BieColl - Bielefeld Electronic Collections

Vompras, Johanna

Data Seal of Approval

Veselkov, Kirill A.

  Proceedings of CELLmicrocosmos neXt 2014 (DOI: 10.2390/biecoll-next2014-4)  11
Top-down systems biology approaches for
“omics”-based tissue and biofluid analytics
Kirill A. Veselkov*
Faculty of Medicine, Department of Surgery & Cancer,
Imperial College London, London SW7 2AZ, United Kingdom
Top-down systems biology identifies molecular interaction networks in health and disease
using  system-wide  data  generated  by  high-throughput  –omics  technologies.  The  rapid
advances in  the post-genomic analytical  technologies,  most  notably  Mass  Spectrometry
(MS), has made possible to simultaneously analyze hundreds to thousands of metabolites in
biological fluids and intact tissues at a relatively low cost. The ability to generate, model,
and interpret such metabolic data in relation to benchmark patient clinical information,
enabled by powerful  bioinformatics  platforms,  makes  personalized medicine a  tangible
proposition.  The  advancements  in  the  field  of  metabolic  phenotyping  have  focused
primarily on instrument development and validation of the MS technologies. 
However, despite the significant advances in these areas, the major barrier to its wider
adoption and transition into main stream medicine and industry has been the challenge of
interpreting  and  managing  the  huge  data  sets  MS  generates.  The  interpretation  of
metabolic  data  is  dependent  on  the  advances  made  by  reconstruction  of  molecular
networks via cellular bottom-up systems biology models. 
This presentation outlines innovative bioinformatics solutions for emerging technologies of
mass  spectrometry  imaging  (MSI)  and  rapid  evaporative  ionization  mass  spectrometry
(REIMS),  targeting  unmet  medical  needs  of  cancer  network-driven  diagnosis  and  rapid
pathogen identification in sepsis. The translational bioinformatics platforms are presented
that allow intuitive clinically-oriented interrogation of MS datasets in an integrated and
streamlined  fashion.  These  developments  aim  to  overcome  current  methodological
roadblocks for effective clinical translation of MS technologies since the existing workflows
for data processing rely on a heterogeneous array of bioinformatic packages which are
poorly optimized and only suitable for specialists in the field [1], [2].
References
 
[1] N. Abbassi-Ghadi, K. Veselkov, S. Kumar, J. Huang, E. Jones, N. Strittmatter, H. Kudo,
R. Goldin, Z. Takáts, and G. B. Hanna. Discrimination of lymph node metastases using
desorption  electrospray  ionisation-mass  spectrometry  imaging.  Chemical
Communications, 50(28):3661–3664, 2014.
[2] K. A. Veselkov, R. Mirnezami, N. Strittmatter, R. D. Goldin, J. Kinross, A. V. Speller, T.
Abramov, E. A. Jones, A. Darzi, and E. Holmes. Chemo-informatic strategy for imaging
mass  spectrometry-based  hyperspectral  profiling  of  lipid  signatures  in  colorectal
cancer. Proceedings of the National Academy of Sciences, 111(3):1216–1221, 2014.
*kirill.veselkov04@imperial.ac.uk


German

Top-down systems biology approaches for 'omics'-based tissue and biofluid analytics

