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P. Romano, Tutorial BITS2005 1 Data integration, web services and workflow management Paolo Romano National Cancer Research Institute, Genova

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Presentation on theme: "P. Romano, Tutorial BITS2005 1 Data integration, web services and workflow management Paolo Romano National Cancer Research Institute, Genova"— Presentation transcript:

1 P. Romano, Tutorial BITS2005 1 Data integration, web services and workflow management Paolo Romano National Cancer Research Institute, Genova (

2 P. Romano, Tutorial BITS20052 Summary Information and data integration Web Services CABRI and TP53 databases Implementation of Web Services (soaplab) Workflow management Demo: execution of workflows with taverna

3 P. Romano, Tutorial BITS20053 Information in biology Biomedical research produces an increasing quantity of new information Some domains, like genomics and proteomics, contributes to huge databases Emerging domains, like mutation and variation analysy, polymorphisms, metabolism, and technologies, e.g., microarrays, will contribute with even huger amounts of data

4 P. Romano, Tutorial BITS20054 Information in biology EMBL Data Library 74 (Mar 2003): o Sequences: 23,234,788, Bases: 30,356,786,718 EMBL Data Library 81 (Dec 2004): o Sequences: 40,696,839, Bases: 44,285,259,441 o WGS sequences: 5,408,558, Bases: 34,986,041,399 EMBL Data Library 82 (Mar 2005): o Sequences: 43,246,005, Bases: 46,927,070,905 o WGS sequences: 6,228,397, Bases: 38,207,643,477 o Size: 7,3% more vs 81 (3 months), 112,9% vs 74 (24 months)

5 P. Romano, Tutorial BITS20055 Heterogeneicity of databanks Only a few databanks are managed in an almost homogenous way by EBI, NCBI, DDBJ (sequence) Many databanks are created by small groups or single researchers Secondary databases are of high quality (good and extended annotation, quality control) Many databases are highly specialized, e.g. by gene, organism, disease, mutation, etc… Databanks are distributed: different DBMS, data structures, information, semantics, distribution methods

6 P. Romano, Tutorial BITS20056 Softwares Specialist softwares are essential for almost all analysis in molecular biology: o Sequence analysis, secondary and tertiary protein structure prediction, gene prediction, molecular evolution, etc… Softwares must interoperate with databases o Databases as input for softwares o Results as new data to record and analyze

7 P. Romano, Tutorial BITS20057 Goals of the integration Integration is needed in order to: o Achieve a better and wider view of all available information o Carry out analysis and/or searches involving more databases and softwares automatically o Perform analysis involving large data sets o Carry out a real data mining

8 P. Romano, Tutorial BITS20058 Integration needs stability o Standardization…… o Good domain knowledge o Well defined data o Well defined goals Integration fears: o Heterogeneicity of data and systems o Uncertain domain knowledge o Fast evolution of data o Highly specialized data o Lacking of predefined, clear goals o Originality, experimentalism (“ let me see if this works” ) Integration longevity

9 P. Romano, Tutorial BITS20059 Integration of biological information In biology: o Goals and needs of researchers evolve very quickly according to new theories and discoveries o A pre-analysis and reorganization of the data is very difficult, because data and related knowledge vary continuosly o Complexity of information makes it difficult to design data models which can be valid for different domains and over time

10 P. Romano, Tutorial BITS200510 Integration methods Explicit (reciprocal) links (xrefs) Implicit links (e.g., names) Common contents (vocabularies) Shared data models and schemas Ontologies

11 P. Romano, Tutorial BITS200511 Web Services XML based network services Implement standard transport protocols (SOAP, HTTP) Standards available for their retrieval and identification (UDDI), description (WSDL) and composition (WSFL) Allow software applications to access data “intelligently”: identification of contents, interpretation of semantics information Metadata needed Web Services implemented by many Institutes and service nodes (EBI, NCBI,....)

