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Joanna Polanska
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2020 – today
- 2024
- [i7]Michael Götz, Christian Weber, Franciszek Binczyk, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Ullrich Köthe, Jens Kleesiek, Bram Stieltjes, Klaus H. Maier-Hein:
DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images. CoRR abs/2403.07434 (2024) - 2023
- [j16]Marek Socha, Wojciech Prazuch, Aleksandra Suwalska, Pawel Foszner, Joanna Tobiasz, Jerzy Jaroszewicz
, Katarzyna Gruszczynska, Magdalena Sliwinska, Mateusz Nowak, Barbara Gizycka, Gabriela Zapolska, Tadeusz Popiela, Grzegorz Przybylski
, Piotr Fiedor, Malgorzata Pawlowska, Robert Flisiak, Krzysztof Simon, Jerzy Walecki
, Andrzej Cieszanowski, Edyta Szurowska
, Michal Marczyk, Joanna Polanska:
Pathological changes or technical artefacts? The problem of the heterogenous databases in COVID-19 CXR image analysis. Comput. Methods Programs Biomed. 240: 107684 (2023) - [j15]Aleksandra Suwalska, Joanna Siuda, Szymon Kocot, Weronika Zmuda, Monika Rudzinska-Bar, Joanna Polanska:
Activation maps of convolutional neural networks as a tool for brain degeneration tracking in early diagnosis of dementia in Parkinson's disease based on magnetic resonance imaging. Signal Image Video Process. 17(8): 4115-4121 (2023) - [c45]Kamila Szumala, Joanna Polanska
, Joanna Zyla
:
Unsupervised Investigation of Information Captured in Pathway Activity Score in scRNA-Seq Analysis. IWBBIO (2) 2023: 180-192 - [c44]Katarzyna Sieradzka
, Joanna Polanska
:
Feature Selection Methods Comparison: Logistic Regression-Based Algorithm and Neural Network Tools. PACBB 2023: 34-43 - [i6]Anna Glodek, Joanna Polanska, Marta Gawin:
Isotopic envelope identification by analysis of the spatial distribution of components in MALDI-MSI data. CoRR abs/2302.06051 (2023) - [i5]Wojciech Prazuch, Marek Socha, Anna Mrukwa, Aleksandra Suwalska, Agata Durawa, Malgorzata Jelitto-Górska, Katarzyna Dziadziuszko, Edyta Szurowska, Pawel Bozek
, Michal Marczyk, Witold Rzyman, Joanna Polanska:
BRONCO: Automated modelling of the bronchovascular bundle using the Computed Tomography Images. CoRR abs/2309.09410 (2023) - [i4]Joanna Zyla, Michal Marczyk, Wojciech Prazuch, Marek Socha, Aleksandra Suwalska, Agata Durawa, Malgorzata Jelitto-Górska, Katarzyna Dziadziuszko, Edyta Szurowska, Witold Rzyman, Piotr Widlak, Joanna Polanska:
Combining low-dose CT-based radiomics and metabolomics for early lung cancer screening support. CoRR abs/2311.12810 (2023) - 2022
- [j14]Grzegorz Mrukwa, Joanna Polanska
:
DiviK: divisive intelligent K-means for hands-free unsupervised clustering in big biological data. BMC Bioinform. 23(1): 538 (2022) - [j13]Aleksandra Suwalska, Yingzhe Wang, Ziyu Yuan, Yanfeng Jiang, Dongliang Zhu, Jinhua Chen, Mei Cui, Xingdong Chen, Chen Suo
, Joanna Polanska:
CMB-HUNT: Automatic detection of cerebral microbleeds using a deep neural network. Comput. Biol. Medicine 151(Part): 106233 (2022) - [c43]Joanna Tobiasz
, Joanna Polanska
:
How to Compare Various Clustering Outcomes? Metrices to Investigate Breast Cancer Patient Subpopulations Based on Proteomic Profiles. IWBBIO (2) 2022: 309-318 - [c42]Wojciech Prazuch
