Hasil Pencarian - Aleksandra Gruca

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  1. 1
    Data- and expert-driven rule induction and filtering framework for functional interpretation and description of gene sets

    Data- and expert-driven rule induction and filtering framework for functional interpretation and description of gene sets oleh Aleksandra Gruca, Marek Sikora

    Diterbitkan 2017-06-01
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  2. 2
    Synthetic Genistein Glycosides Inhibiting EGFR Phosphorylation Enhance the Effect of Radiation in HCT 116 Colon Cancer Cells

    Synthetic Genistein Glycosides Inhibiting EGFR Phosphorylation Enhance the Effect of Radiation in HCT 116 Colon Cancer Cells oleh Aleksandra Gruca, Zdzisław Krawczyk, Wiesław Szeja, Grzegorz Grynkiewicz, Aleksandra Rusin

    Diterbitkan 2014-11-01
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  3. 3
    Common low complexity regions for SARS-CoV-2 and human proteomes as potential multidirectional risk factor in vaccine development

    Common low complexity regions for SARS-CoV-2 and human proteomes as potential multidirectional risk factor in vaccine development oleh Aleksandra Gruca, Joanna Ziemska-Legiecka, Patryk Jarnot, Elzbieta Sarnowska, Tomasz J. Sarnowski, Marcin Grynberg

    Diterbitkan 2021-04-01
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  4. 4
    Enhancement of COVID-19 symptom-based screening with quality-based classifier optimisation

    Enhancement of COVID-19 symptom-based screening with quality-based classifier optimisation oleh Michał Kozielski, Joanna Henzel, Joanna Tobiasz, Aleksandra Gruca, Paweł Foszner, Joanna Zyla, Małgorzata Bach, Aleksandra Werner, Jerzy Jaroszewicz, Joanna Polańska, Marek Sikora

    Diterbitkan 2021-05-01
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  5. 5
    Screening Support System Based on Patient Survey Data—Case Study on Classification of Initial, Locally Collected COVID-19 Data

    Screening Support System Based on Patient Survey Data—Case Study on Classification of Initial, Locally Collected COVID-19 Data oleh Joanna Henzel, Joanna Tobiasz, Michał Kozielski, Małgorzata Bach, Paweł Foszner, Aleksandra Gruca, Mateusz Kania, Justyna Mika, Anna Papiez, Aleksandra Werner, Joanna Zyla, Jerzy Jaroszewicz, Joanna Polanska, Marek Sikora

    Diterbitkan 2021-11-01
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  6. 6
    The need for standardisation in life science research - an approach to excellence and trust. [version 2; peer review: 3 approved]

    The need for standardisation in life science research - an approach to excellence and trust. [version 2; peer review: 3 approved] oleh Susanne Hollmann, Andreas Kremer, Špela Baebler, Christophe Trefois, Kristina Gruden, Witold R. Rudnicki, Weida Tong, Aleksandra Gruca, Erik Bongcam-Rudloff, Chris T. Evelo, Alina Nechyporenko, Marcus Frohme, David Šafránek, Babette Regierer, Domenica D'Elia

    Diterbitkan 2021-05-01
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  7. 7
    Symptom-based early-stage differentiation between SARS-CoV-2 versus other respiratory tract infections—Upper Silesia pilot study

    Symptom-based early-stage differentiation between SARS-CoV-2 versus other respiratory tract infections—Upper Silesia pilot study oleh Justyna Mika, Joanna Tobiasz, Joanna Zyla, Anna Papiez, Małgorzata Bach, Aleksandra Werner, Michał Kozielski, Mateusz Kania, Aleksandra Gruca, Damian Piotrowski, Barbara Sobala-Szczygieł, Bożena Włostowska, Paweł Foszner, Marek Sikora, Joanna Polanska, Jerzy Jaroszewicz

    Diterbitkan 2021-06-01
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  8. 8
    The need for standardisation in life science research - an approach to excellence and trust. [version 1; peer review: 2 approved]

    The need for standardisation in life science research - an approach to excellence and trust. [version 1; peer review: 2 approved] oleh Susanne Hollmann, Andreas Kremer, Špela Baebler, Christophe Trefois, Kristina Gruden, Witold R. Rudnicki, Weida Tong, Aleksandra Gruca, Erik Bongcam-Rudloff, Chris T. Evelo, Alina Nechyporenko, Marcus Frohme, David Šafránek, Babette Regierer, Domenica D'Elia

