Summary The Cytoscape Cyberinfrastructure (CI) extends the successful Cytoscape development and community model by enabling network biologists to contribute and leverage microservices deployable at scale. The CI solves many of Cytoscape’s limitations while also delivering novel and dynamic functionality to both Cytoscape and standalone workflows, thus further empowering the already vital network biology community. Abstract Cytoscape is an indispensable tool for network data analysis and visualization. One of Cytoscape’s greatest strengths is that it is powered by a vibrant array of developer-contributed apps. However, as network biologists’ requirements evolve, Cytoscape is challenged not only to keep pace, but to lead new and existing developers to create even greater value. Currently, multiscale and multifaceted networks push the memory limits of a Cytoscape workstation, while complex calculations such as Network Based Stratification and Network Based GWAS strain workstation processors. Increasingly, users demand support for collaborative projects, reproducible workflows, and interoperability with external tool chains. Finally, economic pressures favor solutions that promote code and algorithm reusability and evolvability. In response, we have created the Cytoscape Cyberinfrastructure (CI), which is both an Internet-scale distributed system (based on Microservices [1]) and the network biology community it serves. Its mission is to enable and encourage network biologists to create and deploy high quality, innovative and scalable services focusing on network-based computation, collaboration and visualization. Microservices can be written in any language, and are highly testable and evolvable. They can run on servers ranging from a single thread to a large cloud-based cluster. They can easily be reused in reproducible workflows or can serve as components in larger services. The CI links microservices via a light weight REST-based aspect-oriented interchange protocol (called CX), which enables tailored data streams while supporting service innovation via evolvable standards. CI infrastructure services support user authentication, long duration job execution, and a service repository that enables researchers to publish their services or discover services published by others. This model builds on the successful Cytoscape app community, which is based on similar mechanisms though at the scale of individual workstations. Prominent examples of microservices include NDEx [2] (a repository for biological networks), NodeWalker (which uses heat dispersion to identify the most relevant subnetworks containing a given set of genes), cyNetShare [3] (which visualizes a network in a browser) and Cytoscape itself (which can also call CI services). Interfaces are available for Python, IPython, R and Matlab. Future work includes adding clustering, analysis, layout, publishing and display microservices and interfaces to Galaxy and Taverna workflows.

1. Cytoscape Cyberinfrastructure
Leveraging Microservices
to the Cloud and Beyond
Chapter 1
ISMB/NetBioSIG 2015
Dublin, Ireland
July 10, 2015
Keiichiro Ono, Dexter Pratt & Barry Demchak
Ideker Lab
1

2. Cytoscape’s 3 Wishes
 More …
 memory for networks
 cores for analysis
 code reusability
 languages/libraries for coding
 Better browser presence
 Access to long running calculations
 Quicker/cheaper novel workflows
 Higher quality, more shareable code
 Even more vibrant NB community 2

3. Cytoscape Cyberinfrastructure (CI)
 Internet-based computing ecosystem that
 Complements Cytoscape
 Supports producers, consumers, and
operators (as COIs)
 Scales and evolves to support data
acquisition, computing, storage, management,
integration, mining, and visualization
 Sharable and Testable
 Coevolution – community w/ CI / community
 Service Oriented Architecture (SOA)
 Microservices + data bus + discovery 3

4. Roadmap
 Existing Ecosystem
 Cyberinfrastructure (CI) & Network Biology
 Use Cases
 Strategy
 Technology
 SOA & REST
 CX & middleware
 CI Now & Later
 Support
 Call to Community 4

5. Existing Ecosystem
 Visual Workflow Systems - Taverna & Galaxy (& MyExperiment)
 Service Repositories - BioCatalogue
 General programming languages & tools - Python, R, Java,
Matlab, IPython/Jupyter
 Network Analysis & Visualization – Cytoscape, cytoscape.js,
GeneMANIA
5
Cytoscape CI
 shared workflows
 shared services
 novel workflows
 scalable