, Malgorzata Jelitto-Górska
, Agata Durawa
, Katarzyna Dziadziuszko
, Joanna Polanska
:
Radiomic-Based Lung Nodule Classification in Low-Dose Computed Tomography. IWBBIO (1) 2022: 357-363 - [c41]Aleksandra Suwalska
, Nelita du Plessis-Burger
, Gian van der Spuy
, Joanna Polanska
:
Comparison of Batch Effect Removal Methods for High Dimensional Mass Cytometry Data. IWBBIO (2) 2022: 399-410 - [c40]Justyna Mika
, Serge M. Candéias
, Christophe Badie
, Joanna Polanska
:
Can We Detect T Cell Receptors from Long-Read RNA-Seq Data? IWBBIO (2) 2022: 450-463 - [i3]Wojciech Prazuch, Aleksandra Suwalska, Marek Socha, Joanna Tobiasz, Pawel Foszner, Jerzy Jaroszewicz
, Katarzyna Gruszczynska, Magdalena Sliwinska, Jerzy Walecki
, Tadeusz Popiela, Grzegorz Przybylski, Andrzej Cieszanowski, Mateusz Nowak, Malgorzata Pawlowska, Robert Flisiak, Krzysztof Simon, Gabriela Zapolska, Barbara Gizycka, Edyta Szurowska, Michal Marczyk, Joanna Polanska:
CIRCA: comprehensible online system in support of chest X-rays-based COVID-19 diagnosis. CoRR abs/2210.05440 (2022) - [i2]Aleksandra Suwalska, Joanna Tobiasz, Wojciech Prazuch, Marek Socha, Pawel Foszner, Jerzy Jaroszewicz
, Katarzyna Gruszczynska, Magdalena Sliwinska, Jerzy Walecki
, Tadeusz Popiela, Grzegorz Przybylski, Mateusz Nowak, Piotr Fiedor, Malgorzata Pawlowska, Robert Flisiak, Krzysztof Simon, Gabriela Zapolska, Barbara Gizycka, Edyta Szurowska, Michal Marczyk, Andrzej Cieszanowski, Joanna Polanska:
POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020-2021). CoRR abs/2211.16359 (2022) - 2021
- [c39]Aleksandra Suwalska
, Joanna Polanska
:
Preliminary study for a fully automated pre-gating method for high-dimensional mass cytometry data. BIBE 2021: 1-5 - [c38]Agnieszka Cecotka, Lukasz Krol, Grainne O'Brien, Christophe Badie, Joanna Polanska
:
May Gender Have an Impact on Methylation Profile and Survival Prognosis in Acute Myeloid Leukemia? PACBB 2021: 126-135 - 2020
- [j12]Michal Marczyk
, Roman Jaksik
, Andrzej Polanski
, Joanna Polanska
:
GaMRed - Adaptive Filtering of High-Throughput Biological Data. IEEE ACM Trans. Comput. Biol. Bioinform. 17(1): 149-157 (2020) - [c37]Joanna Zyla
, Kinga Leszczorz
, Joanna Polanska
:
Robustness of Pathway Enrichment Analysis to Transcriptome-Wide Gene Expression Platform. PACBB 2020: 176-185 - [i1]Joanna Henzel, Joanna Tobiasz, Michal Kozielski, Malgorzata Bach, Pawel Foszner, Aleksandra Gruca, Mateusz Kania, Justyna Mika, Anna Papiez
, Aleksandra Werner, Joanna Zyla, Jerzy Jaroszewicz, Joanna Polanska, Marek Sikora:
Classification supporting COVID-19 diagnostics based on patient survey data. CoRR abs/2011.12247 (2020)
2010 – 2019
- 2019
- [j11]Anna Papiez
, Christophe Badie, Joanna Polanska
:
Machine learning techniques combined with dose profiles indicate radiation response biomarkers. Int. J. Appl. Math. Comput. Sci. 29(1): 169-178 (2019) - [j10]Anna Papiez
, Michal Marczyk
, Joanna Polanska
, Andrzej Polanski
:
BatchI: Batch effect Identification in high-throughput screening data using a dynamic programming algorithm. Bioinform. 35(11): 1885-1892 (2019) - [j9]Joanna Zyla
, Michal Marczyk
, Teresa Domaszewska, Stefan H. E. Kaufmann, Joanna Polanska
, January 3rd Weiner
:
