Daniel Biass

502 citations
10 papers · 445 · h-index 10

Impact in

  • Microbiology top 10%
    • Antimicrobial Peptides and Activities
  • Paleontology top 10%
    • Marine Invertebrate Physiology and Ecology

Papers in

    • Nicotinic Acetylcholine Receptors Study 10
    • Ion channel regulation and function 4
    • Receptor Mechanisms and Signaling 3
    • Chemical Synthesis and Analysis 3
    • Antimicrobial Peptides and Activities 4

Daniel Biass

10 papers receiving 432 citations

Peers

Daniel Biass
Comparison fields: 5 of 50
  • Microbiology 61
  • Paleontology 42
  • Molecular Biology 360
  • Genetics 104
  • Insect Science 33
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Carolina Möller United States
Edgar P. Heimer de la Cotera Mexico
Zhigui Duan China
Marie France Martin-Eauclaire France
Liesl C. Birinyi-Strachan Australia
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Michelle J. Little Australia
Maik Damm Germany
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Biass

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Biass

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 201173
2 200971
3 201269
4 201069
5 201243
6 201330
7 201229
8 201228
9 201417
10 201416

About Daniel Biass

Daniel Biass is a scholar working on Molecular Biology, Microbiology, Cellular and Molecular Neuroscience, Spectroscopy and Genetics, having authored 10 papers that have together received 445 indexed citations. Recurring topics across this work include Nicotinic Acetylcholine Receptors Study (10 papers), Ion channel regulation and function (4 papers), Antimicrobial Peptides and Activities (4 papers), Receptor Mechanisms and Signaling (3 papers), Chemical Synthesis and Analysis (3 papers), Mass Spectrometry Techniques and Applications (2 papers), Neuropeptides and Animal Physiology (1 paper) and Venomous Animal Envenomation and Studies (1 paper). The work is most often cited by research in Microbiology (61 citations), Paleontology (42 citations), Molecular Biology (360 citations), Genetics (104 citations) and Insect Science (33 citations). Daniel Biass has collaborated with scholars based in Switzerland, France and Belgium. Frequent co-authors include Reto Stöcklin, Philippe Favreau, Sébastien Dutertre, David Piquemal, Aude Violette, Yves Terrat, Frédéric Ducancel, Jean‐Louis Menou, Robin E. Offord and Adrijana Leonardi. Their work appears in journals such as Journal of Proteome Research, Journal of Proteomics, Toxicon, Journal of Chromatography A 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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