Machine Learning Frontiers in Precision Medicine

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Closing conference
Software implementing the method developed

ESR 9: Software implementing the method developed

1st summer school
Publication of all research results
Software implementing methods for heterogeneous data integration

ESR 9: Software implementing methods for heterogeneous data integration

Systematic review on existing methods

ESR 9: Systematic review on existing methods

Software implementation of the models

ESR 10: Software implementation of the models

Sequential decision-making

ESR 2: Sequential decision-making

Identification, development and im

ESR 4: Identification, development and im

2nd summer school
Software implementation of Network GWAS approaches

ESR 1: Software implementation of Network GWAS approaches

3rd summer school
Defining patient states

ESR 2: Defining patient states

Methodology to embed sparse somatic genetic profiles

ESR 5: Methodology to embed sparse somatic genetic profiles

Software and report for learning prognosis and response to treatment from multimodal clinical records

ESR 11: Software and report for learning prognosis and response to treatment from multimodal clinical records

Implementation + publication of tools for large-scale, accurate causal inference

ESR 14: Implementation + publication of tools for large-scale, accurate causal inference

Implementation and publication of tool to compare networks with uncertainty; networks comprising results from studies addressing the same problem

ESR 3: Implementation and publication of tool to compare networks with uncertainty; networks comprising results from studies addressing the same problem

A framework for discovery and validation of omics-based predictors for follow-up data in large population-based biobanks

ESR 7: A framework for discovery and validation of omics-based predictors for follow-up data in large population-based biobanks.

Analysis of germline/somatic interactions and association with phenotype information

ESR 5: Analysis of germline/somatic interactions and association with phenotype information

Comparison of methods for network analysis of individual omics data

ESR 12: Comparison of methods for network analysis of individual comics data

Publication of results

ESR 10: Publication of results

Developing polygenic risk models with rich full medical profiles

ESR 8: Developing polygenic risk models with rich full medical profiles

Implementation of Qlucore visualizations of deep learning techniques

ESR 13: Implementation of Qlucore visualizations of deep learning techniques

Implementation and publication of tool to construct and combine statistical epistasis networks, ignoring network uncertainty or heterogeneity

ESR 3: Implementation and publication of tool to construct and combine statistical epistasis networks, ignoring network uncertainty or heterogeneity

Publication describing the application of current causal inference tools to a representative use-case

ESR 14: Publication describing the application of current causal inference tools to a representative use-case

Development and implementation of methods for integrated network analysis of multi-omics data

ESR 12: Development and implementation of methods for integrated network analysis of multi-omics data

Deep learning methods to find molecular components relevant for signaling that define functions that can be related to phenotypes (disease, drug response, etc.)

ESR 9: Deep learning methods to find molecular components relevant for signaling that define functions that can be related to phenotypes (disease, drug response, etc.)

Methodology to embed dense germline mutations

ESR 5: Methodology to embed dense germline mutations

Models for the integration of phenotypic and genomic data with precision prognostic purposes

ESR 9: Models for the integration of phenotypic and genomic data with precision prognostic purposes

e-ETN: Setup of homepage

Central Data Repository for Open Research Data Pilot

Pubblicazioni

Prediction of recovery from multiple organ dysfunction syndrome in pediatric sepsis patients

Autori: Bowen Fan, Juliane Klatt, Michael M. Moor, Latasha A. Daniels, Swiss Pediatric Sepsis Study, Lazaro N. Sanchez-Pinto, Philipp K. A. Agyeman, Luregn J. Schlapbach, Karsten M. Borgwardt
Pubblicato in: Bioinformatics, Numero 38 (Supplement_1), 2022, Pagina/e i101–i108, ISSN 1367-4803
Editore: Oxford University Press
DOI: 10.1093/bioinformatics/btac229

Machine-Learning-Aided Prediction Of Brain Metastases Development In Non-Small Cell Lung Cancers