Biere, Niklas

Doebbe, Anja

Rothe, Nils

Huser, Thomas

Kruse, Olaf

Sommer, Björn

  Proceedings of CELLmicrocosmos neXt 2014 (DOI: 10.2390/biecoll-next2014-2)  7
Towards a 3D Cell Model of Chlamydomonas reinhardtii
Niklas Biere1, Anja Doebbe2, Nils Rothe1,
Thomas Huser3, Olaf Kruse2, Björn Sommer1,*
1Bio-/Medical Informatics Department, Bielefeld University/Center for Biotechnology
2Algae Biotechnology & Bioenergy, Bielefeld University/Center for Biotechnology
3Biomolecular Photonics Group, Bielefeld University
Universitätsstr. 25, 33615 Bielefeld, Germany
1 Introduction
Chlamydomonas reinhardtii is a green alga which is often used in Biotechnology as a model
organism. This  single-cell  organism has a size of approx. 10 µm, contains a very large
chloroplast relevant for the energy production which is partly used to move by using two
flagella. An important biotechnological application is the production of biofuels.
2 Cell Modeling
A visualization approach of the interpretative abstraction level is used to create the C.
reinhardtii model [1]. By combining the information of different publications, microscopic
images and videos at multiple scales, this project aims to present a more precise three-
dimensional structure of this cell type. The cell model is generated by using Blender [2]. In
addition, 3D microscopy data was used as  a base to model the  Endoplasmic reticulum
which was previously segmented with FIJI [3].
To  visualize  the  energy-relevant  pathways  of  C.  reinhardtii,  a  simplified  network  was
modeled  and  localized  using  the  CELLmicrocosmos  4.2  PathwayIntegration  [4].  This
pathway was afterwards used in Blender to illustrate the intracellular processes.
Figure 1: An anaglyph stereoscopic rendering (red/cyan) of Chlamydomonas reinhardtii
*bjoern@CELLmicrocosmos.org
  Proceedings of CELLmicrocosmos neXt 2014 (DOI: 10.2390/biecoll-next2014-2)  8
3 Animation and Visualization
The colors of the different cell components are basically derived from the natural colors
which are visible using a light microscope. For example, the color of the Chloroplast is
green, caused by the Chlorophyl. There is also a number of publications and videos which
are presenting the movement of the flagella. These sources have been taken into account
during the modeling process [5].
4 Outlook
A first version of this video was presented at the conference “Prospects and challenges for
the  development  of  algal  biotechnology”  and  the  CELLmicrocosmos  neXt  workshop  in
September 2014. Future approaches may be the integration of the molecular level, e.g.,
by modeling the photo system complexes, by using the MembraneEditor [6].
Acknowledgments
This project is sponsored in part by the program “Bioinformatics of Signaling Networks” at
the Center for Biotechnology of Bielefeld University, and by the Ministry of Innovation,
Science,  Research  and  Technology  of  North  Rhine-Westphalia  (MIWFT)  as  part  of  the
research cooperation “MoRitS - Model-based Realization of intelligent Systems in Nano- and
Biotechnologies” (grant no. 321 - 8.03.04.03 2012/02).
References
[1] B. Sommer. CELLmicrocosmos –  Integrative cell modeling at the molecular, mesoscopic
and functional level. Doctorate Thesis, Bielefeld University, Bielefeld, Germany, 2012.
[2] blender.org -  Home of the Blender project  -  Free and Open 3D Creation Software.
[Online]. Available: http://www.blender.org/. [Accessed: 22-Jul-2014].
[3] J.  Schindelin,  I.  Arganda-Carreras,  E.  Frise,  V.  Kaynig,  M.  Longair,  T.  Pietzsch,  S.
Preibisch, C. Rueden, S. Saalfeld, and B. Schmid. Fiji: an open-source platform for
biological-image analysis. Nature Methods, 9(7):676–682, 2012.
[4] B.  Sommer,  J.  Künsemöller,  N.  Sand,  A.  Husemann, M.  Rumming,  and B.  Kormeier.
CELLmicrocosmos  4.1:  an  interactive  approach  to  integrating  spatially  localized
metabolic networks into a virtual 3D cell environment. in  BIOSTEC  BIOINFORMATICS
2010, 2010:90–95.
[5] V. F. Geyer, F. Jülicher, J. Howard, and B. M. Friedrich. Cell-body rocking is a dominant
mechanism  for  flagellar  synchronization  in  a  swimming  alga.  Proceedings  of  the
National Academy of Sciences, 110(45):18058–18063, 2013.
[6] B. Sommer, T. Dingersen, C. Gamroth, S. E. Schneider, S. Rubert, J. Krüger, and K. J.
Dietz.  CELLmicrocosmos  2.2  MembraneEditor:  a  modular  interactive  shape-based
software approach  to  solve heterogeneous  Membrane Packing  Problems.  Journal  of
Chemical Information and Modeling, 5(51):1165–1182, 2011.


