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CORDIS - EU research results
CORDIS

Computational ONcology TRaining Alliance

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Software for phylogeny with migration (opens in new window)

A software for analysing phylogeny in combination with migration.

Progression inference software (opens in new window)

A software for progression inference for multiple tumors.

Resistance onset prediction model (opens in new window)

A model for resistance onset prediction.

A first software for tumour phylogeny reconstruction (opens in new window)

Software for tumour phylogeny reconstruction from mutations.

Resistance risk evaluation tool (opens in new window)

A software tool for resistance risk evaluation.

Project communicating and promoting material, including web site. (opens in new window)

Compilation of all project communicating and promoting material, including web site.

Communication and dissemination activities (opens in new window)

Completion of all communication and dissemination activities

All recruitment measures (opens in new window)

All recruitment measures finalized including advertising on web, Facebook, and standard media.

Experimentally validated relapse and metastasis drivers (opens in new window)

A list of experimentally validated relapse and metastasis drivers

Growth rate and progression type based biomarker (opens in new window)

A growth rate and progression type based biomarker for cancer

Experimentally validated cancer drivers (opens in new window)

A list of experimentally validated cancer drivers

Time dependent mutation signatures (opens in new window)

Time dependent cancer mutation signatures

CONTRA PhD Theses (opens in new window)

Completion of all CONTRA PhD Theses

New biomarkers that inform treatment sensitivity (opens in new window)

A list of new biomarkers that inform treatment sensitivity

Publications

CACTUS: integrating clonal architecture with genomic clustering and transcriptome profiling of single tumor cells (opens in new window)

Author(s): Shadi Darvish Shafighi; Szymon M. Kielbasa; Julieta Sepulveda-Yanez; Ramin Monajemi; Davy Cats; Hailiang Mei; Roberta Menafra; Susan L. Kloet; Hendrik Veelken; Cornelis A.M. van Bergen; Ewa Szczurek
Published in: Genome Medicine, Issue 4, 2021, ISSN 1471-2458
Publisher: BioMed Central
DOI: 10.1101/2020.06.05.134452

Integrative radiogenomics for virtual biopsy and treatment monitoring in ovarian cancer. (opens in new window)

Author(s): Paula Martin-Gonzalez; Mireia Crispin-Ortuzar; Leonardo Rundo; Maria Delgado-Ortet; Marika Reinius; Lucian Beer; Ramona Woitek; Stephan Ursprung; Helen Addley; Helen Addley; James D. Brenton; Florian Markowetz; Evis Sala
Published in: Insights into Imaging, Vol 11, Iss 1, Pp 1-10 (2020), Issue 4, 2020, ISSN 1869-4101
Publisher: Springer Science and Business Media Deutschland GmbH
DOI: 10.17863/cam.74310

Bayesian non-parametric clustering of single-cell mutation profiles (opens in new window)

Author(s): Nico Borgsmüller; Nico Borgsmüller; Jose Bonet; Francesco Marass; Francesco Marass; Abel Gonzalez-Perez; Nuria Lopez-Bigas; Niko Beerenwinkel; Niko Beerenwinkel
Published in: Bioinformatics, Issue Volume 36, Issue 19, 2020, Page(s) 4854–4859, ISSN 1367-4803
Publisher: Oxford University Press
DOI: 10.1101/2020.01.15.907345

Pan-cancer detection of driver genes at the single-patient resolution. (opens in new window)

Author(s): Joel Nulsen; Hrvoje Misetic; Christopher Yau; Francesca D. Ciccarelli
Published in: Genome Medicine, Issue 9, 2021, ISSN 1756-994X
Publisher: BioMed Central
DOI: 10.1186/s13073-021-00830-0

DeepMP: a deep learning tool to detect DNA base modifications on Nanopore sequencing data (opens in new window)

Author(s): Jose Bonet; Mandi Chen; Mandi Chen; Marc Dabad; Simon Heath; Abel Gonzalez-Perez; Nuria Lopez-Bigas; Nuria Lopez-Bigas; Jens Lagergren; Jens Lagergren
Published in: Bioinformatics, Issue Volume 38, Issue 5,, 2021, Page(s) 1235–1243, ISSN 1367-4803
Publisher: Oxford University Press
DOI: 10.1101/2021.06.28.450135

Cell Abundance Aware Deep Learning For Cell Detection On Highly Imbalanced Pathological Data (opens in new window)

Author(s): Yeman Brhane Hagos; Catherine S. Y. Lecat; Dominic Patel; Lydia Lee; Thien-An Tran; Manuel Rodriguez–Justo; Kwee Yong; Yinyin Yuan
Published in: ISBI, Issue 10, 2021
Publisher: IEEE
DOI: 10.1109/isbi48211.2021.9433994

ConCORDe-Net: Cell Count Regularized Convolutional Neural Network for Cell Detection in Multiplex Immunohistochemistry Images

Author(s): Hagos, Yeman Brhane; Narayanan, Priya Lakshmi; Akarca, Ayse U.; Marafioti, Teresa; Yuan, Yinyin
Published in: Issue 7, 2019
Publisher: Springer

ConCORDe-Net: Cell Count Regularized Convolutional Neural Network for Cell Detection in Multiplex Immunohistochemistry Images (opens in new window)

Author(s): Yeman Brhane Hagos; Priya Narayanan; Ayse U. Akarca; Teresa Marafioti; Yinyin Yuan
Published in: MICCAI (1), Issue 2, 2019
Publisher: Springer
DOI: 10.1007/978-3-030-32239-7_74

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