Using the Grid for the interactive workflow management in biomedicine. Andrea Schenone BIOLAB DIST University of Genova

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1 Using the Grid for the interactive workflow management in biomedicine Andrea Schenone BIOLAB DIST University of Genova

2 overview background requirements solution case study results

3 background A multilevel approach is more and more required medical cellular molecular >patient model Virtual P hysiological Human clinical and genomic studies personalized medicine multiscale biomedical experiments drug design & discovery

4 background morphological & functional increasing number of images different formats analysis protocols diagnosis disease progression medical imaging acquisitions over time geographically distributed therapy follow up

5 background high throughput sequencing microarray analysis interactive acquisitions bioinformatics analysis tools instruments repositories virtual experiments interoperability metadata ontologies

6 the environment laboratories facilities analysis instruments services data computing resources repositories

7 requirements functional sequences of acquisition and analysis heterogeneous datasets distributed instruments interoperability distributed computing resources data mining web services hiding complexity data analysis friendly user interface high sensitivity of biomedical information large scale experiments standards distributed repositories automatic enactment of complex workflows

8 the Grid approach standardized sharing of resources secure robust reliable performance scaling dynamically terabytes scenarios privacy issues authentication schema certificate based

9 the BMPortal platform job scheduling BMPortal Grid based job submission plugin Genius glite 3.0 monitoring accounting data management metadata access AMGA J2EE tomcat servlet container server EnginFrame Grid Gateway agents services XML

10 the BMPortal platform databases system commands library functions resources model user web GUI portal web GUI portal view controller web services WSDL requests commands to server results resources

11 workflow management Grid services WSDL EF SOAP Web services standard nodes workflows definition enactment Taverna Moteur Grid resources parallelism

12 workflow management definition of workflows upload of workflows input data submission of workflows Grid jobs monitoring of workflows download spooling of results visualization

13 portal architecture

14 case study gene expression profiling breast cancer tissues microarray analysis 448 patients different databases KEGG GEO HG-U133 microarray chips GeneChip TM Affymetrix

15 functional sequence KEGG GEO search of suitable data downloading of datasets semantic search filtering of data subset of genes merging of datasets normalization gene expression profiling differentially expressed genes

16 workflow

17 operating sequence definition of workflow Taverna MPI parallelization exposition of web services dchip enactment of workflow accessing monitoring workflow retrieving results Moteur visualization download distributed resources remote data access data computing

18 workflow selection

19 workflow monitoring

20 conclusions A Grid platform has been developed to support distributed applications in the biomedical domain The platform can act as Web interface for performing workflow management and enactment on the Grid Results are produced using distributed resources both for data and for computation The results are displayed to the user through the portal interface The platform can act as provider of Grid services to be used in workflows as standard nodes The complexity and the heterogeneity of data are hidden from users The execution status is continuously checked while performing workflows The platform has been tested on a case study concerning the analysis of microarray data for breast cancer studies

21 Future work to include a workflow definition tool in the platform to develop semantic tools for data mining to fully exploit metadata to extend the data types manageable by the workflow enactor

22 thanks Andrea Schenone

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