Towards a 3D Cell Model of Chlamydomonas reinhardtii

Hochstenbach, Patrick

Processing Linked Data with Catmandu

Wiljes, Cord

AG Semantic Computing
Cord Wiljes
Universität Bielefeld
Kolloquium Wissensinfrastruktur
23. Mai 2014
Wikidata
Die freie, universelle Datenbank zur
Unterstützung der Wikipedia
Cord Wiljes
AG Semantic Computing
Cord Wiljes
Wikipedia
▶ gegründet am 15. Januar 2001 von
Jimmy Wales Larry Sanger
AG Semantic Computing
Cord Wiljes
Wikipedia
▶ 30 Millionen Artikel
▶ englisch: 4,519,457
▶ deutsch: 1.720.439
▶ betrieben von der Wikimedia Foundation
▶ 100,000 aktive Autoren
▶ Ausgaben in 287 Sprachen
▶ 500 Mio Besucher / Monat
AG Semantic Computing
Cord Wiljes
Wikipedia: Grundsätze
▶ Wikipedia ist eine Enzyklopädie.
▶ Beiträge sind so zu verfassen, dass sie dem Grundsatz des
neutralen Standpunkts entsprechen.
▶ Geltendes Recht – insbesondere das Urheberrecht – ist strikt zu
beachten.
▶ Andere Benutzer sind zu respektieren und die Wikiquette
einzuhalten.
AG Semantic Computing
Cord Wiljes
Spin-Offs
▶ Wikimedia Commons: Medien
▶ Wikiquote: Zitate
▶ Wikibooks: Lehrbücher
▶ Wikiversity: Lernplattform
▶ Wikisource: Quellen
▶ Wiktionary: Wörterbuch
▶ Wikinews: Nachrichten
AG Semantic Computing
Cord Wiljes
Demo: Wikipedia
http://www.wikpedia.org
AG Semantic Computing
Cord Wiljes
Mehrsprachigkeit in der Wikipedia
German http://de.wikipedia.org/wiki/Universität_Bielefeld
English http://en.wikipedia.org/wiki/Bielefeld_University
French http://fr.wikipedia.org/wiki/Université_de_Bielefeld
Italian http://it.wikipedia.org/wiki/Università_di_Bielefeld
Chinese http://zh.wikipedia.org/wiki/比勒费尔德大学
...
AG Semantic Computing
Cord Wiljes
Language Links
display edit
AG Semantic Computing
Cord Wiljes
Infoboxes
German English Chinese
AG Semantic Computing
Cord Wiljes
Wikidata: Mission Statement
"Wikidata is a project to create a free knowledge base about the world
that can be read and edited by humans and machines alike. It will
provide data in all of the languages of the Wikimedia projects, and will
enable central access to the data in a way similar to what Wikimedia
Commons allows for multimedia files."
AG Semantic Computing
Cord Wiljes
Wikidata
▶ Start im April 2012
▶ betrieben von der Wikimedia Deutschland e.V.
▶ Zentrale in Berlin
▶ finanziert Allen Institute for Artificial Intelligence, der Gordon and
Betty Moore Foundation, Google, Inc.
▶ CC-0 Lizenz
AG Semantic Computing
Cord Wiljes
Wikidata Team
AG Semantic Computing
Cord Wiljes
Ziele
▶ Step 1: Sprachverlinkungen zentralisieren
▶ Step 2: zentrale Datenobjekte
▶ Step 3: Automatische Listengenerierung
AG Semantic Computing
Cord Wiljes
Demo: Wikidata
http://www.wikidata.org
AG Semantic Computing
Cord Wiljes
Philosophie
"Wikidata will not be about the truth, but about statements and their
references. These can be contradictory."
AG Semantic Computing
Cord Wiljes
Wikidata Data Model
AG Semantic Computing
Cord Wiljes
Linked Data: Wikidata als RDF
▶ Das Ding:
http://wikidata.org/entity/Q24382
▶ Für die Maschine:
http://wikidata.org/entity/Q24382.rdf
http://wikidata.org/entity/Q24382.nt
http://wikidata.org/entity/Q24382.json
AG Semantic Computing
Cord Wiljes
Anwendungen
▶ Reasonator
▶ LUA
▶ Catmandu
AG Semantic Computing
Cord Wiljes
Nächste Schritte
▶ weitere Properties + Datentypen
▶ Queries (Listen)
▶ Usabillity verbessern
▶ Vertrauen aufbauen
▶ Visualisierungen
AG Semantic Computing
Cord Wiljes
"Vielen Dank!"