6. CI & Network Biology
Identify
network
Add data
to network
Layout
nodes
Color
nodes
Publish
New Service New Service New Service New Service
BridgeDB
Clients Services
Critical CI Outcomes
 Cheap services ~ innovation
 Reproducible workflows
 Interoperable tool chains
 Code & algorithm reusability
 Community
 Community
 Community
6

7. CI - Future of Publishing
7

8. NAV – CI-based Workflow
8

9. Generic Microservices
Producer Database
OK
StoreData(xxx)
Time
Producer Database
Message Bus
StoreData(xxx)
OK
)(xfy


For a service, the meaning of life:
Benefits
 Loose Coupling
 Late Binding
 Decentralized
Governance
 Scalability
 Reusability
 Distributability
 Portability
 Composability
 Interoperability
 Testability
9

10. Cytoscape CI
Cytoscape
Desktop
Message Bus (Internet)Message Bus (Internet)
Analytics Layout
NDEx
(Store/
Retrieve)
Journal
Publishing
NeXO
Personal
Publishing
R/Python/
Matlab
LayoutLayoutLayout
AnalyticsAnalyticsAnalytics
cyNetShare
Gene-
MANIA
BridgeDB MCODE
Data
Model
Layouts
ServicesApplications
10
 CX is an aspect-oriented transfer format
 CX carries networks and related data

11. CX Transfer Format
1
3 2
Example Graph
4
5
nodes Aspect
edges Aspect
cartesianLayout Aspect
Aspect Relationships
Organizes
Positions
ID=1 ID=2 ID=3
nodes Aspect (3 nodes)
edges Aspect (2 edges)
Source Target Source TargetID=4 ID=5
cartesianLayout Aspect
X=100 Y=100ID X=200 Y=200ID X=100 Y=200ID
CX Encoding
11
Benefits
 Streamable (large networks)
 Lossless (BioPAX, SGML, OpenBEL…)
 Extensible (new aspects)
 Mature parsers (JSON)
 JSON LD (RDF compatible)
 Purpose-optimized transfers (aspects)
 Community, community, community

12. CX in Action
[
{"nodes": [{"@id": "_:1"}, {"@id": "_:2"}]},
{"edges": [{"source": "_:1", "@id": "_:4", "target": "_:2"}]},
{"cartesianLayout": [{"x": "100", "node": "_:1", "y": "100"}]},
{"cartesianLayout": [{"x": "200", "node": "_:2", "y": "300"}]},
{"nodes": [{"@id": "_:3"}]},
{"edges": [{"source": "_:2", "@id": "_:5", "target": "_:3"}]},
{"cartesianLayout": [{"x": "100", "node": "_:3", "y": "200"}]}
]
12

13. API Perspective - Simple
13
ServiceClient
CX Library
Service call (w/CX)
REST
Results return (w/CX)
CX Library
 Long running jobs require long running clients
 Allows only one service at a time

14. API Perspective - Elaborated
14
Node
Service
Interface
CX Library
Service
Interface
CX Library
Service
Interface
CX Library
Submit
Agent
...
Node
Running
Results
Collector
Results DatabaseResults Database
Client
CX Library
Complete
Monitor DatabaseMonitor Database
Status
Monitor
Service call (w/CX)
Service return (jobID)
Status call (jobID)
Status return
REST
MessageBroker
Service call (w/CX)
MQ
Saveresults
Query status
(jobID)
Results call (jobID)
Results return (w/CX)
Queued
Load
Balancer

15. Implementation Perspective
15
Node
Service (any
language)Interface
(Zero
M
Q)
CX Library
Submit
Agent
(Python
Flask)
Node
Results
Collector
(Python)
Results DatabaseResults Database
Client
(any
language)
CX Library
Monitor DatabaseMonitor Database
Status
Monitor
(Python)
ZeroMQ
REST MQ