Autori: Giovanni Visonà, Lisa M. Spiller, Sophia Hahn, Elke Hattingen, Thomas J. Vogl, Gabriele Schweikert, Katrin Bankov, Melanie Demes, Henning Reis, Peter Wild, Pia S. Zeiner, Fabian Acker, Martin Sebastian, and Katharina J. Wenger
Pubblicato in: Clinical Lung Cancer, 2023, ISSN 1938-0690
Editore: Elsevier
DOI: 10.1016/j.cllc.2023.08.002

Persistent complement dysregulation with signs of thromboinflammation in active Long Covid

Autori: Cervia, Carlo; Brüningk, sarah; Hoch, Tobias; Fan, Bowen; Muzio, Giulia; Thompson, Ryan; Ceglarek, Laura; Meledin, Roman; Westermann, Patrick; Emmenegger, Marc; Taeschler, Patrick; Zurbuchen, Yves; Pons, Michele; Menges, Dominik; Ballouz, Tala; Hasler, Sara; Adamo, Sarah; Merad, Miriam; Charney, Alexander; Puhan, Milo; Brodin, Petter; Nilsson, Jakob; Aguzzi, Adriano; Miro, Raeber; Messner, Christ
Pubblicato in: Science, Numero Vol 383, Numero 6680, 2024, ISSN 0036-8075
Editore: American Association for the Advancement of Science
DOI: 10.1126/science.adg7942

Graph-based multi-modality integration for prediction of cancer subtype and severity

Autori: Diane Duroux, Christian Wohlfart, Kristel Van Steen, Antoaneta Vladimirova, Michael King
Pubblicato in: Scientific Reports, Numero 13, 2023, Pagina/e 19653, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-023-46392-6

Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data

Autori: Pelin Gundogdu, Carlos Loucera, Inmaculada Alamo-Alvarez, Joaquin Dopazo, Isabel Nepomuceno
Pubblicato in: BioData Mining, Numero 15, 2022, ISSN 1756-0381
Editore: BioMed Central
DOI: 10.1186/s13040-021-00285-4

Systematic Review of Functional MRI Applications for Psychiatric Disease Subtyping

Autori: Lucas Miranda, Riya Paul, Benno Pütz, Nikolaos Koutsouleris, Bertram Müller-Myhsok
Pubblicato in: Frontiers in Psychiatry, Numero 12, 2021, ISSN 1664-0640
Editore: Frontiers Research Foundation
DOI: 10.3389/fpsyt.2021.665536

Biological network analysis with deep learning

Autori: Giulia Muzio, Leslie O’Bray, Karsten Borgwardt
Pubblicato in: Briefings in Bioinformatics, 2020, ISSN 1467-5463
Editore: Oxford University Press
DOI: 10.1093/bib/bbaa257

netANOVA: novel graph clustering technique with significance assessment via hierarchical ANOVA

Autori: Diane Duroux, Kristel Van Steen
Pubblicato in: Briefings in Bioinformatics, Numero Volume 24, Numero 2,, 2023, Pagina/e bbad029, ISSN 1477-4054
Editore: Oxford University Press
DOI: 10.1093/bib/bbad029

Virtual Biopsy by Using Artificial Intelligence–based Multimodal Modeling of Binational Mammography Data

Autori: Vesna Barros, Tal Tlusty, Ella Barkan, Efrat Hexter, David Gruen, Michal Guindy, Michal Rosen-Zvi
Pubblicato in: Radiology, Numero 00338419, 2022, ISSN 0033-8419
Editore: Radiological Society of North America
DOI: 10.1148/radiol.220027

DeepOF: a Python package for supervised and unsupervised pattern recognition in mice motion tracking data

Autori: Lucas Miranda, Joeri Bordes, Benno Pütz, Mathias V. Schmidt, Bertram Müller-Myhsok
Pubblicato in: Journal of Open Source Software, Numero 8(86), 2023, Pagina/e 5394, ISSN 2475-9066
Editore: Open Journals
DOI: 10.21105/joss.05394

AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID-19

Autori: Parthasarathy Suryanarayanan, Ching-Huei Tsou, Ananya Poddar, Diwakar Mahajan, Bharath Dandala, Piyush Madan, Anshul Agrawal, Charles Wachira, Osebe Mogaka Samuel, Osnat Bar-Shira, Clifton Kipchirchir, Sharon Okwako, William Ogallo, Fred Otieno, Timothy Nyota, Fiona Matu, Vesna Resende Barros, Daniel Shats, Oren Kagan, Sekou Remy, Oliver Bent, Pooja Guhan, Shilpa Mahatma, Aisha Walcott-Bryant, Div
Pubblicato in: Scientific Data, Numero 8/1, 2021, ISSN 2052-4463
Editore: Springer
DOI: 10.1038/s41597-021-00878-y

Identification of Gene Modules Shared by Childhood-Onset Asthma and Immunoglobulin-E Levels by Integrated Network Analysis of Multi-Omics Data

Autori: Eranti, Pradeep; Bouzigon, Emmanuelle; Demenais, Florence; The EGEA Cooperative Group
Pubblicato in: Human Heredity, Numero 85 (2), 2021, Pagina/e 69–100, ISSN 0001-5652
Editore: S. Karger AG
DOI: 10.1159/000516194

Interpretable network-guided epistasis detection

Autori: Diane Duroux; Héctor Climente-González; Chloé-Agathe Azencott; Kristel Van Steen
Pubblicato in: Gigascience, Numero 11, 2022, Pagina/e giab093, ISSN 2047-217X
Editore: Oxford University Press
DOI: 10.1101/2020.09.24.310136

Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical information

Autori: Giovanni Visonà, Diane Duroux, Lucas Miranda, Emese Sükei, Yiran Li, Karsten Borgwardt, Carlos Oliver
Pubblicato in: Bioinformatics, Numero Volume 39, Numero 12, 2023, Pagina/e btad717, ISSN 1367-4811
Editore: Oxford University Press
DOI: 10.1093/bioinformatics/btad717

Detecting gene–gene interactions from GWAS using diffusion kernel principal components

Autori: Andrew Walakira, Junior Ocira, Diane Duroux, Ramouna Fouladi, Miha Moškon, Damjana Rozman, Kristel Van Steen
Pubblicato in: BMC Bioinformatics, Numero 23, 2022, ISSN 1471-2105
Editore: BioMed Central
DOI: 10.1186/s12859-022-04580-7

Automatic patient functionality assessment from multimodal data using deep learning techniques – Development and feasibility evaluation

Autori: Emese Sükei, Santiago de Leon-Martinez, Pablo M. Olmos, Antonio Artés
Pubblicato in: Internet Interventions, Numero 33, 2023, Pagina/e 100657, ISSN 2214-7829
Editore: Elsevier BV
DOI: 10.1016/j.invent.2023.100657

Increasing resolution in stress neurobiology: from single cells to complex group behaviors

Autori: Lucas Miranda, Joeri Bordes, Serena Gasperoni, Juan Pablo Lopez
Pubblicato in: Stress, Numero 26(1), 2023, ISSN 1607-8888
Editore: Taylor & Francis
DOI: 10.1080/10253890.2023.2186141

Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning–Based Ecological Momentary Assessment Study

Autori: Jihan Ryu, Emese Sükei, Agnes Norbury, Shelley H Liu, Juan José Campaña-Montes, Enrique Baca-Garcia, Antonio Artés, M Mercedes Perez-Rodriguez
Pubblicato in: JMIR Mental Health, Numero 8/9, 2021, Pagina/e e30833, ISSN 2368-7959
Editore: JMIR Publications
DOI: 10.2196/30833

Automatically annotated motion tracking identifies a distinct social behavioral profile following chronic social defeat stress

Autori: Joeri Bordes; Lucas Miranda; Maya Reinhardt; Sowmya Narayan; Jakob Hartmann; Emily L. Newman; Lea Maria Brix; Lotte van Doeselaar; Clara Engelhardt; Larissa Dillmann; Shiladitya Mitra; Kerry J. Ressler; Benno Pütz; Felix Agakov; Bertram Müller-Myhsok; Mathias V. Schmidt
Pubblicato in: Nature Communications, Numero Vol 14, Iss 1, 2023, Pagina/e 1, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.1038/s41467-023-40040-3

