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ECCR IU Mar15 07

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Published on November 21, 2007

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Overview of Chemical Informatics and Cyberinfrastructure Collaboratory:  Overview of Chemical Informatics and Cyberinfrastructure Collaboratory March 15 2007 Geoffrey Fox Computer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington IN 47401 gcf@indiana.edu http://www.infomall.org http://www.chembiogrid.org Indiana University Summary:  Indiana University Summary Indiana University is focusing on two major areas: Creating a comprehensive, easily accessible infrastructure for chemoinformatics tools and data sources, linked with PubChem and made available as web services, and partnering with screening centers and other users to demonstrate how this infrastructure can be usefully applied Infrastructure can include any tools, not just ours (commercial/open source, chemoinformatics, bioinformatics, and so on) New, custom applications can be built quickly using existing services in a similar way to Google Maps and other “web 2.0” resources Being a central hub of chemoinformatics education, including offering distance courses on chemoinformatics theory and techniques, practical workshops on using chemoinformatics resources, and freely available web-based educational resources We currently offer a Ph.D, M.S. and graduate certificate (distance) in chemical informatics Distance education program allows you to “pick and choose” courses to meet educational needs: certificate is awarded on completion of four courses CICC Senior Personnel:  CICC Senior Personnel Geoffrey C. Fox Mu-Hyun (Mookie) Baik Dennis B. Gannon Kevin E. Gilbert Rajarshi Guha Marlon Pierce Beth A. Plale Gary D. Wiggins David J. Wild Yuqing (Melanie) Wu Peter T. Cherbas Mehmet M. Dalkilic Charles H. Davis A. Keith Dunker Kelsey M. Forsythe John C. Huffman Malika Mahoui Daniel J. Mindiola Santiago D. Schnell William Scott Craig A. Stewart David R. Williams From Biology, Chemistry, Computer Science, Informatics at IU Bloomington and IUPUI (Indianapolis) Slide4:  CICC Combines Grid Computing with Chemical Informatics CICC CICC Chemical Informatics and Cyberinfrastucture Collaboratory Funded by the National Institutes of Health www.chembiogrid.org Indiana University Department of Chemistry, School of Informatics, and Pervasive Technology Laboratories Science and Cyberinfrastructure . Large Scale Computing Challenges Chemical Informatics is non-traditional area of high performance computing, but many new, challenging problems may be investigated. CICC is an NIH funded project to support chemical informatics needs of High Throughput Cancer Screening Centers. The NIH is creating a data deluge of publicly available data on potential new drugs. CICC supports the NIH mission by combining state of the art chemical informatics techniques with World class high performance computing National-scale computing resources (TeraGrid) Internet-standard web services International activities for service orchestration Open distributed computing infrastructure for scientists world wide NIH PubMed DataBase OSCAR Text Analysis POVRay Parallel Rendering Initial 3D Structure Calculation Toxicity Filtering Cluster Grouping Docking Molecular Mechanics Calculations Quantum Mechanics Calculations IU’s Varuna DataBase NIH PubChem DataBase Chemical informatics text analysis programs can process 100,000’s of abstracts of online journal articles to extract chemical signatures of potential drugs. OSCAR-mined molecular signatures can be clustered, filtered for toxicity, and docked onto larger proteins. These are classic “pleasingly parallel” tasks. Top-ranking docked molecules can be further examined for drug potential. Big Red (and the TeraGrid) will also enable us to perform time consuming, multi-stepped Quantum Chemistry calculations on all of PubMed. Results go back to public databases that are freely accessible by the scientific community. CICC Web Service Infrastructure:  CICC Web Service Infrastructure Slide6:  Web Service Locations Indiana University Clustering VOTables OSCAR3 Toxicity classification Database services Cambridge University InChi generation / search CMLRSS OpenBabel Web Service Locations Indiana University Clustering VOTables Toxicity classification Database services Statistics services Cambridge University InChi generation / search CMLRSS OpenBabel University of Cologne NMRShiftDB NCI CSLS VCC Laboratory ALogPS Slide7:  Where Does The Functionality Come From? Indiana University VOTables NCI DTP predictions Database services Cambridge University InChi generation / search OSCAR OpenEye Docking DigitalChemistry BCI fingerprints DivKMeans CDK Cheminformatics University of Michigan PkCell R Foundation R package NIH PubChem PubMed gNova Consulting European Chemicals