Dimitar Hristozov

Evotec (United Kingdom) — United Kingdom

Computer Science · Physical Sciences

10h-index353citations24works3.52yr avg
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Research Topics

Computational Drug Discovery Methods(13), Machine Learning in Materials Science(8), Chemical Synthesis and Analysis(5), Analytical Chemistry and Chromatography(4), Phytochemistry and Biological Activities(4)

Publications24 total

Synthetically accessible de novo design using reaction vectors: Application to PARP1 inhibitors**
Molecular Informatics·2024· 6 citedOpen Access
<scp>AI</scp> ‐Based Protein Structure Predictions and Their Implications in Drug Discovery
2024· 1 citedOpen Access
dunXai: DO-U-Net for Explainable (Multi-label) Image Classification
Lecture notes in computer science·2022
RENATE: A Pseudo‐retrosynthetic Tool for Synthetically Accessible <i>de novo</i> Design
Molecular Informatics·2021· 16 citedOpen Access
Deep Learning and Computational Chemistry
Methods in molecular biology·2021· 8 cited
Enhancing reaction-based de novo design using a multi-label reaction class recommender
Journal of Computer-Aided Molecular Design·2020· 19 citedOpen Access
Development and Application of a Data-Driven Reaction Classification Model: Comparison of an Electronic Lab Notebook and Medicinal Chemistry Literature
Journal of Chemical Information and Modeling·2019· 52 citedOpen Access
Multiobjective<i>De Novo</i>Design of Synthetically Accessible Compounds
2013· 7 cited
Data Collation and Curation for the COSMOS Database
2013
ChemInform Abstract: Validation of Reaction Vectors for de novo Design
ChemInform·2012· 4 cited
Validation of Reaction Vectors for<i>de Novo</i>Design
ACS symposium series·2011· 6 cited
ChemInform Abstract: Exploring Potency and Selectivity Receptor Antagonist Profiles Using a Multilabel Classification Approach: The Human Adenosine Receptors as a Key Study.
ChemInform·2010
Applications of Integrated Data Mining Methods to Exploring Natural Product Space for Acetylcholinesterase Inhibitors
Combinatorial Chemistry & High Throughput Screening·2009· 20 cited
Exploring Potency and Selectivity Receptor Antagonist Profiles Using a Multilabel Classification Approach: The Human Adenosine Receptors as a Key Study
Journal of Chemical Information and Modeling·2009· 20 cited
ChemInform Abstract: Multilabeled Classification Approach to Find a Plant Source for Terpenoids.
ChemInform·2008
ChemInform Abstract: Ligand‐Based Virtual Screening by Novelty Detection with Self‐Organizing Maps.
ChemInform·2008
Multilabeled Classification Approach To Find a Plant Source for Terpenoids
Journal of Chemical Information and Modeling·2007· 12 cited
Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios
Journal of Computer-Aided Molecular Design·2007· 51 cited
Ligand-Based Virtual Screening by Novelty Detection with Self-Organizing Maps
Journal of Chemical Information and Modeling·2007· 31 cited
Sesquiterpene Lactones Based Classification of the Family Asteracease Using Neural Networks and ϰ‐Nearest Neighbors.
ChemInform·2007
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Frequent Co-authors

Johann Gasteiger(11), Michael J. Bodkin(7), Valerie J. Gillet(7), Beining Chen(6), Gian Marco Ghiandoni(4), James E. A. Wallace(4), James Webster(4), Fernando B. Da Costa(4), Tudor I. Oprea(3), Lothar Terfloth(3), Claudia E. Domini(2), Antonio Canals(2), Lisa Michielan(2), Stephanie Federico(2), Barbara Cacciari(2), Karl‐Norbert Klotz(2), Giampiero Spalluto(2), Stefano Moro(2), Tim James(2), H. K. Patel(2)