Nature Communications (Nov 2016)
In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development
- Ivan V. Ozerov,
- Ksenia V. Lezhnina,
- Evgeny Izumchenko,
- Artem V. Artemov,
- Sergey Medintsev,
- Quentin Vanhaelen,
- Alexander Aliper,
- Jan Vijg,
- Andreyan N. Osipov,
- Ivan Labat,
- Michael D. West,
- Anton Buzdin,
- Charles R. Cantor,
- Yuri Nikolsky,
- Nikolay Borisov,
- Irina Irincheeva,
- Edward Khokhlovich,
- David Sidransky,
- Miguel Luiz Camargo,
- Alex Zhavoronkov
Affiliations
- Ivan V. Ozerov
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Ksenia V. Lezhnina
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Evgeny Izumchenko
- Department of Otolaryngology, The Johns Hopkins University, School of Medicine, Head and Neck Cancer Research
- Artem V. Artemov
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Sergey Medintsev
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Quentin Vanhaelen
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Alexander Aliper
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Jan Vijg
- Department of Genetics, Albert Einstein College of Medicine
- Andreyan N. Osipov
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Ivan Labat
- BioTime, Inc.
- Michael D. West
- BioTime, Inc.
- Anton Buzdin
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Charles R. Cantor
- Department of Biomedical Engineering, Boston University
- Yuri Nikolsky
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Nikolay Borisov
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- Irina Irincheeva
- Nutrition and Metabolic Health group, Nestlé Institute of Health Sciences
- Edward Khokhlovich
- Novartis Institutes for BioMedical Research
- David Sidransky
- Department of Otolaryngology, The Johns Hopkins University, School of Medicine, Head and Neck Cancer Research
- Miguel Luiz Camargo
- Novartis Institutes for BioMedical Research
- Alex Zhavoronkov
- Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern
- DOI
- https://doi.org/10.1038/ncomms13427
- Journal volume & issue
-
Vol. 7,
no. 1
pp. 1 – 11
Abstract
Pathway analysis aids interpretation of large-scale gene expression data, but existing algorithms fall short of providing robust pathway identification. The method introduced here includes coexpression analysis and gene importance estimation to robustly identify relevant pathways and biomarkers for patient stratification.