Wikidata: Die freie, universelle Datenbank zur Unterstützung der Wikipedia

Jahn, Najko

Pieper, Dirk

Open Access Publikationsfonds

Rimmert, Edith

Digitalisierung

In this talk recent development on automated state machine-based system testing, with a focus on robotics simulation, is presented. In particular, I present the implementation of the simulation environment for the humanoid robot head &amp;quot;Flobi&amp;quot; and the testing framework (FSMT) to assess its preciseness with respect to executed joint trajectories --- compared to its physical counterpart. In addition, I present a fully automated system testing approach, embedded in a Continuous Integration Server

Lier, Florian

MORSE AND STATE-MACHINE-BASED TESTING FOR 
THE HUMANOID ROBOT HEAD FLOBI
International Workshop on MORSE and HRI 2014
Florian Lier | CITEC, Bielefeld University | flier@cit-ec.uni-bielefeld.de | 07.03.2014
FLOBI
https://www.youtube.com/watch?v=dG7kNhxrOG8
FLOBI FACTS
Designed as a comic-like human face to avoid uncanny effects	

Hair, eyebrows, lips and frontal face parts are exchangeable	

Features stereo vision, stereo audio and a gyroscope	

Innovative magnetic actuation mechanism	

Custom design motor control boards	

Eye saccades reach ~400 degree/s	

Overall18 DoF	

More about Flobi: http://pub.uni-bielefeld.de/publication?ftext=flobi
[1]
Rapid prototyping & testing 
required a simulator
FLOBI SOFTWARE STACK
Virtual Robot
Physical Robot
setRegister(0x80, 30)ros.pub(msg, JointState)
Flobi API
C++ Java Python
Control Server [-v]
ROS:: / RSB
setJoint(“NECK_PAN”, 30)
running in virtual or hardware mode	

virtualizes controller boards in “-v mode”	

simulates motor characteristics (ramps, vel, etc.)
[2]
MORSE [5] (of course)
FLOBI SOFTWARE STACK
https://www.youtube.com/watch?v=PBs0c2LzMVM
But…
… how precise is our simulator?
/off: who doesn’t know CI?
http://en.wikipedia.org/wiki/Continuous_integration
CI PRIMER
CI PRIMER
http://jenkins-ci.org/
CI PRIMER
http://jenkins-ci.org/
FLOBI SIMULATION VALIDATION
[3]
FLOBI SIMULATION VALIDATION
[3]
FLOBI SIMULATION VALIDATION
[3]
FLOBI SIMULATION VALIDATION
Worked well, so far…	

Does not scale for multiple projects/test	

Time consuming configuration via GUI	

Not 100% deterministic (default Jenkins job scheduler)	

Requires profound “Jenkins knowledge” to setup test scenarios	

Technology for developers, which often excludes, i.e., social sciences
New approach: FSMT
FINITE-STATE-MACHINE-BASED-TESTING
[4]
FINITE-STATE-MACHINE-BASED-TESTING
[4]
FINITE-STATE-MACHINE-BASED-TESTING
[4]
FINITE-STATE-MACHINE-BASED-TESTING
[4]
FINITE-STATE-MACHINE-BASED-TESTING
FINITE-STATE-MACHINE-BASED-TESTING
FINITE-STATE-MACHINE-BASED-TESTING
FINITE-STATE-MACHINE-BASED-TESTING
[4]
FINITE-STATE-MACHINE-BASED-TESTING
LIVE Demo :)
https://opensource.cit-ec.de
Of course we will make FSMT open soon 
Thank you!
REFERENCES
[1] Wachsmuth S, Schulz S, Lier F, Lütkebohle I. The Robot Head "Flobi": A Research Platform for Cognitive Interaction Technology. Presented at the 
German Conference on Artificial Intelligence, Saarbrücken  
[2] Wienke J, Wrede S. A Middleware for Collaborative Research in Experimental Robotics. In: IEEE/SICE International Symposium on System Integration 
(SII2011). IEEE; 2011: 1183–1190.	

[3] Lier F, Lütkebohle I. Continuous Integration for Iterative Validation of Simulated Robot Models. In: SIMPAR 2012 proceedings. Lecture Notes in 
Computer Science, 7628. Berlin: Springer-Verlag; 2012.	

