MLFPM Publications

Peer-reviewed publications

  1. Duroux Diane, Climente-González Héctor, Wienbrandt Lars, and Van Steen Kristel. (2020). Network Aggregation to Enhance Results Derived from Multiple Analytics. In Artificial Intelligence Applications and Innovations. AIAI 2020. IFIP Advances in Information and Communication Technology, vol 583. Springer, Cham. http://doi.org/10.1007/978-3-030-49161-1_12
  2. Michal Chorev, Yoel Shoshan, Adam Spiro, Shaked Naor, Alon Hazan, Vesna Barros, Iuliana Weinstein, Esma Herzel, Varda Shalev, Michal Guind, and Michal Rosen-Zvi. (2020). The Case of Missed Cancers: Applying AI as a Radiologist’s Safety Net. In: Martel A.L. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. MICCAI 2020. Lecture Notes in Computer Science, vol 12266. Springer, Cham. http://doi.org/10.5281/zenodo.4076798
  3. Giulia Muzio*, Leslie O’Bray* and Karsten Borgwardt (* = equal contribution). (2020). Biological network analysis with deep learning. Briefings in Bioinformatics 2020, bbaa257. https://doi.org/10.1093/bib/bbaa257
  4. Emese Sükei, Agnes Norbury, M Mercedes Perez-Rodriguez, Pable M Olmos, and Antonio Artés. (2021). Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach. JMIR Mhealth Uhealth 2021; 9(3): e24465. https://mhealth.jmir.org/2021/3/e24465
  5. 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, Divya Pathak, and Michal Rosen-Zvi. (2021). AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID-19. Scientific Data 8, 94. https://doi.org/10.1038/s41597-021-00878-y
  6. Jihan Ryu, Emese Sükei, Agnes Norbury, Shelley H Liu, Juan José Campaña-Montes, Enrique Baca-Garcia, Antonio Artés, M Mercedes Perez-Rodriguez. (2021). Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning–Based Ecological Momentary Assessment Study. JMIR Mental Health 2021; 8(9): e30833.
    https://mental.jmir.org/2021/9/e30833
  7. Lucas Miranda, Riya Paul , Benno Pütz, Nikolaos Koutsouleris and Bertram Müller-Myhsok. (2021). Systematic Review of Functional MRI Applications for Psychiatric Disease Subtyping. Frontiers in Psychiatry 2021, 12:665536. doi: 10.3389/fpsyt.2021.665536.
  8. Pelin Gundogdu, Carlos Loucera, Inmaculada Alamo-Alvarez, Joaquin Dopazo and Isabel Nepomuceno. Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data. BioData Mining 15, 1 (2022). https://doi.org/10.1186/s13040-021-00285-4
  9. Aditya Kashyap, Maria Anna Rapsomaniki, Vesna Barros, Anna Fomitcheva-Khartchenko, Adriano Luca Martinelli, Antonio Foncubierta Rodriguez, Maria Gabrani, Michal Rosen-Zvi, and Govind Kaigala. Quantification of tumor heterogeneity: from data acquisition to metric generation. Trends in Biotechnology 2021. https://doi.org/10.1016/j.tibtech.2021.11.006
  10. Diane Duroux, Héctor Climente-González, Chloé-Agathe Azencott, Kristel Van Steen. Interpretable network-guided epistasis detection, GigaScience, Volume 11, 2022, giab093, https://doi.org/10.1093/gigascience/giab093
  11. Andrew Walakira, Junior Ocira, Diane Duroux, Ramouna Fouladi, Miha Moškon, Damjana Rozman, and Kristel Van Steen. Detecting gene–gene interactions from GWAS using diffusion kernel principal components. BMC Bioinformatics 23, 57 (2022). https://doi.org/10.1186/s12859-022-04580-7
  12. 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, and Karsten M. Borgwardt. Prediction of recovery from multiple organ dysfunction syndrome in pediatric sepsis patients. International Conference on Intelligent Systems for Molecular Biology (ISMB 2022) and Bioinformatics 2022, 38 (Supplement_1): i101–i108. https://doi.org/10.1093/bioinformatics/btac229

Preprints

  1. Kadri Künnapuu, Solomon Ioannou, Kadri Ligi, Raivo Kolde, Sven Laur, Jaak Vilo, Peter R. Rijnbeek, Sulev Reisberg. (2021). Trajectories: a framework for detecting temporal clinical event sequences from health data standardized to the OMOP Common Data Model. medRxiv 2021.11.18.21266518; doi:10.1101/2021.11.18.21266518
  2. Fernando Moreno-Pino, Emese Sükei, Pablo M. Olmos, Antonio Artés-Rodríguez. (2022). PyHHMM: A Python Library for Heterogeneous Hidden Markov Models. arXiv:2201.06968; doi:https://doi.org/10.48550/arXiv.2201.06968
  3. Alex Hawkins-Hooker, Giovanni Visonà, Tanmayee Narendra, Mateo Rojas-Carulla, Bernhard Schölkopf, Gabriele Schweikert. (2022). Getting Personal with Epigenetics: Towards Machine-Learning-Assisted Precision Epigenomics. bioRxiv 2022.02.11.479115; doi: https://doi.org/10.1101/2022.02.11.479115
  4. Vesna Barros, Itay Manes, Victor Akinwande, Celia Cintas, Osnat Bar-Shira, MichalOzery-Flato, Yishai Shimoni, Michal Rosen-Zvi. (2022). A causal inference approach for estimating effects of non-pharmaceutical interventions during Covid-19 pandemic. medRxiv 2022.02.28.22271671; doi:https://doi.org/10.1101/2022.02.28.22271671
  5. Joeri Bordes, Lucas Miranda, Maya Reinhardt, Lea Maria Brix, Lotte van Doeselaar, Clara Engelhardt, Benno Puetz, Felix Agakov, Bertram Mueller-Myhsok, Mathias V.Schmidt. (2022). Automatically annotated motion tracking identifies a distinct social behavioral profile following chronic social defeat stress. bioRxiv 2022.06.23.497350; doi: https://doi.org/10.1101/2022.06.23.497350
  6. Diane Duroux, Kristel Van Steen. (2022). netANOVA: novel graph clustering technique with significance assessment via hierarchical ANOVA. bioRxiv 2022.06.28.497741; doi: https://doi.org/10.1101/2022.06.28.497741
  7. Dexiong Chen, Bowen Fan, Carlos Oliver, and Karsten Borgwardt. (2022). Unsupervised Manifold Alignment with Joint Multidimensional Scaling. arXiv:2207.02968; doi:https://doi.org/10.48550/arXiv.2207.02968