Continuous Assessment of Function and Disability via Mobile Sensing: Real-World Data-Driven Feasibility Study

Autori: Emese Sükei, Lorena Romero-Medrano, Santiago de Leon-Martinez, Jesús Herrera López, Juan José Campaña-Montes, Pablo M Olmos, Enrique Baca-Garcia, Antonio Artés
Pubblicato in: JMIR Formative Research, 2023, Pagina/e e47167, ISSN 2561-326X
Editore: JMIR Publications
DOI: 10.2196/47167

Higher-order genetic interaction discovery with network-based biological priors

Autori: Paolo Pellizzoni, Giulia Muzio, Karsten Borgwardt
Pubblicato in: Bioinformatics, Numero Volume 39, Numero Supplement_1, 2023, Pagina/e i523–i533, ISSN 1367-4811
Editore: Oxford University Press
DOI: 10.1093/bioinformatics/btad273

Quantification of tumor heterogeneity: from data acquisition to metric generation

Autori: Aditya Kashyap, Maria Anna Rapsomaniki, Vesna Barros, Anna Fomitcheva-Khartchenko, Adriano Luca Martinelli, Antonio Foncubierta Rodriguez, Maria Gabrani, Michal Rosen-Zvi, Govind Kaigala
Pubblicato in: Trends in Biotechnology, Numero Volume 40, Numero 6, 2022, Pagina/e 647-676, ISSN 0968-0004
Editore: Elsevier BV
DOI: 10.1016/j.tibtech.2021.11.006

Early life adversity shapes social subordination and cell type–specific transcriptomic patterning in the ventral hippocampus

Autori: Aron Kos, Juan Pablo Lopez, Joeri Bordes, Carlo de Donno, Julien Dine, Elena Brivio, Stoyo Karamihalev, Malte D. Luecken, Suellen Almeida-Correa, Serena Gasperoni, Alec Dick, Lucas Miranda, Maren Büttner, Rainer Stoffel, Cornelia Flachskamm, Fabian J. Theis, Mathias V. Schmidt, Alon Chen
Pubblicato in: Science Advances, Numero 9, 2023, Pagina/e eadj3793, ISSN 2375-2548
Editore: American Association for the Advancement of Science
DOI: 10.1126/sciadv.adj3793

Network propagation for GWAS analysis: a practical guide to leveraging molecular networks for disease gene discovery

Autori: Visonà, Giovanni; Bouzigon, Emmanuelle; Demenais, Florence; Schweikert, Gabriele
Pubblicato in: Briefings in Bioinformatics, Numero Volume 25, Numero 2, 2024, Pagina/e bbae014, ISSN 1477-4054
Editore: Oxford University Press
DOI: 10.1093/bib/bbae014

A retrospective cohort study of incidence and risk factors for severe SARS-CoV-2 breakthrough infection among fully vaccinated people

Autori: Tatjana Meister, Anastassia Kolde, Krista Fischer, Heti Pisarev, Raivo Kolde, Ruth Kalda, Kadri Suija, Anna Tisler, Anneli Uusküla
Pubblicato in: Scientific Reports, Numero 13: 8531, 2023, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-023-35591-w

Advancing social behavioral neuroscience by integrating ethology and comparative psychology methods through machine learning

Autori: Joeri Bordes, Lucas Miranda, Bertram Müller-Myhsok, and Mathias V. Schmidt
Pubblicato in: Neuroscience & Biobehavioral Reviews, Numero 151, 2023, Pagina/e 105243, ISSN 1873-7528
Editore: Elsevier
DOI: 10.1016/j.neubiorev.2023.105243

Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach

Autori: Emese Sükei, Agnes Norbury, M Mercedes Perez-Rodriguez, Pablo M Olmos, Antonio Artés
Pubblicato in: JMIR mHealth and uHealth, Numero 9/3, 2021, Pagina/e e24465, ISSN 2291-5222
Editore: JMIR Publications
DOI: 10.2196/24465

Getting personal with epigenetics: towards individual-specific epigenomic imputation with machine learning.

