Projekty

Pełna lista dostępna na Google Scholar

Rozprawa doktorska, Identifying low-dimensional structures through model selection in high-dimensional data
Bayesian dimensionality reduction with PCA using penalized semi-integrated likelihood, Piotr Sobczyk, Malgorzata Bogdan, Julie Josse; Journal of Computational and Graphical Statistics, 2017
Controlling the rate of GWAS false discoveries, Damian Brzyski, Christine B. Peterson, Piotr Sobczyk, Emmanuel J. Candes, Malgorzata Bogdan, Chiara Sabatti; Genetics, 2017
Methods for comparing multiple digital PCR experiments, Michal Burdukiewicz, Stefan Rödiger, Piotr Sobczyk, Mario Menschikowski, Peter Schierack, Paweł Mackiewicz; Biomolecular Detection and Quantification, 2016
Prediction of signal peptides in proteins from malaria parasites Michał Burdukiewicz, Piotr Sobczyk, Jarosław Chilimoniuk, Przemysław Gagat, Paweł Mackiewicz; International journal of molecular sciences, 2018
Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control, Sangkyun Lee, Piotr Sobczyk, Malgorzata Bogdan; Symmetry, 2019

varclust. Clustering variables. Performs clustering of quantitative variables, assuming that clusters lie in low-dimensional subspaces. Segmentation of variables, number of clusters and their dimensions are selected based on BIC. Candidate models are identified based on many runs of K-means algorithm with different random initializations of cluster centers. Available on CRAN
pesel, Automatic estimation of number of principal components in PCA with PEnalized SEmi-integrated Likelihood (PESEL). Available on CRAN
biogram: N-Gram Analysis of Biological Sequences. Tools for extraction and analysis of various n-grams (k-mers) derived from biological sequences (proteins or nucleic acids). Contains QuiPT (quick permutation test) for fast feature-filtering of the n-gram data. Available on CRAN
giosAPI, a set of tools that provide access to the GIOS air quality data API. Available on Github