author_facet Hache, Hendrik
Wierling, Christoph
Lehrach, Hans
Herwig, Ralf
Hache, Hendrik
Wierling, Christoph
Lehrach, Hans
Herwig, Ralf
author Hache, Hendrik
Wierling, Christoph
Lehrach, Hans
Herwig, Ralf
spellingShingle Hache, Hendrik
Wierling, Christoph
Lehrach, Hans
Herwig, Ralf
Bioinformatics
GeNGe: systematic generation of gene regulatory networks
Computational Mathematics
Computational Theory and Mathematics
Computer Science Applications
Molecular Biology
Biochemistry
Statistics and Probability
author_sort hache, hendrik
spelling Hache, Hendrik Wierling, Christoph Lehrach, Hans Herwig, Ralf 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/btp115 <jats:title>Abstract</jats:title> <jats:p>Summary: The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent. To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a non-linear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g. as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiments.</jats:p> <jats:p>Availability: Available online at http://genge.molgen.mpg.de</jats:p> <jats:p>Contact: hache@molgen.mpg.de</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> GeNGe: systematic generation of gene regulatory networks Bioinformatics
doi_str_mv 10.1093/bioinformatics/btp115
facet_avail Online
Free
finc_class_facet Mathematik
Informatik
Biologie
Chemie und Pharmazie
format ElectronicArticle
fullrecord blob:ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTA5My9iaW9pbmZvcm1hdGljcy9idHAxMTU
id ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTA5My9iaW9pbmZvcm1hdGljcy9idHAxMTU
institution DE-D275
DE-Bn3
DE-Brt1
DE-Zwi2
DE-D161
DE-Gla1
DE-Zi4
DE-15
DE-Pl11
DE-Rs1
DE-105
DE-14
DE-Ch1
DE-L229
imprint Oxford University Press (OUP), 2009
imprint_str_mv Oxford University Press (OUP), 2009
issn 1367-4811
1367-4803
issn_str_mv 1367-4811
1367-4803
language English
mega_collection Oxford University Press (OUP) (CrossRef)
match_str hache2009gengesystematicgenerationofgeneregulatorynetworks
publishDateSort 2009
publisher Oxford University Press (OUP)
recordtype ai
record_format ai
series Bioinformatics
source_id 49
title GeNGe: systematic generation of gene regulatory networks
title_unstemmed GeNGe: systematic generation of gene regulatory networks
title_full GeNGe: systematic generation of gene regulatory networks
title_fullStr GeNGe: systematic generation of gene regulatory networks
title_full_unstemmed GeNGe: systematic generation of gene regulatory networks
title_short GeNGe: systematic generation of gene regulatory networks
title_sort genge: systematic generation of gene regulatory networks
topic Computational Mathematics
Computational Theory and Mathematics
Computer Science Applications
Molecular Biology
Biochemistry
Statistics and Probability
url http://dx.doi.org/10.1093/bioinformatics/btp115
publishDate 2009
physical 1205-1207
description <jats:title>Abstract</jats:title> <jats:p>Summary: The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent. To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a non-linear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g. as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiments.</jats:p> <jats:p>Availability: Available online at http://genge.molgen.mpg.de</jats:p> <jats:p>Contact:  hache@molgen.mpg.de</jats:p> <jats:p>Supplementary information:  Supplementary data are available at Bioinformatics online.</jats:p>
container_issue 9
container_start_page 1205
container_title Bioinformatics
container_volume 25
format_de105 Article, E-Article
format_de14 Article, E-Article
format_de15 Article, E-Article
format_de520 Article, E-Article
format_de540 Article, E-Article
format_dech1 Article, E-Article
format_ded117 Article, E-Article
format_degla1 E-Article
format_del152 Buch
format_del189 Article, E-Article
format_dezi4 Article
format_dezwi2 Article, E-Article
format_finc Article, E-Article
format_nrw Article, E-Article
_version_ 1792332808887205900
geogr_code not assigned
last_indexed 2024-03-01T14:02:18.589Z
geogr_code_person not assigned
