Ing. et Ing.

Jana Schwarzerová

MSc

FEKT, UBMI – vědecký pracovník

+420 54114 6646
xschwa16@vut.cz

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Ing. et Ing. Jana Schwarzerová, MSc

Publikace

  • 2024

    SCHWARZEROVÁ, J.; HURTA, M.; BARTOŇ, V.; LEXA, M.; WALTHER, D.; PROVAZNÍK, V.; WECKWERTH, W. A perspective on genetic and polygenic risk scores—advances and limitations and overview of associated tools. Briefings in Bioinformatics, 2024, roč. 25, č. 3, s. 1-11. ISSN: 1477-4054.
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    VAIBAROVA, V.; KRÁLOVÁ, S.; PALÍKOVÁ, M.; SCHWARZEROVÁ, J.; NEJEZCHLEBOVÁ, J.; ČEJKOVÁ, D.; ČÍŽEK, A. Genetic and phenotypic diversity of Flavobacterium psychrophilum isolates from Czech salmonid fish farms. BMC MICROBIOLOGY, 2024, roč. 24, č. 1, s. 1-15. ISSN: 1471-2180.
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  • 2023

    NEJEZCHLEBOVÁ, J.; SCHWARZEROVÁ, J.; ČEJKOVÁ, D. An insight into horizontal gene transfer in Bacteroidetes spp. using in-silico analysisof operon structures. Proceedings I of the 29th Conference STUDENT EEICT 2023 General papers. 1. Brno: Brno University of Technology, Faculty of Electrical Engineering and Communication, 2023. s. 210-213. ISBN: 978-80-214-6153-6.
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    SCHWARZEROVÁ, J.; OLEŠOVÁ, D.; KVASNIČKA, A.; FRIEDECKÝ, D.; VARGA, M.; PROVAZNÍK, V.; WECKWERTH, W. Systematic comparison of advanced network analysis and visualization of lipidomics data. In Bioinformatics and Biomedical Engineering. 1. Springer Cham, 2023. s. 391-402. ISBN: 978-3-031-34953-9.
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    SCHWARZEROVÁ, J.; RETZER, K.; WECKWERTH, W. In-silico modelling of signalling pathways for dual functional of SnRK1 and SnRK2. Auxins and Cytokinins in Plant Development 2023 ... and cross-talk with other phytohormones in interactions with the changing environment. 2023. s. 116-116.
    Detail

    SCHWARZEROVÁ, J.; ZEMAN, M.; BABÁK, V.; JUREČKOVÁ, K.; NYKRÝNOVÁ, M.; VARGA, M.; WECKWERTH, W.; DOLEJSKÁ, M.; PROVAZNÍK, V.; RYCHLÍK, I.; ČEJKOVÁ, D. Detecting horizontal gene transfer among microbiota: an innovative pipeline for identifying co-shared genes within the mobilome through advanced comparative analysis. Microbiology spectrum, 2023, roč. 12, č. 1, ISSN: 2165-0497.
    Detail | WWW | Plný text v Digitální knihovně

    SCHWARZEROVÁ, J.; WECKWERTH, W. A Comprehensive Tool for State-of-the-Art Pre-processing Analysis in Metabolomics included in updated App: COVAIN v2.0.0. Book of Abstracts from the Eleventh Annual Conference of the Czech Society for Mass Spectrometry. first. Czech Society for Mass Spectrometry, 2023. s. 38-38. ISBN: 978-80-907478-2-1.
    Detail

    SCHWARZEROVÁ, J.; LABANAVA, A.; RYCHLÍK, I.; VARGA, M.; ČEJKOVÁ, D. A minireview on the bioinformatics analysis of mobile gene elements in microbiome research. Frontiers in Bacteriology, 2023, roč. 2, č. 1, ISSN: 2813-6144.
    Detail | WWW | Plný text v Digitální knihovně

    HURTA, M.; SCHWARZEROVÁ, J.; NAGELE, T.; WECKWERTH, W.; PROVAZNÍK, V.; SEKANINA, L. Utilizing Genetic Programming to Enhance Polygenic Risk Score Calculation. In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2023). Istanbul: Institute of Electrical and Electronics Engineers, 2023. s. 3782-3787. ISBN: 979-8-3503-3748-8.
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    SCHWARZEROVÁ, J.; BARTOŇ, V.; WALTHER, D.; WECKWERTH, W. Comprehensive analysis of putrescine metabolism in A. thaliana using GWAS, genetic risk score, metabolic modelling and data mining. In Proceedings II of the 29th Conference STUDENT EEICT 2023 Selected Papers. 1. Brno: Brno University of Technology, Faculty of Elektronic Engineering and Communication, 2023. s. 151-155. ISBN: 978-80-214-6154-3.
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    SCHWARZEROVÁ, J.; HURTA, M.; WECKWERTH, W.; WALTHER, D. Decoding the Hidden Secrets of SNP Data: Revealing Ancestral Origins, Genomic Predictions, and Polygenic Risk Score. Germany: 2023.
    Detail

