Geometry optimization method versus predictive ability in QSPR modeling for ionic liquids.
- Published in:
- Journal of Computer-Aided Molecular Design, 2016, v. 30, n. 2, p. 165, doi. 10.1007/s10822-016-9894-3
- By:
- Publication type:
- Article
Works matching IS 0920654X AND DT 2016 AND VI 30 AND IP 2
Results: 5
1
2
Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout.
- Published in:
- Journal of Computer-Aided Molecular Design, 2016, v. 30, n. 2, p. 177, doi. 10.1007/s10822-016-9895-2
- By:
- Publication type:
- Article
3
Extrapolative prediction using physically-based QSAR.
- Published in:
- Journal of Computer-Aided Molecular Design, 2016, v. 30, n. 2, p. 127, doi. 10.1007/s10822-016-9896-1
- By:
- Publication type:
- Article
4
Confidence limits, error bars and method comparison in molecular modeling. Part 2: comparing methods.
- Published in:
- Journal of Computer-Aided Molecular Design, 2016, v. 30, n. 2, p. 103, doi. 10.1007/s10822-016-9904-5
- By:
- Publication type:
- Article
5
A β-solenoid model of the Pmel17 repeat domain: insights to the formation of functional amyloid fibrils.
- Published in:
- Journal of Computer-Aided Molecular Design, 2016, v. 30, n. 2, p. 153, doi. 10.1007/s10822-015-9892-x
- By:
- Publication type:
- Article