CONFERENCES
Organization of conferences:
- Konferencja Chmury dla Nauki i Biznesu, 4.02.2020r., Aula Wydziału Matematyki UwB, Uniwersyteckie Centrum Obliczeniowe UwB: W. Rudnicki
- Local Organizing Committee (A. Golińska, W. Lesiński, W. Rudnicki, A. Polewko-Klim) 9th Symposium of the Polish Bioinformatics Society, Białystok, Poland, 2016, Sep 28-30 PTBI Polish Bioinformatics Society, Faculty of Mathematics and Informatics, University of Białystok (org.)
- BIT Toruń 2015, 2016, 2017, 2018, 2019 Organizing Committee: W. Rudnicki
- PTBI 2015, 2016, 2017, 2018, 2019 Organizing Committee: W. Rudnicki
Participation in conferences:
- ECCB2024: The 23rd European Conference on Computational Biology, Turku, Finland, 16-20 September 2024
P. Stomma, W. R. Rudnicki, HCS—hierarchical algorithm for simulation of omics datasets.
- 16th International Conference, ICCCI 2024, Leipzig, Germany, September 9–11, 2024
Lesiński, W., Golińska, A.K., Rudnicki, W.R. Modelling of Drug-Induced Liver Injury with Multiple Machine Learning Algorithms.
- II Ogólnopolski Kongres Nauk Ścisłych i Przyrodniczych, 20 lipca 2024, Center for Science & Technology, Politechnika Wrocławska, Uniwersytetu Przyrodniczy we Wrocławiu, online
A. Kitlas Golińska. Determining descriptors in the study of biomedical signals using R packages.
- The International Conference on Computational Science ICCS 2024, Malaga, Spain, July 2–4, 2024
Polewko-Klim, A., Grablis, P., Rudnicki, W. EnsembleFS: an R Toolkit and a Web-Based Tool for a Filter Ensemble Feature Selection of Molecular Omics Data.
- Towards Comprehensive Population Studies II, December 1-2, 2023 A. Golińska, W. Lesiński, P. Stomma, W. Rudnicki
A. Golińska. Poincare plots in the study of the selected biomedical signals.
R. Toscan, W. Lesiński, P. Stomma, A. Kitlas Golińska, W. Rudnicki, P. Łabaj. Antimicrobial Resistance in Diverse Urban Microbiomes: Uncovering Patterns and Predictive Markers.
P. Stomma, W. Rudnicki. Interpretable generative model of correlation structure of multidimensional biological datasets
W. Wydmański, D. Błaszczyk, K. Zielinska, K. Mnich, V. Bezshapkin, T. Kosciolek, W. Rudnicki, P. P. Łabaj. Predicting Microbial Communities: A Machine Learning and Network Analysis Approach
K. Zielinska, D. Błaszczyk, K. Mnich, W. Wydmański, V. Bezshapkin, T. Kosciolek, W. Rudnicki, P. P. Łabaj. Redefining the definition of microbiome health
W. Wydmański, K. Mnich, K. Zielinska,V. Bezshapkin, M. Kowalski, A. Frolova, R. Zbieć-Piekarska, W. Branicki, W. Rudnicki, P. P. Łabaj. Towards improved biome understanding and classification – exploiting intra-community synergies
W. Lesiński, W. Rudnicki. A Robust Machine Learning Protocol for Prediction of Prostate Cancer Survival at Multiple Time-Horizons.
P. Stomma, W. Rudnicki. Interpretable generative model of correlation structure of multidimensional biological datasets
W. R. Rudnicki, R. Piliszek, O. Podbielska, P. Wszeborowska, P. Stomma. Biomarkers discovery with machine learning and feature discovery
W. Lesiński, W. Rudnicki. A Robust Machine Learning Protocol for Prediction of Prostate Cancer Survival at Multiple Time-Horizons
W. Lesiński, A. Kitlas Golińska, W. Rudnicki. Modelling of Drug-induced Liver Injury with multiple Machine Learning algorithms
P. Stomma, W. Rudnicki. Effectively simulating correlation structure of multidimensional biological datasets
R. Piliszek, W. Rudnicki. Let the STIG find the most relevant features
K. Mnich, W. Rudnicki Parametric Monte Carlo Feature Filtering
K. Mnich, W. Lesiński, W. Rudnicki. Far tail approximation of non-standard test statistic distribution
D. Błaszczyk, W. Wydmański, K. Mnich, V. Bezshapkin, M. B. Kowalski, A. Frolova, W. Rudnicki, P. P. Łabaj. From climate defined ecological niches to microbiome diversity and intra-community synergies
V. Bezshapkin, W. Wydmański, K. Mnich, M. Kowalski, D. Błaszczyk, T. Kościółek, W. Rudnicki, P. Łabaj. Towards interpretable machine learning applications in human microbiome via information theory-guided feature selection
K. Mnich, A. Kitlas Golińska, A. Polewko-Klim, W. Lesiński, W. R. Rudnicki. Improvements of Super Learning Algorithm
