A comprehensive review and comparison of different computational methods for protein remote homology detection

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ProteinNet: a standardized data set for machine learning of protein structure (2019, background): “Creating a matching validation set is thus non-trivial owing to the difficulty of detecting weak homology [16, 17].”
BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches (2019, background): “…analysis task is to investigate the structure and function characteristics of the entire sequences, such as enhancer identification (7,8), protein remote homology detection and fold recognition (9–12), recombination spot identification (13,14), DNA / RNA binding protein identification (15,16), etc.”
Protein remote homology detection based on bidirectional long short-term memory (2017, methodology): “For more information of these methods, please refer to a recent review paper [1].”