NPC Bioinformatics survey

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Please fill in this form, and send back to Peter Horvatovich (p.l.horvatovich@rug.nl) or Bas van Breukelen (b.vanbreukelen@uu.nl) until 25 November 2010 in order that we prepare efficiently a workshop on the subject. This document serves to provide overview on the actual bioinformatics bottlenecks, and expertise, at the different NPC members. Based on this survey we will organize a workshop with aim to alleviate these bottlenecks and better organize the bioinformatics support provided by NPC/NBIC gaining momentum initiative. The content of the filled forms by the different laboratory is listed below (https://wiki.nbic.nl/index.php/NPC_Bioinformatics_survey). The empty form can be also downloaded by clicking here and you can report changes of bottlenecks and expertise any time.


Laboratory
Analytical Biochemistry, Department of Pharmacy, University of Groningen
PIs: Peter Horvatovich, Rainer Bischoff

Instrumentation

  • 1 Agilent 6510 chip-qTOF
  • 2 Agilent SL iontrap LC-MS (one equipped with chip interface and one with capillary LC)
  • 1 Agilent 6410 chip-qqq

Applied proteomics strategies

  • Label-free MS1 and DDA LC-MS/MS
  • Biomarker validation with MRM assays
  • SIL-PEG based labeling (label developed in our lab and performing labeling in MS1)
  • Activity based metalloprotein profiling

Bioinformatics bottlenecks

  1. We are producing more that, that we can analyse → we need user high-throughput user friendly data processing solution to solve this problem.
  2. Identification pipeline for PTM rich data
  3. We need good and user friendly MRM pipeline

Bioinformatics expertise

  • in-house Phenyx protein identification software (8 core 16GB)
  • framework for quantitative processing of LC-MS image (command line and implemented in in-house Galaxy server running on 8 core 64GB machine)
  • in-house developed LC-MS time alignment algorithms

Laboratory
Biomolecular Mass Spectrometry and Proteomics Group, Utrecht University
PIs: B. van Breukelen

Instrumentation

  • Orbitrap (Velos) (multiple)
  • Orbitrap + ETD (multiple)
  • Q-tof, MALDI-tof, Synapt, others

Applied proteomics strategies

  • Labeled quantitative proteomics (and a bit of label free)
  • Shotgun proteomics
  • Development of new application in mass spectrometry (and proteomics)


Bioinformatics bottlenecks

  1. A lot of data is produced. Analysis is a bottleneck, we are looking for a more streamlined (all in one?) pipeline/workflow
  2. Pre-processing and post processing of MS data. Specifically in labeled quantitation
  3. Data analysis of proteomics experiments --> over/under representation, statistics, pathways/networks etc

Bioinformatics expertise

  • Mascot server (32 cpu/ 64gb memory)
  • Data storage (cloud server solution 128tb)
  • Development of mini LIMS systems
  • De Novo sequencing algorithms
  • Scaffold software for multiple ms search results comparison
  • APEX label free quantitation
  • Protein grouping
  • MaxQuant/MSQuant/MSInspect labeled quantitfication workflows/software
  • Galaxy server
  • PRIDE repository for MS data
  • Scripting in PERL, PHP and JAVA (and a bit of python, C++)