Comments (4)
based on the past couple reviews I've read there doesn't appear to be too much niche carving...they all are quite similar although they claim to offer unique perspectives (either make the claim or omit citations to alternative reviews all together!).
I think we should try to carve a niche - not sure what it could be yet though
from deep-review.
The published version appeared recently http://doi.org/10.1093/bib/bbw068
from deep-review.
Another wide-net-casting review (225 references!). Very similar to #47 and #28. Structure is as follows:
- Introduce MLP, CNN, RNN, and "emergent architechtures"
- Review each of these deep learning techniques in the following bioinformatics topics
- Omics
- Imaging
- Signal processing (e.g. EEG)
- Discussion
Their discussion is also broken up into sections that we've seen before:
- Limited and imbalanced data
- Black-box algorithms
- Similar to #28
- Do provide some insight into "changing the black-box into the white-box"
- Hyperparameter selection difficulty
- Multimodal deep learning
- Data integration
- Very limited discussion that we can greatly expand upon
- Accelerating deep learning
- discusses optimization strategies
- computational hurdles, etc.
- Future of deep learning
- they do briefly touch upon how they view unsupervised tasks as gaining traction
- e.g. Adversarial Nets
from deep-review.
Cited in the intro
from deep-review.
Related Issues (20)
- Potential Reorganization HOT 7
- Deep Learning for the Life Sciences
- Deepprune: Learning Efficient and Interpretable Convolutional Networks Through Weight Pruning for Predicting DNA-Protein Binding
- Predicting or Pretending: Artificial Intelligence for Protein-Ligand Interactions Lack of Sufficiently Large and Unbiased Datasets
- In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening
- Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening
- Update subsection: Structure-based prediction of bioactivity HOT 2
- Update 'Imaging applications in healthcare'
- Applications in sleep research HOT 2
- LISA: Towards Learned DNA Sequence Search HOT 1
- DeepArk: modeling cis-regulatory codes of model species with deep learning
- Human Protein Atlas (HPA) Cell Type Prediction using Deep Learning and estimating uncertainty HOT 2
- How can one cite this dynamic review? HOT 3
- Update for 2020? HOT 3
- Add a Systematic Text-Mining Component to the Review? HOT 3
- Titrating gene expression using libraries of systematically attenuated CRISPR guide RNAs HOT 3
- Alpha Fold 2 HOT 1
- feature and labels HOT 1
- Update in Proteomics mass spectrometry HOT 2
- Consider change to reference 346 HOT 9
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from deep-review.