Author

Maiju Pesonen

University of Helsinki

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

Same name, identified by ORCID

Biology Disciplines

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Genomics· 2 Genetics· 1

Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 3 Approach:statistical model· 3 Assay:whole-genome sequencing· 3 Research Focus:gene regulatory network inference· 2 Research Focus:variant effect prediction· 2 Research Focus:benchmarking· 1 Research Focus:GWAS / association mapping· 1 Approach:matrix factorization· 1

Frequent Co-Authors

Jukka CoranderiD· 3 shared Santeri PuraneniD· 3 shared Claire ChewapreechaiD· 2 shared Johan PensariD· 2 shared John A. LeesiD· 2 shared Julian ParkhilliD· 2 shared Nicholas J. CroucheriD· 2 shared Stephen D. BentleyiD· 2 shared

Activity by Year

2017-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersGenomics

Jukka CoranderORCID

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3 papers

Recent·Most cited

Genome-wide epistasis and co-selection study using mutual information

Johan Pensar, Santeri Puranen, Brian Arnold, Neil MacAlasdair, Juri Kuronen, Gerry Q. Tonkin‐Hill, Maiju Pesonen, Yingying Xu, Aleksi Sipola, Leonor Sánchez-Busó, John A. Lees, Claire Chewapreecha, Stephen D. Bentley, Simon R. Harris, Julian Parkhill, , Jukka Corander

This paper introduces SpydrPick, a model-free method to detect co-selection and epistasis in bacterial genomes, revealing both known and novel targets in human pathogens.

Nucleic Acids Research · Jul 24, 2019Peer-reviewedGenomics

SuperDCA for genome-wide epistasis analysis

Santeri Puranen, Maiju Pesonen, Johan Pensar, Ying Xu, John A. Lees, Stephen D. Bentley, Nicholas J. Croucher, Jukka Corander, Erik M. Aurell

SuperDCA enables genome-wide epistasis analysis in bacteria by efficiently modeling interactions among polymorphisms, revealing novel biological insights in Streptococcus pneumoniae.

Microbial Genomics · May 29, 2018Peer-reviewedGenomics

Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis

Marcin J Skwark, Nicholas J Croucher, Santeri Puranen, Claire Chewapreecha, Maiju Pesonen, Yingying Xu, Paul Turner, Simon R Harris, Julian Parkhill, Stephen D Bentley, Erik Aurell, Jukka Corander

This paper introduces genomeDCA, a statistical method to identify epistatic interactions in Streptococcus pneumoniae genomes, revealing networks of resistance, virulence, and core genes.

PLOS Genetics · Feb 16, 2017Peer-reviewedGenetics