Gene set enrichment for reproducible science: comparison of CERNO and eight other algorithms. Bioinform. 35(24): 5146-5154 (2019) - [c36]Kinga Leszczorz, Omid Azimzadeh, Soile Tapio, Michael Atkinson, Joanna Polanska
:
Mathematical Modelling and Effect Size Analysis in Support of Searching for the Proteomic Signature of Radiotherapy Toxicity. BIBE 2019: 244-249 - [c35]Joanna Tobiasz
, Christos Hatzis
, Joanna Polanska
:
Breast Cancer Heterogeneity Investigation: Multiple k-Means Clustering Approach. BIBE 2019: 410-414 - 2018
- [c34]Joanna Tobiasz
, Najla Al-Harbi, Sara Bin Judia, Salma Majid, Ghazi Alsbeih, Joanna Polanska
:
Are Radiosensitive and Regular Response Cells Homogeneous in Their Correlations Between Copy Number State and Surviving Fraction After Irradiation? IWBBIO (1) 2018: 197-208 - [c33]Anna Papiez
, Marcin Skrzypski
, Amelia Szymanowska-Narloch, Ewa Jassem, Agnieszka Maciejewska, Ryszard Pawlowski, Rafal Dziadziuszko
, Jacek Jassem
, Witold Rzyman
, Joanna Polanska
:
Can an Integrative SNP Approach Substitute Standard Identification in Comprehensive Case/Control Analyses? PACBB 2018: 123-130 - 2017
- [j8]Joanna Zyla
, Michal Marczyk
, January 3rd Weiner
, Joanna Polanska
:
Ranking metrics in gene set enrichment analysis: do they matter? BMC Bioinform. 18(1): 256:1-256:12 (2017) - [j7]Franciszek Binczyk, Bram Stjelties, Christian Weber, Michael Götz
, Klaus H. Maier-Hein
, Hans-Peter Meinzer, Barbara Bobek-Billewicz
, Rafal Tarnawski
, Joanna Polanska
:
MiMSeg - an algorithm for automated detection of tumor tissue on NMR apparent diffusion coefficient maps. Inf. Sci. 384: 235-248 (2017) - [c32]Michal Marczyk
, Joanna Polanska
, Andrzej Polanski
:
Improving peak detection by Gaussian mixture modeling of mass spectral signal. ICFSP 2017: 39-43 - [c31]Anna Krawczyk, Joanna Polanska
:
Comparative Analysis of MicroRNA-Target Gene Interaction Prediction Algorithms Based on Integrated P-Value Calculation. ICMMI 2017: 137-143 - [c30]Lukasz Krol, Joanna Polanska
:
Multidimensional Feature Selection and Interaction Mining with Decision Tree Based Ensemble Methods. PACBB 2017: 118-125 - [c29]Joanna Zyla
, Michal Marczyk
, Joanna Polanska
:
Reproducibility of Finding Enriched Gene Sets in Biological Data Analysis. PACBB 2017: 146-154 - [c28]Agnieszka Cecotka, Joanna Polanska
:
Novel Method of Identifying DNA Methylation Fingerprint of Acute Myeloid Leukaemia. PACBB 2017: 189-196 - 2016
- [j6]Michael Götz
, Christian Weber, Franciszek Binczyk, Joanna Polanska
, Rafal Tarnawski
, Barbara Bobek-Billewicz
, Ullrich Köthe
, Jens Kleesiek, Bram Stieltjes, Klaus H. Maier-Hein
:
DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images. IEEE Trans. Medical Imaging 35(1): 184-196 (2016) - [c27]Anna Krawczyk, Joanna Polanska
:
Comparative Analysis of microRNA-Target Gene Interaction Prediction Algorithms - The Attempt to Compare the Results of Three Algorithms. IWBBIO 2016: 103-112 - [c26]Grzegorz Mrukwa, Grzegorz Drazek, Monika Pietrowska
, Piotr Widlak, Joanna Polanska
:
A Novel Divisive iK-Means Algorithm with Region-Driven Feature Selection as a Tool for Automated Detection of Tumour Heterogeneity in MALDI IMS Experiments. IWBBIO 2016: 113-124 - [c25]Joanna Zyla
, Christophe Badie
