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Researcher · Collaborations Pharmaceuticals (United States) · United States

Fabio Urbina

Fabio Urbina publishes mostly in Molecular Biology, Computational Theory and Mathematics and Materials Chemistry, on topics such as Computational Drug Discovery Methods, Machine Learning in Materials Science and Cellular transport and secretion.

OpenAlex
World rank
#870,337
of 7,710,434 ranked researchers
Rank in United States
#287,941
of 1,627,098
Works
70
Citations
1.3k
Citations per work
19.1
h-index
19
i10-index 29Top 36% in Molecular Biology
Fabio Urbina

What does Fabio Urbina research?

Fabio Urbina's work is mostly in Biochemistry, Genetics and Molecular Biology (26%), Computer Science (18%), Materials Science (7%).

Everything else: 26 works · 37.4% of their workLife Sciences: 23 works · 32.5% of their workBiochemistry, Genetics and Molecular Biology: 18 works · 26.2% of their workMolecular Biology: 14 works · 19.9% of their workCell Biology: 4 works · 6.3% of their workNeuroscience: 4 works · 6.3% of their workCellular and Molecular Neuroscience: 4 works · 6.3% of their workPhysical Sciences: 18 works · 25.0% of their workComputer Science: 13 works · 18.2% of their workComputational Theory and Mathematics: 13 works · 18.2% of their workMaterials Science: 5 works · 6.8% of their workMaterials Chemistry: 5 works · 6.8% of their workHealth Sciences: 4 works · 5.1% of their workMedicine: 4 works · 5.1% of their workPharmacology: 4 works · 5.1% of their workTHEIR WORKFabio Urbina70works
Life Sciences33%Physical Sciences25%Health Sciences5%

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 else2637.4%
    1. Biochemistry, Genetics and Molecular Biology1826.2%
    2. Neuroscience46.3%
    1. Computer Science1318.2%
    2. Materials Science56.8%
    1. Medicine45.1%
  1. 1Molecular Biology20% of their works
  2. 2Computational Theory and Mathematics18% of their works
  3. 3Materials Chemistry7% of their works
  4. 4Cell Biology6% of their works
  5. 5Cellular and Molecular Neuroscience6% of their works
  6. 6Pharmacology5% of their works

Research topics

Which keywords describe Fabio Urbina's research?

The keywords of their largest research topics: Machine Learning, Pharmacokinetics, Molecular Docking, Virtual Screening, High-Throughput, Materials Informatics, Genomics and Bioinformatics.

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 19 words, with their numbers
  1. Machine Learning442 topics
  2. Pharmacokinetics372 topics
  3. Molecular Docking321 topic
  4. Virtual Screening321 topic
  5. High-Throughput121 topic
  6. Materials Informatics121 topic
  7. Genomics102 topics
  8. Bioinformatics61 topic
  9. Education61 topic
  10. Endocytosis61 topic
  11. Lipid Rafts61 topic
  12. Membrane Fusion61 topic
  13. Membrane Lipids61 topic
  14. Cytochrome P45051 topic
  15. Eph receptors51 topic
  16. Pharmacogenetics51 topic
  17. Semaphorins51 topic
  18. Influenza41 topic
  19. Virus41 topic

Where does Fabio Urbina work?

Fabio Urbina's main affiliation in the publication record is Collaborations Pharmaceuticals (United States), United States.

How many publications and citations does Fabio Urbina have?

OpenAlex counts 70 works and 1,336 citations for Fabio Urbina, an h-index of 19, ranking #870,337 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.

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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