Software - Department 3: Computational Biology & Applied Algorithmics


BiLayout BioMyn BiQ Analyzer BiQ Analyzer HT CalSpec DASMI DomainGraph DomainNetworkBuilder EpiExplorer EpiGRAPH EuResist FunSimMat Geno2pheno GOTaxExplorer IRECS MethMarker Mtreemix NetworkAnalyzer NOXclass PSISCOREweb Recco RINalyzer RnBeads ROCR STRuster topGO



BiLayout is a Java plugin for Cytoscape, a software platform for the analysis and visualization of molecular interaction networks. This plugin computes a bipartite network layout for 2 user-selected groups of nodes.


BioMyn is a comprehensive online resource that integrates information related to human genes and proteins from over a dozen external databases. It includes Gene Ontology annotations of human genes and proteins, sequence family classifications, protein domain architectures, metabolic and signaling pathways, protein interactions and protein complexes, and disease associations. 
Reference: Ramirez, F., G. Lawyer, and M. Albrecht, Novel search method for the discovery of functional relationships. Bioinformatics, 2012. 28(2): p. 269-76.

BiQ Analyzer

BiQ Analyzer (http://biq-analyzer.bioinf is a software tool for easy visualization and quality control of DNA methylation data. With more than a thousand downloads so far, BiQ Analyzer has become a standard tool for processing DNA methylation data from bisulfite sequencing. BiQ Analyzer has been selected by ABI to be part of the Applied Biosystems Software CommunityProgram.
Reference: Bock C, et al. (2005) BiQ Analyzer: visualization and quality control for DNA methylation data from bisulfite sequencing. Bioinformatics 21(21):4067-4068.

BiQ Analyzer HT

BiQ Analyzer HT is an enhanced version of BiQ Analyzer that provides extensive support for high-throughput bisulfite sequencing. BiQ Analyzer HT facilitates the processing, quality control and initial analysis of single-basepair resolution DNA methylation data. It was developed for deep bisulfite sequencing of one or more loci using the Roche 454 platform, but it easily extends to other sequencing platforms. BiQ Analyzer HT features a biologist-friendly graphical user interface, a fast alignment algorithm and a variety of ways to visualize DNA methylation data. Nevertheless, users of clonal bisulfite sequencing who do not need these new features are encouraged to keep using the classical BiQ Analyzer.
Reference: Pavlo Lutsik, Lars Feuerbach, Julia Arand, Thomas Lengauer, Jörn Walter and Christoph Bock. BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing. Nucleic Acids Research May 12, 2011 [Epub ahead of print] (Abstract).


CalSpec (Calculate Spectra) is a software module for automated processing of mass spectrometric spectra, calculation of Mass Isotopomer Distribution in protein hydrolysates and estimation of spectral peak quality. Mass spectroscopic measurement of 13C-labeling patterns of biomass constitutents combined with tracer studies with 13C-labeled substrates is a powerful approach for quantification of metabolic fluxes, but it suffers from time consuming and error-prone manual procedure for estimation of labelling patterns. CalSpec is developed to address this problem.
Reference: Talwar P, Wittmann C, Lengauer T, & Heinzle E (2003) Software tool for automated processing of 13C labeling data from mass spectrometric spectra. Biotechniques 35(6):1214-1215.


DASMI uses the DAS protocol to share experimental and predicted molecular interaction data. Our current DASMIweb client is focused on interactions of human proteins and Pfam domains. It also supports scoring the retrieved interactions with confidence values using different quality measures.
Reference: Blankenburg, H., Finn, R.D., Prlić, A., Jenkinson, A.M., Ramírez, F., Emig, D., Schelhorn, S.E., Büch, J., Lengauer, T., Albrecht, M. (2009) DASMI: exchanging, annotating and assessing molecular interaction data. Bioinformatics, 25(10):1321-1328. (Abstract)