[4] Lier F, Lütkebohle I, Wachsmuth S. Towards Automated Execution and Evaluation of Simulated Prototype HRI Experiments. In: Human-Robot 
Interaction (HRI), 2014 9th ACM/IEEE. Bielefeld, Germany: Human-Robot Interaction (HRI), 2014 9th ACM/IEEE;	

[5] Echeverria, Gilberto, et al. "Modular open robots simulation engine: Morse." Robotics and Automation (ICRA), 2011 IEEE International Conference 
on. IEEE, 2011.


MORSE and State-Machine-Based Testing for the Humanoid Robot Head FloBI

Chen, Ming

  Proceedings of CELLmicrocosmos neXt 2014 (DOI: 10.2390/biecoll-next2014-9)  20
A novel Lecture Program in Bioinformatics:
Interdisciplinary Cell Visualization and Modeling
Björn Sommer1,2*, Ming Chen1,2
1 Bio-/Medical Informatics Department, Bielefeld University/Center for Biotechnology
Universitätsstr. 25, 33615 Bielefeld, Germany
2 Bioinformatics Group, Zheijang University/College of Life Sciences,
 Yuhagntang Road No. 866, 310058 Hangzhou, P.R. China
1 Introduction
The creation of  a  virtual  cell  scenario  is  a  multidisciplinary  vision.  Cell  modeling is  a
specific field which can be applied to a number of quite diverse approaches, starting from
simulation-based ones, such as the Virtual Cell project – which is able to convert biological
descriptions into a mathematical system of ordinary and/or partial differential equations –
to visualization-based approaches, such as cellPACK – which is based on the idea to create
visual filled cell representations [1], [2]. Integrative Bioinformatics is a field which tries to
unite different information sources to solve biological  questions. The CELLmicrocosmos
project consists of a number of different projects trying to approach the vision of a virtual
cell environment, such as  [3], [4]. Starting from 2004, a remarkable number of students
were  involved  in  the  aforementioned  projects.  In  addition  to  our  custom tools,  also
external tools, such as Blender, Fiji (IsJustImageJ), or GROMACS played an important role
in our daily work [5–7]. 
Figure 1: The logo of “Interdisciplinary Cell Visualization and Modeling”. The cell model
goes back to the initial Bachelor thesis from 2004 created with Autodesk 3ds max®.
2 The Lecture Program
In  2012,  the  idea  emerged  to  develop  a  teaching  module.  First,  these  course  should
provide  the  students  with  background  knowledge  concerning  cytology,  microscopy,
modeling and simulation, as well as bioinformatics. And second, practical lessons should be
included.  Finally,  a  module  was  initiated  and  developed  in  2012  consisting  of  three
different parts:
1. the  lecture  “Interdisciplinary  Cell  Visualization  and  Modeling”,  introducing  the
theoretical background,
2. different seminars, focusing and extending specific lecture topics (see below),
3. and the student project “CELLmicrocosmos Cell Modeling/Cell Visualization”, where
the  practical  work  –  programing,  3D  stereoscopic  modeling  and  visualization,
database applications – was carried out.
*bjoern@CELLmicrocosmos.org
  Proceedings of CELLmicrocosmos neXt 2014 (DOI: 10.2390/biecoll-next2014-9)  21
Three different seminars were offered. “(Multidisciplinary) Cell Visualization” was focusing
on  cytological  visualization,  e.g.  in  school  books  or  digital  edutainment.  The  seminar