openURL url_ver=Z39.88-2004&ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fvufind.svn.sourceforge.net%3Agenerator&rft.title=GeNGe%3A+systematic+generation+of+gene+regulatory+networks&rft.date=2009-05-01&genre=article&issn=1367-4803&volume=25&issue=9&spage=1205&epage=1207&pages=1205-1207&jtitle=Bioinformatics&atitle=GeNGe%3A+systematic+generation+of+gene+regulatory+networks&aulast=Herwig&aufirst=Ralf&rft_id=info%3Adoi%2F10.1093%2Fbioinformatics%2Fbtp115&rft.language%5B0%5D=eng
SOLR
_version_ 1792332808887205900
author Hache, Hendrik, Wierling, Christoph, Lehrach, Hans, Herwig, Ralf
author_facet Hache, Hendrik, Wierling, Christoph, Lehrach, Hans, Herwig, Ralf, Hache, Hendrik, Wierling, Christoph, Lehrach, Hans, Herwig, Ralf
author_sort hache, hendrik
container_issue 9
container_start_page 1205
container_title Bioinformatics
container_volume 25
description <jats:title>Abstract</jats:title> <jats:p>Summary: The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent. To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a non-linear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g. as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiments.</jats:p> <jats:p>Availability: Available online at http://genge.molgen.mpg.de</jats:p> <jats:p>Contact:  hache@molgen.mpg.de</jats:p> <jats:p>Supplementary information:  Supplementary data are available at Bioinformatics online.</jats:p>
doi_str_mv 10.1093/bioinformatics/btp115
facet_avail Online, Free
finc_class_facet Mathematik, Informatik, Biologie, Chemie und Pharmazie
format ElectronicArticle
format_de105 Article, E-Article
format_de14 Article, E-Article
format_de15 Article, E-Article
format_de520 Article, E-Article
format_de540 Article, E-Article
format_dech1 Article, E-Article
format_ded117 Article, E-Article
format_degla1 E-Article
format_del152 Buch
format_del189 Article, E-Article
format_dezi4 Article
format_dezwi2 Article, E-Article
format_finc Article, E-Article
format_nrw Article, E-Article
geogr_code not assigned
geogr_code_person not assigned
id ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTA5My9iaW9pbmZvcm1hdGljcy9idHAxMTU
imprint Oxford University Press (OUP), 2009
imprint_str_mv Oxford University Press (OUP), 2009
institution DE-D275, DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161, DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229
issn 1367-4811, 1367-4803
issn_str_mv 1367-4811, 1367-4803
language English
last_indexed 2024-03-01T14:02:18.589Z
match_str hache2009gengesystematicgenerationofgeneregulatorynetworks
mega_collection Oxford University Press (OUP) (CrossRef)
physical 1205-1207
publishDate 2009
publishDateSort 2009
publisher Oxford University Press (OUP)
record_format ai
recordtype ai
series Bioinformatics
source_id 49
spelling Hache, Hendrik Wierling, Christoph Lehrach, Hans Herwig, Ralf 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/btp115 <jats:title>Abstract</jats:title> <jats:p>Summary: The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent. To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a non-linear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g. as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiments.</jats:p> <jats:p>Availability: Available online at http://genge.molgen.mpg.de</jats:p> <jats:p>Contact: hache@molgen.mpg.de</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> GeNGe: systematic generation of gene regulatory networks Bioinformatics
spellingShingle Hache, Hendrik, Wierling, Christoph, Lehrach, Hans, Herwig, Ralf, Bioinformatics, GeNGe: systematic generation of gene regulatory networks, Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability
title GeNGe: systematic generation of gene regulatory networks
title_full GeNGe: systematic generation of gene regulatory networks
title_fullStr GeNGe: systematic generation of gene regulatory networks
title_full_unstemmed GeNGe: systematic generation of gene regulatory networks
title_short GeNGe: systematic generation of gene regulatory networks
title_sort genge: systematic generation of gene regulatory networks
title_unstemmed GeNGe: systematic generation of gene regulatory networks
topic Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability
url http://dx.doi.org/10.1093/bioinformatics/btp115