica Acta and Frontiers in Immunology.

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