Seminar Homepage : Druckversion


http://www.dagstuhl.de/17491

December 3 – 8 , 2017, Dagstuhl Seminar 17491

Computational Metabolomics: Identification, Interpretation, Imaging

Organizers

Theodore Alexandrov (EMBL Heidelberg, DE)
Sebastian Böcker (Universität Jena, DE)
Pieter Dorrestein (UC – San Diego, US)
Emma Schymanski (University of Luxembourg, LU)

For support, please contact

Annette Beyer for administrative matters

Michael Gerke for scientific matters

Dagstuhl Reports

As part of the mandatory documentation, participants are asked to submit their talk abstracts, working group results, etc. for publication in our series Dagstuhl Reports via the Dagstuhl Reports Submission System.

Documents

List of Participants
Shared Documents
Dagstuhl Seminar Wiki

(Use seminar number and access code to log in)

Motivation

Metabolomics is the study of metabolites (the small molecules involved in metabolism) in living cells, cell populations, organisms or communities. Metabolites are key players in almost all biological processes, play various functional roles providing energy, building blocks, signaling, communication, and defense and serve as clinical biomarkers for detecting medical conditions such as cancer. Small molecule drugs (many of which are derived from metabolites) account for 90 % of prescribed therapeutics. Complete understanding of biological systems requires detecting and interpreting the metabolome in time and space.

Mass spectrometry is the predominant analytical technique for detecting and identifying metabolites and other small molecules in high–throughput experiments. Huge technological advances in mass spectrometry and experimental workflows during the last decade enabled novel investigations of biological systems on the metabolite level. Research into computational workflows, the simulation of tandem mass spectra, compound identification and molecular networking have helped disentangle the vast amount of information that mass spectrometry provides. Spatial metabolomics on different spatial scales from single cells to organs and organisms has posed data analysis challenges, in particular due to an unprecedented data volume generated that grows quadratically with the increase of spatial resolution.

Other omics fields have benefited greatly from close cooperations between experimental and computational scientists, which is still in its infancy for metabolomics. Many of the methods established in other omics fields, especially proteomics, are not directly transferable to metabolomics due to the striking chemical variety of metabolites. Here, lessons learned in other fields such as pharmaceutical and environmental sciences, forensics, and toxicology are invaluable to extending the window of metabolomics beyond its current state. This seminar aims to foster communication between the computational and experimental scientists to bring metabolomics in line with the other omics fields.

Continued improvements to instruments, resolution, ionization and acquisition techniques mean that metabolomics mass spectrometry experiments can generate massive amounts of data, and the field is evolving into a “big data” science. This is particularly the case for imaging mass spectrometry, where a single dataset can easily be many gigabytes or even terabytes in size. Despite this dramatic increase in data, much of the data analysis in metabolomics is still performed manually and requires expert knowledge as well as the collation of data from a plethora of sources. Novel computational methods are required to exploit spectral and, in the case of imaging, also spatial information from the data, while remaining efficient enough to process tens to hundreds of gigabytes of data.

This Dagstuhl Seminar will build upon the success of the first Computational Metabolomics Dagstuhl Seminar (15492). It will address the core themes and challenges applicable to computational metabolomics, while adding a parallel focus on spatial aspects and imaging mass spectrometry. The key goals are (i) to foster the exchange of ideas between the experimental and computational communities, (ii) to expose the novel computational developments and challenges, and (iii) establish collaborations to address grand and priority challenges by bridging the best available data with the best methods.

The seminar will start with leaders in the field presenting current opportunities and computational challenges in classical metabolomics, imaging and environmental sciences. Main topics will include MS1 and MS/MS analysis, feature building, annotation and un-annotated “dark matter”, structural identification, substructure recognition, computational workflows and services, as well as network-based or integrative analysis. Several breakout sessions throughout the seminar will facilitate discussion of multiple smaller topics and cater to all participants. Potential topic leaders and speakers will be contacted in advance. We look forward to lively discussions and contributions from all participants.

License
  Creative Commons BY 3.0 DE
  Theodore Alexandrov, Sebastian Böcker, Pieter Dorrestein, Emma Schymanski, and Nicola Zamboni

Related Dagstuhl Seminar

Classification

Keywords



Book exhibition

Books from the participants of the current Seminar 

Book exhibition in the library, ground floor, during the seminar week.

Documentation

In the series Dagstuhl Reports each Dagstuhl Seminar and Dagstuhl Perspectives Workshop is documented. The seminar organizers, in cooperation with the collector, prepare a report that includes contributions from the participants' talks together with a summary of the seminar.

 

Download overview leaflet (PDF).

Publications

Furthermore, a comprehensive peer-reviewed collection of research papers can be published in the series Dagstuhl Follow-Ups.

Dagstuhl's Impact

Please inform us when a publication was published as a result from your seminar. These publications are listed in the category Dagstuhl's Impact and are presented on a special shelf on the ground floor of the library.

NSF young researcher support


Seminar Homepage : Last Update 15.12.2017, 07:26 o'clock