Scholar Data

Datasets

MOESM2 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 2. HBA database.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

1 Citation0 Mentions13% FAIR0.7 Dataset Index

10.6084/m9.figshare.9809711January 2019

MOESM2 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 2. HBA database.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

0 Citations0 Mentions13% FAIR0.1 Dataset Index

10.6084/m9.figshare.9809711.v1January 2019

MOESM5 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 3. HBD database.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

1 Citation0 Mentions48% FAIR1.5 Dataset Index

10.6084/m9.figshare.9809714January 2019

MOESM5 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 3. HBD database.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

0 Citations0 Mentions13% FAIR0.1 Dataset Index

10.6084/m9.figshare.9809714.v1January 2019

MOESM6 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 4. HBA complexes database.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

1 Citation0 Mentions13% FAIR0.7 Dataset Index

10.6084/m9.figshare.9809717January 2019

MOESM6 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 4. HBA complexes database.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

0 Citations0 Mentions56% FAIR0.6 Dataset Index

10.6084/m9.figshare.9809717.v1January 2019

MOESM7 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 5. HBD complexes database.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

1 Citation0 Mentions13% FAIR0.7 Dataset Index

10.6084/m9.figshare.9809720January 2019

MOESM7 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 5. HBD complexes database.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

0 Citations0 Mentions13% FAIR0.1 Dataset Index

10.6084/m9.figshare.9809720.v1January 2019

MOESM8 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 8. Source code for training the HBA and HBD models and two example molecules.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

1 Citation0 Mentions13% FAIR0.7 Dataset Index

10.6084/m9.figshare.9809729January 2019

MOESM8 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Additional file 8. Source code for training the HBA and HBD models and two example molecules.

Authors

Bauer, Christoph ;
Schneider, Gisbert ;
Gรถller, Andreas

0 Citations0 Mentions13% FAIR0.3 Dataset Index

10.6084/m9.figshare.9809729.v1January 2019

Automated Author Profile
Gรถller, Andreas

Gรถller, Andreas

Current S-Index

Average Dataset Index per Dataset

Total Datasets

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Cumulative Mentions Over Time

Datasets

MOESM2 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM2 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM5 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM5 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM6 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM6 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM7 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM7 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM8 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM8 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Automated Author ProfileGรถller, Andreas

Gรถller, Andreas

Current S-Index

Average Dataset Index per Dataset

Total Datasets

Average FAIR Score

Total Citations

Total Mentions

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

MOESM2 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM2 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM5 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM5 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM6 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM6 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM7 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM7 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM8 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

MOESM8 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

Automated Author Profile
Gรถller, Andreas