12 P. Romano, Tutorial BITS200512 WSDL: the description Web Services Description Language (WSDL) Standard for the description of Web Services Define localization, access ways and detailed description Abstract functionalities, practical details WSDL Binding: implementation for SOAP, HTTP, MIME

13 P. Romano, Tutorial BITS200513 CABRI: Objectives Common Access to Biological Resources and Information Setting Quality Management Guidelines Distributing biological resources of the highest quality Integrating searches and access to catalogues Ad hoc search (CABRI Simple Search) Shopping cart (pre-ordering facility)

14 P. Romano, Tutorial BITS200514 CABRI: Partners and resources Partners: BCCM, CABI, CBS, CIP, DSMZ, ECACC, ICLC, NCCB, NCIMB (culture collections) IST, CERDIC (ICT) Resources: Microorganisms (bacteria, yeasts, fungi strains) Animal cells (animal and human cell lines, hybridomas, HLA typed B lines) Plasmids, phages, viruses, DNA probes Overall, more than 110.000 biological resources

15 P. Romano, Tutorial BITS200515 CABRI: SRS Reasons why o Manages heterogeneous databases o Flat file format o Simple and effective interface o Internal and external links o Link operator o Easily expandible (new databases) o Flexibility in creation of indexes

16 P. Romano, Tutorial BITS200516 CABRI: data structure For each material, three data sets identified: Minimum Data Set (MDS): essential data, needed to identify individual resources Recommended Data Set (RDS): all data that are useful to describe individual resources Full Data Set (FDS): all data available on the resources

17 P. Romano, Tutorial BITS200517 CABRI: data structure For each information, data input and authentication guidelines, including: Detailed textual description of the information In-house reference lists of terms and controlled vocabularies Predefined syntaxes (e.g., Literature, scientific names)

18 P. Romano, Tutorial BITS200518 CABRI: Name field FieldName DescriptionFull scientific and most recent name of the strain. It includes:  Genus name and species epithet  Subspecies  Pathovar  Authors of the name  Year of valid publication or validation  Approbation of the name Input processEnter full scientific name as given by depositor and confirmed (or changed) by collection. Names of authors of the name, year of valid publication or validation and approbation are included after a comma. Values for approbation: AL = approved list, c.f.r. IJSB 1980 VL = validation list, in IJSB after 1980 VP = validly published, paper in IJSB after 1980 Reference list: DSMZ list of bacterial names Required forMDS

19 P. Romano, Tutorial BITS200519 CABRI: Reference paper field FieldReference paper DescriptionOriginal paper [if available] Input processNew entries: JournalTitle Year; Volume(issue): beginning page#-ending page# The title is abbreviated following international standard rules (ISSN). Abbreviations are without dot. Authors and title of the article are not mentioned. The reference can be followed by the Pubmed ID enclosed within square brackets as follows: [PMID: 1234567], where '1234567' is the Pubmed ID of the paper Required forMDS

20 P. Romano, Tutorial BITS200520 CABRI: integration For each material: Common data structure and syntax Integrated searches/results through SRS For each catalogue: SRS and HTML links to reference dbs (media, synonyms, hazard, etc…) For many catalogues: Explicit links to Medline, EMBL, plamisd maps

21 P. Romano, Tutorial BITS200521 IARC TP53 database IARC TP53 Mutation Database Release 9: 19,809 somatic mutations, 1,769 papers, Information: mutation, source, patient’s life style. Vocabularies and standardized annotations On-line queries imply human interaction. SRS implementation of the TP53 Database SRS based service Definition of an ad hoc DTD XML based data interchange Improved automated accessibility

22 P. Romano, Tutorial BITS200522 CABRI and TP53 Web Services Implementing web services that allow: The retrieval of information from CABRI and TP53 databases by using remote calls to SRS The possibility of including such services in complex workflows Reproducing current behaviour: Search by name, identifier and free text (CABRI) Search by interesting properties (TP53) Combine results Integrate data with other sources by using IDs/common terms Two types of services: Search for a specific feature and return ID Search for an ID and return full record (or predefined sections)

