J. Selbig

J. Selbig, N. Beerenwinkel, R. Kaiser, 2005, Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology.

Applying supervised and unsupervised learning methods to discover regularities in protein sequences and structures

J. Selbig, 2007 .

Gene expression Non-linear PCA : a missing data approach

Matthias Scholz, J. Selbig, F. Kaplan, 2005 .

Heterosis manifestation during early Arabidopsis seedling development is characterized by intermediate gene expression and enhanced metabolic activity in the hybrids.

Matthias Scholz, O. Fiehn, J. Selbig, 2012, The Plant journal : for cell and molecular biology.

Quantitative phenotype prediction by support vector machines

Thomas Lengauer, Joachim Selbig, Barbara Schmidt, 2002 .

Tree models for the evolution of drug resistance

Thomas Lengauer, Jörg Rahnenführer, Joachim Selbig, 2003 .

Identification of metabolic and biomass QTL in Arabidopsis thaliana in a parallel analysis of RIL and IL populations

Joachim Selbig, Thomas Altmann, Henning Redestig, 2007, The Plant journal : for cell and molecular biology.

Understanding the Relationship between Cotton Fiber Properties and Non-Cellulosic Cell Wall Polysaccharides

J. Selbig, D. Rajasundaram, W. Willats, 2014, PloS one.

Data set heterogeneities and their effects on the derivation of contact potentials

J. Selbig, 2007 .

Integration of a Systems Biological Network Analysis and QTL Results for Biomass Heterosis in Arabidopsis thaliana

J. Selbig, D. Repsilber, Sandra Andorf, 2012, PloS one.

Bioinformatics of Eukaryotic Gene Regulation

H. Herzel, M. Vingron, J. Selbig, 2006 .

Data integration for identification of important transcription factors of STAT6-mediated cell fate decisions.

U. Leser, Wei Chen, Z. Fang, 2016, Genetics and molecular research : GMR.

Robin: An Intuitive Wizard Application for R-Based Expression Microarray Quality Assessment and Analysis1[W][OA]

Joachim Selbig, Dirk Walther, Mark Stitt, 2010, Plant Physiology.

Correlative GC-TOF-MS-based metabolite profiling and LC-MS-based protein profiling reveal time-related systemic regulation of metabolite–protein networks and improve pattern recognition for multiple biomarker selection

Joachim Selbig, Matthias Scholz, Wolfram Weckwerth, 2005, Metabolomics.

A distinct metabolic signature predicts development of fasting plasma glucose

Joachim Selbig, Lothar Willmitzer, Joachim Spranger, 2012, Journal of Clinical Bioinformatics.

Identification of metabolic and biomass QTL in Arabidopsis thaliana in a parallel analysis of RIL and IL populations

O. Fiehn, J. Selbig, L. Willmitzer, 2007, The Plant journal : for cell and molecular biology.

Exploiting Gene Families for Phylogenomic Analysis of Myzostomid Transcriptome Data

B. Nickel, M. Meyer, J. Selbig, 2012, PloS one.

Structural analysis of the DNA-binding domain of alternatively spliced steroid receptors.

J. Selbig, L. Wickert, 2002, The Journal of endocrinology.

QTL analysis of early stage heterosis for biomass in Arabidopsis

Hanno Scharr, Ulrich Schurr, Joachim Selbig, 2009, Theoretical and Applied Genetics.

The expression of Wnt-inhibitor DKK1 (Dickkopf 1) is determined by intercellular crosstalk and hypoxia in human malignant gliomas

J. Selbig, J. Tonn, H. Motaln, 2014, Journal of Cancer Research and Clinical Oncology.

Differential mRNA Expression of the Two Mineralocorticoid Receptor Splice Variants Within the Human Brain: Structure Analysis of their Different DNA Binding Domains

J. Selbig, J. Schramm, L. Wickert, 2000, Journal of neuroendocrinology.

Systematic framework for metabolic networks with constrained biological information : analysis and applications

P. May, J. Selbig, Z. Nikoloski, 2007 .

A new network model explains the evolution of plant-specific metabolic networks

Joachim Selbig, Joachim Selbig, Zoran Nikoloski, 2009 .

