Knowledge Enabled Information and Services Science What can SW do for HCLS today? Panel at HCSL Workshop, WWW2007 Amit Sheth Kno.e.sis Center Wright State.

Slides:



Advertisements
Similar presentations
Knowledge Modeling and its Application in Life Sciences: A Tale of two ontologies Bioinformatics for Glycan Expression Integrated Technology Resource for.
Advertisements

Semantic empowerment of Health Care and Life Science Applications WWW 2006 W3C Track, May WWW 2006 W3C Track, May Amit Sheth LSDIS LabLSDIS.
Protein Quantitation II: Multiple Reaction Monitoring
RDB2RDF: Incorporating Domain Semantics in Structured Data Satya S. Sahoo Kno.e.sis CenterKno.e.sis Center, Computer Science and Engineering Department,
Web Services for N-Glycosylation Process Integrated Technology Resource for Biomedical Glycomics NCRR/NIH Satya S. Sahoo, Amit P. Sheth, William S. York,
Semantic Web & Semantic Web Services: Applications in Healthcare and Scientific Research International IFIP Conference on Applications of Semantic Web.
UC Mass Spectrometry Facility & Protein Characterization for Proteomics Core Proteomics Capabilities: Examples of Protein ID and Analysis of Modified Proteins.
Prof. Carolina Ruiz Computer Science Department Bioinformatics and Computational Biology Program WPI WELCOME TO BCB4003/CS4803 BCB503/CS583 BIOLOGICAL.
Knowledge Enabled Information and Services Science Semantic Web for Health Care and Biomedical Informatics Keynote at NSF Biomed Web Workshop, December.
Faculty of Computer Science © 2006 CMPUT 605February 11, 2008 A Data Warehouse Architecture for Clinical Data Warehousing Tony R. Sahama and Peter R. Croll.
Semantic Web: promising technologies and current applications in Health care & Life Sciences Amit Sheth Thanks: Kno.e.sis team, collaborators at CCRC,
Jennifer A. Dunne Santa Fe Institute Pacific Ecoinformatics & Computational Ecology Lab Rich William, Neo Martinez, et al. Challenges.
Sensemaking and Ground Truth Ontology Development Chinua Umoja William M. Pottenger Jason Perry Christopher Janneck.
A Flexible Workbench for Document Analysis and Text Mining NLDB’2004, Salford, June Gulla, Brasethvik and Kaada A Flexible Workbench for Document.
Semantic Web Technology in Support of Bioinformatics for Glycan Expression Amit Sheth Large Scale Distributed Information Systems (LSDIS) lab, Univ. of.
Semantics powered Bioinformatics Amit Sheth, William S. York, et al Large Scale Distributed Information Systems Lab & Complex Carbohydrate Research Center.
Proteomics: A Challenge for Technology and Information Science CBCB Seminar, November 21, 2005 Tim Griffin Dept. Biochemistry, Molecular Biology and Biophysics.
ReQuest (Validating Semantic Searches) Norman Piedade de Noronha 16 th July, 2004.
Personal Data Management Why is this such an issue? Data Provenance Representing links v Representing data Identifying resources: Life Science Identifiers.
Proteomics Informatics – Protein identification II: search engines and protein sequence databases (Week 5)
Mass Spectrometry. What are mass spectrometers? They are analytical tools used to measure the molecular weight of a sample. Accuracy – 0.01 % of the total.
FIGURE 5. Plot of peptide charge state ratios. Quality Control Concept Figure 6 shows a concept for the implementation of quality control as system suitability.
Scaffold Download free viewer:
Proteomics Informatics (BMSC-GA 4437) Course Director David Fenyö Contact information
Proteomics Informatics (BMSC-GA 4437) Course Director David Fenyö Contact information
Evaluated Reference MS/MS Spectra Libraries Current and Future NIST Programs.
Isolation of N-linked glycopeptides from plasma Yong Zhou 1, Ruedi Aebersold 2, and Hui Zhang 1,3 * 1 Institute for Systems Biology, Seattle, Washington.
Predicting Missing Provenance Using Semantic Associations in Reservoir Engineering Jing Zhao University of Southern California Sep 19 th,
Ontologies: Making Computers Smarter to Deal with Data Kei Cheung, PhD Yale Center for Medical Informatics CBB752, February 9, 2015, Yale University.
Copyright © 2010 Accenture All Rights Reserved. Accenture, its logo, and High Performance Delivered are trademarks of Accenture. Multiple Ontologies in.
