191 citations · 284 across the 23 of their papers we have counts for
5 papers · 1 filter
Exploring Molecular Odor Taxonomies for Structure-based Odor Predictions using Machine Learning
Akshay Sajan, Stijn Sluis, Reza Haydarlou +6
One of the key challenges to predict odor from molecular structure is unarguably our limited understanding of the odor space and the complexity of the underlying structure-odor rel…
Explainable AI in Healthcare: to Explain, to Predict, or to Describe?
Alex Carriero, Anne de Hond, Bram Cappers +4
Explainable Artificial Intelligence (AI) methods are designed to provide information about how AI-based models make predictions. In healthcare, there is a widespread expectation th…
Beyond Olfaction: New Insights into Human Odorant Binding Proteins
Mifen Chen, Soufyan Lakbir, Mihyeon Jeon +3
Until today, the exact function of mammalian odorant binding proteins (OBPs) remains a topic of debate. Although their main established function lacks direct evidence in human olfa…
PLM-eXplain: Divide and Conquer the Protein Embedding Space
Jan van Eck, Dea Gogishvili, Wilson Silva +1
Protein language models (PLMs) have revolutionised computational biology through their ability to generate powerful sequence representations for diverse prediction tasks. However,…
Disentangled and Interpretable Multimodal Attention Fusion for Cancer Survival Prediction
Aniek Eijpe, Soufyan Lakbir, Melis Erdal Cesur +3
To improve the prediction of cancer survival using whole-slide images and transcriptomics data, it is crucial to capture both modality-shared and modality-specific information. How…