Implementation of an AI-assisted fragment-generator in an open-source platform

We recently reported a deep learning model to facilitate fragment library design, which is critical for efficient hit identification. However, our model was implemented in Python. We have now created an implementation in the KNIME graphical pipelining environment which we hope will allow experimenta...

Descripción completa

Detalles Bibliográficos
Autores principales: Bilsland, Alan E., Pugliese, Angelo, Bower, Justin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: RSC 2022
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9579942/
https://www.ncbi.nlm.nih.gov/pubmed/36320432
http://dx.doi.org/10.1039/d2md00152g
_version_ 1784812289844576256
author Bilsland, Alan E.
Pugliese, Angelo
Bower, Justin
author_facet Bilsland, Alan E.
Pugliese, Angelo
Bower, Justin
author_sort Bilsland, Alan E.
collection PubMed
description We recently reported a deep learning model to facilitate fragment library design, which is critical for efficient hit identification. However, our model was implemented in Python. We have now created an implementation in the KNIME graphical pipelining environment which we hope will allow experimentation by users with limited programming knowledge.
format Online
Article
Text
id pubmed-9579942
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher RSC
record_format MEDLINE/PubMed
spelling pubmed-95799422022-10-31 Implementation of an AI-assisted fragment-generator in an open-source platform Bilsland, Alan E. Pugliese, Angelo Bower, Justin RSC Med Chem Chemistry We recently reported a deep learning model to facilitate fragment library design, which is critical for efficient hit identification. However, our model was implemented in Python. We have now created an implementation in the KNIME graphical pipelining environment which we hope will allow experimentation by users with limited programming knowledge. RSC 2022-08-15 /pmc/articles/PMC9579942/ /pubmed/36320432 http://dx.doi.org/10.1039/d2md00152g Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Bilsland, Alan E.
Pugliese, Angelo
Bower, Justin
Implementation of an AI-assisted fragment-generator in an open-source platform
title Implementation of an AI-assisted fragment-generator in an open-source platform
title_full Implementation of an AI-assisted fragment-generator in an open-source platform
title_fullStr Implementation of an AI-assisted fragment-generator in an open-source platform
title_full_unstemmed Implementation of an AI-assisted fragment-generator in an open-source platform
title_short Implementation of an AI-assisted fragment-generator in an open-source platform
title_sort implementation of an ai-assisted fragment-generator in an open-source platform
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9579942/
https://www.ncbi.nlm.nih.gov/pubmed/36320432
http://dx.doi.org/10.1039/d2md00152g
work_keys_str_mv AT bilslandalane implementationofanaiassistedfragmentgeneratorinanopensourceplatform
AT puglieseangelo implementationofanaiassistedfragmentgeneratorinanopensourceplatform
AT bowerjustin implementationofanaiassistedfragmentgeneratorinanopensourceplatform

Ejemplares similares