University of Groningen
Novel peptide replicators from dynamic combinatorial libraries Altay, Yigit
DOI:
10.33612/diss.90041906
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Publication date: 2019
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
Altay, Y. (2019). Novel peptide replicators from dynamic combinatorial libraries. University of Groningen. https://doi.org/10.33612/diss.90041906
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Propositions
associated with the dissertation
Novel Peptide Replicators
from Dynamic Combinatorial Libraries
by
Yi ˘git Altay
1. Propositions should be an optional component of the PhD defense.
2. Discussions on the possible outcome(s) of an experiment involving a com-plex molecular system may take longer than running the actual experiment and observing the outcome.
3. Pseudo-scientists are more dangerous than pseudo-science.
4. The number of citations that a scientist receives is a better quality indica-tor than the number of articles (s)he has published. However, neither fully reflect the quality of the work.
5. A PhD student should work in freedom and should not be under pressure of completing a certain number of chapters within four years.
6. On the way to fully understand the universe, serendipity remains as the most powerful, yet, the least credited instrument that scientists have.
7. The order of the authors in a publication does not always reflect their contri-bution. ”Author contributions” should be a compulsory part of all scientific publications in order to fairly credit each co-author.
8. In modern day science, every scientist can be an academic but every aca-demic cannot be a scientist. A scientist can be motivated just by the question itself whereas an academic looks for a publication at the end.
9. Evolution is a blind process. Defining evolution as a process of progressive complexification is as desperate as NASA missions that search exclusively for water to find extraterrestrial life. (J. Mol. Evol., 2013, 76, 185-191.)
10. Collecting data without fully understanding the experiment is poor research practice. Yet you often cannot fully understand an experiment prior to col-lecting and analysing the data.
