Structure learning for protein signaling pathways
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Updated
Apr 28, 2017 - Python
Structure learning for protein signaling pathways
gr-eventstream is a set of GNU Radio blocks for creating precisely timed events and either inserting them into, or extracting them from normal data-streams precisely. It allows for the definition of high speed time-synchronous c++ burst event handlers, as well as bridging to standard GNU Radio Async PDU messages with precise timing easily.
Code for analysis of single cell signaling network kinetics from flow cytometry (CyTOF) datasets
Computations required for https://doi.org/10.1103/PhysRevE.97.020402 and additional work
A kinetic model of dopamine- and calcium-dependent striatal synaptic plasticity (Nakano et al. 2010)
Converting SBGN encoded pathways to the SIF file format
Modeling signaling networks in cancer
Ligand-Receptor Interaction map based on scRNA-seq and pathway enrichment
Converting KGML encoded KEGG pathways to the SIF file format
PHOsphoproteomic dissecTiOn using Networks
Rescue of plasticity by a computationally predicted protocol (Liu et al. 2013)
Model of a BDNF feedback loop (Zhang et al 2016)
Finding paths of interest in networks
Pathway Enrichment-Guided Activity Study of Alternative Splicing (PEGASAS)
The functional analysis of genes provides relevant information to understand cellular function. Further, the mapping of genetic interactions sheds light on how genes act in the emergence of cellular complexity. Here, we present the most extensive genetic interaction and morphological profiling screen in a metazoan cell to date. We profiled 680 0…
Code repository for the publication. Contains MATLAB codes and sequence data used for evolutionary analysis.
Computational modeling of gephyrin-dependent inhibitory transsynaptic signaling (Lupascu et al 2020)
An integrative dynamic model of brain energy metabolism (Coultier et al 2009)
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