Semantic Web applications in Financial Industry, Government, Health care and Life Sciences SWEG 2006, March 2006 Amit Sheth LSDIS Lab, Department of Computer.
Knowledge Enabled Information and Services Science GlycO.
Kno.e.sis Center, Wright State University,
Semantics Enabled Industrial and Scientific Applications: Research, Technology and Deployed Applications Part III: Biological Applications Keynote - the.
The dynamic nature of the proteome
Towards the Management of Information Quality in Proteomics David Stead University of Aberdeen.
Semantics in the Semantic Web– the implicit, the formal and the powerful (with a few examples from Glycomics) Amit Sheth Large Scale Distributed Information.
IPAW'08 – Salt Lake City, Utah, June 2008 Exploiting provenance to make sense of automated decisions in scientific workflows Paolo Missier, Suzanne Embury,
Common parameters At the beginning one need to set up the parameters.
Analysis of Complex Proteomic Datasets Using Scaffold Free Scaffold Viewer can be downloaded at:
Phase II Additions to LSG Search capability to Gene Browser –Though GUI in Gene Browser BLAST plugin that invokes remote EBI BLAST service Working set.
Laxman Yetukuri T : Modeling of Proteomics Data
Semantic empowerment of Life Science Applications October 2006 Amit Sheth LSDIS Lab, Department of Computer Science, University of Georgia Acknowledgement:
Knowledge Enabled Information and Services Science SAWSDL: Tools and Applications Amit P. Sheth Kno.e.sis Center Wright State University, Dayton, OH Knoesis.wright.edu.
Knowledge Enabled Information and Services Science Glycomics project overview.
XML Standards for Proteomics Data Andrew Jones, Dr Jonathan Wastling and Dr Ela Hunt Department of Computing Science and the Institute of Biomedical and.
FuGE: A framework for developing standards for functional genomics Andrew Jones School of Computer Science, University of Manchester Metabomeeting 2.0.
Applying Semantic Technologies to the Glycoproteomics Domain W. S York May 15, 2006.
Knowledge Enabled Information and Services Science Relationship Web: Realizing the Memex vision with the help of Semantic Web SemGrail Workshop, Redmond,
Bioinformatics Research Overview Outline Biomedical Ontologies oGlycO oEnzyO oProPreO Scientific Workflow for analysis of Proteomics Data Framework for.
Overview of Mass Spectrometry
EBI is an Outstation of the European Molecular Biology Laboratory. In silico analysis of accurate proteomics, complemented by selective isolation of peptides.
Proposed Research Problem Solving Environment for T. cruzi Intuitive querying of multiple sets of heterogeneous databases Formulate scientific workflows.
Data Management Support for Life Sciences or What can we do for the Life Sciences? Mourad Ouzzani
Interface for Glyco Vault Functionality and requirements. Initial proposal. Maciej Janik.
Proteomics Informatics (BMSC-GA 4437) Instructor David Fenyö Contact information
Salamanca, March 16th 2010 Participants: Laboratori de Proteomica-HUVH Servicio de Proteómica-CNB-CSIC Participants: Laboratori de Proteomica-HUVH Servicio.
Semantic Data Extraction for B2B Integration Syntactic-to-Semantic Middleware Bruno Silva 1, Jorge Cardoso 2 1 2
Japan Consortium for Glycobiology and Glycotechnology DataBase 日本糖鎖科学統合データベース PACDB - Pathogen Adherence to Carbohydrate Database The Pathogen Adherence.
IIC Information Flow Interesting ions? Priority list of interesting ions Empty priority list? QA/QC? Peptide identification Protein identification External.
High throughput biology data management and data intensive computing drivers George Michaels.
Proteomics Informatics (BMSC-GA 4437) Course Directors David Fenyö Kelly Ruggles Beatrix Ueberheide Contact information
Constructing high resolution consensus spectra for a peptide library
LSDIS Lab, Department of Computer Science,
Amit Sheth LSDIS Lab & Semagix University of Georgia
Accelerating Research in Life Sciences
Collaborative RO1 with NCBO
High level view of the MAE algorithm.
Accelerating Research in Life Sciences
Tryptic glycopeptides of IGFBP-5 from T47D cells separated by HPLC detected by ESI-MS and sequenced by tandem MS.a, ESI-MS spectrum of combined fractions.
Presentation transcript:

