Danchin A. auteur aut IRD Ouzounis C. auteur aut IRD Tokuyasu T. auteur aut IRD Zucker Jean-Daniel auteur aut IRD text journalArticle eng text/pdf reformatted digital access Science and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. Discovery‐driven genome research rests on knowledge passed on via gene annotations. In response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. We argue this hinders progress through the generation and propagation of errors, leading investigators into blind alleys. More subtly, this inductive process discourages the discovery of novelty, which remains essential in biological research and reflects the nature of biology itself. Annotation systems, rather than being repositories of facts, should be tools that support multiple modes of inference. By combining deduction, induction and abduction, investigators can generate hypotheses when accurate knowledge is extracted from model databases. A key stance is to depart from 'the sequence tells the structure tells the function' fallacy, placing function first. We illustrate our approach with examples of critical or unexpected pathways, using MicroScope to demonstrate how tools can be implemented following the principles we advocate. We end with a challenge to the reader. specialized 020STAT02 084GENIG 11 4 588-605 2018 1751-7915 https://www.documentation.ird.fr/hor/fdi:010079274 10.1111/1751-7915.13284 1751-7915 [F B010079274] https://www.documentation.ird.fr/hor/fdi:010079274 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers20-08/010079274.pdf IRD - Base Horizon / Pleins textes 2020-08-14 2020-09-17 fdi:010079274 fre