Autori: Hawkins-Hooker, Alex; Visonà, Giovanni; Narendra, Tanmayee; Rojas-Carulla, Mateo; Schölkopf, Bernhard; Schweikert, Gabriele
Pubblicato in: Nature Communications, Numero 14, 2023, Pagina/e 4750, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.1038/s41467-023-40211-2

Network Analysis of Multi-omics Data Identifies Shared Genes and Pathways Underlying the Risk of Allergic Diseases and IgE Production

Autori: Eranti, Pradeep; Vernet, Raphaël; Bouzigon, Emmanuelle; Demenais, Florence; on behalf of the EGEA, EVADA and RESET-AID Consortia
Pubblicato in: Genetic Epidemiology, Numero 46, 2022, Pagina/e 475-551, ISSN 0741-0395
Editore: John Wiley & Sons Inc.
DOI: 10.1002/gepi.22503

netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity

Autori: Zuqi Li, Federico Melograna, Hanne Hoskens, Diane Duroux, Mary L. Marazita, Susan Walsh, Seth M. Weinberg, Mark D. Shriver, Bertram Müller-Myhsok, Peter Claes, Kristel Van Steen
Pubblicato in: Frontiers in Genetics, Numero Volume 14, 2023, Pagina/e 1286800, ISSN 1664-8021
Editore: Frontiers Media
DOI: 10.3389/fgene.2023.1286800

A causal inference approach for estimating effects of non-pharmaceutical interventions during Covid-19 pandemic

Autori: Vesna Barros , Itay Manes, Victor Akinwande, Celia Cintas, Osnat Bar-Shira, Michal Ozery-Flato, Yishai Shimoni, Michal Rosen-Zvi
Pubblicato in: PLOS ONE, Numero 19326203, 2022, Pagina/e e0265289, ISSN 1932-6203
Editore: Public Library of Science
DOI: 10.1371/journal.pone.0265289

Trajectories: a framework for detecting temporal clinical event sequences from health data standardized to the Observational Medical Outcomes Partnership (OMOP) Common Data Model

Autori: Kadri Künnapuu, Solomon Ioannou, Kadri Ligi, Raivo Kolde, Sven Laur, Jaak Vilo, Peter R Rijnbeek, Sulev Reisberg
Pubblicato in: JAMIA Open, Numero 25742531, 2022, Pagina/e ooac021, ISSN 2574-2531
Editore: Oxford University Press
DOI: 10.1093/jamiaopen/ooac021

Targeted Methylation Profiling of Single Laser-Capture Microdissected Post-Mortem Brain Cells by Adapted Limiting Dilution Bisulfite Pyrosequencing (LDBSP)

Autori: Renzo J. M. Riemens, Gunter Kenis, Jennifer Nolz, Sonia C. Susano Chaves, Diane Duroux, Ehsan Pishva, Diego Mastroeni, Kristel Van Steen, Thomas Haaf, Daniël L. A. van den Hove
Pubblicato in: International Journal of Molecular Sciences, Numero 23(24), 2022, Pagina/e 15571, ISSN 1422-0067
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/ijms232415571

A historical perspective of biomedical explainable AI research

Autori: Luca Malinverno, Vesna Barros, Francesco Ghisoni, Giovanni Visonà, Roman Kern, Philip J. Nickel, Barbara Elvira Ventura, Ilija Šimić, Sarah Stryeck, Francesca Manni, Cesar Ferri, Claire Jean-Quartier, Laura Genga, Gabriele Schweikert, Mario Lovrić, Michal Rosen-Zvi
Pubblicato in: Patterns, Numero Volume 4, Numero 9, 2023, ISSN 2666-3899
Editore: Elsevier
DOI: 10.1016/j.patter.2023.100830

networkGWAS: a network-based approach to discover genetic associations

Autori: Giulia Muzio, Leslie O’Bray, Laetitia Meng-Papaxanthos, Juliane Klatt, Krista Fischer, Karsten Borgwardt
Pubblicato in: Bioinformatics, Numero Volume 39, Numero 6, 2023, Pagina/e btad370, ISSN 1367-4811
Editore: Oxford University Press
DOI: 10.1093/bioinformatics/btad370

