Author

Aleksandra Kalisz

ORCID 0000-0003-3696-1535Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1

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Anthony R BradleyiD· 1 shared Charlotte Mary DeaneiD· 1 shared Fergus ImrieiD· 1 shared Maranga MokayaiD· 1 shared Willem P. van HoorniD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

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5 top collaborators · 10 mutual co-author links

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1 shared paperBioinformatics

Anthony R BradleyORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintJul 15, 2022

Testing the Limits of SMILES-based De Novo Molecular Generation with Curriculum and Deep Reinforcement Learning

Maranga Mokaya, Fergus Imrie, Willem P. van Hoorn…·Charlotte Mary Deane

This paper evaluates RNN-based de novo molecular generation under limited training data and proposes a curriculum learning approach to improve diversity and control, while highlighting limitations of SMILES representations.

1 citation

deep learningmachine learning (classical)

𝕏 PostBluesky