Proceedings of the German Conference on Bioinformatics, GCB 2007, September 26-28, 2007, Potsdam, Germany

Martin Vingron, Alexander Schliep, Joachim Selbig, 2007, German Conference on Bioinformatics.

Hypothesis-driven approach to predict transcriptional units from gene expression data

Joachim Selbig, Björn H. Junker, Alexander Lüdemann, 2004, Bioinform..

pcaMethods - a bioconductor package providing PCA methods for incomplete data

Joachim Selbig, Dirk Walther, Matthias Scholz, 2007, Bioinform..

Data Integration, Metabolic Networks and Systems Biology

Henning Redestig, Jedrzej Szymanski, Masami Yokota Hirai, 2011 .

From structure to dynamics of metabolic pathways: application to the plant mitochondrial TCA cycle

Joachim Selbig, Thilo Gross, Alisdair R. Fernie, 2007, Bioinform..

Metabolomic and transcriptomic stress response of Escherichia coli

J. Selbig, L. Willmitzer, D. Steinhauser, 2010, Molecular systems biology.

Visualization and analysis of molecular data.

Joachim Selbig, Matthias Scholz, Matthias Scholz, 2007, Methods in molecular biology.

Metabolite fingerprinting: detecting biological features by independent component analysis

Joachim Selbig, Matthias Scholz, Oliver Fiehn, 2004, Bioinform..

Independent components analysis of starch deficient pgm mutants

Joachim Selbig, Matthias Scholz, Yves Gibon, 2004, German Conference on Bioinformatics.

BioMiner: Paving the Way for Personalized Medicine

Joachim Selbig, Kristina Gruden, Michal Or-Guil, 2015, Cancer informatics.

The Golm Metabolome Database: a database for GC-MS based metabolite profiling

Joachim Selbig, Dirk Walther, Jan Hummel, 2007 .

Biological Cluster Evaluation for Gene Function Prediction

Joachim Selbig, Zoran Nikoloski, Sebastian Klie, 2014, J. Comput. Biol..

Improved Heterosis Prediction by Combining Information on DNA- and Metabolic Markers

J. Selbig, L. Willmitzer, Sandra Andorf, 2009, PloS one.

Isolation and characterization of bone marrow-derived progenitor cells from malignant gliomas.

J. Selbig, J. Tonn, S. Eigenbrod, 2012, Anticancer research.

Mesenchymal stem cells and glioma cells form a structural as well as a functional syncytium in vitro

J. Selbig, H. Motaln, R. Riesenberg, 2012, Experimental Neurology.

PhosPhAt: a database of phosphorylation sites in Arabidopsis thaliana and a plant-specific phosphorylation site predictor

Joachim Selbig, Dirk Walther, Wolfram Weckwerth, 2007, Nucleic Acids Res..

Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

Joachim Selbig, Dirk Repsilber, Sabine Kern, 2010, BMC Bioinformatics.

Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins

Joachim Selbig, Dirk Walther, Wolfram Weckwerth, 2009, BMC Bioinformatics.

Transcription factor target prediction using multiple short expression time series from Arabidopsis thaliana

Joachim Selbig, Henning Redestig, Daniel Weicht, 2007, BMC Bioinformatics.

Decision tree supported substructure prediction of metabolites from GC-MS profiles

Joachim Selbig, Dirk Walther, Jan Hummel, 2010, Metabolomics.

More effort - more results: recent advances in integrative 'omics' data analysis.

J. Selbig, D. Rajasundaram, 2016, Current opinion in plant biology.

Parallel analysis of transcript and metabolic profiles: a new approach in systems biology

J. Selbig, A. Fernie, L. Willmitzer, 2003, EMBO reports.

Knowledge Acquisition by Inductive Learning from Examples

Joachim Selbig, J. Selbig, 1986, AII.

