Oksana Sorokina

Protein trafficking and synaptic demand configure complex and dynamic synaptome architectures of individual neurons

The paper develops computational models to explain synaptic protein distribution patterns in neurons by integrating molecular transport and local synaptic demand mechanisms across different ages and cell types.

SynaptopathyDB: a resource for studying the genetic and synaptic basis of nervous system disorders

SynaptopathyDB integrates synapse proteomic and genetic data to identify synaptic gene variants associated with neurological and systemic disorders.

Modelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases

MoNvIso predicts the correct protein isoform for mutations and builds structural models of wild-type and variant isoforms using gene names and mutation lists.

BioNAR: An Integrated Biological Network Analysis Package in Bioconductor

BioNAR is a Bioconductor package for analyzing biological networks to quantify and rank vertices based on topology and clustering, enabling discovery of disease and function-enriched subcomplexes.

A configurable model of the synaptic proteome reveals the molecular mechanisms of disease co-morbidity.

The paper constructs a configurable synaptic proteome network model to analyze molecular mechanisms of disease co-morbidity by integrating proteomic and interaction data.

Regional diversity in the postsynaptic proteome of the mouse brain

The paper identifies regional differences in the postsynaptic proteome across mouse brain regions using proteomic mass spectrometry, revealing unique compositional signatures correlated with anatomy and embryology.

Analysis of proteins in computational models of synaptic plasticity

The paper maps proteins in biophysical models of synaptic plasticity, finding 4.2% of synaptic proteins are modelled and identifying gaps in disease-related proteins.