Filter

    2023

    1. Curing Cancer with Knowledge Graphs (and other Outrageous Ideas)
      NOVACEK, Vít. Curing Cancer with Knowledge Graphs (and other Outrageous Ideas). In Knowledge Graphs and Semantic Computing Series at University of Illinois Urbana-Champaign. 2023.
      URL
      Name (in English): Curing Cancer with Knowledge Graphs (and other Outrageous Ideas)
      English. Czech Republic.
      Keywords in English: knowledge graphs; link prediction; health informatics
      Type of participation: requested lecture
      International impact: yes
      Changed by: doc. Mgr. Bc. Vít Nováček, PhD, učo 4049. Changed: 23/2/2024 10:57.
      More: https://is.muni.cz/publication/2377458/en

    2022

    1. AI for Cancer Patient Empowerment - Interim Results of the AIcope Project
      NOVACEK, Vít; Marko ŘEHÁČEK; Petr ZELINA and Jana HALÁMKOVÁ. AI for Cancer Patient Empowerment - Interim Results of the AIcope Project. 2022.
      Name (in English): AI for Cancer Patient Empowerment - Interim Results of the AIcope Project
      English. Czech Republic.
      Keywords in English: patient empowement; oncology; AI
      Type of participation: requested lecture
      Changed by: doc. Mgr. Bc. Vít Nováček, PhD, učo 4049. Changed: 31/1/2023 18:30.
      More: https://is.muni.cz/publication/2251603/en
    2. An Artificial Intelligence-Based Tool for Data Analysis and Prognosis in Cancer Patients: Results from the Clarify Study
      TORRENTE, María; Pedro A SOUSA; Roberto HERNÁNDEZ; Mariola BLANCO; Virginia Calvo Ana COLLAZO; Gracinda R GUERREIRO; Beatriz NÚÑEZ; Joao PIMENTAO; Juan Cristóbal SÁNCHEZ; Manuel CAMPOS; Luca COSTABELLO; Vít NOVÁČEK; Ernestina MENASALVAS; María Esther VIDAL; Mariano PROVENCIO and Virginia CALVO. An Artificial Intelligence-Based Tool for Data Analysis and Prognosis in Cancer Patients: Results from the Clarify Study. CANCERS. SWITZERLAND: MDPI, 2022, vol. 14, No 16, p. 1-10. ISSN 2072-6694. Available from: https://doi.org/10.3390/cancers14164041.
      original online article
      RIV/00216224:14330/22:00127570 Article in a journal. English. Switzerland.
      Nováček, Vít (203 Czech Republic, guarantor, belonging to the institution)
      Keywords in English: artificial intelligence; data integration; cancer patients; patient stratification; precision oncology; decision support system
      International impact: yes
      Reviewed: yes
      Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 6/4/2023 13:36.
      More: https://is.muni.cz/publication/2241660/en
    3. Boundary heat diffusion classifier for a semi-supervised learning in a multilayer network embedding
      TIMILSINA, Mohan; Vít NOVÁČEK; Mathieu DAQUIN and Haixuan YANG. Boundary heat diffusion classifier for a semi-supervised learning in a multilayer network embedding. NEURAL NETWORKS. ENGLAND: PERGAMON-ELSEVIER SCIENCE LTD, 2022, vol. 156, No 1, p. 205-217. ISSN 0893-6080. Available from: https://doi.org/10.1016/j.neunet.2022.10.005.
      original online article
      Name in Czech: Boundary heat diffusion classifier for a semi-supervised learning in a multilayer network embedding
      Name (in English): Boundary heat diffusion classifier for a semi-supervised learning in a multilayer network embedding
      RIV/00216224:14330/22:00127569 Article in a journal. English. Netherlands.
      Nováček, Vít (203 Czech Republic, guarantor, belonging to the institution)
      Keywords in English: diffusion; multi-layer embedding; neural network
      International impact: yes
      Reviewed: yes
      Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 28/3/2023 12:05.
      More: https://is.muni.cz/publication/2241658/en
    4. Integration of Medical and Genomic Information to Enhance Relapse Prediction in Early Stage Lung Cancer Patients
      TIMILSINA, Mohan; Dirk FEY; Adrianna JANIK; Maria TORRENTE; Mariano PROVENCIO; Alberto Cruz BERMUDEZ; Enric CARCERENY; Luca COSTABELLO; Delvys Rodrıguez ABREU; Manuel COBO; Rafael Lopez CASTRO; Reyes BERNABE; Maria GUIRADO; Pasquale MINERVINI and Vít NOVÁČEK. Integration of Medical and Genomic Information to Enhance Relapse Prediction in Early Stage Lung Cancer Patients. Online. In Proceedings of the Annual Symposium of the American Medical Informatics Association. Washington, USA: AMIA, 2022, p. 1082-1091. ISSN 1559-4076.
      URL
      Name (in English): Integration of Medical and Genomic Information to Enhance Relapse Prediction in Early Stage Lung Cancer Patients
      RIV/00216224:14330/22:00135069 Proceedings paper. English. United States of America.
      Nováček, Vít (203 Czech Republic, guarantor, belonging to the institution)
      Keywords in English: relapse; lung cancer; imputation; machine learning; genomic scores
      Type of proceedings: post-proceedings
      International impact: yes
      Reviewed: yes
      Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 24/4/2024 14:26.
      More: https://is.muni.cz/publication/2241663/en

