
@article{Roy:2018Regional,
  title = {Regional {{Diversity}} in the {{Postsynaptic Proteome}} of the {{Mouse Brain}}},
  author = {Roy, Marcia and Sorokina, Oksana and McLean, Colin and {Tapia-Gonz{\'a}lez}, Silvia and DeFelipe, Javier and Armstrong, J. Douglas and Grant, Seth G. N.},
  year = {2018},
  month = sep,
  journal = {Proteomes},
  volume = {6},
  number = {3},
  pages = {31},
  publisher = {{Multidisciplinary Digital Publishing Institute}},
  issn = {2227-7382},
  doi = {10.3390/proteomes6030031},
  url = {https://www.mdpi.com/2227-7382/6/3/31},
  urldate = {2022-07-08},
  abstract = {The proteome of the postsynaptic terminal of excitatory synapses comprises over one thousand proteins in vertebrate species and plays a central role in behavior and brain disease. The brain is organized into anatomically distinct regions and whether the synapse proteome differs across these regions is poorly understood. Postsynaptic proteomes were isolated from seven forebrain and hindbrain regions in mice and their composition determined using proteomic mass spectrometry. Seventy-four percent of proteins showed differential expression and each region displayed a unique compositional signature. These signatures correlated with the anatomical divisions of the brain and their embryological origins. Biochemical pathways controlling plasticity and disease, protein interaction networks and individual proteins involved with cognition all showed differential regional expression. Combining proteomic and connectomic data shows that interconnected regions have specific proteome signatures. Diversity in synapse proteome composition is key feature of mouse and human brain structure.},
  copyright = {http://creativecommons.org/licenses/by/3.0/},
  langid = {english},
  keywords = {connectome,mass spectrometry,postsynaptic,protein interaction networks,proteome,synapse},
  file = {/Users/lptolik/Zotero/storage/S7ANVUHN/Roy et al. - 2018 - Regional Diversity in the Postsynaptic Proteome of.pdf;/Users/lptolik/Zotero/storage/B5KPLCV7/htm.html}
}

@article{PhysRevE.74.036104,
  title = {Finding community structure in networks using the eigenvectors of matrices},
  author = {Newman, M. E. J.},
  journal = {Phys. Rev. E},
  volume = {74},
  issue = {3},
  pages = {036104},
  numpages = {19},
  year = {2006},
  month = {Sep},
  publisher = {American Physical Society},
  doi = {10.1103/PhysRevE.74.036104},
  url = {https://link.aps.org/doi/10.1103/PhysRevE.74.036104}
}
