Results & Downloads
Paper published in Bioinformatics
Paper entitled: FUNKI: Interactive functional footprint-based analysis of omics data
Paper published in the Frontiers in Immunology
Paper entitled: “From Infection to Immunity: Understanding the Response to SARS-CoV2 Through In-Silico Modeling (SP)“
Paper published in Symmetry 2021
Paper entitled: “The Multiple Dimensions of Networks in Cancer: A Perspective”
Paper published in the Elsevier Journal
Paper entitled “Applications of single-cell and bulk RNA sequencing in onco-immunology”.
Paper published in the Special Issue Hepatoblastoma and Other Pediatric Liver Tumors
Paper entitled “Bridging molecular basis, prognosis, and treatment of pediatric liver tumors”.
Paper published in the Current Protocols in Bioinformatics.
Paper entitled “PIONEER: Pipeline for Generating High‐Quality Spectral Libraries for DIA‐MS Data”.
Paper published in the Journal for ImmunoTherapy of Cancer
Paper entitled “Identification and validation of viral antigens sharing sequence and structural homology with tumor-associated antigens (TAAs).”
Paper presented in the “Computer Vision for Microscopy Image Analysis (CVMI)” workshop
Paper entitled “Unsupervised Detection of Cancerous Regions in Histology Imagery using Image-to-Image Translation”
Paper published in Bioinformatics
Paper entitled: “Improved identification and quantification of peptides in mass spectrometry data via chemical and random additive noise elimination (CRANE)”
Paper published in Physics of Life Reviews: pp. 132-134
Paper entiteld: „Adaptation through the lense of single-cell multi-omics data Comment on “Dynamic and thermodynamic models of adaptation” by A.N. Gorban et al.”
Paper published in the BIORXIV.
Paper entitled “Hepatoblastomas with carcinoma features represent a biological spectrum of aggressive neoplasms in children and young adults”.
Paper published in Bioinformatics
Paper entitled: “On the feasibility of deep learning applications using raw mass spectrometry data”
Paper published in Bioinformatics
Paper entitled: “TITAN: T-cell receptor specificity prediction with bimodal attention networks“
Paper published in Bioinformatics
Paper entitled: “SysMod: the ISCB community for data-driven computational modelling and multi-scale analysis of biological systems”
Paper published in the Proceedings of International Conference on Machine Learning (ICML) 2021
A new network inference algorithm from TUDA with iPC acknowledge was published in the ICML 2021. Paper entitled “Active Learning of Continuous-Time Bayesian Networks Through Interventions”.
Estimage: a webserver hub for the computation of methylation age (SP)
Article published in the Nucleic Acids Research Journal.
Artificial Intelligence in Cancer Research: learning at different levels of data granularity
Article published in the Molecular Oncology Journal, Volume 15, Issue 4 Pages 817-829.
Article published in the Cancer Cell Journal, Volume 39, Issue 6, P 810-826
Article entitled “STAG2 mutations alter CTCF-anchored loop extrusion, reduce cis-regulatory interactions and EWSR1-FLI1 activity in Ewing sarcoma”.
The multilayer community structure of medulloblastoma
Article published in the iScience Journal, Volume 24, ISSUE 4 by partner Barcelona Supercomputing Center (BSC).
Paper published in Machine Learning: Science and Technology
Paper entitled: “Data-driven molecular design for discovery and synthesis of novel ligands: a case study on SARS-CoV-2”
Publication in the Journal of Medical Internet Research (JMIR).
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).
Tumor to normal single-cell mRNA comparisons reveal a pan-neuroblastoma cancer cell
Article published in the Science Advances Journal, Vol. 7, no. 6.
Paper published in the International Joint Conference on Neural Networks-2021 (IJCNN2021)
Paper entitled: “Clinical trajectories estimated from bulk tumoral molecular proles using elastic principal trees”
Benchmarking of cell type deconvolution pipelines for transcriptomics data
Article published in “Nature Communications” (2020, 11:5650) by partner UGENT
FPGA Accelerated Analysis of Boolean Gene Regulatory Networks
Article published in the IEEE/ACM Transactions on Computational Biology and Bioinformatics ( Volume: 17, Issue: 6)
COSIFER: a Python package for the consensus inference of molecular interaction networks
Article published in the Bioinformatics Journal.
D2.2 “Initial infrastructure framework”
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.
Designing a Network Proximity-Based Drug Repurposing Strategy for COVID-19
The ongoing COVID-19 pandemic still requires fast and effective efforts from all fronts, including epidemiology, clinical practice, molecular medicine, and pharmacology.
Journal article in MICCAI 2020
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.
Inferring clonal composition from multiple tumor biopsies
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.
ICML 2020 paper
TUDA submitted a manuscript about continous-time Bayesian networks to the 37th International Conference on Machine Learning.