Metabolite profiles as a reflection of physiological status -- a methodological validation

Joachim Selbig, Dirk Repsilber, Alisdair R. Fernie, 2006, J. Integr. Bioinform..

Scoring and identifying organism-specific functional patterns and putative phosphorylation sites in protein sequences using mutual information.

Joachim Selbig, Wolfram Weckwerth, J. Selbig, 2003, Biochemical and biophysical research communications.

Evolutionary significance of metabolic network properties

Joachim Selbig, Oliver Ebenhöh, Zoran Nikoloski, 2011, Journal of The Royal Society Interface.

Robustness of metabolic networks: A review of existing definitions

Joachim Selbig, Zoran Nikoloski, Sylvain Blachon, 2011, Biosyst..

Mass-balanced randomization of metabolic networks

Joachim Selbig, Oliver Ebenhöh, Zoran Nikoloski, 2011, Bioinform..

A gentle guide to the analysis of metabolomic data.

Joachim Selbig, Wolfram Weckwerth, Ralf Steuer, 2007, Methods in molecular biology.

HIV-1 Drug Resistance Prediction and Therapy Optimization: A Case Study for the Application of Classification and Clustering Methods

Joachim Selbig, Michal Rosen-Zvi, Ehud Aharoni, 2009, Similarity-Based Clustering.

Analysis of phylogenetic signal in protostomial intron patterns using Mutual Information

Joachim Selbig, Natascha Hill, Alexander Leow, 2012, Theory in Biosciences.

Exercise training alters DNA methylation patterns in genes related to muscle growth and differentiation in mice.

J. Selbig, R. Schwenk, A. Schürmann, 2015, American journal of physiology. Endocrinology and metabolism.

Identification of heterotic metabolite QTL in Arabidopsis thaliana RIL and IL populations.

Joachim Selbig, Thomas Altmann, Lothar Willmitzer, 2009, The Plant journal : for cell and molecular biology.

Data and text mining Computational methods for the design of effective therapies against drug resistant HIV strains

Thomas Lengauer, Joachim Selbig, Niko Beerenwinkel, 2005 .

Learning multiple evolutionary pathways from cross-sectional data

Thomas Lengauer, Joachim Selbig, Niko Beerenwinkel, 2004, J. Comput. Biol..

Measuring Distances Between Variables by Mutual Information

Carsten O. Daub, Joachim Selbig, Jürgen Kurths, 2005 .

Nonlinear Principal Component Analysis: Neural Network Models and Applications

Matthias Scholz, J. Selbig, M. Fraunholz, 2008 .

Geno2pheno: estimating phenotypic drug resistance from HIV-1 genotypes

Thomas Lengauer, Joachim Selbig, Niko Beerenwinkel, 2003, Nucleic Acids Res..

Methods for optimizing antiviral combination therapies

Thomas Lengauer, Joachim Selbig, Niko Beerenwinkel, 2003, ISMB.

The mutual information: Detecting and evaluating dependencies between variables

Carsten O. Daub, Joachim Selbig, Jürgen Kurths, 2002, ECCB.

Integration of Metabolomic and Proteomic Phenotypes

Joachim Selbig, Matthias Scholz, Wolfram Weckwerth, 2008, Molecular & Cellular Proteomics.

Machine Learning for Protein Structure Prediction

Joachim Selbig, J. Selbig, 1994 .

Estimating mutual information using B-spline functions – an improved similarity measure for analysing gene expression data

Carsten O. Daub, Sebastian Kloska, Joachim Selbig, 2004, BMC Bioinformatics.

Finding metabolic pathways in decision forests

Torsten Schaub, Joachim Selbig, A. Flöter, 2005 .

Threshold extraction in metabolite concentration data

Torsten Schaub, Joachim Selbig, André Flöter, 2004, German Conference on Bioinformatics.

