Hasil Pencarian - Dominik Heider

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  1. 1
    Gaussian noise up-sampling is better suited than SMOTE and ADASYN for clinical decision making

    Gaussian noise up-sampling is better suited than SMOTE and ADASYN for clinical decision making oleh Jacqueline Beinecke, Dominik Heider

    Diterbitkan 2021-11-01
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  2. 2
    Encodings and models for antimicrobial peptide classification for multi-resistant pathogens

    Encodings and models for antimicrobial peptide classification for multi-resistant pathogens oleh Sebastian Spänig, Dominik Heider

    Diterbitkan 2019-03-01
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  3. 3
    Large language models and their applications in bioinformatics

    Large language models and their applications in bioinformatics oleh Oluwafemi A. Sarumi, Dominik Heider

    Diterbitkan 2024-12-01
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  4. 4
    Chaos game representation and its applications in bioinformatics

    Chaos game representation and its applications in bioinformatics oleh Hannah Franziska Löchel, Dominik Heider

    Diterbitkan 2021-01-01
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  5. 5
    Machine learning with asymmetric abstention for biomedical decision-making

    Machine learning with asymmetric abstention for biomedical decision-making oleh Mariem Gandouz, Hajo Holzmann, Dominik Heider

    Diterbitkan 2021-10-01
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  6. 6
    Editorial: Artificial Intelligence Bioinformatics: Development and Application of Tools for Omics and Inter-Omics Studies

    Editorial: Artificial Intelligence Bioinformatics: Development and Application of Tools for Omics and Inter-Omics Studies oleh Davide Chicco, Dominik Heider, Angelo Facchiano

    Diterbitkan 2020-04-01
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  7. 7
    Privacy-preserving decentralized learning methods for biomedical applications

    Privacy-preserving decentralized learning methods for biomedical applications oleh Mohammad Tajabadi, Roman Martin, Dominik Heider

    Diterbitkan 2024-12-01
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  8. 8
    Unsupervised encoding selection through ensemble pruning for biomedical classification

    Unsupervised encoding selection through ensemble pruning for biomedical classification oleh Sebastian Spänig, Alexander Michel, Dominik Heider

    Diterbitkan 2023-03-01
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  9. 9
    Turbo autoencoders for the DNA data storage channel with Autoturbo-DNA

    Turbo autoencoders for the DNA data storage channel with Autoturbo-DNA oleh Marius Welzel, Hagen Dreßler, Dominik Heider

    Diterbitkan 2024-05-01
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  10. 10
    ContraDRG: Automatic Partial Charge Prediction by Machine Learning

    ContraDRG: Automatic Partial Charge Prediction by Machine Learning oleh Roman Martin, Roman Martin, Dominik Heider

    Diterbitkan 2019-10-01
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  11. 11
    Editorial: Artificial intelligence and bioinformatics applications for omics and multi-omics studies

    Editorial: Artificial intelligence and bioinformatics applications for omics and multi-omics studies oleh Angelo Facchiano, Dominik Heider, Margherita Mutarelli

    Diterbitkan 2024-01-01
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  12. 12
    The visual story of data storage: From storage properties to user interfaces

    The visual story of data storage: From storage properties to user interfaces oleh Aleksandar Anžel, Dominik Heider, Georges Hattab

    Diterbitkan 2021-01-01
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  13. 13
    MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks

    MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks oleh Aleksandar Anžel, Dominik Heider, Georges Hattab

    Diterbitkan 2022-01-01
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  14. 14
    Mushroom data creation, curation, and simulation to support classification tasks

    Mushroom data creation, curation, and simulation to support classification tasks oleh Dennis Wagner, Dominik Heider, Georges Hattab

    Diterbitkan 2021-04-01
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  15. 15
    A theoretical basis for bioindication in complex ecosystems

    A theoretical basis for bioindication in complex ecosystems oleh Theodor Sperlea, Dominik Heider, Georges Hattab

    Diterbitkan 2022-07-01
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  16. 16
    EFS: an ensemble feature selection tool implemented as R-package and web-application

    EFS: an ensemble feature selection tool implemented as R-package and web-application oleh Ursula Neumann, Nikita Genze, Dominik Heider

    Diterbitkan 2017-06-01
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  17. 17
    Correction: Ten simple rules to colorize biological data visualization.

    Correction: Ten simple rules to colorize biological data visualization. oleh Georges Hattab, Theresa-Marie Rhyne, Dominik Heider

    Diterbitkan 2021-04-01
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  18. 18
    Prediction of co-receptor usage of HIV-1 from genotype.

    Prediction of co-receptor usage of HIV-1 from genotype. oleh J Nikolaj Dybowski, Dominik Heider, Daniel Hoffmann

    Diterbitkan 2010-04-01
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  19. 19
    Ten simple rules to colorize biological data visualization.

    Ten simple rules to colorize biological data visualization. oleh Georges Hattab, Theresa-Marie Rhyne, Dominik Heider

    Diterbitkan 2020-10-01
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  20. 20
    NeuralBeds: Neural embeddings for efficient DNA data compression and optimized similarity search

    NeuralBeds: Neural embeddings for efficient DNA data compression and optimized similarity search oleh Oluwafemi A. Sarumi, Maximilian Hahn, Dominik Heider

    Diterbitkan 2024-12-01
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