, Ghazi Alsbeih, Joanna Polanska
:
Multigene P-value Integration Based on SNPs Investigation for Seeking Radiosensitivity Signatures. IWBBIO 2016: 125-134 - [c24]Joanna Zyla
, Michal Marczyk
, Joanna Polanska
:
Sensitivity, Specificity and Prioritization of Gene Set Analysis When Applying Different Ranking Metrics. PACBB 2016: 61-69 - [c23]Wojciech Labaj, Anna Papiez
, Joanna Polanska
, Andrzej Polanski
:
Deep Data Analysis of a Large Microarray Collection for Leukemia Biomarker Identification. PACBB 2016: 71-79 - 2015
- [c22]Christian Weber, Michael Götz
, Franciszek Binczyk, Joanna Polanska
, Rafal Tarnawski
, Barbara Bobek-Billewicz
, Hans-Peter Meinzer, Bram Stieltjes, Klaus H. Maier-Hein:
Überwachtes Lernen zur Prädiktion von Tumorwachstum. Bildverarbeitung für die Medizin 2015: 473-478 - [c21]Michael Götz
, Christian Weber, Franciszek Binczyk, Joanna Polanska
, Rafal Tarnawski
, Barbara Bobek-Billewicz
, Hans-Peter Meinzer, Bram Stieltjes, Klaus H. Maier-Hein:
Automatische Tumorsegmentierung mit spärlich annotierter Lernbasis. Bildverarbeitung für die Medizin 2015: 486-491 - [c20]Michal Staniszewski, Franciszek Binczyk, Agnieszka Skorupa, Lukasz Boguszewicz, Maria Sokol, Joanna Polanska, Andrzej Polanski:
Comparison of Black Box Implementations of Two Algorithms of Processing of NMR Spectra, Gaussian Mixture Model and Singular Value Decomposition. BIOSIGNALS 2015: 57-65 - [c19]Marzena Dolbniak, Joanna Zyla, Sylwia Kabacik, Grainne Manning, Christophe Badie, Ghazi Alsbeih, Joanna Polanska:
Is the Identification of SNP-miRNA Interactions Supporting the Prediction of Human Lymphocyte Transcriptional Radiation Responses?. BIOINFORMATICS 2015: 243-250 - [c18]Michal Marczyk
, Grzegorz Drazek, Monika Pietrowska
, Piotr Widlak
, Joanna Polanska
, Andrzej Polanski
:
Modeling of Imaging Mass Spectrometry Data and Testing by Permutation for Biomarkers Discovery in Tissues. ICCS 2015: 693-702 - [c17]Franciszek Binczyk, Michal Marczyk, Joanna Polanska
:
Mixture Model Based Efficient Method for Magnetic Resonance Spectra Quantification. IWBBIO (2) 2015: 406-417 - [c16]Anna Papiez
, Sylwia Kabacik, Christophe Badie, Simon Bouffler
, Joanna Polanska
:
Statistical Integration of p-values for Enhancing Discovery of Radiotoxicity Gene Signatures. IWBBIO (1) 2015: 503-513 - 2014
- [j5]Roman Jaksik
, Michal Marczyk
, Joanna Polanska
, Joanna Rzeszowska-Wolny
:
Sources of High Variance between Probe Signals in Affymetrix Short Oligonucleotide Microarrays. Sensors 14(1): 532-548 (2014) - [j4]Pawel Foszner, Aleksandra Gruca, Andrzej Polanski
, Michal Marczyk
, Roman Jaksik
, Joanna Polanska
:
An Efficient Algorithm for Microarray Probes Re-annotation. Trans. Comput. Collect. Intell. 13: 201-218 (2014) - [c15]Michal Marczyk, Joanna Polanska:
Methods for Quality Control of Low-resolution MALDI-ToF Spectra. BIOINFORMATICS 2014: 172-177 - [c14]Joanna Zyla, Christophe Badie, Ghazi Alsbeih, Joanna Polanska:
Modelling of Genetic Interactions in GWAS Reveals More Complex Relations between Genotype and Phenotype. BIOINFORMATICS 2014: 204-208 - [c13]Anna Papiez, Paul Finnon, Christophe Badie, Simon Bouffler, Joanna Polanska:
