PredAlgoBC SIGNED
Machine learning prediction for breast cancer therapy
Total Cost €
0EC-Contrib. €
0Partnership
0Views
0PredAlgoBC project word cloud
Explore the words cloud of the PredAlgoBC project. It provides you a very rough idea of what is the project "PredAlgoBC" about.
Project "PredAlgoBC" data sheet
The following table provides information about the project.
| Coordinator |
INSTITUT DE CANCEROLOGIE DE L'OUEST
Organization address contact info |
| Coordinator Country | France [FR] |
| Total cost | 184˙707 € |
| EC max contribution | 184˙707 € (100%) |
| Programme |
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility) |
| Code Call | H2020-MSCA-IF-2018 |
| Funding Scheme | MSCA-IF-EF-ST |
| Starting year | 2019 |
| Duration (year-month-day) | from 2019-10-01 to 2021-09-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | INSTITUT DE CANCEROLOGIE DE L'OUEST | FR (ANGERS) | coordinator | 184˙707.00 |
Map
Project objective
Breast cancer is the cancer with the highest incidence in women worldwide, and is the leading cause of cancer-related death, mainly due to treatment resistance. Recently, tumor heterogeneity has been described as one of the key driver in treatment failure. Indeed, tumor is not a homogeneous entity to treat, but a complex association of subclonal populations driven by their own genetic alterations, and immune and stromal cells from microenvironment. Breast cancer subtypes and tumor heterogeneity advocate for the development of tailored, personalized treatments, but so far, the discovery of efficient predictive markers has been compromised by the lack of adapted biological models and methodological tools. The recent developments of high-throughput methods for bulk and single-cell analyses has generated large ‘omics’ datasets from patients, stored in open access databases (ArrayExpress, GEO). Combining these numerous datasets will grant a sufficient statistical power to reveal a comprehensive overview of tumor complexity. However, this data mining is currently limited by methodological challenges like cross-platform normalization and the difficulty to analyze complex data structure with high dimension observations. To overcome these issues, I propose to implement a multidisciplinary project at the interface between mathematics, biology, and information technologies. With the support of the mathematicians and bioinformaticians from the Bioinfomics unit of the regional comprehensive cancer center (ICO), I will develop and implement machine-learning algorithms in the search of predictive biomarkers for breast cancer treatment. This innovative strategy will lead to personalized medicine in breast cancer by guiding clinicians in the selection of the optimal therapeutic option. Moreover, this generated pipeline for predictive marker discovery could be further adapted for the treatment of other cancer types.
Are you the coordinator (or a participant) of this project? Plaese send me more information about the "PREDALGOBC" project.
For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.
Send me an email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.
Thanks. And then put a link of this page into your project's website.
The information about "PREDALGOBC" are provided by the European Opendata Portal: CORDIS opendata.