Danny T. Huang

3.8k citations
49 papers · 2.8k indexed · 1 hit paper · h-index 22
  • Oncology top 2%
    • Cancer-related Molecular Pathways 14
    • Peptidase Inhibition and Analysis 6
    • Ubiquitin and proteasome pathways 32
    • Protein Degradation and Inhibitors 9
    • Glycosylation and Glycoproteins Research 8
    • Biochemical and Molecular Research 6
    • Cancer-related gene regulation 4
    • Autophagy in Disease and Therapy 7

Danny T. Huang

44 papers receiving 2.8k citations

Hit Papers

Structural insights into the catalysis and regulation of ...4842016202620192022100200300400

Peers

Danny T. Huang
Comparison fields: 5 of 92
  • Oncology 1.1k
  • Molecular Biology 2.5k
  • Cell Biology 333
  • Epidemiology 566
  • Parasitology 103
Replace Tycho E.T. Mevissen with:
Tycho E.T. Mevissen United Kingdom
Daniel C. Scott United States
Mark P.A. Luna‐Vargas Netherlands
Paul J. Galardy United States
Ivo A. Hendriks Denmark
Francisca E. Reyes‐Turcu United States
Matthew D. Petroski United States
Wolfgang Heinemeyer Germany
P.R. Elliott United Kingdom
Jianyuan Luo United States
Danny T. Huang relative to Tycho E.T. Mevissen United Kingdom Tycho E.T. Mevissen's profile →
Citations per field
00.5×1.6×
Tycho E.T. Mevissen · 1×
Citations per year

Countries citing papers authored by Danny T. Huang

Since Specialization
Citations

This map shows the geographic impact of Danny T. 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 Danny T. Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danny T. Huang more than expected).

Fields of papers citing papers by Danny T. Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20252
3 20250
4 20240
5 202412
6 20247
7 20234
8 202230
9 20225
10 20218
11 20212
12 202067
13 202055
14 202028
15 20189
16 201815
17 201753
18 201615
19 201617
20 2003225

About Danny T. Huang

Danny T. Huang is a scholar working on Oncology, Molecular Biology and Physiology, having authored 49 papers that have together received 2.8k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (32 papers), Cancer-related Molecular Pathways (14 papers), Protein Degradation and Inhibitors (9 papers), Glycosylation and Glycoproteins Research (8 papers), Autophagy in Disease and Therapy (7 papers), Biochemical and Molecular Research (6 papers), Peptidase Inhibition and Analysis (6 papers) and Cancer-related gene regulation (4 papers). The work is most often cited by research in Oncology (1.1k citations), Molecular Biology (2.5k citations) and Cell Biology (333 citations). Danny T. Huang has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Lori Buetow, Brenda A. Schulman, Gary Sibbet, Hao Dou, James M. Holton, Kenneth Cameron, Min Zhuang, David M. Duda, David W. Miller and Helen Walden. Their work appears in journals such as Nature, Nucleic Acids Research and Journal of Biological Chemistry.

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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