16. CI Now
16
Cytoscape
R / Python /
Matlab / C#
cyREST
cyNetShare
cytoscape.js
cytoscape.js
cytoscape.js
ScienceDirect
Cyrface
cytoscape.js
NDEx
cytoscape.js
NAV
Network
Based
Stratification
Heat
Dissipation
ID
Translation
(BridgeDB)
XGMML
.cyjs
App
Store
.cyjs
WS/SOAP

17. CI Later
17
Cytoscape
R / Python /
Matlab / C#
cyREST/CX
cyNetShare
cytoscape.js
cytoscape.js
cytoscape.js
ScienceDirect
Cyrface
cytoscape.js
NDEx
cytoscape.js
NAV
Network
Based
Stratification
?DREAM?
?GIANT?
Heat
Dissipation
ID
Translation
(BridgeDB)
Layouts
Clustering
(?MCODE?)
Network
Prediction
(?GeneMANIA?)
Attribute
Merge
CX
Enrichment
CX
CX
CX
?Taverna?
?Galaxy?
CIAuth
App
Store

18. CI Later w/Reuse
18
Cytoscape
R / Python /
Matlab / C#
cyREST/CX
cyNetShare
cytoscape.js
cytoscape.js
cytoscape.js
ScienceDirect
Cyrface
cytoscape.js
NDEx
cytoscape.js
NAV
Network
Based
Stratification
?DREAM?
?GIANT?
Heat
Dissipation
ID
Translation
(BridgeDB)
Layouts
Clustering
(?MCODE?)
Network
Prediction
(?GeneMANIA?)
Attribute
Merge
CX
Enrichment
CX
CX
CX
?Taverna?
?Galaxy?
CIAuth
App
Store

19. Support
 National Resource for Network Biology (NRNB)
 Supports software and staging hardware
 Pharma & NCI support NDEx
 Elsevier
 All sources open and on GitHub
19

20. Call to Community
 App authorshipCytoscape community thrives
 Pride of authorship, listing in App Store
 Tangible realization of useful research
 Valuable workflows for all to use
 Publishable results (e.g., F1000)
 CI community inherits all of these! … but also:
 More direct path from algorithm to useful code
 Wider audience
 Easier coding & dissemination
 Better coding practices
 More resources
20
More Information
bdemchak@ucsd.edu

21. Reading List
 http://martinfowler.com/articles/microservices.html
 http://home.ndexbio.org/about-ndex-2
 http://idekerlab.github.io/cy-net-share
 Lincoln Stein. Towards a cyberinfrastructure for the biological
sciences: progress, visions and challenges.
http://www.nature.com/nrg/journal/v9/n9/full/nrg2414.html
 Barry Demchak, et al. PALMS: A Modern Coevolution of Community
and Computing Using Policy Driven Development.
https://sosa.ucsd.edu/ResearchCentral/view.jsp?id=203
 Stephen Goff, et al. The iPlant collaborative: cyberinfrastructure for
plant biology.
http://journal.frontiersin.org/article/10.3389/fpls.2011.00034/pdf
21

22. End of Deck
 Backup slides are beyond here
22

23. Existing Ecosystem
 Visual Workflow Systems
 Taverna & Galaxy – high level orchestration
 MyExperiment – sharing workflows
 Service Repositories
 BioCatalogue
 General programming languages & tools
 Python, R, Java, Matlab, IPython/Jupyter
 Network Analysis & Visualization
 Cytoscape & cytoscape.js
 GeneMANIA
 Cytoscape Cyberinfrastructure (?)
++ - - ++
++ - - ++
++
+ ++ + -
+ + ++ -
+ - +
++ ++ ++ ++
23

24. CX Timings
 Using Human network (18K nodes, 127K edges)
 CX output around 150MB
 Timings exclude accessing Cytoscape data
model – Cytoscape data model increases
timings by 2-4x
24
Aspect Read (ms) Write (ms)
Nodes 6 3
Edges 97 51
NodeAttrs 77 58
EdgeAttrs 1289 1077