waveform LiDAR data processing and analysis
FPGA embedded multicore processing of an iterative deconvolution method based on sparse data representation aimed at online reconstruction of energy in particle accelerators
On the Inversion of High Energy Proton, K-Fold Inverse of Stochastic Autoconvolution [arXiv:1905.12585]
A benchmark for non-blind deconvolution methods: classical algorithms vs SOTA neural models
Open Source Perfusion Analysis Plugin for OsiriX and Horos
spatially aware scalable and accurate tool for spot deconvolution and clustering in spatial transcriptomics
A lightweight convolutional neural network with end-to-end learning for three-dimensional mineral prospectivity modeling
Snakemake pipeline for benchmarking cell-type deconvolution methods and deconvolving real bulk RNA-seq data with the use of scRNA-seq datasets
A wavelet-based linear programming method using L1-minimal reconstruction loss for accessible chromatin data deconvolution
Detection of single sources solving a deconvolution problem
Utkarsh Mahamune, Aldo Jongejan, Antoine van Kampen and Perry D Moerland: Systematic evaluation of robustness to cell type mismatch of deconvolution methods for spatial transcriptomics
Data for magnetstein paper & web application. For more info see: https://github.com/BDomzal/magnetstein.
Employing Magnetstein for the analysis of chemical reactions.
Personal portfolio enumerating my main omic analyses projects
Tools for quantitative analysis of nuclear magnetic resonance (NMR) spectra using the Wasserstein metric.
Implementation of HIDE as proposed in Völkl et al (2025), HIDE: Hierarchical cell-type Deconvolution
Deconvolution of Hi-C interactions from duplicated genomic copies in ecDNA
Shiny Application for DNAmBenchmarking paper doi: 10.1101/2025.11.27.688590
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