Results & Downloads

Article published in the iScience Journal, Volume 24, ISSUE 4 by partner Barcelona Supercomputing Center (BSC).

Article entitled “Artificial Intelligence–Aided Precision Medicine for COVID-19: Strategic Areas of Research and Development”.

Published in the JMIR, Volume 23 Issue 3 by partner Barcelona Supercomputing Center (BSC).

Article published in “Nature Communications” (2020, 11:5650) by partner UGENT

An initial demonstrator of the iPC infrastructure is reviewed. The platform’s architecture is based on modules, which allow parallel developments and integration of different open source-based software components. This allows us to leverage other efforts and contribute towards its sustainability and maintainability. The release of a minimum viable platform is allowing us to capture early feedback from researchers at iPC.

The ongoing COVID-19 pandemic still requires fast and effective efforts from all fronts, including epidemiology, clinical practice, molecular medicine, and pharmacology. 

XLAB contributed to 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2020) with an article about anomaly detection in visual data.

Knowledge about the clonal evolution of a tumor can help to interpret the function of its genetic alterations by identifying initiating events and events that contribute to the selective advantage of proliferative, metastatic, and drug-resistant subclones. 

TUDA submitted a manuscript about continous-time Bayesian networks to the 37th International Conference on Machine Learning.

The development of iPC predictive models for paediatric cancer genesis, progression, and response to therapies, as well as patient response to therapy, requires a vast quantity of molecular and clinical training data. In this deliverable, we have assembled a collection of these data to enable model construction and testing.

IBM published a new paper about their web service “PaccMann”.

“Comprehensive Map of the Regulated Cell Death Signaling Network” in Issue 990 of the “Cancers” Journal by CURIE.

TUDA contributed to the 34th Conference on Artificial Intelligence with the paper “A Variational Perturbative Approach to Planning in Graph-Based Markov Decision Processes”.

CURIE contributed to the Springer book “Ewing Sarcoma – Methods and Protocols, Springer”.

IGTP contributed with a paper entitled “Epigenetic footprint enables molecular risk stratification of hepatoblastoma with clinical implications”.

XLAB published a paper about “Visual Anomaly Detection in Domains with Limited Amount of Labeled Data”.

CURIE published a paper on “Robust and Scalable Learning of Complex Intrinsic Dataset Geometry via ElPiGraph”

CURIE elaborates on a better understanding of the intratumoral heterogeneity of Ewing sarcoma.

IBM and UKL-HD published a paper on “Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders”

BCM’s paper on “Atovaquone is active against AML by upregulating the integrated stress pathway and suppressing oxidative phosphorylation”

TUDA’s paper “Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data” was accepted

IBM’s paper “PaccMannRL: Designing anticancer drugs from transcriptomic data via reinforcement learning” was accepted

CURIE published a paper on “cd2sbgnml: bidirectional conversion between CellDesigner and SBGN formats”

Publication by CURIE on “Transcriptional programs define intratumoral heterogeneity of Ewing sarcoma at single cell resolution”

CURIE published a paper on “Independent Component Analysis for Unraveling the Complexity of Cancer Omics Datasets”

UGent and collaborators present a more comprehensive atlas of the human transcriptome that is derived from matching polyA-, total-, and small-RNA profiles of a heterogeneous collection of nearly 300 human tissues and cell lines.

Published by Manica Matteo; Oskooei Ali; Born Jannis; Subramanian Vigneshwari; Saez-Rodriguez Julio; Rodriguez Martinez Maria

Publishes by Manica Matteo; Mathis Roland; Cadow Joris; Rodriguez Martinez Maria

Published by Nguyen An-phi; Rodriguez-Martinez

Published by Manica Matteo; Cadow Joris; Mathis Roland; Rodriguez Martinez Maria

Publication by Cadow Joris

Publication by Nguyen An-phi; Rodriguez-Martinez Maria

Publication on enabling explainable drug sensitivity prediction on multimodal data by Manica Matteo; Oskooei Ali; Born Jannis; Subramanian Vigneshwari; Saez-Rodriguez Julio; Rodriguez Martinez Maria

Publication on Memory-Anti-Naïve and Its Curbing by Attrition by Castiglione, Filippo; Ghersi, Dario; Celada, Franco.

Presentation from Rosa Hernansaiz Ballesteros on multi-omic analysis to contextualise large signalling networks on 6th June 2019 at EMBL-EBI, Hixton, UK.

Find out more about identifying effective personalized medicine for paediatric cancer in the explanatory video. 

The official leaflet of the iPC H2020 project containing Partners, Project Information, Mission, Vision and Goals of the project.

Publication by Laura Cantini, Ulykbek Kairov, Aurélien de Reyniès, Emmanuel Barillot, François Radvanyi, Andrei Zinovyev

This deliverable constitutes the launch of the internal and external iPC communication infrastructure including the establishment of mailing lists, new IT infrastructure and the iPC website.

A handbook of the project management process, review process, quality checks, meeting organisation, which is communicated to all partners.

New European Project Squares off against Paediatric Cancer

The Austrian-managed iPC project is now underway and bringing hope to the children with cancer

The official announcement letter contains all relevant information about the iPC H2020 project.