A. Polewko-Klim, K. Mnich, W. R. Rudnicki. A hybrid data integration approach to classification of biomedical data
W. Lesiński, A. Kitlas Golińska, K. Mnich, W. R. Rudnicki. New results in Drug-Induced Liver Injury Prediction
A. Kitlas Golińska, W. Lesiński, A. Przybylski, W. R. Rudnicki. Random Forest Algorithm in Prediction of Heart Arrhythmia Onset
R. Piliszek, W. R. Rudnicki, A. Brożyna. Cross-validated clustering of features to find the most representative biomarkers
A. Polewko-Klim, W. Lesiński, A. Kitlas Golińska, K. Mnich, M. Siwek, W. R. Rudnicki. Machine Learning based sensitivity analysis of immune response
W. Rudnicki. Identification of Informative Features in Data
- 14th Symposium of Polish Bioinformatics Society PTBI 2021, 15-17.09.2021 W. Rudnicki, A. Golińska, A. Polewko-Klim, W. Lesiński
W. Rudnicki. All relevant feature selection
W. Lesiński. Przewidywanie polekowego uszkodzenia wątroby na bazie ekspresji genów oraz właściwości chemicznych leków
- Women in Tech Days 2021, 25-26.05.2021 A. Golińska
R. Piliszek, W. Rudnicki. Hierarchical clustering in search for the most
relevant variables in small-n-large-p datasets
- IEEE International Conference on Data Mining Workshops, ICDM Workshops 2020, Sorrento, Italy, 17-20.11.2020
K. Mnich, A. Polewko-Klim, A. Kitlas Golinska, W. Lesiński, W. R. Rudnicki. Super Learning with Repeated Cross Validation.
- International Conference on Intelligent Systems for Molecular Biology ISMB 2020, Montreal, Canada, 12-16.07.2020 (track: Annual International Conference on Critical Assessment of Massive Data Analysis CAMDA 2020, 13-14.07.2020)
W. Lesinski, W. Rudnicki, K. Mnich. Prediction of Drug Induced Liver Injury with different data sets and different end points.
Witold R. Rudnicki, Krzysztof Mnich. Estimate of Covid-19 prevalence
using imperfect data
- The International Conference on Computational Science ICCS 2020, Amsterdam, The Netherlands, 3-5.06.2020
A. Polewko-Klim, W. R. Rudnicki. Analysis of Ensemble Feature Selection for Correlated High-Dimensional RNA-Seq Cancer Data.
K. Mnich, A. Kitlas Golińska, A. Polewko-Klim, W.R. Rudnicki. Bootstrap Bias Corrected Cross Validation Applied to Super Learning
A. Kitlas Golińska, W. Lesiński, A. Przybylski, W. R. Rudnicki. Towards Prediction of Heart Arrhythmia Onset Using Machine Learning.
W. Lesiński, A. Polewko-Klim, W. R. Rudnicki. Identification of Clinical Variables Relevant for Survival Prediction in Patients with Metastatic Castration-Resistant Prostate Cancer.
A. Polewko-Klim, W. R. Rudnicki. Data Integration Strategy for Robust Classification of Biomedical Data.
W. Lesiński, A. Kitlas Golińska, K. Mnich, W. R. Rudnicki, Prediction of Drug-induced Liver Injury using different integration techniques,
K. Mnich, W. R. Rudnicki, R. Piliszek, MDFS – a statistical filter for multivariate interactions
A. Polewko-Klim, W. Lesiński, K. Mnich, R. Piliszek, B. Sapiński, W. R. Rudnicki, Robust Machine Learning protocol with estimation of biases
W. Lesiński, K. Mnich, A. Kitlas Golińska, W. R. Rudnicki, Drug Induced Liver Injury prediction based on human cel lines gene expression and chemical properties of drugs
W. Lesiński, A. Kitlas Golińska,K. Mnich,W. R. Rudnicki, Integration of human cell lines gene expression and chemical properties of drugs for Drug Induced Liver Injury prediction
A. Polewko-Klim, W. Rudnicki, Building robust machine learning models (workshop)
Chen Suo, Xingdong Chen, A. Polewko-Klim, W. Rudnicki, Sibo Zhu Drug-target genes and drugs identification for more effective diagnosis and treatment of the squamous-cell carcinoma and adenocarcinoma esophageal cancer
A. Polewko-Klim, W. Rudnicki, Clinical and molecular markers for the prediction of clinical endpoints in breast cancer
A. Polewko-Klim, W. Rudnicki, Identification of Informative Variables in Neuroblastoma Patients
- Big Data Training School for Life Sciences, Uppsala, Sweden, 2017, Sep 18-22
A. Polewko-Klim, W. Rudnicki, Identification of informative variables in highly-multidimensional data (machine learning hands-on with expression data) (workshop)
- Computational Approaches in Precision Medicine, Vien, Austria, 2017, Jul 27-28 Boku University Vienna (org.)
