Using knowledge engineering to study the brain Gully APC Burns Knowledge Mechanics Research Group, University of Southern California Gully APC Burns Knowledge.

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Presentation transcript:

Using knowledge engineering to study the brain Gully APC Burns Knowledge Mechanics Research Group, University of Southern California Gully APC Burns Knowledge Mechanics Research Group, University of Southern California

Using knowledge engineering to study the brain Gully APC Burns Knowledge Mechanics Research Group, University of Southern California Gully APC Burns Knowledge Mechanics Research Group, University of Southern California …most complex thing we have yet discovered in our universe James Watson …most complex thing we have yet discovered in our universe James Watson

Neuroscience traverses several spatial orders of magnitude Whole animal System (e.g. visual system) Brain region Cell population Whole cell Organelles Molecular signaling Genetics G. Shepherd (1994) Neurobiology

The number of components in the brain is literally astronomical Whole animal System (e.g. visual system) Brain region Cell population Whole cell Organelles Molecular signaling Genetics In Rat ~ 10 3 regions ~ 10 4 neuronal cell-types ~ 250,000 projections between neuronal cell types ~ 10 8 neurons ~ synapses ~ ??? proteins ~ ??? pathways Rat genome has 2.75 Gb

It involves a large number of sub-disciplines Whole animal System (e.g. visual system) Brain region Cell population Whole cell Organelles Molecular signaling Genetics Anatomy PhysiologyEthology Molecular Biology Molecular Biology Neurochemistry Biophysics

The neuroscience community Society for Neuroscience ~34,000 members. Mostly non-computational Neuroscience Database Gateway (NDG) has 73 separate neuroinformatics projects in different fields ( Community is hungry for informatics solutions but knowledge acquisition still a prime concern

Neuroinformatics is… … the information science infrastructure of neuroscience ( editorial from inaugural issue of the Journal Neuroinformatics ) … hold on a sec! Doesnt neuroscience already have an information science infrastructure already?

The Neuroscientific Literature … is the end-product of scientific research … forms the basis for human understanding of the subject … is structured … is interpretable … is phenomenally expensive to produce … is difficult to track and use … is terse Image taken from U.S. Geological Survey Energy Resource Surveys Program

Unpublished knowledge forms a huge resource within a laboratory u Notes u Laboratory notebooks u Data files u In-house documentation u Powerpoint presentations u Word-of-mouth / conversation

NeuroScholars approach to the literature Fact A Fact B Fact C Interpretation A * Interpretation B * Interpretation C * Relation BC *

This approach may be generalized Fact A Fact B Fact C Interpretation A * Interpretation B * Interpretation C * Relation BC *

All design work built in UML UML packages & classes…

Knowledge sharing architecture

PubMed & the literature

Accessing the contents of pdfs

Diagrams in NeuroScholar

Other systems: NeuroAtlas Not currently available pending resolution of copyright issues with atlas publishers

Open Questions u Build better, faster, larger plumbing u help! u Seeking access to (and building our own) analysis techniques for knowledge base contents u help!

Acknowledgements This work is funded by the National Library of Medicine (LM07061) Arshad Khan Lori Howard Kim Rapp Joel Hahn Mihail Bota Alan Watts Larry Swanson Wei Cheng Chen Shyam Kapadia Yi-Shin Chen Shahram Ghandehanderazdeh Cyrus Shahabi Mark ONeill

It is easy to impose a pattern less easy to make it stick less still to discover one there. Building a snowman. Richard Burns.

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