Creating a table of molecules with R

We are using the excellent rCDK package by Rajarshi Guha,
to quickly summarize or work with chemical structures in R.

One thing that always irritated me was that the view.molecule.2d() function opened a separate Java window to display a table of molecule renderings. Because the Java window has no connection with R, this does not allow to use the rich functionality of the R graphics capabilities, while  view.image.2d() , which can return something I can use in conjunction with rasterImage(), handles only a single molecule but not lists.

library(rcdk)

# load demo data
data(bpdata)
mols <- parse.smiles(bpdata$SMILES)

# Set 10x10 molecules per page, and remove border area
par(mfrow=c(10,10))
par(mai=c(0,0,0,0)+0.1)

# Create and plot images
imgs <- lapply(mols, view.image.2d)
sapply (imgs, function(img) {plot.new(); rasterImage(img, 0,0,1,1)})

As a bonus, you can also output to a PDF or PNG file, and even set the page area for PDF to use a full print page.

Enjoy!

Workshop on Tools for Metabolomics Data Processing, Data Analysis and Pathway Analysis at metabolomics2012.org

The workshop will be held on June 25, the first day of the Metabolomics 2012 conference in Washington, D.C., and provides an opportunity to introduce and to present software and development frameworks for all steps in metabolomic data analysis. The workshop includes the option of live software demonstrations to academic and commercial participants.

The topics include, but are not limited to, data pre-processing of NMR and MS data, spectral alignment of multiple measurements, both library-based and de-novo metabolite identification, data normalization and statistical analysis, pathway mapping, pathway reconstruction and last but not least data integration between multiple studies or between data of multi-omics experiments.

Please submit your abstract through the “Abstract Submission” at www.metabolomics2012.org. Don’t forget to mention whether your presentation will include a live demonstration.

Open position at the IPB Halle in computational mass spectrometry

The research group “bioinformatics and mass spectrometry” in the department of Stress- and Developmental Biology at the Leibniz-Institute of Plant Biochemistry (IPB) is seeking applications by highly motivated candidates for a position as research assistant.

You will work on algorithms for the identification of metabolites from mass spectrometry data, together with colleagues from both bio- and chemoinformatics. The methods will be available as user-friendly web applications, but also as part of universal metabolomics workflows on the IPB compute cluster.

You should hold a diploma or masters degree in bioinformatics or computer science, with experience in algorithm- and software engineering and statistics. You are able to program in Java, the statistics framework R, and have worked with relational databases. Knowledge in metabolomics or biochemistry would be an advantage. The position is available immediately. Payment is according to local regulations TV-L.
The IPB is an international research institute located on the weinberg-campus of the Martin-Luther-University Halle-Wittenberg and provides state-of-the-art facilities for research in bioinformatics, metabolomics and plant biochemistry. Further information is available from the institute's homepage http://www.ipb-halle.de/en/, for inquires please contact Dr. Steffen Neumann, Telephone: +49 345 5582-1470, e-Mail: sneumann@ipb-halle.de

Researcher Bioinformatics for Metabolomics @ PRI/Wageningen, The Netherlands

The Applied Bioinformatics group at Plant Research International is looking for a researcher bioinformatics for metabolomics:

Job description: A position for a researcher is available in the Bioinformatics group at Plant Research International (PRI) to participate as scientific programmer in the development of the BioAssist metabolomics support platform. Within PRI this development is central to various projects related to bioinformatics for metabolomics and the candidate is expected to take a proactive and coordinating role in this area. Specific tasks will include the implementation and further development of the data warehouse Metware and development of standards and webservices for existing metabolomics software tools and their implementation in the workflow management system Taverna.

Profile: We are looking for a communicative team player with:



• A recent PhD in chemoinformatics, chemometrics, bioinformatic or related area


• Advanced programming and database development skills (fluent in Java, SQL, and preferably in C++, Perl, or Python)


• Knowledge of BioMoby, tomcat, SQL, JSF, bioMART and semantic web (e.g. RDF, OWL)


• Basic knowledge of mass spectrometry and metabolomics technology is essential


• The drive, ambition and skills to acquire a leading role in the development of a metabolomics data analysis platform within PRI and to initiate new projects in this field

Further info can be found in here: 08.Biosc.04.

Job: Postdoctoral Researcher at EBI, Hinxton/UK

NatureJobs reports:

Research into and development of methods for computer-assisted structure elucidation of biological metabolites based on mass spectrometry and NMR data. For this position in the Steinbeck group, the postdoctoral researchers need to hold a PhD degree in chemistry, biology, bioinformatics, computer science or a related field. They have good knowledge of standard software development and the ability to use, modify and adapt others code if necessary. Applicants should have proven experience with programming in Java as well as chemoinformatics and bioinformatics software development. The successful applicant must work on their own initiative, but work as part of a wider team and collaborate with colleagues, internally and externally where required. The position is based in the Chemoinformatics and Metabolism (Steinbeck Research Group). It is initially termed for 12 months, extension may be possible.

Paper: Genetic algorithm based two-mode clustering of metabolomics data

Jos Hageman (UvA, now Biometris in Wageningen) published the paper Genetic algorithm based two-mode clustering of metabolomics data (DOI:10.1007/s11306-008-0105-7):

In this paper we introduce a two-mode clustering method based on a genetic algorithm that uses a criterion that searches for homogeneous clusters. Furthermore we introduce a cluster stability criterion to validate the clusters and we provide an extended knee plot to select the optimal number of clusters in both experimental and metabolite modes. The genetic algorithm-based two-mode clustering gave biological relevant results when it was applied to two real life metabolomics data sets.

If you are working in NL and you would like to see you paper listed in this blog too, please send me an email.

Paper: Accurate mass error correction in liquid chromatography time-of-flight mass spectrometry based metabolomics

Velitchka Mihaleva et al. (Plant Research International/Wageningen University) just published a paper in Metabolomics: Accurate mass error correction in liquid chromatography time-of-flight mass spectrometry based metabolomics (doi:10.1007/s11306-008-0108-4):

Experimental LC/TOF-MS platforms equipped with a time-to-digital converter (TDC) give the best mass estimate for those mass signals with an intensity similar to that of the lock-mass used for internal calibration. However, they systematically underestimate the mass obtained at higher signal intensity and overestimate it at low signal intensities compared to that of the lock-mass. To compensate for these effects, specific tools are required for correction and automation of accurate mass calculations from LC/MS signals. Here, we present a computational procedure for the derivation of an intensity-dependent mass correction function.

If you are working in NL and you would like to see you paper listed in this blog too, please send me an email.