Works matching IS 20954689 AND DT 2018 AND VI 6 AND IP 4
Results: 7
Subnetwork identification and chemical modulation for neural regeneration: A study combining network guided forest and heat diffusion model.
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- Quantitative Biology, 2018, v. 6, n. 4, p. 321, doi. 10.1007/s40484-018-0159-0
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- Article
Selecting near-native protein structures from ab initio models using ensemble clustering.
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- Quantitative Biology, 2018, v. 6, n. 4, p. 307, doi. 10.1007/s40484-018-0158-1
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- Article
Analysis of protein features and machine learning algorithms for prediction of druggable proteins.
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- Quantitative Biology, 2018, v. 6, n. 4, p. 334, doi. 10.1007/s40484-018-0157-2
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- Article
Characterizing robustness and sensitivity of convolutional neural networks for quantitative analysis of mitochondrial morphology.
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- Quantitative Biology, 2018, v. 6, n. 4, p. 344, doi. 10.1007/s40484-018-0156-3
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- Article
WaveNano: a signal-level nanopore base-caller via simultaneous prediction of nucleotide labels and move labels through bi-directional WaveNets.
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- Quantitative Biology, 2018, v. 6, n. 4, p. 359, doi. 10.1007/s40484-018-0155-4
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- Article
On the statistical significance of protein complex.
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- Quantitative Biology, 2018, v. 6, n. 4, p. 313, doi. 10.1007/s40484-018-0153-6
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- Article
Experimental design and model reduction in systems biology.
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- Quantitative Biology, 2018, v. 6, n. 4, p. 287, doi. 10.1007/s40484-018-0150-9
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- Article