    2021

    1. Biological applications of knowledge graph embedding models
      MOHAMED, Sameh K; Ayah NOUNU and Vít NOVÁČEK. Biological applications of knowledge graph embedding models. Briefings in Bioinformatics. Oxford (UK): Oxford University Press, 2021, vol. 22, No 2, p. 1679-1693. ISSN 1467-5463. Available from: https://doi.org/10.1093/bib/bbaa012.
      URL
      Name in Czech: Biological applications of knowledge graph embedding models
      Name (in English): Biological applications of knowledge graph embedding models
      English. United Kingdom of Great Britain and Northern Ireland.
      Keywords in English: biomedical knowledge graphs; knowledge graph embeddings; tensor factorization; link prediction; drug target interactions; polypharmacy side effects
      International impact: yes
      Reviewed: yes
      Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 4/4/2025 05:58.
      More: https://is.muni.cz/publication/2326179/en
    2. On Training Knowledge Graph Embedding Models
      MOHAMED, Sameh K; Vít NOVACEK and Emir MUNOZ. On Training Knowledge Graph Embedding Models. Information. Switzerland: MDPI, 2021, vol. 12, No 4, p. 147-165. ISSN 2078-2489. Available from: https://doi.org/10.3390/info12040147.
      URL
      RIV/00216224:14330/21:00121336 Article in a journal. English. Switzerland.
      Novacek, Vít (203 Czech Republic, guarantor, belonging to the institution)
      Keywords in English: loss functions; knowledge graph embeddings; link prediction
      Reviewed: yes
      Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 23/5/2022 14:41.
      More: https://is.muni.cz/publication/1757476/en

    2020

    1. Accurate prediction of kinase-substrate networks using knowledge graphs
      NOVÁČEK, Vít; Gavin MCGAURAN; David MATALLANAS; Adrián Vallejo BLANCO; Piero CONCA; Emir MUÑOZ; Luca COSTABELLO; Kamalesh KANAKARAJ; Zeeshan NAWAZ; Brian WALSH; Sameh K MOHAMED; Pierre-Yves VANDENBUSSCHE; Colm J RYAN; Walter KOLCH and Dirk FEY. Accurate prediction of kinase-substrate networks using knowledge graphs. PLoS Computational Biology. Cambridge: PLoS, 2020, vol. 16, No 12, p. 1-30. ISSN 1553-734X. Available from: https://doi.org/10.1371/journal.pcbi.1007578.
      URL, URL
      RIV/00216224:14330/20:00118443 Article in a journal. English. United Kingdom of Great Britain and Northern Ireland.
      Nováček, Vít (203 Czech Republic, guarantor, belonging to the institution)
      Keywords in English: knowledge graphs; kinase-substrate networks; phosphorylation prediction; relational machine learning
      International impact: yes
      Reviewed: yes
      Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 10/5/2021 06:22.
      More: https://is.muni.cz/publication/1754803/en