Eric Huang

12.8k citations
99 papers · 10.0k indexed · 5 hit papers · h-index 38
    • Cancer, Hypoxia, and Metabolism 48
    • RNA modifications and cancer 11
    • Mitochondrial Function and Pathology 11
    • Epigenetics and DNA Methylation 9
  • Physiology top 1%
  • Biochemistry top 0.5%
  • Genetics top 1%
    • Glioma Diagnosis and Treatment 10
    • High Altitude and Hypoxia 9
    • Cancer-related Molecular Pathways 11
    • Advanced Proteomics Techniques and Applications 6

Eric Huang

96 papers receiving 9.8k citations

Hit Papers

HIF‐1α induces cell cycle arrest by functionally countera...507199620262006201650010001.5k

Peers

Eric Huang
Comparison fields: 5 of 145
  • Cancer Research 6.1k
  • Molecular Biology 6.2k
  • Physiology 1.7k
  • Biochemistry 466
  • Genetics 1.4k
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Citations per field
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Citations per year

Countries citing papers authored by Eric Huang

Since Specialization
Citations

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

Fields of papers citing papers by Eric Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20260
2 20250
3 20250
4 202410
5 202016
6 201742
7 201618
8 201660
9 201518
10 201416
11 201136
12 201128
13
Entity-Based Relevance Feedback for Genomic List Answer Retrieval.
200713
14 200749
15 20072
16 2005279
17 200528
18 2001251
19 2001111
20 1998155

About Eric Huang

Eric Huang is a scholar working on Cancer Research, Aging and Molecular Biology, having authored 99 papers that have together received 10.0k indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (48 papers), Cancer-related Molecular Pathways (11 papers), RNA modifications and cancer (11 papers), Mitochondrial Function and Pathology (11 papers), Glioma Diagnosis and Treatment (10 papers), Epigenetics and DNA Methylation (9 papers), High Altitude and Hypoxia (9 papers) and Advanced Proteomics Techniques and Applications (6 papers). The work is most often cited by research in Cancer Research (6.1k citations), Molecular Biology (6.2k citations) and Physiology (1.7k citations). Eric Huang has collaborated with scholars based in United States, Canada and China. Frequent co-authors include H. Franklin Bunn, Jie Gu, H. Franklin Bunn, Zoltàn Arany, David M. Livingston, Minori Koshiji, Michael A. Hoffman, Michael Ohh, William G. Kaelin and Nikola P. Pavletich. Their work appears in journals such as Journal of Biological Chemistry, Journal of Proteome Research, Proceedings of the National Academy of Sciences, Oncogene and Journal of the American Chemical Society.

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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