    HURTA, M.; SCHWARZEROVÁ, J.; PROVAZNÍK, V.; WECKWERTH, W.; WALTHER, D.; SEKANINA, L. Utilizing Cartesian Genetic Programming for Efficient Polygenic Risk Score Calculation in Plants. Program and Abstract Book: Swedish Bioinformatics Workshop 2023. Stockholm: 2023. s. 49-49.
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    WEISZMANN, J.; WALTHER, D.; CLAUW, P.; BACK, G.; GUNIS, J.; REICHARDT, I.; KOEMEDA, S.; JEZ, J.; NORDBORG, M.; PIERDIES, I.; SCHWARZEROVÁ, J.; NÄGELE, T.; WECKWERTH, W. Metabolome plasticity in 241 Arabidopsis thaliana accessions reveals evolutionary cold adaptation processes. PLANT PHYSIOLOGY, 2023, roč. 192, č. 2, s. 980-1000. ISSN: 0032-0889.
    Detail | WWW | Plný text v Digitální knihovně

  • 2022

    ČEJKOVÁ, D.; STREĎANSKÁ, K.; JUREČKOVÁ, K.; NYKRÝNOVÁ, M.; SCHWARZEROVÁ, J.; DOLEJSKÁ, M. Horizontal gene transfer network in chicken gut microbiome. 14th Host Pathogen Interaction Forum 2022. Hradec Kralove: 2022. ISBN: 978-80-906723-2-1.
    Detail

    SCHWARZEROVÁ, J.; ZEMAN, M.; WECKWERTH, W.; PROVAZNÍK, I.; RYCHLÍK, I.; ČEJKOVÁ, D. Comprehensive analysis of mobile genetic elements in chicken gut microbiome using a novel in-silico approach. 14th Host Pathogen Interaction Forum 2022. Hradec Kralove: 2022. ISBN: 978-80-906723-2-1.
    Detail

    SCHWARZEROVÁ, J.; ZEMAN, M.; RYCHLÍK, I.; WECKWERTH, W.; PROVAZNÍK, I.; DOLEJSKÁ, M.; ČEJKOVÁ, D. Systems biology approach for analysis of mobile genetic elements in chicken gut microbiome. In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE Computer Society, 2022. s. 2865-2870. ISBN: 978-1-4577-1799-4.
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    SIDAK, D.; SCHWARZEROVÁ, J.; WECKWERTH, W.; WALDHERR, S. Interpretable machine learning methods for predictions in systems biology from omics data. Frontiers in Molecular Biosciences, 2022, roč. 9, č. October 2022, s. 1-28. ISSN: 2296-889X.
    Detail | WWW | Plný text v Digitální knihovně

    SCHWARZEROVÁ, J.; NEMČEKOVÁ, P.; PIERDIES, I.; NOHEL, M.; CHMELÍK, J.; SEDLÁŘ, K.; WECKWERTH, W. OMICs prediction for Hordeum vulgare using Random Forest methodology. The Biomania Student Scientific Meeting 2022, Book of abstract. 1st. Brno: Masaryk University Press, 2022. s. 52-52. ISBN: 978-80-280-0040-0.
    Detail

    SCHWARZEROVÁ, J.; WECKWERTH, W.; WALTHER, D. Insight in single nucleotide polymorphisms focused on post transcriptional modifications in Arabidopsis thaliana. NGSymposium in Computational Biology. Warsaw: NGSymposium, 2022. s. 12-12.
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    NEJEZCHLEBOVÁ, J.; SCHWARZEROVÁ, J. Operon identifier: Identification of operon structures in the whole genome. In Proceedings II of the 28th Conference STUDENT EEICT 2022 Selected Papers. Brno: Brno University of Technology, Faculty of electrical engineering and communication, 2022. s. 80-83. ISBN: 978-80-214-6030-0.
    Detail | WWW