23 P. Romano, Tutorial BITS200523 Soaplab: SOAP-based Analysis Web Service “Soaplab is a set of Web Services providing a programatic access to some applications on remote computers.It is often referred to as an Analysis (Web) Service” (Martin Senger, EBI). It allows for the implementation of Web Services offering access to: local command-line applications EMBOSS contents of ordinary web pages (GowLab) Requirements Apache Tomcat servlet engine and Axis SOAP toolkit, Java perl, mySQL

24 P. Romano, Tutorial BITS200524 Soaplab

25 P. Romano, Tutorial BITS200525 Soaplab appl: getCellLineIdsByName [ documentation: "Get cell lines by name from CABRI human and animal cell lines catalogues (see" groups: "CABRI" nonemboss: "Y" comment: "launcher get" supplier: "" comment: "method [{$libs}-nam:'$name'] -ascii“ ] string: libs [ parameter: "Y“ ] string: name [ parameter: "Y“ ] outfile: result [ ]

26 P. Romano, Tutorial BITS200526 Soaplab appl: getCellLineIdsByProperty [ documentation: "Get cell lines by properties (all text) from CABRI human and animal cell lines catalogues (see" groups: "CABRI" nonemboss: "Y" comment: "launcher get" supplier: "" comment: "method [{$libs}-all:'$text'] -ascii" ] string: libs [ parameter: "Y“ ] string: text [ parameter: "Y“ ] outfile: ids [ ]

27 P. Romano, Tutorial BITS200527 Soaplab appl: getCellLinesById [ documentation: "Get cell lines by Id from CABRI human and animal cell lines catalogues (see" groups: "CABRI" nonemboss: "Y" comment: "launcher get" supplier: "" comment: "method -e [{$libs}:'$id'] -ascii" ] string: libs [ parameter: "Y“ ] string: id [ parameter: "Y“ ] outfile: result [ ]

28 P. Romano, Tutorial BITS200528 Workflow management “A computerized facilitation or automation of a business process, in whole or part". (Workflow Management Coalition) Main goal is: the implementation of data analysis processes in standardized environments Main advantages relate to: effectiveness: being an automatic procedure, it frees bio- scientists from repetitive interactions with the web and it supports good practice, reproducibility: analysis can be replicated over time, reusability: intermediate results can be reused, traceability: the workflow is carried out in a transparent analysis environment where data provenance can be checked and/or controlled.

29 P. Romano, Tutorial BITS200529 Workflow management Workflow management softwares: Biopipe, an add-on to bioperl, GPipe, an extension of the Pise interface Taverna (EBI), a component of the myGrid platform, Wildfire (Bioinformatics Institute, Singapore) Pipeline Pilot (SciTegic).

30 P. Romano, Tutorial BITS200530 Workflow management Taverna Workbench constructs complex analysis workflows access both remote and local processors defines alternative processors runs workflows visualizes the results includes a bioinformatics data ontology Requirements: java, Windows or Linux

31 P. Romano, Tutorial BITS200531 Workflow management WSDL services Web Service Description Language (WSDL) file: adds WSDL based service nodes Soaplab servers Soaplab server: adds a list of soaplab provided services Biomoby registries Moby Central repository: determines hosts and their services Workflows XScufl definition file: adds the workflow as a node and processors as child node Biomart databases Biomart data warehouse: adds all available data sets Local processors Simple list/string processors, constant values, beanshell scripts

32 P. Romano, Tutorial BITS200532 Demo: workflows for CABRI dbs

33 P. Romano, Tutorial BITS200533 Demo: workflows for TP53 dbs

34 P. Romano, Tutorial BITS200534 Some acknoledgements….. This work has partially been supported by the Italian Ministry for Education, University and Research (MIUR), project “Oncology over Internet” (2002 – 2005) I wish to thank my colleagues: Domenico Marra (TP53 databases and Soaplab), Federico Malusa (CABRI databases), Francesca Piersigilli (CABRI databases)

35 P. Romano, Tutorial BITS200535 …and an announcement! Workflows management: new abilities for the biological information overflow October 5 - 7, 2005,University of Naples Naples, Italy Workshop NETTAB 2005 Take a brochure!

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