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Researcher · Anhui University · China

Peng Chen

Peng Chen publishes mostly in Molecular Biology, Computer Vision and Pattern Recognition and Plant Science, on topics such as Protein Structure and Dynamics, Machine Learning in Bioinformatics and Computational Drug Discovery Methods.

ORCID 0000-0002-5810-8159 OpenAlex
World rank
#1,629,635
of 7,710,434 ranked researchers
Rank in China
#245,641
of 978,568
Works
338
Citations
6.3k
Citations per work
18.7
h-index
39
i10-index 122Top 7.8% in Molecular Biology
Peng Chen

What does Peng Chen research?

Peng Chen's work is mostly in Computer Science (23%), Biochemistry, Genetics and Molecular Biology (21%), Agricultural and Biological Sciences (6%).

Everything else: 159 works · 46.9% of their workLife Sciences: 91 works · 26.9% of their workBiochemistry, Genetics and Molecular Biology: 71 works · 21.0% of their workMolecular Biology: 71 works · 21.0% of their workAgricultural and Biological Sciences: 20 works · 5.9% of their workPlant Science: 20 works · 5.9% of their workPhysical Sciences: 89 works · 26.2% of their workComputer Science: 77 works · 22.9% of their workComputer Vision and Pattern Recognition: 44 works · 13.1% of their workArtificial Intelligence: 18 works · 5.2% of their workComputational Theory and Mathematics: 16 works · 4.6% of their workMaterials Science: 11 works · 3.3% of their workMaterials Chemistry: 11 works · 3.3% of their workTHEIR WORKPeng Chen338works
Life Sciences27%Physical Sciences26%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
  1. Everything else15946.9%
    1. Biochemistry, Genetics and Molecular Biology7121.0%
    2. Agricultural and Biological Sciences205.9%
    1. Computer Science7722.9%
    2. Materials Science113.3%
  1. 1Molecular Biology21% of their works
  2. 2Computer Vision and Pattern Recognition13% of their works
  3. 3Plant Science6% of their works
  4. 4Artificial Intelligence5% of their works
  5. 5Computational Theory and Mathematics5% of their works
  6. 6Materials Chemistry3% of their works

Research topics

Which keywords describe Peng Chen's research?

The keywords of their largest research topics: Machine Learning, Prediction, Protein, Deep Learning, Molecular Dynamics, Structure, Amino Acid Composition and Molecular Docking.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 21 words, with their numbers
  1. Machine Learning1123 topics
  2. Prediction992 topics
  3. Protein992 topics
  4. Deep Learning633 topics
  5. Molecular Dynamics561 topic
  6. Structure561 topic
  7. Amino Acid Composition431 topic
  8. Molecular Docking431 topic
  9. Subcellular Localization431 topic
  10. Virtual Screening431 topic
  11. Convolutional Neural Networks372 topics
  12. Gene Set Enrichment Analysis271 topic
  13. Protein-Protein Interaction Networks271 topic
  14. Plant Disease Detection261 topic
  15. Smart Farming261 topic
  16. Object Tracking191 topic
  17. Visual Tracking191 topic
  18. Image Recognition181 topic
  19. Object Detection181 topic
  20. Multivariate Calibration141 topic
  21. Near-Infrared Spectroscopy141 topic

Where does Peng Chen work?

Peng Chen's main affiliation in the publication record is Anhui University, China.

How many publications and citations does Peng Chen have?

OpenAlex counts 338 works and 6,323 citations for Peng Chen, an h-index of 39, ranking #1,629,635 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Other researchers named Peng Chen

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

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