Integrating Expression Data from Different Microarray Platforms in Search of Biomarkers of Radiosensitivity. IWBBIO 2014: 484-493 - [c12]Michal Marczyk, Lukasz Krol, Joanna Polanska:
Automatic detection of outlying microarrays using multi-array quality metrics. IWBBIO 2014: 738-746 - [c11]Franciszek Binczyk, Rafal Tarnawski, Joanna Polanska:
Improvement in the accuracy of Nuclear Magnetic Resonance spectrum analysis by automatic tuning of phase correction algorithms. IWBBIO 2014: 778-788 - [c10]Lukasz Krol, Ghazi Alsbeih, Christophe Badie, Joanna Polanska:
Impact of missing genotype imputation on the power of Genome Wide Association Studies. IWBBIO 2014: 1603-1614 - 2013
- [j3]Michal Marczyk
, Roman Jaksik
, Andrzej Polanski
, Joanna Polanska
:
Adaptive filtering of microarray gene expression data based on Gaussian mixture decomposition. BMC Bioinform. 14: 101 (2013) - [c9]Michal Marczyk
, Joanna Polanska
, Andrzej Polanski
:
Comparison of Algorithms for Profile-Based Alignment of Low Resolution MALDI-ToF Spectra. ICMMI 2013: 193-201 - [c8]Joanna Zyla
, Paul Finnon, Robert Bulman, Simon Bouffler
, Christophe Badie
, Joanna Polanska
:
Investigation for Genetic Signature of Radiosensitivity - Data Analysis. ICMMI 2013: 219-227 - [c7]Anna Cichonska, Roman Jaksik, Joanna Polanska, Wieslawa Widlak:
Comparative analysis of the annotation systems of Mus musculus high density expression microarray. IWBBIO 2013: 41-48 - [c6]Joanna Zyla, Joanna Polanska, Paul Finnon, Robert Bulman, Simon Bouffler, Christophe Badie:
Seeking for Genetic Signature of Radiosensitivity - Methods for Data Analysis. IWBBIO 2013: 79-86 - [c5]Joanna Polanska, Franciszek Binczyk, Anna Hebda, Barbara Bobek-Billewicz:
Gaussian mixture model based analysis of apparent diffusion coefficient maps for differentiation between malignant and benign brain tumours - preliminary results. IWBBIO 2013: 647-648 - 2012
- [j2]Joanna Polanska
, Malgorzata Plechawska
, Monika Pietrowska
, Lukasz Marczak
:
Gaussian mixture decomposition in the analysis of MALDI-TOF spectra. Expert Syst. J. Knowl. Eng. 29(3): 216-231 (2012) - 2011
- [c4]Pawel Foszner, Aleksandra Gruca, Andrzej Polanski
, Michal Marczyk
, Roman Jaksik
, Joanna Polanska
:
Efficient Algorithm for Microarray Probes Re-annotation. ICCCI (2) 2011: 281-289 - 2010
- [c3]Pawel Foszner, Aleksandra Gruca, Joanna Polanska
:
Distant Analysis of the GENEPI-ENTB Databank - System Overview. CN 2010: 245-252
2000 – 2009
- 2009
- [c2]Malgorzata Plechawska, Joanna Polanska
, Andrzej Polanski
, Monika Pietrowska, Rafal Tarnawski, Piotr Widlak
, Maciej Stobiecki, Lukasz Marczak:
Analyze of Maldi-TOF Proteomic Spectra with Usage of Mixture of Gaussian Distributions. ICMMI 2009: 113-120 - [c1]Malgorzata Plechawska
, Joanna Polanska
:
Simulation of the Usage of Gaussian Mixture Models for the Purpose of Modelling Virtual Mass Spectrometry Data. MIE 2009: 804-808 - 2004
- [j1]Zbigniew Starosolski, Joanna Polanska
, Mark Groen, Andrzej Polanski
:
Estimating Regions of Absolute Stability with the Use of Piecewise Linear Lyapunov Functions. Eur. J. Control 10(6): 547-556 (2004)
Coauthor Index
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last updated on 2024-08-05 21:17 CEST by the dblp team
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