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Announcing the PLOS Computational Biology Research Prize Collection


As this year’s nominations draw to a close, we are excited to announce the launch of our PLOS Computational Biology Research Prize collection! Our PLOS Computational Biology Research Prize program launched in 2017 with the aim of recognizing some of the journal’s most outstanding Research Articles published the previous year in the following three prize categories: Breakthrough Advance/Innovation, Exemplary Methods/Software, and Public Impact. With this collection we hope to further highlight our past winners.

While we wait to find out the recipients of our 2018 prize, you can find our previous winning articles in the new collection. Our 2017 winners, selected from papers published in 2016, include three studies spanning diverse fields ranging from advanced research in disease transmission to microbiome analysis and epidemic forecasts.


Breakthrough in Advance/Innovation

SCOTTI: Efficient Reconstruction of Transmission within Outbreaks with the Structured Coalescent

Authors: Nicola De Maio, Chieh-Hsi Wu, Daniel J. Wilson


Exemplary Methods/Software

MEGAN Community Edition – Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data

Authors: Daniel H. Huson, Sina Beier, Isabell Flade, Anna Górska, Mohamed El-Hadidi, Suparna Mitra, Hans-Joachim Ruscheweyh, Rewati Tappu


Public Impact

Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks

Authors: Robin N. Thompson, Christopher A. Gilligan, Nik J. Cunniffe


Corresponding author Robin Thompson, winner of our 2017 Public Impact category, is continuing his research on mathematical epidemiology. “One of the major long-term goals of the field is to be able to develop accurate real-time forecasts of pathogen spread that can be used to optimize control interventions during epidemics in humans, animals and plants…”, says Robin Thompson, “I used the [PLOS Computational Biology Research] Prize to fund travel to a conference – which was a great opportunity to present my work, as well as to learn about the current research being conducted by other scientists in my field. Thank you PLOS Computational Biology!”

The corresponding author of our 2017 Breakthrough Advance/Innovation winning article, Nicola De Maio, has also shared that since publishing his work on the computational tool called SCOTTI (Structured COalescent Transmission Tree Inference), “for sure [the PLOS Computational Research Prize] has increased visibility of our method SCOTTI”. Nicola has continued his work, recently developing a “variation of this method to infer transmission in the case when within-sample pathogen genetic variation is present…”

Many congratulations again to our  previous PLOS Computational Biology Research Prize winners!

Want to see your favorite Research Articles join this collection? As a reminder, nominations for our 2018 PLOS Computational Biology Research Prize program, open to all PLOS Computational Biology Research Articles published in 2017, are open until Friday, April 13th, 2018 at 11:59 PM ET!

Have you read a 2017 PLOS Computational Biology Research Article that stood out for you in terms scientific excellence or impact on your field? Maybe you edited or reviewed a manuscript that caught your attention? If so, nominate them now for our “2018 PLOS Computational Biology Research Prize”! If you wish to nominate more than one article, you may submit this form multiple times.

$2,000 (USD) prize will be awarded to the authors of the winning Research Article in each category from a pool of public nominations, selected by the PLOS Computational Biology Research Prize Committee.

Also, to show our appreciation for nominating, each complete nomination of an eligible Research Article published in 2017 will be entered into a random prize drawing to receive a PLOS T-shirt!

For more information on the program, take a look at the Program Page and Program Rules. Questions about the program can also be sent to


Featured image credit: Tekin et al., pcbi.1005223
Featured image credit:
 Ghaffarizadeh et al., pcbi.1005991

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