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#ECCB18 is on. I was supposed to give 1 of the 3 accepted talks from our team at @4Catalyzer. But I couldn't make it bc of ongoing green card application. I will briefly highlight our 3 works here. (thread) >>>
I was going to present "Functional Annotation of Genes Through Integration of Disparate Data Sources with Deep Learning"
We developed an end-to-end trainable framework which performs data integration and functional prediction through a deep learning framework.
We developed an end-to-end trainable framework which performs data integration and functional prediction through a deep learning framework.
Model integration speeds up the convergence and improves the performance of the functional annotation tasks.
Our framework improves the quality of functional annotations by integrating different data sources through cross-modality encoders without handcrafting features.
Our framework improves the quality of functional annotations by integrating different data sources through cross-modality encoders without handcrafting features.
