Ke Hao

158 papers receiving 5.2k citations

Hit Papers

Opportunities and challenges for transcriptome-wide association studies 2019 · 506 citations
5062017202620202023100200300400500

Peers

Ke Hao
Comparison fields: 5 of 178
  • Health, Toxicology and Mutagenesis 898
  • Obstetrics and Gynecology 362
  • Cancer Research 684
  • Genetics 1.1k
  • Reproductive Medicine 290
Replace Luca Chiovato with:
Luca Chiovato Italy
Weiqing Wang China
Weiping Teng China
Jia Chen United States
Joshua N. Sampson United States
Daehee Kang South Korea
Abbas Dehghan Netherlands
Salvatore Benvenga Italy
Marina Sirota United States
Liming Liang United States
Ke Hao relative to Luca Chiovato Italy Luca Chiovato's profile →
Citations per field
00.5×1.5×2.3×
Luca Chiovato · 1×
Citations per year

Countries citing papers authored by Ke Hao

Since Specialization
Citations

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

Fields of papers citing papers by Ke Hao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 163 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Opportunities and challenges for transcriptome-wide association studies
Hit paper breakdown →
2019506
2
Particulate Matter Exposure and Stress Hormone Levels
Hit paper breakdown →
2017383
3 2005238
4 2010207
5 2009203
6 1993160
7 2015142
8 2020121
9 2021120
10 2017118
11 2016115
12 2017113
13 2009107
14 201296
15 201974
16 200474
17 201174
18 202173
19 201867
20 201566

About Ke Hao

Ke Hao is a scholar working on Health, Toxicology and Mutagenesis, Obstetrics and Gynecology, Pediatrics, Perinatology and Child Health, Behavioral Neuroscience and Cancer Research, having authored 163 papers that have together received 5.3k indexed citations. Recurring topics across this work include Birth, Development, and Health (26 papers), Genetic Associations and Epidemiology (20 papers), Air Quality and Health Impacts (19 papers), Epigenetics and DNA Methylation (13 papers), Pregnancy and preeclampsia studies (11 papers), Gene expression and cancer classification (10 papers), Heavy Metal Exposure and Toxicity (9 papers) and Bioinformatics and Genomic Networks (8 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (898 citations), Obstetrics and Gynecology (362 citations), Cancer Research (684 citations), Genetics (1.1k citations) and Reproductive Medicine (290 citations). Ke Hao has collaborated with scholars based in United States, China and Sweden. Frequent co-authors include Eric E. Schadt, Carmen J. Marsit, Jia Chen, Johan Björkegren, W. N. Lipscomb, Yuh Min Chook, Ting Yang, Zhongyang Zhang, Arno Ruusalepp and Maya A. Deyssenroth. Their work appears in journals such as Environmental Science & Technology, Scientific Reports, Nature Communications, Environmental Research and Environment International.

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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