Search Results - "Vogt, Martin" :: K.UTB vyhledávací portál

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Advancing Cheminformatics-A Theme Issue in Honor of Professor Jürgen Bajorath

by Vogt, Martin
Published in Molecules (Basel, Switzerland) (14.04.2022)

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Exploring chemical space — Generative models and their evaluation

by Vogt, Martin
Published in Artificial intelligence in the life sciences (01.12.2023)

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Current Trends in Ligand-Based Virtual Screening: Molecular Representations, Data Mining Methods, New Application Areas, and Performance Evaluation

by Geppert, Hanna, Vogt, Martin, Bajorath, Jürgen
Published in Journal of chemical information and modeling (22.02.2010)

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Set-Theoretic Formalism for Treating Ligand-Target Datasets

by Maggiora, Gerald, Vogt, Martin
Published in Molecules (Basel, Switzerland) (07.12.2021)

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MMP-Cliffs: Systematic Identification of Activity Cliffs on the Basis of Matched Molecular Pairs

by Hu, Xiaoying, Hu, Ye, Vogt, Martin, Stumpfe, Dagmar, Bajorath, Jürgen
Published in Journal of chemical information and modeling (25.05.2012)

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Automatic Identification of Analogue Series from Large Compound Data Sets: Methods and Applications

by Naveja, José J, Vogt, Martin
Published in Molecules (Basel, Switzerland) (31.08.2021)

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Prediction of activity cliffs on the basis of images using convolutional neural networks

by Iqbal, Javed, Vogt, Martin, Bajorath, Jürgen
Published in Journal of computer-aided molecular design (01.12.2021)

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Assessment of Understanding: Student Teachers’ Preparation, Implementation and Reflection of a Lesson Plan for Science

by Juhler, Martin Vogt
Published in Research in science education (Australasian Science Education Research Association) (01.06.2018)

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Chemoinformatics: A view of the field and current trends in method development

by Vogt, Martin, Bajorath, Jürgen
Published in Bioorganic & medicinal chemistry (15.09.2012)

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Computational Method for Quantitative Comparison of Activity Landscapes on the Basis of Image Data

by Iqbal, Javed, Vogt, Martin, Bajorath, Jürgen
Published in Molecules (Basel, Switzerland) (29.08.2020)

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DeepAC – conditional transformer-based chemical language model for the prediction of activity cliffs formed by bioactive compounds

by Chen, Hengwei, Vogt, Martin, Bajorath, Jürgen
Published in Digital discovery (05.12.2022)

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From SAR Diagnostics to Compound Design: Development Chronology of the Compound Optimization Monitor (COMO) Method

by Yonchev, Dimitar, Vogt, Martin, Bajorath, Jürgen
Published in Molecular informatics (01.12.2020)

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ccbmlib - a Python package for modeling Tanimoto similarity value distributions [version 1; peer review: 2 approved]

by Vogt, Martin, Bajorath, Jürgen
Published in F1000 research (2020)

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Comprehensive Data-Driven Assessment of Non-Kinase Targets of Inhibitors of the Human Kinome

by Mobasher, Mona, Vogt, Martin, Xerxa, Elena, Bajorath, Jürgen
Published in Biomolecules (Basel, Switzerland) (21.02.2024)

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Scaffold Hopping Using Two-Dimensional Fingerprints: True Potential, Black Magic, or a Hopeless Endeavor? Guidelines for Virtual Screening

by Vogt, Martin, Stumpfe, Dagmar, Geppert, Hanna, Bajorath, Jürgen
Published in Journal of medicinal chemistry (12.08.2010)

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Activity landscape image analysis using convolutional neural networks

by Iqbal, Javed, Vogt, Martin, Bajorath, Jürgen
Published in Journal of cheminformatics (18.05.2020)

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Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures

by Zhang, Bijun, Vogt, Martin, Maggiora, Gerald M., Bajorath, Jürgen
Published in Journal of computer-aided molecular design (01.10.2015)

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Support Vector Machine Classification and Regression Prioritize Different Structural Features for Binary Compound Activity and Potency Value Prediction

by Rodríguez-Pérez, Raquel, Vogt, Martin, Bajorath, Jürgen
Published in ACS omega (31.10.2017)

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Learning functional group chemistry from molecular images leads to accurate prediction of activity cliffs

by Iqbal, Javed, Vogt, Martin, Bajorath, Jürgen
Published in Artificial intelligence in the life sciences (01.12.2021)

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ccbmlib - a Python package for modeling Tanimoto similarity value distributions [version 2; peer review: 2 approved]

by Vogt, Martin, Bajorath, Jürgen
Published in F1000 research (01.01.2020)

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