A. Polewko-Klim, W. Lesiński, A. Kitlas Golińska, M. Siwek, K. Mnich, W. R. Rudnicki, Application of the random forest method in identification of candidate genes in quantitative trait loci regions for adaptive immune responses of chicken.
W. R. Rudnicki, K. Mnich, S. Migacz, P. Tabaszewski, R. Piliszek, A. Polewko-Klim, W. Lesinski, Knowledge discovery in data using Multidimensional Feature Selection.
K. Mnich,W. R. Rudnicki. Robust feature selection using multidimensional filters
- 9th Symposium of the Polish Bioinformatics Society, Białystok, Poland, 2016, Sep 28-30 PTBI Polish Bioinformatics Society, Faculty of Mathematics and Informatics, University of Białystok (org.)
W. Lesiński, A. Kitlas Golińska, A. Polewko-Klim, A. Przybylski, W. R. Rudnicki, Random Forest as a Tool in Arrhythmia Prediction.
A. Polewko-Klim, W. Lesiński, A. Kitlas Golińska, M. Siwek, W. Rudnicki, Identification of genetic markers for adaptive and innate immune traits in chickens using Random Forest.
W. Lesiński, R. Piliszek, J.S. Rodriguez, W. Rudnicki, DREAM Challenges’ new life.
- Reproducibility, standards and SOP in bioinformatics. Combined CHARME – EMBnet and NETTAB 2016 Workshop, Rome, Italy, 2016, Oct 25-26 COST European Action, EMBnet, NETTAB (org.)
W. Lesiński, R. Piliszek, J.S. Rodriguez, W. Rudnicki, A Robust Estimate of Performance of Reproducible Analytical Models for DREAM Challenges
- Expanding beyond the limits, 2nd Congress of Polish Biochemistry, Cell biology, Biotechnology and Bioinformatics, Wrocław, Poland, 2016, Sep 13-16 Polish Biochemical Society, Polish Cell Biology Society (org.)
W. R. Rudnicki, K. Mnich, S. Migacz, P. Tabaszewski, A. Sułecki, A. Polewko-Klim, W. Lesiński, A. Golińska, Identification of informative variables: a tool for knowledge discovery in life sciences.
- ECCB 2016: 15th European Conference on Computational Biology, Hague, Netherlands, 2016, Sep 3-7 Dutch Techcentre for Life Sciences, the BioSB research school and ELIXIR (org.)
(conference site: http://www.eccb2016.org/, will be at http://eccb.iscb.org/)
A. Polewko-Klim, W. Lesiński, A. Kitlas Golińska, M. Siwek, K. Mnich, W. R. Rudnicki, Application of the random forest method in identification of candidate genes in quantitative trait loci regions for adaptive immune responses of chicken.
W. Lesiński, A. Kitlas Golińska, A. Polewko-Klim, A. Przybylski, W. R. Rudnicki, Predicting arrhytmia with random forest.
K. Mnich, W. Rudnicki, A robust approach for discovery of synergistic variables.
W. Migacz, K. Mnich, R. Piliszek, W. Rudnicki, A. Sułecki, Sz. Tabaszewski, Efficient exhaustive search for synergistic informative variables.
- 7th Podlasie Conference on Mathematics (7th PCM), Białystok, Poland, 2016, Jun 8-11 Polish Mathematical Society, Białystok University of Technology, Poznań University of Technology, the University of Białystok (org.)
W. R. Rudnicki, K. Mnich, S. Migacz, P. Tabaszewski, A. Rościszewski, A. Sułecki, A. Polewko-Klim, W. Lesiński, A. Golińska, Search for Relevant Variables in Multidimensional World.
- RECOMB/ISCB Conference on Regulatory and Systems Genomics, with Dream Challenges 2015, 15-18.11.2015, Philadelphia, USA
W. R. Rudnicki, W. Lesiński, A. Polewko-Klim, K. Mnich, A. Golińska, Feature Selection & Random Forest for ALS prediction.
- VII Konwersatorium Chemii Medycznej oraz VIII Sympozjum PTBI, Toruń, Polska, 2015, Sep 17-19 Polskie Towarzystwo Bioinformatyczne, Polskie Towarzystwo Chemii Medycznej (org.), Ministerstwo Nauki i Szkolnictwa Wyższego (sponsor)
P. Cudek, T. Mroczek, W. Rudnicki, Amino acid properties conserved in molecular evolution
- The 8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2015), London, Great Britain, 2015, Dec 12-14 University of London, European Research Consortium for Informatics and Mathematics, Working Group on Computational and Methodology (org.)
Sz. Migacz, K. Mnich, A. Rościszewski, W. Rudnicki, A. Sulecki, P. Tabaszewski, Variable selection in high-dimensional data sets using GPU