Metabolic profiling reveals key metabolic features of renal cell carcinoma

Joachim Selbig, Lothar Willmitzer, Kurt Miller, 2009, Journal of cellular and molecular medicine.

Arevir: A Secure Platform for Designing Personalized Antiretroviral Therapies Against HIV

Joachim Büch, Thomas Lengauer, Joachim Selbig, 2006, DILS.

Bioinformatics approach to predicting HIV drug resistance

Joachim Selbig, Rolf Kaiser, F. Cordes, 2006, Expert review of molecular diagnostics.

Integrated data analysis for genome-wide research.

Joachim Selbig, Dirk Walther, Dirk Repsilber, 2007, EXS.

Principal components analysis.

Joachim Selbig, Stefanie Hartmann, Sebastian Klie, 2013, Methods in molecular biology.

Impact of the Carbon and Nitrogen Supply on Relationships and Connectivity between Metabolism and Biomass in a Broad Panel of Arabidopsis Accessions1[W][OA]

J. Selbig, M. Stitt, Y. Gibon, 2013, Plant Physiology.

Spatiotemporal dynamics of the Calvin cycle: Multistationarity and symmetry breaking instabilities

Joachim Selbig, Jürgen Kurths, Zoran Nikoloski, 2011, Biosyst..

Predicting Arabidopsis Freezing Tolerance and Heterosis in Freezing Tolerance from Metabolite Composition

J. Selbig, D. Hincha, J. Kopka, 2009, Molecular plant.

Corn hybrids display lower metabolite variability and complex metabolite inheritance patterns.

H. Piepho, J. Selbig, L. Willmitzer, 2011, The Plant journal : for cell and molecular biology.

Refined elasticity sampling for Monte Carlo-based identification of stabilizing network patterns

Joachim Selbig, Sergio Grimbs, Dorothee Childs, 2015, Bioinform..

Geno2pheno: Interpreting Genotypic HIV Drug Resistance Tests

Thomas Lengauer, Joachim Selbig, Niko Beerenwinkel, 2001, IEEE Intell. Syst..

Geno2pheno is predictive of short-term virological response

Thomas Lengauer, Joachim Selbig, Niko Beerenwinkel, 2002 .

Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach

Joachim Selbig, Lothar Willmitzer, Zoran Nikoloski, 2009, PloS one.

MetaGeneAlyse: analysis of integrated transcriptional and metabolite data

Carsten O. Daub, Sebastian Kloska, Joachim Selbig, 2003, Bioinform..

A plant resource and experiment management system based on the Golm Plant Database as a basic tool for omics research

Joachim Selbig, Dirk Walther, Alexander Lüdemann, 2008, Plant Methods.

Decision trees as a simple-to-use and reliable tool to identify individuals with impaired glucose metabolism or type 2 diabetes mellitus.

Joachim Selbig, Joachim Spranger, Manuela Hische, 2010, European journal of endocrinology.

9 Phylogeny and evolution of Annelida based on molecular data

J. Selbig, G. Purschke, C. Bleidorn, 2014 .

Mtreemix: a software package for learning and using mixture models of mutagenetic trees

Thomas Lengauer, Joachim Selbig, Niko Beerenwinkel, 2005, Bioinform..

Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers

J. Selbig, L. Willmitzer, R. Meyer, 2009, Theoretical and Applied Genetics.

Non-linear PCA: a missing data approach

Joachim Selbig, Matthias Scholz, Charles L. Guy, 2005, Bioinform..

Species-specific analysis of protein sequence motifs using mutual information

Joachim Selbig, Wolfram Weckwerth, Jan Hummel, 2005, BMC Bioinformatics.

Phenomic prediction of maize hybrids

Joachim Selbig, Thomas Altmann, Christian Edlich-Muth, 2016, Biosyst..

PaVESy: Pathway Visualization and Editing System

Joachim Selbig, Alexander Lüdemann, Daniel Weicht, 2004, Bioinform..

F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks

Joachim Selbig, Alexander Bockmayr, Abdelhalim Larhlimi, 2012, BMC Bioinformatics.