    SCHWARZEROVÁ, J.; ČEJKOVÁ, D. Identification of horizontal genes transfer elements across strains inhabiting the same niche using pan-genome analysis. In Proceedings I of the 28th Conference STUDENT EEICT 2022 General Papers. Brno: Brno University of Technology, Faculty of Electrical Engineering and Communication, 2022. s. 416-420. ISBN: 978-80-214-6029-4.
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    NEMČEKOVÁ, P.; SCHWARZEROVÁ, J. Dynamic metabolomic prediction based on genetic variation for Hordeum vulgare. In Proceedings I of the 28th Conference STUDENT EEICT 2022 General Papers. Brno: Brno University of Technology, Faculty of Electrical Engineering and Communication, 2022. s. 251-254. ISBN: 978-80-214-6029-4.
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    POMYKALOVÁ, B.; POLZEROVÁ, N.; NEJEZCHLEBOVÁ, J.; SCHWARZEROVÁ, J.; JUREČKOVÁ, K.; SEDLÁŘ, K. Advanced annotation related to gene regulation in Clostridium beijerinckii NRRL B-598. The Biomania Student Scientific Meeting 2022 - Book of Abstracts. Brno: Masaryk University Press, 2022. s. 136-136. ISBN: 978-80-280-0040-0.
    Detail

    KOŠTOVAL, A.; SCHWARZEROVÁ, J. Concept Drift Detection in Prediction Classifiers for Determining Gender in Metabolomics Analysis. In Proceedings I of the 28th Conference STUDENT EEICT 2022 General Papers. 1. Brno: Brno University of Technology, Faculty of Electronic Engineering and Communication, 2022. s. 128-131. ISBN: 978-80-214-6029-4.
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    SCHWARZEROVÁ, J.; KOŠTOVAL, A.; BAJGER, A.; JAKUBIKOVA, L.; PIERDIES, I.; POPELINSKY, L.; SEDLÁŘ, K.; WECKWERTH, W. A Revealed Imperfection in Concept Drift Correction in Metabolomics Modeling. In Information Technology in Biomedicine. Springer, 2022. s. 498-509. ISBN: 978-3-031-09135-3.
    Detail

    SCHWARZEROVÁ, J.; PIERDIES, I.; SEDLÁŘ, K.; WECKWERTH, W. Linear Predictive Modeling for Immune Metabolites Related to Other Metabolites. In Bioinformatics and Biomedical Engineering. Springer, 2022. s. 16-27. ISBN: 978-3-031-07704-3.
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  • 2021

    SCHWARZEROVÁ, J. OPERON-EXPRESSER: The Innovated Gene Expression-based Algorithm for Operon Structures Inference. Proceedings of the 27th Conference STUDENT EEICT 2021. Brno: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2021. s. 301-306. ISBN: 978-80-214-5942-7.
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    SCHWARZEROVÁ, J. Metabolite Genome-wide Association Studies of Arabidopsis Thaliana. In Proceedings of the 27th Conference STUDENT EEICT 2021 selected papers. 1. Brno: Brno University of Technology, Faculty of Electrical Engineering and Communication, 2021. s. 41-44. ISBN: 978-80-214-5943-4.
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    KOUŘILOVÁ, X.; SCHWARZEROVÁ, J.; PERNICOVÁ, I.; SEDLÁŘ, K.; MRÁZOVÁ, K.; KRZYŽÁNEK, V.; NEBESÁŘOVÁ, J.; OBRUČA, S. The First Insight into Polyhydroxyalkanoates Accumulation in Multi-Extremophilic Rubrobacter xylanophilus and Rubrobacter spartanus. Microorganisms, 2021, roč. 9, č. 5, s. 1-13. ISSN: 2076-2607.
    Detail | WWW | Plný text v Digitální knihovně

    SCHWARZEROVÁ, J.; MUSILOVÁ, J.; JUREČKOVÁ, K.; BRANSKÁ, B.; PROVAZNÍK, I.; PATÁKOVÁ, P.; SEDLÁŘ, K. Operon Structure Inference in Clostridium beijerinckii NRRL B-589 using RNA-Seq. In 8th International Conference on Chemical Technology. 2021. s. 284-289. ISBN: 978-80-88307-08-2.
    Detail

    SCHWARZEROVÁ, J.; BAJGER, A.; PIERDOU, I.; POPELINSKY, L.; SEDLÁŘ, K.; WECKWERTH, W. An Innovative Perspective on Metabolomics Data Analysis in Biomedical Research Using Concept Drift Detection. In 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Institute of Electrical and Electronics Engineers Inc., 2021. s. 3075-3082. ISBN: 978-1-6654-0126-5.
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  • 2020

    SCHWARZEROVÁ, J. Reproducible analytical pipeline for using raw RNA-Seq data from non-model organisms. Proceedings of the 26th Conference STUDENT EEICT 2020. Brno: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2020. s. 225-228. ISBN: 978-80-214-5867-3.
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*) Citace publikací se generují jednou za 24 hodin.