Author

Magdalena Krochmal

Biomedical Research Foundation of the Academy of AthensORCID 0000-0002-7167-8463Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexander PolyzosiD· 1 shared Anastasia A. VarvarigouiD· 1 shared Antonia VlahouiD· 1 shared Archimides Aggelopoulos· 1 shared Dimitris ThanosiD· 1 shared Elizabeth O. JohnsoniD· 1 shared Ioannis S. PaterasiD· 1 shared Jiří BártekiD· 1 shared

Activity by Year

2017-2017 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Alexander PolyzosORCID

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1 paper

Recent·Most cited

Deep Learning and Association Rule Mining for Predicting Drug Response in Cancer. A Personalised Medicine Approach.

Konstantinos N. Vougas, Magdalena Krochmal, Thomas Jackson, Alexander Polyzos, Archimides Aggelopoulos, Ioannis S. Pateras, Michael Liontos, Anastasia A. Varvarigou, Elizabeth O. Johnson, Vassilis Georgoulias, Antonia Vlahou, Paul A. Townsend, Dimitris Thanos, Jiří Bártek, Vassilis G. Gorgoulis

The paper uses deep learning and association rule mining to predict drug response in cancer cell lines, outperforming existing methods and demonstrating a novel approach for therapeutic target identification.

bioRxiv · May 9, 2017 · PreprintBioinformatics