Multitask Learning for Protein Subcellular Location Prediction

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An Overview of Multi-task Learning (2018, methodology): “…personalized brain–computer interfaces [105], MHC-I binding prediction [106], splice-site prediction [106], protein subcellular location prediction [107], Alzheimer’s disease assessment scale cognitive subscale [108], prediction of cognitive outcomes from neuroimaging measures in Alzheimer’s…”
A Survey on Multi-Task Learning (2017, methodology): “In [187], two multi-task methods proposed in [11], [73] are used for protein subcellular location prediction.”
Feature-based transfer learning with real-world applications (2010, background): “In Bioinformatics, motivated by that different biological entities, such as organisms, genes, etc, may be related to each other from a biological point of view, some research works have been proposed to apply transfer learning techniques to solve various computational biological problems, such as id”
A Survey of Transfer and Multitask Learning in Bioinformatics (2011, methodology): “[36] compared a multitask learning method with a common feature representation.”
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning (2016, background): “When considering any type of prediction task per individual subject in such settings (for example, whether the subject is indeed suffering a speciﬁc medical afﬂiction or not), relying solely on the scarce data per individual most often leads to inadequate predictive performance.”