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Researcher · Selventa (United States) · United States

David de Graaf

David de Graaf publishes mostly in Molecular Biology, Oncology and Computational Theory and Mathematics, on topics such as Computational Drug Discovery Methods, Bioinformatics and Genomic Networks and Gene Regulatory Network Analysis.

OpenAlex
World rank
#1,317,032
of 7,710,434 ranked researchers
Rank in United States
#418,367
of 1,627,098
Works
28
Citations
1.4k
Citations per work
51.2
h-index
12
i10-index 14Top 65% in Molecular Biology
David de Graaf

What does David de Graaf research?

David de Graaf's work is mostly in Biochemistry, Genetics and Molecular Biology (34%), Medicine (19%), Computer Science (10%).

Life Sciences: 13 works · 45.1% of their workBiochemistry, Genetics and Molecular Biology: 9 works · 33.8% of their workMolecular Biology: 9 works · 33.8% of their workImmunology and Microbiology: 2 works · 7.5% of their workImmunology: 2 works · 7.5% of their workPharmacology, Toxicology and Pharmaceutics: 1 works · 3.8% of their workPharmacology: 1 works · 3.8% of their workEverything else: 7 works · 26.1% of their workHealth Sciences: 5 works · 18.8% of their workMedicine: 5 works · 18.8% of their workOncology: 4 works · 13.8% of their workPublic Health, Environmental and Occupational Health: 1 works · 5.0% of their workPhysical Sciences: 3 works · 10.0% of their workComputer Science: 3 works · 10.0% of their workComputational Theory and Mathematics: 3 works · 10.0% of their workTHEIR WORKDavid de Graaf28works
Life Sciences45%Physical Sciences10%Health Sciences19%

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. Biochemistry, Genetics and Molecular Biology933.8%
    2. Immunology and Microbiology27.5%
    3. Pharmacology, Toxicology and Pharmaceutics13.8%
  2. Everything else726.1%
    1. Medicine518.8%
    1. Computer Science310.0%
  1. 1Molecular Biology34% of their works
  2. 2Oncology14% of their works
  3. 3Computational Theory and Mathematics10% of their works
  4. 4Immunology8% of their works
  5. 5Public Health, Environmental and Occupational Health5% of their works
  6. 6Pharmacology4% of their works

Research topics

Which keywords describe David de Graaf's research?

The keywords of their largest research topics: Machine Learning, Molecular Docking, Virtual Screening, Bioinformatics, Gene Set Enrichment Analysis, Protein-Protein Interaction Networks, Gene Regulatory Networks and Stochastic Gene Expression.

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.

All 18 words, with their numbers
  1. Machine Learning122 topics
  2. Molecular Docking81 topic
  3. Virtual Screening81 topic
  4. Bioinformatics62 topics
  5. Gene Set Enrichment Analysis61 topic
  6. Protein-Protein Interaction Networks61 topic
  7. Gene Regulatory Networks51 topic
  8. Stochastic Gene Expression51 topic
  9. ATP-dependent Transporters41 topic
  10. Gene Expression41 topic
  11. Microarray41 topic
  12. Multidrug Resistance41 topic
  13. Acute Lymphoblastic Leukemia31 topic
  14. BRAF gene31 topic
  15. Childhood Cancer31 topic
  16. MAP Kinase31 topic
  17. Education21 topic
  18. Training21 topic

Where does David de Graaf work?

David de Graaf's main affiliation in the publication record is Selventa (United States), United States.

How many publications and citations does David de Graaf have?

OpenAlex counts 28 works and 1,434 citations for David de Graaf, an h-index of 12, ranking #1,317,032 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised 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.

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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