@article{fdi:010079274,
  title = {{N}o wisdom in the crowd : genome annotation in the era of big data - current status and future prospects},
  author = {{D}anchin, {A}. and {O}uzounis, {C}. and {T}okuyasu, {T}. and {Z}ucker, {J}ean-{D}aniel},
  editor = {},
  language = {{ENG}},
  abstract = {{S}cience and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. {D}iscovery‐driven genome research rests on knowledge passed on via gene annotations. {I}n response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. {W}e argue this hinders progress through the generation and propagation of errors, leading investigators into blind alleys. {M}ore subtly, this inductive process discourages the discovery of novelty, which remains essential in biological research and reflects the nature of biology itself. {A}nnotation systems, rather than being repositories of facts, should be tools that support multiple modes of inference. {B}y 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. {W}e illustrate our approach with examples of critical or unexpected pathways, using {M}icro{S}cope to demonstrate how tools can be implemented following the principles we advocate. {W}e end with a challenge to the reader.},
  keywords = {},
  booktitle = {},
  journal = {{M}icrobial {B}iotechnology},
  volume = {11},
  numero = {4},
  pages = {588--605},
  ISSN = {1751-7915},
  year = {2018},
  DOI = {10.1111/1751-7915.13284 },
  URL = {https://www.documentation.ird.fr/hor/fdi:010079274},
}