1 / 10

Outline

The PL-Grid Virtual Laboratory in the Life Sciences Domain Maciej Malawski, Eryk Ciepiela , Tomasz Gubała, Piotr Nowakowski, Daniel Harężlak, Marek Kasztelnik, Joanna Kocot, Tomasz Bartyński, Marian Bubak Institute of Computer Science AGH ACC Cyfronet AGH. …. Outline.

shyla
Download Presentation

Outline

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The PL-Grid Virtual Laboratory in the Life Sciences DomainMaciej Malawski, Eryk Ciepiela, Tomasz Gubała, Piotr Nowakowski, Daniel Harężlak, Marek Kasztelnik, Joanna Kocot, Tomasz Bartyński, Marian BubakInstitute of Computer Science AGHACC Cyfronet AGH …

  2. Outline Motivation – complex scientific applications on modern computing infrastructures In-silico experiments and Virtual Laboratory GridSpace2 as a solution Architecture Working with GridSpace Examples of applications Computational chemistry Bioinformatics Conclusions

  3. Motivation Complex scientific applications on modern computing infrastructures Clusters, Grids, Clouds Diverse software packages Applications (Gaussian, NAMD,…) Web Services Scripts: Perl, Python, Ruby Different users Chemists, biologists Programmers End users Various data types Files, databases, URLs Exploratory programming Unstructured, dynamic, prototyping Collaboration Teams, communities

  4. Experiment Experiment (in-silico)- a process that combines together data with a set ofactivities (programs, services) that act on that data in order to produce experiment results Experiment plan – a specific type of software Experiment run – a specific execution of the experiment Complex workflow going beyond manual simple and repeatable execution of installed programs Combines steps realized on a range of software environments, platforms, tools, languages etc. Developed, shared and reused collaboratively amongst ad-hoc researching teams Composed of collaboratively owned libraries and services used (called gems) and experiment parts (called snippets) Virtual Laboratory – environment for development, execution and sharing of experiments

  5. Working with GridSpace2 Easy access using Web browser Experiment Workbench Constructing experiment plans from code snippets Interactively run experiments Experiment Execution Environment Multiple interpreters Access to libraries, programs and services (gems) Access to computing infrastructure Cluster, grid, cloud

  6. Experiment Workbench

  7. Binding sites in proteins Comparison of Services for Predicting Ligand Binding Sites Multiple services available on the Web Conversions between data formats Visualization scripts (Jmol, Gnuplot) Single access based on experiments developed in Virtual Laboratory Calculation of hydrophobicity profiles Multiple scales, parameters, input data Computed using PL-Grid resources – easy access to Zeus cluster at Cyfronet Management of experiment results: ~ 1 Million output files Using semantic integration framework for metadata management Collaboration with Departament of Bioinformatics and Telemedicine, Jagiellonian University, Prof. Irena Roterman-Konieczna, Katarzyna Prymula

  8. Analysis of water solutions of aminoacids Involving multiple steps realized with many tools, langauges and libraries used for Packmol – molecular dynamics simulations of packing molecules in a defined regions of space Jmol – visualization of solution Gaussian – computing a spectrum of thesolution Python/CCLIB – extracting spectrum info jqPlot – displaying plot Collaboration with computational chemists of ACC Cyfronet AGH and Departament of Chemistry, Jagiellonian University, Dr. Mariusz Sterzel, Klemens Noga

  9. Conclusions Complex scientific applications need dedicated tools and approaches. In-silico experiments are supported by Virtual Laboratory powered by GridSpace2 technology. Applications: Bioinformatics Computational chemistry More are welcome! Virtual laboratory is open for PL-Grid users.

  10. References http://wl.plgrid.pl – open the Virtual Labortory in your browser http://gs2.cyfronet.pl – learn more about GridSpaace2 technology http://virolab.cyfronet.pl – see our earlier achievements http://www.plgrid.pl – become a user of PL-Grid

More Related