Author

Grazia Piizzi

Merck & Co., Inc., Rahway, NJ, USA (United States)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 1 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Andrej Palička· 1 shared Christopher H. WoelkiD· 1 shared Dan ChangiD· 1 shared Danny A. BittoniD· 1 shared Daria J. HazudaiD· 1 shared David PříhodaiD· 1 shared Geoffrey D. HanniganiD· 1 shared Gergely TemesiiD· 1 shared

Activity by Year

2019-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Andrej Palička

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1 paper

Recent·Most cited

A Deep Learning Genome-Mining Strategy Improves Biosynthetic Gene Cluster Prediction

Geoffrey D. Hannigan, David Příhoda, Andrej Palička, Jindřich Soukup, Ondřej Klempíř, Lena Rampula, Jindrich Durcak, Michael Wurst, Jakub Kotowski, Dan Chang, Rurun Wang, Grazia Piizzi, Gergely Temesi, Daria J. Hazuda, Christopher H. Woelk, Danny A. Bitton

This paper introduces DeepBGC, a deep learning method for improved biosynthetic gene cluster prediction, uncovering previously undetectable clusters with potential novel biological activities.

Nucleic Acids Research · Aug 8, 2019Peer-reviewedBioinformatics