University of Groningen
Bacterial protein sorting: experimental and computational approaches Grasso, Stefano
DOI:
10.33612/diss.150510580
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Publication date: 2020
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Grasso, S. (2020). Bacterial protein sorting: experimental and computational approaches. University of Groningen. https://doi.org/10.33612/diss.150510580
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Propositions accompanying the thesis
BACTERIAL PROTEIN SORTING: EXPERIMENTAL AND COMPUTATIONAL APPROACHES
1. Biotechnological exploitation of living (micro-)organisms has started some millennia ago, probably as a cause or as a consequence of the development of agriculture and the domestication of animals. (Chapter 1)
2. With respect to usability and parsability, a paradigm shift in the development of subcellular protein localization predictors is needed. (Chapter 2)
3. A key aspect demanded by all users of expert system predictors for subcellular protein localization is a high interpretability of the results. (Chapter 2)
4. The protein sorting ambiguities encountered in silico are perhaps an unintended reflection of the imperfections of sorting systems employed by a bacterial cell in vivo but, as long as these imperfections have no bearing on the competitive success of a bacterium, they do not matter. (Chapter 3)
5. Knowledge of the sub-cellular localization of bacterial proteins can provide valuable insights into protein functions, especially in relation to colonization of the host, fitness and virulence. (Chapter 4)
6. By both quantifying the impact of signal peptide features on secretion efficiency, and predicting the efficiency of designed and pseudo-random signal peptides, a Design-Build-Test-Learn (DBTL) cycle can be devised to define critical signal peptide features (Chapter 5)
7. When models are generated through machine learning methods, the “learning” step belongs to the machine (i.e. the machine learning model) and not to the human operator, causing an actual loss of knowledge and understanding. (Chapter 7)
8. “Indeed, in science (as in philosophy), defining a term or concept is an essential prerequisite to developing coherent, logical and rational thinking.” (Desvaux et al., Secretion and subcellular localizations of bacterial proteins: a semantic awareness issue. Trends Microbiol 2009)
9. “The strong version of the motto ‘from sequence to structure to function’ directly leads to intelligent design while, by stark contrast, the proper annotation of gene sequences must start with a first constructive principle of no intelligent design in Biology.” (Based on Danchin et al., No wisdom in the crowd: genome annotation in the era of big data - current status and future prospects. Microb Biotechnol 2018).
10. “We are survival machines - robot vehicles blindly programmed to preserve the selfish molecules known as genes” (Dawkins, Preface of ‘The selfish gene’).
11. “This is what the distinction between ‘formal’ and ‘actual’ freedom ultimately amounts to: the former refers to freedom of choice within the coordinates of the existing power relations, while the latter designates the site of an intervention that undermines these very coordinates.” (Žižek, ‘Lenin 2017: Remembering, Repeating, and Working Through’)
12. “Cercate di guardare tutte le ricette, compreso quelle che fate da anni, con spirito scientifico. Non date mai nulla per scontato, non fidatevi troppo degli insegnamenti della tradizione e chiedetevi sempre il perché di certe prescrizioni” (Bressanini, Introduzione of ‘La scienza in
cucina’). / “Try to look at all recipes, including those you have prepared for years, with scientific
spirit. Don’t ever take anything for granted, don’t trust too much the teachings of traditions, and always ask yourself the reason of certain recommendations.” (Bressanini, Introduction of ‘La
scienza in cucina’).
Groningen, 16th December 2020 Stefano Grasso
