Browsing by Author "Karadeniz, İlknur"
Now showing items 1-5 of 5
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BOUN-ISIK participation: an unsupervised approach for the named entity normalization and relation extraction of Bacteria Biotopes
Karadeniz, İlknur; Tuna, Ömer Faruk; Özgu, Arzucan (Association for Computational Linguistics (ACL), 2019-11-04)This paper presents our participation at the Bacteria Biotope Task of the BioNLP Shared Task 2019. Our participation includes two systems for the two subtasks of the Bacteria Biotope Task: the normalization of entities ... -
Çizge evrişim ağı kullanarak patojen-konak ağlarında protein etkileşim tahmini
Koca, Mehmet Burak; Karadeniz, İlknur; Nourani, Esmaeil; Sevilgen, Fatih Erdoğan (IEEE, 2021-06-09)Proteinler yaşamsal faaliyetlerin gerçekleşmesinde kritik rol oynayan biyolojik moleküllerdir. Konak canlı proteinleri ile patojen proteinleri arasındaki etkileşimler patojenkonak etkileşim (PHI) ağlarını oluşturmaktadır. ... -
Graph convolutional network based virus-human protein-protein interaction prediction for novel viruses
Koca, Mehmet Burak; Nourani, Esmaeil; Abbasoğlu, Ferda; Karadeniz, İlknur; Sevilgen, Fatih Erdoğan (Elsevier Ltd, 2022-08-13)Computational identification of human-virus protein-protein interactions (PHIs) is a worthwhile step towards understanding infection mechanisms. Analysis of the PHI networks is important for the determination of path-ogenic ... -
ISIKSumm at BioLaySumm task 1: BART-based summarization system enhanced with Bio-entity labels
Çolak, Çağla; Karadeniz, İlknur (Association for Computational Linguistics (ACL), 2023-07-13)Communicating scientific research to the general public is an essential yet challenging task. Lay summaries, which provide a simplified version of research findings, can bridge the gap between scientific knowledge and ... -
ISIKUN at the FinCausal 2020: Linguistically informed machine-learning approach for causality identification in financial documents
Özenir, Hüseyin Gökberk; Karadeniz, İlknur (Association for Computational Linguistics (ACL), 2020)This paper presents our participation to the FinCausal-2020 Shared Task whose ultimate aim is to extract cause-effect relations from a given financial text. Our participation includes two systems for the two sub-tasks of ...
