Developments and accessibility of computational methods within machine learning and deep learning have led to the resurgence of methods for computer assisted synthesis planning (CASP). In this paper we introduce our viewpoints on the analysis of reaction data, model building and evaluation. We show how the models’ performance is affected by the specificity of the extracted reaction rules (templates) and outline the direction of research within our group
With the increasing application of deep-learning-based generative models for de novo molecule design...
We explore advantages that can be gained from using expressive logic languages for semantic modelli...
© The Royal Society of Chemistry. Computer aided synthesis planning of synthetic pathways with green...
Computer-aided synthesis planning (CASP) has been helping chemists to synthesize novel molecules at ...
Copyright © 2020 American Chemical Society. This work presents efforts to augment the performance of...
Computer Assisted Synthesis Planning (CASP) has gained considerable interest as of late. Herein we i...
Computer Assisted Synthesis Planning (CASP) has gained considerable interest as of late. Herein we i...
With the idea of retrosynthetic analysis, which was raised in the 1960s, chemical synthesis analysis...
State of the art computer-aided synthesis planning models are naturally biased toward commonly repor...
In 2020, a "hybrid" expert-AI computer program called Chematica (a.k.a. Synthia) was shown...
Several tools for the computational planning of synthetic routes have been developed over the last 6...
When computers plan multistep syntheses, they can rely either on expert knowledge or information mac...
Computer Aided Synthesis Planning (CASP) development of reaction routes requires understanding of co...
Computer-aided synthesis design, automation, and analytics assisted by machine learning are promisin...
Chemical synthesis planning is a key aspect in many fields of chemistry, especially drug discovery. ...
With the increasing application of deep-learning-based generative models for de novo molecule design...
We explore advantages that can be gained from using expressive logic languages for semantic modelli...
© The Royal Society of Chemistry. Computer aided synthesis planning of synthetic pathways with green...
Computer-aided synthesis planning (CASP) has been helping chemists to synthesize novel molecules at ...
Copyright © 2020 American Chemical Society. This work presents efforts to augment the performance of...
Computer Assisted Synthesis Planning (CASP) has gained considerable interest as of late. Herein we i...
Computer Assisted Synthesis Planning (CASP) has gained considerable interest as of late. Herein we i...
With the idea of retrosynthetic analysis, which was raised in the 1960s, chemical synthesis analysis...
State of the art computer-aided synthesis planning models are naturally biased toward commonly repor...
In 2020, a "hybrid" expert-AI computer program called Chematica (a.k.a. Synthia) was shown...
Several tools for the computational planning of synthetic routes have been developed over the last 6...
When computers plan multistep syntheses, they can rely either on expert knowledge or information mac...
Computer Aided Synthesis Planning (CASP) development of reaction routes requires understanding of co...
Computer-aided synthesis design, automation, and analytics assisted by machine learning are promisin...
Chemical synthesis planning is a key aspect in many fields of chemistry, especially drug discovery. ...
With the increasing application of deep-learning-based generative models for de novo molecule design...
We explore advantages that can be gained from using expressive logic languages for semantic modelli...
© The Royal Society of Chemistry. Computer aided synthesis planning of synthetic pathways with green...