    Diterbitkan 2020-12-01
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  9. 9
    Corrigendum: Ni2+-assisted hydrolysis may affect the human proteome; filaggrin degradation ex vivo as an example of possible consequences

    Corrigendum: Ni2+-assisted hydrolysis may affect the human proteome; filaggrin degradation ex vivo as an example of possible consequences oleh Ewa Izabela Podobas, Ewa Izabela Podobas, Ewa Izabela Podobas, Danuta Gutowska-Owsiak, Danuta Gutowska-Owsiak, Sébastien Moretti, Jarosław Poznański, Mariusz Kulińczak, Marcin Grynberg, Aleksandra Gruca, Arkadiusz Bonna, Dawid Płonka, Tomasz Frączyk, Graham Ogg, Wojciech Bal

    Diterbitkan 2022-12-01
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  10. 10
    Ni2+-Assisted Hydrolysis May Affect the Human Proteome; Filaggrin Degradation Ex Vivo as an Example of Possible Consequences

    Ni2+-Assisted Hydrolysis May Affect the Human Proteome; Filaggrin Degradation Ex Vivo as an Example of Possible Consequences oleh Ewa Izabela Podobas, Ewa Izabela Podobas, Ewa Izabela Podobas, Danuta Gutowska-Owsiak, Danuta Gutowska-Owsiak, Sébastien Moretti, Jarosław Poznański, Mariusz Kulińczak, Marcin Grynberg, Aleksandra Gruca, Arkadiusz Bonna, Dawid Płonka, Tomasz Frączyk, Graham Ogg, Wojciech Bal

    Diterbitkan 2022-03-01
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  11. 11
    Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment

    Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment oleh Laura Judith Marcos-Zambrano, Kanita Karaduzovic-Hadziabdic, Tatjana Loncar Turukalo, Piotr Przymus, Vladimir Trajkovik, Oliver Aasmets, Oliver Aasmets, Magali Berland, Aleksandra Gruca, Jasminka Hasic, Karel Hron, Thomas Klammsteiner, Mikhail Kolev, Leo Lahti, Marta B. Lopes, Marta B. Lopes, Victor Moreno, Victor Moreno, Victor Moreno, Victor Moreno, Irina Naskinova, Elin Org, Inês Paciência, Georgios Papoutsoglou, Rajesh Shigdel, Blaz Stres, Baiba Vilne, Malik Yousef, Malik Yousef, Eftim Zdravevski, Ioannis Tsamardinos, Enrique Carrillo de Santa Pau, Marcus J. Claesson, Isabel Moreno-Indias, Isabel Moreno-Indias, Jaak Truu

    Diterbitkan 2021-02-01
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  12. 12
    Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action

    Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action oleh Domenica D’Elia, Jaak Truu, Leo Lahti, Magali Berland, Georgios Papoutsoglou, Georgios Papoutsoglou, Michelangelo Ceci, Aldert Zomer, Marta B. Lopes, Marta B. Lopes, Eliana Ibrahimi, Aleksandra Gruca, Alina Nechyporenko, Alina Nechyporenko, Marcus Frohme, Thomas Klammsteiner, Thomas Klammsteiner, Enrique Carrillo-de Santa Pau, Laura Judith Marcos-Zambrano, Karel Hron, Gianvito Pio, Andrea Simeon, Ramona Suharoschi, Isabel Moreno-Indias, Andriy Temko, Miroslava Nedyalkova, Elena-Simona Apostol, Ciprian-Octavian Truică, Rajesh Shigdel, Jasminka Hasić Telalović, Erik Bongcam-Rudloff, Piotr Przymus, Naida Babić Jordamović, Naida Babić Jordamović, Laurent Falquet, Sonia Tarazona, Alexia Sampri, Alexia Sampri, Gaetano Isola, David Pérez-Serrano, Vladimir Trajkovik, Lubos Klucar, Tatjana Loncar-Turukalo, Aki S. Havulinna, Aki S. Havulinna, Christian Jansen, Christian Jansen, Randi J. Bertelsen, Marcus Joakim Claesson

    Diterbitkan 2023-09-01
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