Knowledge Enabled Information and Services Science What can SW do for HCLS today? Panel at HCSL Workshop, WWW2007 Amit Sheth Kno.e.sis Center Wright State University Key contributors: Satya Sahoo, Christopher Thomas, William S. York

Knowledge Enabled Information and Services Science Active Semantic Medical Records Active Semantic Medical Records (operational since January 2006) Goals: Increase efficiency Reduce Errors, Improve Patient Satisfaction & Reporting Improve Profitability (better billing) Technologies: Ontologies, semantic annotations & rules Service Oriented Architecture Thanks -- Dr. Agrawal, Dr. Wingeth, and others. ISWC2006 paperISWC2006 paper Semantic Applications: Health Care

Knowledge Enabled Information and Services Science GlycO is a focused ontology for the description of glycomics models the biosynthesis, metabolism, and biological relevance of complex glycans models complex carbohydrates as sets of simpler structures that are connected with rich relationships An ontology for structure and function of Glycopeptides Published through the National Center for Biomedical Ontology (NCBO) More at:

Knowledge Enabled Information and Services Science An ontology for capturing process and lifecycle information related to proteomic experiments Two aspects of glycoproteomics: What is it? → identification How much of it is there? → quantification Heterogeneity in data generation process, instrumental parameters, formats Need data and process provenance → ontology-mediated provenance Hence, ProPreO models both the glycoproteomics experimental process and attendant data Published through the National Center for Biomedical Ontology (NCBO) and Open Biomedical Ontologies (OBO) More info. On Knowledge Representation in Life Sciences at Kno.e.sisOn Knowledge Representation in Life Sciences at Kno.e.sis ProPreO ontology

Knowledge Enabled Information and Services Science

Semantic annotation of scientific/experimental data

Knowledge Enabled Information and Services Science Scientific Data Computational Methods Ontology instances ProPreO population: transformation to rdf

Knowledge Enabled Information and Services Science parent ion m/z fragment ion m/z ms/ms peaklist data fragment ion abundance parent ion abundance parent ion charge ProPreO: Ontology-mediated provenance Mass Spectrometry (MS) Data

Knowledge Enabled Information and Services Science N-Glycosylation Process (NGP) Cell Culture Glycoprotein Fraction Glycopeptides Fraction extract Separation technique I Glycopeptides Fraction n*m n Signal integration Data correlation Peptide Fraction ms datams/ms data ms peaklist ms/ms peaklist Peptide listN-dimensional array Glycopeptide identification and quantification proteolysis Separation technique II PNGase Mass spectrometry Data reduction Peptide identification binning n 1

Knowledge Enabled Information and Services Science Workflow based on Web Services = Web Process

Knowledge Enabled Information and Services Science Semantic Web Process to incorporate provenance Storage Standard Format Data Raw Data Filtered Data Search Results Final Output Agent Biological Sample Analysis by MS/MS Raw Data to Standard Format Data Pre- process DB Search (Mascot/ Sequest) Results Post- process (ProValt) OIOIOIOIO Biological Information Semantic Annotation Applications ISiS – Integrated Semantic Information and Knowledge System

Knowledge Enabled Information and Services Science Evaluate the specific effects of changing a biological parameter: Retrieve abundance data for a given protein expressed by three different cell types of a specific organism. Retrieve raw data supporting a structural assignment: Find all the raw ms data files that contain the spectrum of a given peptide sequence having a specific modification and charge state. Detect errors: Find and compare all peptide lists identified in Mascot output files obtained using a similar organism, cell-type, sample preparation protocol, and mass spectrometry conditions. ProPreO concepts highlighted in red A Web Service Must Be Invoked Semantic Annotation Facilitates Complex Queries

Knowledge Enabled Information and Services Science Semantic Browser: contextual browsing of PubMed Semantic Browser Semantic Applications: Life Science More at Knoesis research in life sciencesKnoesis research in life sciences