Stoichiometric capacitance reveals the theoretical capabilities of metabolic networks

Joachim Selbig, Zoran Nikoloski, Sergio Grimbs, 2012, Bioinform..

Comparison of metabolite profiles in U87 glioma cells and mesenchymal stem cells

Joachim Selbig, Lothar Willmitzer, Christian Schichor, 2011, Biosyst..

J. Selbig, R. Schwenk, A. Schürmann, 2015 .

Analysis of phylogenetic signal in protostomial intron patterns using Mutual Information

J. Selbig, C. Bleidorn, Natascha Hill, 2013, Theory in Biosciences.

Nonlinear Principal Component Analysis: Neural Network Models and Applications

Matthias Scholz, J. Selbig, M. Fraunholz, 2008 .

Geno2pheno: Genotypic HIV Drug Resistance Tests

Thomas Lengauer, J. Selbig, N. Beerenwinkel, 2001 .

Analysis of protein sheet topologies by graph theoretical methods

Joachim Selbig, Ina Koch, J. Selbig, 1992, Proteins.

A “Crossomics” Study Analysing Variability of Different Components in Peripheral Blood of Healthy Caucasoid Individuals

J. Selbig, K. Gruden, A. Blejec, 2012, PloS one.

Mesenchymal stem cells and glioma cells form a structural as well as a functional syncytium in vitro

J. Selbig, H. Motaln, R. Riesenberg, 2012, Experimental Neurology.

Decision tree-based formation of consensus protein secondary structure prediction

Heinz-Theodor Mevissen, Thomas Lengauer, Joachim Selbig, 1999, Bioinform..

Diversity and complexity of HIV-1 drug resistance: A bioinformatics approach to predicting phenotype from genotype

Thomas Lengauer, J. Selbig, N. Beerenwinkel, 2002, Proceedings of the National Academy of Sciences of the United States of America.

Computational Methods for the Design of Effective Therapies against Drug Resistant Hiv Strains

J. Selbig, N. Beerenwinkel, H. Walter, 2022 .

Computational methods for the design of effective therapies against drug resistant HIV strains

J. Selbig, N. Beerenwinkel, H. Walter, 2005, Bioinform..

Geno2pheno and the Arevir database: tools for determination of clinically relevant cut-offs and prediction of viral load change from HIV-1 genotype.

Thomas Lengauer, J. Selbig, N. Beerenwinkel, 2003 .

Phenomic prediction of maize hybrids

J. Selbig, M. Muraya, T. Altmann, 2016, Biosyst..

Proteome-wide survey of phosphorylation patterns affected by nuclear DNA polymorphisms in Arabidopsis thaliana

J. Selbig, D. Riaño-Pachón, P. Durek, 2010, BMC Genomics.

Starch as a major integrator in the regulation of plant growth

J. Selbig, B. Usadel, M. Stitt, 2009, Proceedings of the National Academy of Sciences.

Modeling Biological Networks by Action Languages via Answer Set Programming

Torsten Schaub, Joachim Selbig, Susanne Grell, 2008, Constraints.

Modelling Biological Networks by Action Languages Via Answer Set Programming

Torsten Schaub, Joachim Selbig, Susanne Grell, 2006, ICLP.

Robin: An Intuitive Wizard Application for R-Based Expression Microarray Quality Assessment and Analysis1[W][OA]

J. Selbig, B. Usadel, M. Stitt, 2010, Plant Physiology.

Validation and functional annotation of expression-based clusters based on gene ontology

Joachim Selbig, Ralf Steuer, Peter Humburg, 2005, BMC Bioinformatics.

Nonlinear Principal Component Analysis: Neural Network Models and Applications

Matthias Scholz, J. Selbig, M. Fraunholz, 2008 .

Metabolite fingerprinting: detecting biological features by independent component analysis

J. Selbig, A. Fernie, Oliver Fiehn, 2004, Bioinform..