D1.1 “Collection of public molecular and clinical data”
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.
Paper published in BMC Bioinformatics
Paper entitled: “Methylation data imputation performances under different representations and missingness patterns”
Publication in Nucleic Acids Research
IBM published a new paper about their web service “PaccMann”.
Publication in Cancers 2020
“Comprehensive Map of the Regulated Cell Death Signaling Network” in Issue 990 of the “Cancers” Journal by CURIE.
AAAI 2020 paper
TUDA contributed to the 34th Conference on Artificial Intelligence with the paper “A Variational Perturbative Approach to Planning in Graph-Based Markov Decision Processes”.
Ewing sarcoma book
CURIE contributed to the Springer book “Ewing Sarcoma – Methods and Protocols, Springer”.
Publication in Journal of Hepatology
IGTP contributed with a paper entitled “Epigenetic footprint enables molecular risk stratification of hepatoblastoma with clinical implications”.
ROSUS 2020 paper
XLAB published a paper about “Visual Anomaly Detection in Domains with Limited Amount of Labeled Data”.
Publication in Entropy
CURIE published a paper on “Robust and Scalable Learning of Complex Intrinsic Dataset Geometry via ElPiGraph”
Press Release
CURIE elaborates on a better understanding of the intratumoral heterogeneity of Ewing sarcoma.
Publication in Molecular Pharmaceutics
IBM and UKL-HD published a paper on “Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders”
Paper published in Scientific Reports (Sci Rep)
Paper entitled: “Stabilized Reconstruction of Signaling Networks from Single-Cell Cue-Response Data”
Publication in Blood Advances
BCM’s paper on “Atovaquone is active against AML by upregulating the integrated stress pathway and suppressing oxidative phosphorylation”
NeurIPS 2019 paper
TUDA’s paper “Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data” was accepted
NeurIPS 2019 paper
IBM’s paper “PaccMannRL: Designing anticancer drugs from transcriptomic data via reinforcement learning” was accepted
Publication in Bioinformatics Journal
CURIE published a paper on “cd2sbgnml: bidirectional conversion between CellDesigner and SBGN formats”
Paper published in Explainable AI in Healthcare and Medicine
Paper entitled: “DeStress: Deep Learning for Unsupervised Identification of Mental Stress in Firefighters from Heart-rate Variability (HRV) Data”
Publication in Cell Reports
Publication by CURIE on “Transcriptional programs define intratumoral heterogeneity of Ewing sarcoma at single cell resolution”
Publication in International Journal of Molecular Sciences
CURIE published a paper on “Independent Component Analysis for Unraveling the Complexity of Cancer Omics Datasets”
The RNA Atlas
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.
Using attention-based neural networks to enable explainable drug sensitivity prediction
Published by Manica Matteo; Oskooei Ali; Born Jannis; Subramanian Vigneshwari; Saez-Rodriguez Julio; Rodriguez Martinez Maria
Inferring context specific PPI networks
Publishes by Manica Matteo; Mathis Roland; Cadow Joris; Rodriguez Martinez Maria
Interpretability for computational biology
Published by Nguyen An-phi; Rodriguez-Martinez
PIMKL: Pathway Induced Multiple Kernel Learning
Published by Manica Matteo; Cadow Joris; Mathis Roland; Rodriguez Martinez Maria
Interpretable classification of molecular measurements
Publication by Cadow Joris
Interpretability for computational biology
Publication by Nguyen An-phi; Rodriguez-Martinez Maria
Using attention-based neural networks
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
Computer Modeling of Clonal Dominance
Publication on Memory-Anti-Naïve and Its Curbing by Attrition by Castiglione, Filippo; Ghersi, Dario; Celada, Franco.
From causal pathways to drug-response targets
Presentation from Rosa Hernansaiz Ballesteros on multi-omic analysis to contextualise large signalling networks on 6th June 2019 at EMBL-EBI, Hixton, UK.
Video
Find out more about identifying effective personalized medicine for paediatric cancer in the explanatory video.
iPC Leaflet
The official leaflet of the iPC H2020 project containing Partners, Project Information, Mission, Vision and Goals of the project.
Assessing reproducibility of matrix factorization methods in independent transcriptomes
Publication by Laura Cantini, Ulykbek Kairov, Aurélien de Reyniès, Emmanuel Barillot, François Radvanyi, Andrei Zinovyev
D10.1 “Internal and external IT communication infrastructure and project website”
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.
D11.1 “Project Quality Plan”
A handbook of the project management process, review process, quality checks, meeting organisation, which is communicated to all partners.
Press Release
New European Project Squares off against Paediatric Cancer
The Austrian-managed iPC project is now underway and bringing hope to the children with cancer
Announcement Letter
The official announcement letter contains all relevant information about the iPC H2020 project.
