Work from our group has been recognised in the
PLoS Computational Biology 2017 Research Prizes.
SCOTTI, which infers transmission routes from genetic and epidemiological information,
won the Breakthrough in Advance/Innovation category. The citation reads
Our Breakthrough Advance/Innovation
winning article presents a new computational tool, called SCOTTI
(Structured COalescent Transmission Tree Inference), developed by Nicola De Maio
of the University of Oxford (UK), and colleagues. De Maio says, “SCOTTI
represents a convenient tool to reconstruct who-infected-whom within
outbreaks… [and] has been used in particular for the study of bacterial
hospital outbreaks”. It combines epidemiological information about
patient exposure with genetic information about the infectious agent
itself.
Work is nominated and selected as described in the announcement:
The journal invited the community to nominate their favorite 2016 published Research Articles. From these nominations the PLOS Computational Biology Research Prize Committee, made up of Editorial Board members Dina Schneidman, Nicola Segata, Maricel Kann, Isidore Rigoutsos, Avner Schlessinger, Lilia Iakoucheva, Ilya Ioshikhes, Shi-Jie Chen, and Becca Asquith,
selected the winners. To help support future work, the authors of each
winning paper will receive award certificates and a $2,000 (USD) prize.
You can
read more about SCOTTI and the accompanying paper, written by Nicola De Maio, Jessie Wu and me, here.
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