TICL - a web tool for network-based interpretation of compound lists inferred by high-throughput metabolomics

被引:25
作者
Antonov, Alexey V. [1 ]
Dietmann, Sabine
Wong, Philip
Mewes, Hans W. [2 ]
机构
[1] Helmholtz Zentrum Munchen, German Res Ctr Environm Hlth GmbH, Inst Bioinformat & Syst Biol, D-85764 Neuherberg, Germany
[2] Tech Univ Munich, Dept Genome Oriented Bioinformat, D-8050 Freising Weihenstephan, Germany
关键词
bioinformatics tools for high-throughput metabolomics; metabolomics; statistical analysis and data mining; statistical and bioinformatics tools; web tools for metabolomics; GENE-EXPRESSION; COMPLEX FUNCTIONALITY; SPECTROMETRY; PATTERNS; ROUTES;
D O I
10.1111/j.1742-4658.2009.06943.x
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
High-throughput metabolomics is a dynamically developing technology that enables the mass separation of complex mixtures at very high resolution. Metabolic profiling has begun to be widely used in clinical research to study the molecular mechanisms of complex cell disorders. Similar to transcriptomics, which is capable of detecting genes at differential states, metabolomics is able to deliver a list of compounds differentially present between explored cell physiological conditions. The bioinformatics challenge lies in a statistically valid interpretation of the functional context for identified sets of metabolites. Here, we present TICL, a web tool for the automatic interpretation of lists of compounds. The major advance of TICL is that it not only provides a model of possible compound transformations related to the input list, but also implements a robust statistical framework to estimate the significance of the inferred model. The TICL web tool is freely accessible at http://mips.helmholtz-muenchen.de.
引用
收藏
页码:2084 / 2094
页数:11
相关论文
共 39 条
[1]   KEGGanim:: pathway animations for high-throughput data [J].
Adler, Priit ;
Reimand, Jueri ;
Jaenes, Juergen ;
Kolde, Raivo ;
Peterson, Hedi ;
Vilo, Jaak .
BIOINFORMATICS, 2008, 24 (04) :588-590
[2]   Bioinformatics analysis of targeted metabolomics - Uncovering old and new tales of diabetic mice under medication [J].
Altmaier, Elisabeth ;
Ramsay, Steven L. ;
Graber, Armin ;
Mewes, Hans-Werner ;
Weinberger, Klaus M. ;
Suhre, Karsten .
ENDOCRINOLOGY, 2008, 149 (07) :3478-3489
[3]  
[Anonymous], 1993, Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment
[4]   ProfCom: a web tool for profiling the complex functionality of gene groups identified from high-throughput data [J].
Antonov, Alexey V. ;
Schmidt, Thorsten ;
Wang, Yu ;
Mewes, Hans W. .
NUCLEIC ACIDS RESEARCH, 2008, 36 :W347-W351
[5]   Complex functionality of gene groups identified from high-throughput data [J].
Antonov, Alexey V. ;
Mewes, Hans W. .
JOURNAL OF MOLECULAR BIOLOGY, 2006, 363 (01) :289-296
[6]   Complex phylogenetic profiling reveals fundamental genotype-phenotype associations [J].
Antonov, Alexey V. ;
Mewes, Hans W. .
COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2008, 32 (06) :412-416
[7]   Characterizing gene sets with FuncAssociate [J].
Berriz, GF ;
King, OD ;
Bryant, B ;
Sander, C ;
Roth, FP .
BIOINFORMATICS, 2003, 19 (18) :2502-2504
[8]   MetaRoute: fast search for relevant metabolic routes for interactive network navigation and visualization [J].
Blum, Torsten ;
Kohlbacher, Oliver .
BIOINFORMATICS, 2008, 24 (18) :2108-2109
[9]   Using atom mapping rules for an improved detection of relevant routes in weighted metabolic networks [J].
Blum, Torsten ;
Kohlbacher, Oliver .
JOURNAL OF COMPUTATIONAL BIOLOGY, 2008, 15 (06) :565-576
[10]   Precision mapping of the metabolome [J].
Breitling, Rainer ;
Pitt, Andrew R. ;
Barrett, Michael P. .
TRENDS IN BIOTECHNOLOGY, 2006, 24 (12) :543-548