Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

Equipment

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MLGenSig: Machine Learning Methods for building of Integrated Genetic Signatures

2016/21/B/ST6/02176

Keywords:

personalized medicine integrated modelling genetic signatures high throughput technics cancer data next generation sequencing

Descriptors:

  • ST6_13: Bioinformatics, biocomputing, DNA and molecular computation
  • ST6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
  • NZ2_7: Bioinformatics

Panel:

ST6 - Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

Host institution :

Politechnika Warszawska, Wydział Matematyki i Nauk Informacyjnych

woj. mazowieckie

Other projects carried out by the institution 

Principal investigator (from the host institution):

dr hab. Przemysław Biecek 

Number of co-investigators in the project: 4

Call: OPUS 11 - announced on 2016-03-15

Amount awarded: 489 800 PLN

Project start date (Y-m-d): 2017-01-19

Project end date (Y-m-d): 2021-01-18

Project duration:: 48 months (the same as in the proposal)

Project status: Project settled

Project description

Download the project description in a pdf file

Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Equipment purchased [PL]

  1. Komputer stacjonarny (7 600 PLN)
  2. Laptop (5 100 PLN)

Information in the final report

  • Publication in academic press/journals (12)
  1. ROCK1 and ROCK2 Are Down-regulated in Aggressive and Advanced Skin Melanomas – A Clinicopathological Perspective
    Authors:
    MACIEJ KACZOROWSKI, PRZEMYSŁAW BIECEK, PIOTR DONIZY, MAŁGORZATA PIENIĄŻEK, RAFAŁ MATKOWSKI, AGNIESZKA HAŁOŃ
    Academic press:
    ANTICANCER RESEARCH (rok: 2020, tom: 40, strony: 1931-1942), Wydawca: International Institute of Anticancer Research
    Status:
    Published
    DOI:
    10.21873/anticanres.14148 - link to the publication
  2. modelStudio: Interactive Studio with Explanations for ML Predictive Models
    Authors:
    Hubert Baniecki and Przemyslaw Biecek
    Academic press:
    The Journal of Open Source Software (rok: 2019, tom: 4 (43), strony: 5), Wydawca: https://joss.theoj.org/
    Status:
    Published
    DOI:
    10.21105/joss.01798 - link to the publication
  3. survxai: an R package for structure-agnostic explanations of survival models
    Authors:
    Aleksandra Grudziaz1, 2, Alicja Gosiewska1, and Przemyslaw Biecek1, 2
    Academic press:
    Journal of Open Source Software (rok: 2018, tom: 3, strony: 45297), Wydawca: Journal of Open Source Software
    Status:
    Published
    DOI:
    10.21105/joss.00961 - link to the publication
  4. DALEX: Explainers for Complex Predictive Models in R
    Authors:
    Przemyslaw Biecek
    Academic press:
    Journal of Machine Learning Research (rok: 2018, tom: 19, strony: 45296), Wydawca: Microtome Publishing
    Status:
    Published
    DOI:
    brak - link to the publication
  5. KRAB ZNF explorer – the online tool for the exploration of the transcriptomic profiles of KRAB-ZNF factors in The Cancer Genome Atlas
    Authors:
    Rafał Cylwa, Kornel Kiełczewski, Marta Machnik, Urszula Oleksiewicz, Przemysław Biecek
    Academic press:
    Bioinformatics (rok: 2019, tom: 36 (3), strony: 980-981), Wydawca: Oxford University Press
    Status:
    Published
    DOI:
    10.1093/bioinformatics/btz624 - link to the publication
  6. Low RhoA expression is associated with adverse outcome in melanoma patients: a clinicopathological analysis
    Authors:
    Maciej Kaczorowski, Przemyslaw Biecek, Piotr Donizy, Malgorzata Pieniazek, Rafal Matkowski, Agnieszka Halon
    Academic press:
    American Journal of Translational Research (rok: 2019, tom: 11 (7), strony: 4524-4532), Wydawca: e-Century Publishing Corporation
    Status:
    Published
    DOI:
    brak - link to the publication
  7. The Landscape of R Packages for Automated Exploratory Data Analysis
    Authors:
    Mateusz Staniak, Przemysław Biecek
    Academic press:
    The R Journal (rok: 2019, tom: 45598, strony: 45314), Wydawca: The R Foundation
    Status:
    Published
    DOI:
    10.32614/RJ-2019-033 - link to the publication
  8. SMAD7 is a novel independent predictor of survival in patients with cutaneous melanoma
    Authors:
    MACIEJ KACZOROWSKI, PRZEMYSLAW BIECEK, PIOTR DONIZY, MALGORZATA PIENIAZEK, RAFAL MATKOWSKI, and AGNIESZKA HALON
    Academic press:
    Translational Research (rok: 2019, tom: -, strony: -), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.trsl.2018.09.002 - link to the publication
  9. Extended 3D and 4D cumulative plots for evaluation of unmatched incurred sample reanalysis
    Authors:
    Piotr Rudzki, Michal Kaza, Przemyslaw Biecek
    Academic press:
    Bioanalysis (rok: 2018, tom: 10(3), strony: 153-162), Wydawca: Future Science Ltd
    Status:
    Published
    DOI:
    10.4155/bio-2017-0210 - link to the publication
  10. Incurred Sample Reanalysis: Time to Change the Sample Size Calculation?
    Authors:
    Piotr J. Rudzki,1,3 Przemysław Biecek,2 and Michał Kaza1
    Academic press:
    The AAPS Journal (rok: 2019, tom: 2019, strony: 21-28), Wydawca: AAPS
    Status:
    Published
    DOI:
    10.1208/s12248-019-0293-2 - link to the publication
  11. The expression signature of cancer-associated KRAB-ZNF factors identified in TCGA pan-cancer transcriptomic data
    Authors:
    Marta Machnik1,2, Rafał Cylwa3, Kornel Kiełczewski4, Przemysław Biecek4, Triantafillos Liloglou5, Andrzej Mackiewicz1,2 and Urszula Oleksiewicz1,2
    Academic press:
    Molecular Oncology (rok: 2019, tom: -, strony: -), Wydawca: FEBS Press and John Wiley & Sons
    Status:
    Published
    DOI:
    10.1002/1878-0261.12407 - link to the publication
  12. auditor: an R Package for Model-Agnostic Visual Validation and Diagnostics
    Authors:
    Alicja Gosiewska, Przemysław Biecek
    Academic press:
    The R Journal (rok: 2019, tom: 11, strony: 85-98), Wydawca: The R Foundation
    Status:
    Accepted for publication
    DOI:
    10.32614/RJ-2019-036 - link to the publication

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