“Stereoscopic 3D Visualization” discussed the technical background and the difficulties of
demanding  biological  stereoscopic  visualizations,  which  resulted  in  a  short  film
presentation in a cinema and an accompanying publication [8]. Also, some work presented
at the CELLmicrocosmos neXt workshop is a result of this new teaching module. Moreover,
the seminar “Genome-wide biological Network Modeling and Analysis” discussed aspects
like graph analysis, Petri net simulation, and the visualization of biological networks.
Based on this Sino-German collaboration between the Bio-/Medical Informatics Department
Bielefeld and Bioinformatics Group of Zheijang University, a bilateral exchange teaching
and  workshop  program  was  started  and  there  are  a  number  of  plans  for  our  future
collaborations.  From  2012  to  2014,  workshop  events  of  this  program  took  place  in
Bielefeld, Hangzhou, Harbin, and Tongliao. Moreover, a first book including some ideas of
this collaboration was published in 2014 [9].
3 Acknowledgments
We would  like  to  address  our  thanks  for  the kind  support  to  the  “International  guest
lectureship  program  of  Bielefeld  University”  (2012  and  2014),  as  well  as  the  “NSFC
Research Fund for International Young Scientists” (No. 31450110068, 2014-2015).
4 References
[1] L.  M.  Loew  and  J.  C.  Schaff.  The  Virtual  Cell:  a  software  environment  for
computational cell biology. TRENDS in Biotechnology, 19(10):401–406, 2001.
[2] G. Johnson, D. Goodsell,  L.  Autin, S.  Forli,  M. Sanner, and A. Olson. 3D molecular
models of whole HIV-1 virions generated with cellPACK. Faraday Discussions, 169:1–21, 2014.
[3] B. Sommer, T. Dingersen, C. Gamroth, S. E. Schneider, S. Rubert, J. Krüger, and K. J.
Dietz.  CELLmicrocosmos  2.2  MembraneEditor:  a  modular  interactive  shape-based
software approach  to  solve heterogeneous  Membrane Packing  Problems.  Journal  of
Chemical Information and Modeling, 5(51):1165–1182, 2011.
[4] B.  Sommer,  J.  Künsemöller,  N.  Sand,  A.  Husemann, M.  Rumming,  and B.  Kormeier.
CELLmicrocosmos  4.1:  an  interactive  approach  to  integrating  spatially  localized
metabolic networks into a virtual 3D cell environment. in  BIOSTEC  BIOINFORMATICS
2010, 2010:90–95.
[5] J.  Schindelin,  I.  Arganda-Carreras,  E.  Frise,  V.  Kaynig,  M.  Longair,  T.  Pietzsch,  S.
Preibisch, C. Rueden, S. Saalfeld, and B. Schmid. Fiji: an open-source platform for
biological-image analysis. Nature Methods, 9(7):676–682, 2012.
[6] blender.org -  Home of the Blender project  -  Free and Open 3D Creation Software.
[Online]. Available: http://www.blender.org/. [Accessed: 22-Jul-2014].
[7] B. Hess, C. Kutzner, D. van der Spoel, and E. Lindahl. Gromacs 4: Algorithms for highly
efficient, load-balanced, and scalable molecular simulation. J. Chem. Theory Comput,
4(3):435–447, 2008.
[8] B.  Sommer,  C.  Bender,  T.  Hoppe,  C.  Gamroth,  and  L.  Jelonek.  Stereoscopic  cell
visualization:  from  mesoscopic  to  molecular  scale.  Journal  of  Electronic  Imaging,
23(1):011007–1 – 011007–10, 2014.
[9] M. Chen and R. Hofestädt. Approaches in Integrative Bioinformatics: Towards the 
Virtual Cell. Springer Publishing Company, Incorporated, 2014.


