Table 1.
Categories of solutions that use different inter-relations between GO terms.
| Solutions | Inter-relations | Basic techniques | |
|---|---|---|---|
| Predicting missing annotations | ProWL (Yu et al., 2012b) | Flat | Weak label learning |
| ProDM (Yu et al., 2013a) | Flat | Weak label learning | |
| ProHG (Liu et al., 2016) | Flat | Random walks | |
| ITSS (Tao et al., 2007) | Hierarchical | Semantic similarity | |
| NtN (Done et al., 2010) | Hierarchical | Singular value decomposition | |
| dRW (Yu et al., 2015d) | Hierarchical | Random walks | |
| PILL (Yu et al., 2015b) | Hierarchical | Random walks | |
| DeepGO (Kulmanov et al., 2017) | Hierarchical | Deep learning | |
| NewGOA (Yu et al., 2018a) | Hierarchical | Bi-random walks | |
| AsyRW (Zhao et al., 2019b) | Hierarchical | Bi-random walks | |
| Identifying noisy annotations | NoisyGOA (Lu et al., 2016) | Hierarchical | Semantic-based kNN |
| NoGOA (Yu et al., 2017c) | Hierarchical | Sparse representation | |
| NFA (Lu et al., 2018) | Hierarchical | Sparse representation | |
| Selecting negative annotations | ALBias (Youngs et al., 2013) | Flat | Bayesian model |
| ProPN (Fu et al., 2016b) | Flat | Random walks | |
| SNOB (Youngs et al., 2014) | Hierarchical | Bayesian model | |
| NETL (Youngs et al., 2014) | Hierarchical | Topic model | |
| IFDR (Yu et al., 2017b) | Hierarchical | Semi-supervised linear regression | |
| NegGOA (Fu et al., 2016a) | Hierarchical | Random walks |