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We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genomescale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curateddoi:10.1371/journal.pcbi.1003465 pmid:24516375 pmcid:PMC3916221 fatcat:p23xv7hrmne6leo2c4k32cehb4