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Jonas Boström
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2020 – today
- 2022
- [j16]Giovanni Bolcato, Esther Heid
, Jonas Boström
On the Value of Using 3D Shape and Electrostatic Similarities in Deep Generative Methods. J. Chem. Inf. Model. 62(6): 1388-1398 (2022) - 2021
- [j15]Jonas Boström
Transformers for future medicinal chemists. Nat. Mach. Intell. 3(2): 102-103 (2021) - [j14]Jon Paul Janet
Reusability report: Learning the language of synthetic methods used in medicinal chemistry. Nat. Mach. Intell. 3(7): 572-575 (2021)
2010 – 2019
- 2019
- [j13]Niclas Ståhl
Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design. J. Chem. Inf. Model. 59(7): 3166-3176 (2019) - [j12]Niclas Ståhl, Göran Falkman
Deep Convolutional Neural Networks for the Prediction of Molecular Properties: Challenges and Opportunities Connected to the Data. J. Integr. Bioinform. 16(1) (2019) - 2018
- [c1]Niclas Ståhl, Göran Falkman
Improving the Use of Deep Convolutional Neural Networks for the Prediction of Molecular Properties. PACBB 2018: 71-79 - 2017
- [j11]Thomas C. Schmidt
Discovery and Evaluation of Anti-Fibrinolytic Plasmin Inhibitors Derived from 5-(4-Piperidyl)isoxazol-3-ol (4-PIOL). J. Chem. Inf. Model. 57(7): 1703-1714 (2017) - 2015
- [j10]Magnus Norrby, Christoph Grebner, Joakim Eriksson, Jonas Boström
Molecular Rift: Virtual Reality for Drug Designers. J. Chem. Inf. Model. 55(11): 2475-2484 (2015) - 2014
- [j9]Noel M. O'Boyle, Roger A. Sayle
What compound should I make next? Using Matched Molecular Series for prospective medicinal chemistry. J. Cheminformatics 6(S-1): 5 (2014) - 2013
- [j8]Victor Vysotskiy, Jonas Boström, Valera Veryazov
A new module for constrained multi-fragment geometry optimization in internal coordinates implemented in the MOLCAS package. J. Comput. Chem. 34(30): 2657-2665 (2013) - 2012
- [j7]Christian Tyrchan
Exploiting Structural Information in Patent Specifications for Key Compound Prediction. J. Chem. Inf. Model. 52(6): 1480-1489 (2012) - 2010
- [j6]Asbjørn Holt, Jonas Boström, Gunnar Karlström, Roland Lindh
A NEMO potential that includes the dipole-quadrupole and quadrupole-quadrupole polarizability. J. Comput. Chem. 31(8): 1583-1591 (2010)
2000 – 2009
- 2006
- [j5]Jens Sadowski, Jonas Boström:
MIMUMBA Revisited: Torsion Angle Rules for Conformer Generation Derived from X-ray Structures. J. Chem. Inf. Model. 46(6): 2305-2309 (2006) - 2003
- [j4]Jonas Boström, Markus Böhm, Klaus Gundertofte, Gerhard Klebe:
A 3D QSAR Study on a Set of Dopamine D4 Receptor Antagonists. J. Chem. Inf. Comput. Sci. 43(3): 1020-1027 (2003) - 2001
- [j3]Jonas Boström
Reproducing the conformations of protein-bound ligands: A critical evaluation of several popular conformational searching tools. J. Comput. Aided Mol. Des. 15(12): 1137-1152 (2001) - 2000
- [j2]Jonas Boström
A pharmacophore model for dopamine D4 receptor antagonists. J. Comput. Aided Mol. Des. 14(8): 769-786 (2000)
1990 – 1999
- 1998
- [j1]Jonas Boström
Conformational energy penalties of protein-bound ligands. J. Comput. Aided Mol. Des. 12(4): 383-396 (1998)
Coauthor Index
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