A novel Lecture Program in Bioinformatics: Interdisciplinary Cell Visualization and Modeling

Krüger, Jens

  Proceedings of CELLmicrocosmos neXt 2014 (DOI: 10.2390/biecoll-next2014-7)  16
Web-based MD Simulations using MoSGrid
Jens Krüger*
Applied Bioinformatics Group, University of Tübingen
Sand 14, 72076 Tübingen, Germany
1 Introduction
Molecular  simulations  play  an  increasingly  important  role  in  the  fields  of  chemistry,
biology,  physics  and  life  sciences.  Despite  their  importance  most  tool  suites  and
applications  are  lacking  a  user-friendly  interface  and  direct  connection  to  high-
performance or high-throughput compute resources (HPC/HTC). The molecular simulation
grid  (MosGrid;  www.mosgrid.de)  is  a  web-based science gateway bridging this  gap and
enabling easy access to molecular simulations [1].
2 MoSGrid
The gateway represents a multi-layered stack of different services needed to compose,
submit, monitor and analyse simulations belonging to the domains of quantum chemistry,
molecular dynamics or docking. The only component visible for users is the Liferay-based
webpage, hiding the complexity beneath. In brief, MoSGrid relies on WSPGRADE/gUSE for
workflow and job management, connected via the UNICORE middleware to HPC and HTC
resources [2], using a federated storage solution based on XtreemFS. The authentication
relies on personal X.509 certificates and trust delegation based on them. Currently access
is possible for all researchers with an affiliation to a German research institution. 
Figure 1: The MD portlet of the MoSGrid portal and some of its functionality are shown. In
addition  to  monitoring  and  navigation  capabilities,  the  visualization  of  molecules,
numerical data and textual information is possible.
*krueger@informatik.uni-tuebingen.de
  Proceedings of CELLmicrocosmos neXt 2014 (DOI: 10.2390/biecoll-next2014-7)  17
3 Molecular Dynamics
The focus  of  the  presentation  will  be  on  molecular  dynamics  (MD)  simulations,  while
MoSGrid is able to support a variety of other simulation types. MD simulations in particular
with GROMACS,  follow a distinct  pattern: a molecular  input structure is  pre-processed
using multiple small applications, a job description is compiled, the actual simulation is
carried out, the raw data is processed and analyzed [3]. Such a simulation protocol can be
conveniently represented as workflow. The presentation will highlight all essential steps
for such a typical MD workflow, from the simulation system preparation, over equilibration
steps to the analysis of a production run. 
In  order  to  ensure  full  metadata  annotation  and  storage  of  provenance  information
consequently ensuring full reproducibility a molecular simulation markup language (MSML)
template is  associated to each workflow. Furthermore this documents serves as basis  to
dynamically create the graphical user interface (see Figure 1). Workflows for different kinds
of MD simulations are provided aiming at different scientific use cases and different levels of
user expertise. 
4 Outlook
The maintenance and extension of the MoSGrid is ongoing work. Depending on the needs of
the community modifications, additions and extensions are planned and implemented. In
the  past  auxiliary  applications  such  as  a  direct  UNICORE  connection  for  the  Cm2
MembraneEditor  or  APL@Voro  were  developed  [4].  Current  endeavour  focuses  on  the
connection to PRACE resources via UNICORE and the implementation of an US version of
MoSGrid, enabling convenient access to XSEDE resources. 
Acknowledgments
The author  would  like  to  thank  the  BMBF  (German  Federal  Ministry  of  Education  and
Research) for the opportunity to do research in the MoSGrid project (reference 01IG09006).
The  research  leading  to  these  results  has  partially  been  supported  by  the  European
Commission's Seventh Framework Programme (FP7/2007-2013) under grant agreement no
283481 (SCI-BUS). Special thanks are due to the university compute centers supporting MoSGrid.
References
[1] J.  Krüger,  R.  Grunzke,  S.  Gesing,  S.  Breuers,  A.  Brinkmann,  L.  de  la  Garza,  O.
Kohlbacher, M. Kruse, W.E. Nagel, L. Packschies, R. Müller-Pfefferkorn, P. Schäfer, C.
Schärfe, T. Steinke, T. Schlemmer, K. Warzecha, A. Zink and S. Herres-Pawlis: The
MoSGrid Science Gateway – A Complete Solution for Molecular Simulations, Journal of
Chemical Theory and Computation, 10 (6):2232–2245, 2014.
[2] J. Krüger, R. Grunzke, S. Herres-Pawlis, A. Hoffmann, L. de la Garza, O. Kohlbacher,
W.E.  Nagel  and  S.  Gesing:  Performance  Studies  on  Distributed  Virtual  Screening,
BioMed Research International, Volume 2014, Article ID 624024, 2014.
[3] S. Pronk, S. Páll1, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. R. Shirts, J.C.
Smith, P.M. Kasson, D. van der Spoel, B. Hess and E. Lindahl: GROMACS 4.5: a high-
throughput  and  highly  parallel  open  source  molecular  simulation  toolkit,
Bioinformatics, 29 (7): 845-854, 2013.
[4] G. Lukat, J. Krüger and B. Sommer: APL@Voro: A Voronoi-Based Membrane Analysis 
Tool for GROMACS Trajectories, Journal of Chemical Information and Modeling, 
53(11): 2908–2925, 2013.


Web-based MD Simulations using MoSGrid

Not a member yet