Author

Ekaterina S. Maksimova

Institute of Science and Technology AustriaORCID 0000-0001-6445-8043Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 2 Approach:Bayesian inference· 1 Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Assay:protein structure· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Dmitry N. IvankoviD· 1 shared Dmitry S. Petrov· 1 shared Fyodor A. KondrashoviD· 1 shared Ilya S. Vorobyev· 1 shared Karina A. Markhieva· 1 shared Kristi LälliD· 1 shared Marie C. SadleriD· 1 shared Mariia S. Novikova· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBioinformatics

Dmitry N. IvankovORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Using AlphaFold to predict the impact of single mutations on protein stability and function

Marina A. Pak, Karina A. Markhieva, Mariia S. Novikova, Dmitry S. Petrov, Ilya S. Vorobyev, Ekaterina S. Maksimova, Fyodor A. Kondrashov, Dmitry N. Ivankov

This study assesses AlphaFold's ability to predict the impact of single mutations on protein stability and function, finding weak or no correlation with experimental data.

PLoS ONE · Mar 16, 2023Peer-reviewedBioinformatics

Novel discoveries and enhanced genomic prediction from modelling genetic risk of cancer age-at-onset

Ekaterina S. Maksimova, Sven E. Ojavee, Kristi Läll, Marie C. Sadler, Reedik Mägi, Zoltán Kutalik, Matthew R. Robinson

This paper improves cancer genomic prediction by analyzing age-at-diagnosis instead of case-control data, finding new genomic regions and enhancing prediction accuracy using Bayesian time-to-event modeling.

medRxiv · Mar 25, 2022 · PreprintGenetic & Genomic Medicine