Bureau ToxTree toxicity predictions CICC Infrastructure Vision:  CICC Infrastructure Vision Drug Discovery and other academic chemistry and pharmacology research will be aided by powerful modern information technology ChemBioGrid set up as distributed cyberinfrastructure in eScience model ChemBioGrid will provide portals (user interfaces) to distributed databases, results of high throughput screening instruments, results of computational chemical simulations and other analyses ChemBioGrid will provide services to manipulate this data and combine in workflows; it will have convenient ways to submit and manage multiple jobs ChemBioGrid will include access to PubChem, PubMed, PubMed Central, the Internet and its derivatives like Microsoft Academic Live and Google Scholar The services include open-source software like CDK, commercial code from vendors from BCI, OpenEye, Gaussian and Google, and any user contributed programs ChemBioGrid will define open interfaces to use for a particular type of service allowing plug and play choice between different implementations Cheminformatics Education at IU:  Cheminformatics Education at IU Linked to bioinformatics in Indiana University’s School of Informatics School of Informatics degree programs BS, MS, PhD Programs offered at both the Indianapolis (IUPUI) and Bloomington (IUB) campuses Bioinformatics MS and track on PhD Chemical Informatics MS and track on PhD Informatics Undergraduates can choose a chemistry cognate (change to Life Sciences ) PhD in Informatics started in August 2005 and offers tracks in bioinformatics; chemical informatics; health informatics; human-computer interaction design; social and organizational informatics; more to come! Good employer interest but modest student understanding of value of Cheminformatics degree 3 core courses in Cheminformatics plus seminar/independent studies Significant interest in distance education version of introductory Cheminformatics course (enrollment promising in Distance Graduate Certificate in Chemical Informatics) Example: Spreading chemoinformatics education with CIC courseshare:  Example: Spreading chemoinformatics education with CIC courseshare We have partnered with the University of Michigan to offer our introductory chemoinformatics (I571) course concurrently at Indiana University and the University of Michigan as a CIC courseshare, so UM pharmacy, chemistry and engineering students can be trained in chemoinformatics techniques for course credit at UM In addition, individual students in academia, government, and small and large life science companies have taken the class remotely from all over the country for credit towards the graduate certificate Uses mixture of web conferencing (Breeze), videoconferencing, and online resources for maximum flexibility Minimally all that is required is a telephone and internet-connected PC Students can replay any of the classes using just a regular PC Most recent course wiki is available at http://cheminfo.informatics.indiana.edu/djwild/I571_2006_wiki Giving a class remotely to UM students with video and web conferencing MLSCN Post-HTS Biology Decision Support:  MLSCN Post-HTS Biology Decision Support Percent Inhibition or IC50 data is retrieved from HTS Question: Was this screen successful? Question: What should the active/inactive cutoffs be? Question: What can we learn about the target protein or cell line from this screen? Compounds submitted to PubChem Workflows encoding distribution analysis of screening results Grids can link data analysis ( e.g image processing developed in existing Grids), traditional Chem-informatics tools, as well as annotation tools (Semantic Web, del.icio.us) and enhance lead ID and SAR analysis A Grid of Grids linking collections of services at PubChem ECCR centers MLSCN centers Workflows encoding plate & control well statistics, distribution analysis, etc Workflows encoding statistical comparison of results to similar screens, docking of compounds into proteins to correlate binding, with activity, literature search of active compounds, etc CHEMINFORMATICS PROCESS GRIDS Example HTS workflow: finding cell-protein relationships:  Example HTS workflow: finding cell-protein relationships A protein implicated in tumor growth with known ligand is selected (in this case HSP90 taken from the PDB 1Y4 complex) Similar structures to the ligand can be browsed using client portlets. Once docking is complete, the user visualizes the high-scoring docked structures in a portlet using the JMOL applet. Similar structures are filtered for drugability, are converted to 3D, and are automatically passed to the OpenEye FRED docking program for docking into the target protein. The screening data from a cellular HTS assay is similarity searched for compounds with similar 2D structures to the ligand. Docking results and activity patterns fed into R services for