@article{fdi:010084636,
  title = {{C}ontribution of genome-scale metabolic modelling to niche theory},
  author = {{R}egimbeau, {A}. and {B}udinich, {M}. and {L}arhlimi, {A}. and {K}arlusich, {J}. {J}. {P}. and {A}umont, {O}livier and {M}emery, {L}. and {B}owler, {C}. and {E}veillard, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{S}tandard niche modelling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome-scale descriptions of these organisms. {T}his study overcomes this shortcoming by proposing a new conceptual niche that resumes the whole metabolic capabilities of an organism. {T}he so-called metabolic niche resumes well-known traits such as nutrient needs and their dependencies for survival. {D}espite the computational challenge, its implementation allows the detection of traits and the formal comparison of niches of different organisms, emphasising that the presence-absence of functional genes is not enough to approximate the phenotype. {F}urther statistical exploration of an organism's niche sheds light on genes essential for the metabolic niche and their role in understanding various biological experiments, such as transcriptomics, paving the way for incorporating better genome-scale description in ecological studies.},
  keywords = {marine ecology ; metabolic network ; metabolic niche ; microbial ecology ; molecular ecology ; niche modelling},
  booktitle = {},
  journal = {{E}cology {L}etters},
  volume = {[{E}arly access]},
  numero = {},
  pages = {[13 p.]},
  ISSN = {1461-023{X}},
  year = {2022},
  DOI = {10.1111/ele.13954},
  URL = {https://www.documentation.ird.fr/hor/fdi:010084636},
}