SigPrimedNet: A Signaling-Informed Neural Network for scRNA-seq Annotation of Known and Unknown Cell Types

Autori: Gundogdu, Pelin; Álamo-Álvarez, Inmaculada; Nepomuceno-Chamorro, Isabel A.; Dopazo, Joaquin; Loucera, Carlos
Pubblicato in: Biology, Numero Volume 12, Numero 4, 2023, Pagina/e 579, ISSN 2079-7737
Editore: MDPI
DOI: 10.3390/biology12040579

Unsupervised Manifold Alignment with Joint Multidimensional Scaling

Autori: Dexiong Chen, Bowen Fan, Carlos Oliver, Karsten Borgwardt
Pubblicato in: The Eleventh International Conference on Learning Representations, Numero 2023, 2023
Editore: International Conference on Learning Representations
DOI: 10.48550/arxiv.2207.02968

Leveraging Comprehensive Health Records for Breast Cancer Risk Prediction: A Binational Assessment

Autori: Michal Chorev, Vesna Barros, Adam Spiro, Ella Evron, Ella Barkan, Oren Kagan, Mika Amit, Michal Ozery-Flato, Ayelet Akselrod-Balin, Varda Shalev, Michal Rosen-Zvi, Michal Guindy
Pubblicato in: AMIA ... Annual Symposium proceedings. AMIA Symposium, 2022, Pagina/e 385–394
Editore: AMIA

Pre-biopsy Multi-Class Classification of Breast Lesion Pathology in Mammograms

Autori: Tal Tlusty, Michal Ozery-Flato, Vesna Barros, Ella Barkan, Mika Amit, David Gruen, Michal Guindy, Tal Arazi, Mona Rozin, Michal Rosen-Zvi, Efrat Hexter
Pubblicato in: Machine Learning in Medical Imaging. MLMI 2021. Lecture Notes in Computer Science, Numero 12966, 2021, ISBN 978-3-030-87588-6
Editore: Springer
DOI: 10.1007/978-3-030-87589-3_29

The Case of Missed Cancers: Applying AI as a Radiologist's Safety Net

Autori: Michal Chorev, Yoel Shoshan, Ayelet Akselrod-Ballin, Adam Spiro, Shaked Naor, Alon Hazan, Vesna Barros, Iuliana Weinstein, Esma Herzel, Varda Shalev, Michal Guindy, Michal Rosen-Zvi
Pubblicato in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 2020, Pagina/e 220-229
Editore: Springer
DOI: 10.5281/zenodo.4076797

Cell-Level Pathway Scoring Comparison with a Biologically Constrained Variational Autoencoder

Autori: Pelin Gundogdu, Miriam Payá-Milans, Inmaculada Alamo-Alvarez, Isabel A. Nepomuceno-Chamorro, Joaquin Dopazo, Carlos Loucera
Pubblicato in: Lecture Notes in Computer Science, Numero volume 14137, 2023, Pagina/e 62–77, ISBN 978-3-031-42696-4
Editore: Springer
DOI: 10.1007/978-3-031-42697-1_5

Network Aggregation to Enhance Results Derived from Multiple Analytics

Autori: Diane Duroux, Héctor Climente-González, Lars Wienbrandt, Kristel Van Steen
Pubblicato in: Artificial Intelligence Applications and Innovations - 16th IFIP WG 12.5 International Conference, AIAI 2020, Neos Marmaras, Greece, June 5–7, 2020, Proceedings, Part I, Numero 583, 2020, Pagina/e 128-140, ISBN 978-3-030-49160-4
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-49161-1_12

È in corso la ricerca di dati su OpenAIRE...

Risultati finali

Pubblicazioni

Condividi questa pagina Condividi questa pagina sui social network

Scarica Scarica il contenuto della pagina