Artikel
Open Access
CBSF: A New Empirical Scoring Function for Docking Parameterized by Weights of Neural Network
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Raulia R. Syrlybaeva
und
Marat R. Talipov
Veröffentlicht/Copyright:
31. Dezember 2019
Received: 2019-10-07
Accepted: 2019-12-04
Published Online: 2019-12-31
© 2019 Raulia R. Syrlybaeva et al., published by De Gruyter
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Creative Commons
BY 4.0
Artikel in diesem Heft
- Special Issue: Biomolecular data modeling and mining.
- AngularQA: Protein Model Quality Assessment with LSTM Networks
- A study on discrete and discrete fractional pharmacokinetics-pharmacodynamics models for tumor growth and anti-cancer effects
- Nonlinear simulation of an elastic tumor-host interface
- Towards an understanding of RNA structural modalities: a riboswitch case study
- Special Issue Develop. Appl. Novel Meth. Comput. Biol.
- Using computational approaches to study dengue virus capsid assembly
- Thermal Response in Cellulose Iβ Based on Molecular Dynamics
- Analyzing high dimensional correlated data using feature ranking and classifiers
- CBSF: A New Empirical Scoring Function for Docking Parameterized by Weights of Neural Network
- Special Issue MMBB
- A treecode based on barycentric Hermite interpolation for electrostatic particle interactions
