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Bits, Brains and Behaviors. The science - NeuronBank The history of the project What did we learn? Big Theme – Collaboration. ******-informatics *****- omics. Common theme. More than just store information Analysis - increase our understanding of biological processes

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bits brains and behaviors
Bits, Brains and Behaviors
  • The science - NeuronBank
  • The history of the project
  • What did we learn?
  • Big Theme – Collaboration


*****- omics

common theme
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
problem we are using publications as a method to catalog neurons and neural circuits
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 knowledge.
  • 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
The Neurome is harder to represent than the Genome.
  • Neurons are identified based on their properties.
    • Idiosyncratic
    • Species-specific
    • Constantly evolving
the neurome is harder to represent than the genome1
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
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.
neuronbank org 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 circuitry.

Collection of ontologies and tools to access them A Neuromics Tool
Lesson 0: (Obvious)

Cross-Disciplinary Challenges

  • Different disciplines
  • Different cultures/languages
  • Reward: The satisfaction of working on real problems
  • 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 this
    • Give and take of size/scope through the funding process
example neuroviz
Example: NeuroViz
  • Moved from a 3D program to a 2D web browser based applet
  • That:
neuronbank v2 0
NeuronBank v2.0
  • NeuronBank 1.0 achieved its objectives.
  • First system to:
    • Support a varying data model for Species specific representation
    • 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
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 v1.0
  • 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
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
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 system
Lesson 4: Managing Humans
  • Who owns this?
    • Code
    • Project/Sub-project
  • Academic Attrition
  • Publication potential to keep students interested
    • Ideally enough research for this to be the honors/thesis/dissertation topic for a student
lesson 5 institutional support
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
  • Computer Science
    • Sushil Prasad, Ph.D.
    • Ying Zhu, Ph.D.
    • Raj Sunderraman, Ph.D.
  • Students:
  • Chad Frederick
  • Weiling Li
  • Rasanjalee Dissanayaka Mudiyanselage
  • Shuman Gao

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