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To handle changing environmental surroundings and to manage unfavourable conditions, all microbial organisms have
evolved complex
transcriptional gene regulatory networks. My aim is to reconstruct and analyze these networks. Therefore, we
developed
two platforms: CoryneRegNet and MycoRegNet. Both provide comprehensive visualization capabilities and offer
easy-to-use interfaces
to execute computer analysis features to predict promising wet lab targets. CoryneRegNet is the reference database
for corynebacteria, organisms of high impact
in biotechnology (Corynebacterium glutamicum) and human medicine (C. diphtheriae and C.
jeikeium). MycoRegNet concentrates
on the human pathogen Mycobacterium tuberculosis.
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| Tools |
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| Selected Papers |
Krawczyk J, Kohl TA, Goesmann A, Kalinowski J, Baumbach J (2009)
From Corynebacterium glutamicum to Mycobacterium tuberculosis -
Towards transfers of gene regulatory networks and integrated data
analyses with MycoRegNet. Nucleic Acids Res. 2009
Aug;37(14):e97. PubMed
Baumbach J, Wittkop T, Kleindt CK, Tauch A (2009) Integrated analysis and reconstruction of microbial
transcriptional gene regulatory networks using CoryneRegNet. Nature Protocols. 2009 Jun;4(6):992-1005.
PubMed
Baumbach J, Rahmann S, Tauch A (2009) Towards the integrated analysis, visualization, and reconstruction
of microbial gene regulatory networks. Brief Bioinform. 2009 Jan;10(1):75-83. PubMed
Baumbach J (2007) CoryneRegNet 4.0 - A reference database for corynebacterial gene regulatory
networks. BMC Bioinformatics 2007, 8:429. PubMed
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Partitioning data objects into groups, such that the objects in each group share common traits, is a long-standing
challenge in computer science. We developed integrated biological data clustering frameworks: FORCE and
Transitivity Clustering.
They are based on solving the NP-hard Weighted Transitive Graph Projection aka. Weighted Cluster Editing. While
TransClust
was developed very recently, FORCE finds frequent application in protein homology detection.
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| Selected Papers |
Wittkop T, Emig D, Lange SJ, Rahmann S, Albrecht M, Morris JH, Boecker S, Stoye J, Baumbach J (2010) Partitioning biological data
with Transitivity Clustering. Nature Methods 2010
Jun;7(6):419-20. PubMed
Wittkop T, Baumbach J, Lobo FP, Rahmann S (2007) Large scale clustering of protein sequences with FORCE
-- A layout based heuristic for weighted cluster editing. BMC Bioinformatics 2007, 8:396. PubMed
Rahmann S, Wittkop T, Baumbach J, Martin M, Truss A, Boecker S (2007) Exact and Heuristic Algorithms for
Weighted Cluster Editing. In Proc. 6th CSB, volume 6 of Computational Systems Bioinformatics.
Imperial College Press, 2007. PubMed
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A precise identification of transcription factor binding sites (TFBSs) is time-consuming and difficult.
Often, TFBS annotations are extracted from the literature and stored routinely 5' → 3' relative to the target
gene.
Mixing the two possible orientations of a TFBS results in poor information content of subsequently computed
models.
Since these models are used to predict further TFBSs, we developed MoRAine and MotifAdjuster. They aim to
re-adjust TFBS
annotations automatically to improve subsequent classification performance. Note that this problem is very related
to
the so-called "Motif Discovery".
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MotifAdjuster
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| Selected Papers |
Wittkop T, Rahmann S, Baumbach J (2010) Efficient Online Transcription Factor Binding Site Adjustment by Integrating Transitive Graph Projection with MoRAine 2.0. J Integr Bioinform, 2008 Aug 25;5(2). PubMed
Baumbach J, Wittkop T, Weile J, Kohl T, Rahmann S, (2008) MoRAine - A web server for fast computational
transcription factor binding motif re-annotation. J Integr Bioinform, 5(2):91, 2008.
PubMed
Keilwagen J, Baumbach J, Kohl T, Grosse I (2009) MotifAdjuster: A tool for computational reassessment of
transcription factor binding site annotations. Genome Biol 2009 May 1;10(5):R46. PubMed
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The introduction of high-throughput genome sequencing and post-genome analysis technologies has created the
potential to
unravel complex biological pathways on a large scale. To analyze and interpret this data in the context of
experimental
results, we developed tools that help to integrate and visualize all available pathway data together with wet lab
data.
ONDEX enables data from diverse biological data sets to be integrated and visualised. CoryneCenter is specialized
for the
analysis of corynebacterial gene regulatory interactions together with gene expression data. While ONDEX follows a
so-called "Data Warehouse" strategy, CoryneCenter utilizes a SOAP-based Web Service communication scheme that
integrates
all contributing, independent platforms on demand.
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| Selected Papers |
Baumbach J, Apeltsin L (2008) Linking Cytoscape and the corynebacterial reference database
CoryneRegNet. BMC Genomics. 2008 Apr 21;9(1):184. PubMed
Neuweger H, Baumbach J, Albaum S, Bekel T, Dondrup M, Hueser AT, Kalinowski J, Oehm S, Puehler A, Rahmann
S, Weile J, Goesmann A (2007) CoryneCenter - An online resource for the integrated analysis of corynebacterial
genome and transcriptome data. BMC Syst Biol 1(1):55. PubMed
Koehler J, Baumbach J, Taubert J, Specht M, Skusa A, Rueegg A, Rawlings C, Verrier P, Philippi S (2006)
Graph-based analysis and visualization of experimental results with ONDEX. Bioinformatics. 2006 Mar
13;22(11):1383-1390. PubMed
Baumbach J, Brinkrolf K, Czaja LF, Rahmann S, Tauch A (2006) CoryneRegNet: An ontology-based data
warehouse of corynebacterial transcription factors and regulatory networks. BMC Genomics. 2006 Feb
14;7(1):24. PubMed
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The genome-scale reconstruction of transcriptional gene regulatory networks is important for biotechnology and
human
medicine but cost-intensive, time-consuming, and impossible to perform for any species separately. By using
bioinformatics methods one can partially transfer networks from model organisms to closely related species. Here,
we
developed bioinformatics workflows for CoryneRegNet and MycoRegNet that perform reliable network transfers from
C. glutamicum to other corynebacteria, e.g. C. diphtheriae, and to M. tuberculosis. The main
idea behind the prediction pipeline is illustrated here.
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| Selected Papers |
Baumbach J, Rahmann S, Tauch A (2009) Reliable transfer of transcriptional gene regulatory networks
between taxonomically related organisms. BMC Syst Biol. 2009 Jan 15;3(1):8. PubMed
Krawczyk J, Kohl TA, Goesmann A, Kalinowski J, Baumbach J (2009)
From Corynebacterium glutamicum to Mycobacterium tuberculosis -
Towards transfers of gene regulatory networks and integrated data
analyses with MycoRegNet. Nucleic Acids Res. 2009
Aug;37(14):e97. PubMed
Baumbach J, Wittkop T, Kleindt CK, Tauch A (2009) Integrated analysis and reconstruction of microbial
transcriptional gene regulatory networks using CoryneRegNet. Nature Protocols. 2009 Jun;4(6):992-1005.
PubMed
Baumbach J, Rahmann S, Tauch A (2009) Towards the integrated analysis, visualization, and reconstruction
of microbial gene regulatory networks. Brief Bioinform. 2009 Jan;10(1):75-83. PubMed
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