IMAGE: 2018 prizes honor advancements in protein folding, bacterial genome sequencing, and tumor analysis. view more
Credit: Ghaffarizadeh et al., https://doi.org/10.1371/journal.pcbi.1005991
The second annual PLOS Computational Biology Research Prize program has awarded top prizes to three exemplary studies published in 2017. The program launched last year to celebrate some of the journal’s most outstanding research articles.
This year’s winners stood out from an international pool of studies nominated by the public in three categories: Breakthrough Advance/Innovation, Exemplary Methods/Software, and Public Impact. A committee made up of editorial board members chose the final winner in each category.
Taking home the top Breakthrough Advance/Innovation prize is a study that addressed protein structure using ideas from the revolutionary computer science field known as deep learning. Study author Sheng Wang and colleagues at Toyota Technological Institute at Chicago, Illinois, developed a new deep learning method that improves predictions of how proteins fold and assemble into their final 3-D forms, which could help reveal new biological insights.
The top study in the Exemplary Methods/Software category presented a new, open source program called Unicycler, which assembles bacterial genomes from DNA sequencing data. Developed by Ryan Wick and colleagues at The University of Melbourne, Australia, Unicycler
Article originally posted at