Adaptive sampling for nanopore direct RNA-sequencing
Published in RNA, 2023
Here we show how Adaptive Sampling for direct RNA sequencing with Oxford-Nanopore technology is feasible considering the specific technical and biological challenges.
Selected Publications
Characterizing alternative splicing effects on protein interaction networks with LINDA
Published in Bioinformatics, 2023
LINDA (Linear Integer programming for Network reconstruction using transcriptomics and Differential splicing data Analysis) is a method that integrates resources of protein–protein and domain–domain interactions, transcription factor targets, and differential splicing/transcript analysis to infer splicing-dependent effects on cellular pathways and regulatory networks.
PHONEMeS: Efficient Modeling of Signaling Networks Derived from Large-Scale Mass Spectrometry Data
Published in Journal of Proteome Research, 2021
PHONEMeS is a method that uses high-content shotgun phosphoproteomic data to build logical network models of signal perturbation flow through the implementation of an efficient Integer Linear Programming (ILP) formulation.
Causal integration of multi‐omics data with prior knowledge to generate mechanistic hypotheses
Published in Molecular Systems Biology, 2021
COSMOS combines extensive prior knowledge of signaling, metabolic, and gene regulatory networks with computational methods to estimate activities of transcription factors and kinases as well as network‐level causal reasoning.
Converting networks to predictive logic models from perturbation signalling data with CellNOpt
Published in Bioinformatics, 2020
CellNOpt is a collection of Bioconductor R packages for building logic models from perturbation data and prior knowledge of signalling networks.
From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVAL
Published in npj Systems Biology and Applications, 2019
CARNIVAL - a causal network contextualization tool which derives network architectures from gene expression footprints.
Literature and data-driven based inference of signalling interactions using time-course data
Published in IFAC-PapersOnLine, 2019
This paper describes Dynamic-Feeder as a method which combines data-driven inference methods with general literature-based knowledge of proteins interaction networks.
Elucidating essential kinases of endothelin signalling by logic modelling of phosphoproteomics data
Published in Molecular Systems Biology, 2019
A comprehensive logic model of endothelin signalling was constructed using phosphoproteomics data from melanoma cell lines, highlighting the role of specific kinases in Endothelin (EDN)-induced cell migration and supporting the strategic selection of kinase inhibitors for combined treatments with EDN receptor antagonists.