2 citations · 5 across the 3 of their papers we have counts for
3 papers
Multi-modal Representation Learning Enables Accurate Protein Function Prediction in Low-Data Setting
Serbülent Ünsal, Sinem Özdemir, Bünyamin Kasap +4
In this study, we propose HOPER (HOlistic ProtEin Representation), a novel multimodal learning framework designed to enhance protein function prediction (PFP) in low-data settings.…
Democratising Knowledge Representation with BioCypher
Sebastian Lobentanzer, Patrick Aloy, Jan Baumbach +26
Standardising the representation of biomedical knowledge among all researchers is an insurmountable task, hindering the effectiveness of many computational methods. To facilitate h…
Multi-task Deep Neural Networks in Automated Protein Function Prediction
Ahmet Sureyya Rifaioglu, Tunca Doğan, Maria Jesus Martin +2
In recent years, deep learning algorithms have outperformed the state-of-the art methods in several areas thanks to the efficient methods for training and for preventing overfittin…