NeuronBank - Ursinus College

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Transcript NeuronBank - Ursinus College

Bits, Brains and Behaviors
• The science - NeuronBank
• The history of the project
• What did we learn?
Big Theme – Collaboration
*****- omics
Common theme
• More than just store information
• Analysis - increase our understanding of
biological processes
• Applying computationally intensive techniques
(e.g., pattern recognition, data mining, machine
learning algorithms, and visualization) to achieve
this goal.
• Sequence alignment, gene finding, genome
assembly, drug design, drug discovery, protein
structure alignment, protein structure prediction
Understanding the brain requires
understanding its circuitry
Problem: We are using publications
as a method to catalog neurons
and neural circuits
• Information is distributed and fragmented.
• No means to efficiently search this
• No means to publish incremental
knowledge without a functional story.
• Genomics is the study of the Genome,
where the Genome consists of all of the
genes in an organism
• Neuromics is the study of the Neurome,
where the Neurome consists of all of the
neurons in an organism
The Neurome is harder to
represent than the Genome.
• Neurons are identified based on their
– Idiosyncratic
– Species-specific
– Constantly evolving
The Neurome is harder to
represent than the Genome.
• No standards for representing our knowledge of
neural circuits.
• No means to database this knowledge
Our Approach
• Traditional databases are not a good fit Changes in representation would cause the
database schema to change
• Ontology: A formal representation of a set of
concepts within a domain and the relationships
between those concepts – A Vocabulary
• We created a core ontology that applies to all
nervous systems
• We also support extensible species-specific
ontologies. A Neuromics Tool
• NeuronBank is to neurons
what GenBank is to genes.
– A place to publish knowledge about neurons
and neural connectivity
– Tools to represent, search, analyze, and
share knowledge of neurons and neural
– Collection of ontologies and tools to access
them A Neuromics Tool A Neuromics Tool A Neuromics Tool
DSI A Neuromics Tool
DSI A Neuromics Tool
Lesson 0: (Obvious)
Cross-Disciplinary Challenges
• Different disciplines
• Different cultures/languages
• Reward: The satisfaction of working on real
• Key: Realistic expectations.
Lesson 1:Defining Requirements
• Requirements describe in detail what a
software system is supposed to do
• Easier said than done
• The Myth of Stable Requirements
– Specially true in a research project such as
– Give and take of size/scope through the
funding process
Example: NeuroViz
• Moved from a 3D program to a 2D web
browser based applet
• That:
• Became this
NeuronBank v2.0
• NeuronBank 1.0 achieved its objectives.
• First system to:
– Support a varying data model for Species specific
– While still allowing searches across species
• At the time of commencing work on v1.0
no clear standards existed for storing data
as per our requirements
Problems with v1.0
• Since v1.0 a lot of research has gone towards
realizing the Semantic Web
• Extension to the WWW where the semantics of
the information is defined
• We used a combination of technologies to build
• This works… But:
– Standards have now emerged for the Semantic Web
(OWL) and Biological Ontologies (OBO). We need to
conform to these.
– Development Challenges.
– Interface problems.
Lesson 2: Design for Change
• Need to design for change
• It’s the only thing that’s a given
• Projects should have the ability to evolve,
discard and replace individual components
with minimal impact on other pieces
– Going from a stand alone 3-D Viz Tool to a
browser based tool meant several changes
for the branch
– Moving to a Semantic Web version
Lesson 3: Community Building is hard
• A lot of excitement every time we pitch this
to a group of researchers working on
some species.
• But who will enter the data? 80/20 rule
• The system is only as good as what’s in it.
• Some sort of an incentive is needed to get
new species started
– Using NeuronBank wiki in classes
– Then moving this data into NeuronBank
• Some visible advantage to using the
Cerebral Ganglia
Lesson 4: Managing Humans
• Who owns this?
– Code
– Project/Sub-project
• Academic Attrition
• Publication potential to keep students
– Ideally enough research for this to be the
honors/thesis/dissertation topic for a student
Lesson 5: Institutional support
Was this a good investment?
$36,000 - 2004 Seed Grant:
$25,976 - 2005 2nd Seed Grant:
$61,976 - Total initial investment by GSU
$258,102 - Funded Grants (R21 grant)
– (4x initial investment)
• $1,873,102 – NSF and NIH
– (30x initial investment)
Neuroscience Institute
Paul Katz
Past Members
Akshaye Dhawan
(now at Ursinus College)
Bob Calin-Jageman,
(now at Dominican University)
Jason Pamplin
Hao Tian
Hong Yang
Hsui Wang
Janaka Balasooriya
Xiuyun Shen
Wenjun Ma
Piyaphol Phoungphol
Naveen Hiremath
Monika Patel
Suzy Gentner
Computer Science
Sushil Prasad, Ph.D.
Ying Zhu, Ph.D.
Raj Sunderraman, Ph.D.
•Chad Frederick
•Weiling Li
•Rasanjalee Dissanayaka Mudiyanselage
•Shuman Gao
Thank You for your time and attention