building of activity models and correlations Least Squares Regression Random Forests Neural Nets Example: PubDock :  Example: PubDock Database of approximately 1 million PubChem structures (the most drug-like) docked into proteins taken from the PDB Available as a web service, so structures can be accessed in your own programs, or using workflow tools like Pipeline Polit Several interfaces developed, including one based on Chimera (below) which integrates the database with the PDB to allow browsing of compounds in different targets, or different compounds in the same target Can be used as a tool to help understand molecular basis of activity in cellular or image based assays Example: R Statistics applied to PubChem data:  Example: R Statistics applied to PubChem data By exposing the R statistical package, and the Chemistry Development Kit (CDK) toolkit as web services and integrating them with PubChem, we can quickly and easily perform statistical analysis and virtual screening of PubChem assay data Predictive models for particular screens are exposed as web services, and can be used either as simple web tools or integrated into other applications Example below uses DTP Tumor Cell Line screens - a predictive model using Random Forests in R makes predictions of probability of activity across multiple cell lines (available at http://rguha.ath.cx/~rguha/ncidtp/dtp) Varuna environment for molecular modeling (Baik, IU):  Varuna environment for molecular modeling (Baik, IU) QM Database Researcher Simulation Service FORTRAN Code, Scripts Chemical Concepts Experiments QM/MM Database PubChem, PDB, NCI, etc. ChemBioGrid Reaction DB DB Service Queries, Clustering, Curation, etc. Papers etc. Condor TeraGrid Supercomputers “Flocks” Methods Development at the CICC:  Methods Development at the CICC Tagging methods for web-based annotation exploiting del.icio.us and Connotea Development of QSAR model interpretability and applicability methods RNN-Profiles for exploration of chemical spaces VisualiSAR - SAR through visual analysis See http://www.daylight.com/meetings/mug99/Wild/Mug99.html Visual Similarity Matrices for High Volume Datasets See http://www.osl.iu.edu/~chemuell/new/bioinformatics.php Fast, accurate clustering using parallel Divisive K-means Mapping of Natural Language queries to use cases and workflows Advanced data mining models for drug discovery information Physics-based Scoring Algorithms What Do You Get in a Web Service?:  What Do You Get in a Web Service? WSDL for all services available Collected on a web page Available in a UDDI repository Javadocs or plain text descriptions Source code and associated unit tests Various client examples Web pages (via PHP) Python Chimera Web Service Vision:  Web Service Vision Web services provide a neutral approach to exposing functionality You can utilize them in Workflow tools – Pipeline Pilot, Taverna, XBaya Desktop clients – Chimera, custom Web pages They can be located anywhere On your desktop Intranet Internet Web Service Vision:  Web Service Vision Literally anything can be made into a web service Libraries Standalone programs Commerical code Open-source code RSS Feeds:  RSS Feeds Provide access to DB's via RSS feeds Feeds include 2D/3D structures in CML Viewable in Bioclipse, Jmol as well as Sage etc. Two feeds currently available SynSearch – get structures based on full or partial chemical names DockSearch – get best N structures for a target R, CDK & PubChem:  R, CDK & PubChem Goals Access cheminformatics from within R Access PubChem data from within R rcdk package allows to do cheminformatics within R using CDK functionality rpubchem provides access to PubChem compound data and bioassay data Searchable via assay ID, keywords J. Stat. Soft, 2007, 18(6) Databases:  Databases Most of our databases aim to add value to PubChem or link into PubChem We maintain a local mirror for testing, data mining 3D structures (MMFF94) Searchable by CID, SMARTS, 3D similarity Docked ligands (FRED) 906K drug-like compounds into 7 ligands Will eventually cover ~2000 targets (Cheminformatics) Algorithm Development:  (Cheminformatics) Algorithm Development Goals Focus on interpretability and applicability Devise novel approaches to clustering problems Investigate the utility of low dimensional representations for a variety of problems Examples Ensemble feature selection (JCIM, in press) Cluster counting with R-NN curves (in revision) Chemical Data Mining:  Chemical Data Mining Working on screening data with Scripps, FL Random forests (modeling & feature selection) Naïve Bayes (modeling) Identifying features indicative of toxicity Domain applicability NCI DTP Cell line activity predictions Random forest models for 60 cell lines All available as downloadable R models web services (supply SMILES, get prediction) with web page clients

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