DomainGraph is the successor tool of DomainNetworkBuilder and works as Java plugin for Cytoscape, a free open-source software platform for visualization and analysis of biomolecular networks. This plugin decomposes protein networks into domain-domain interactions and generates a new network of interacting domains. It also allows the integration of exon expression data measured using Affymetrix GeneChip microarrays, which supports the analysis of alternative splicing events and the characterization of their effects on protein and domain interaction networks.
Reference: Emig, D., Salomonis, N., Baumbach, J., Lengauer, T., Conklin, BR., Albrecht, M. (2010) AltAnalyze and DomainGraph: analyzing and visualizing exon expression data. Nucleic Acids Res. (Abstract)


DomainNetworkBuilder works as Java plugin for Cytoscape, a free open-source software platform for visualization and analysis of biomolecular networks. This plugin decomposes protein networks into domain-domain interactions and generates a new network of interacting domains.
Reference: Albrecht, M.; Huthmacher, C.; Tosatto, S. C.; Lengauer, T., Decomposing protein networks into domain-domain interactions. Bioinformatics 2005, 21 Suppl 2, ii220-ii221.


The EpiExplorer integrates multiple epigenetic and genetic annotations and make them explorable via an interactive interface. 
Reference: Halachev, K., et al., EpiExplorer: live exploration and global analysis of large epigenomic datasets. Genome Biol, 2012. 13(10): p. R96. 


EpiGRAPH ( enables biologists to analyze genome and epigenome datasets with powerful statistical and machine learning methods. In a typical workflow, the user uploads a set of genomic regions of interest (e.g. experimentally mapped enhancers, hotspots of epigenetic regulation or sites exhibiting disease-specific alterations), and EpiGRAPH searches a large database of (epi-) genomic attributes for significant overlap and correlation with the regions in the input dataset. Furthermore, EpiGRAPH can predict the status of genomic regions that were not included in the input dataset.
Reference: Bock C, Halachev K, Büch J, & Lengauer T (2009) EpiGRAPH: User-friendly software for statistical analysis and prediction of (epi-) genomic data. Genome Biol 10(2):R14


The EuResist project (IST-2004-027173) aims at developing an integrated European system for computer-based clinical management of antiretroviral drug resistance. The resulting EuResist prediction engine is a data-driven system, which predicts the response to an antiretroviral combination drug therapy for HIV infected patients. The system comprises three prediction engines that are located at different sites: Italy (informa S.r.l.), Israel (IBM Israel), and Germany (Max Planck Institute for Informatics). The three services are connected via a SOAP client-server acrchitecture.
Reference: Rosen-Zvi, M.; Altmann, A.; Prosperi, M.; Aharoni, E.; Neuvirth, H.; Sonnerborg, A.; Schülter, E.; Struck, D.; Peres, Y.; Incardona, F.; Kaiser, R.; Zazzi, M.; Lengauer, T., Selecting anti-HIV therapies based on a variety of genomic and clinical factors. Bioinformatics 2008, 24 (13), i399-406.


FunSimMat is a comprehensive functional similarity database that provides several different semantic similarity measures for Gene Ontology terms. It offers various precomputed functional similarity values for proteins contained in UniProtKB and for protein families and domains in Pfam and SMART. The web interface allows users to efficiently perform both semantic similarity searches with GO terms and functional similarity searches with proteins or protein families.
Reference: Schlicker, A., Albrecht, M. (2008) FunSimMat: a comprehensive functional similarity database. Nucleic Acids Research, 36(Database issue):D434-D439. (Abstract)


Geno2pheno is a server that is freely accessible and that supports patient-specific analysis of viral resistance to drugs and ranking of combination drug therapies with respect to their effectiveness. The pathogens covered by the server are HIV, HBV and HCV. A dozen analyses are offered. All analyses are based on the viral genotype. For some analyses additional information on clinical parameters of the patient and/or on patient history can be added. Predictions are based partly on rule sets hand-crafted by medical experts, and partly on models trained on resistance data with statistical learning methods.
Reference: Lengauer, T. and T. Sing, Bioinformatics-assisted anti-HIV therapy. Nat Rev Microbiol, 2006. 4(10): p. 790-7.
Lengauer, T., et al., Bioinformatics prediction of HIV coreceptor usage. Nat Biotechnol, 2007. 25(12): p. 1407-10. 


GOTax is a comparative genomics platform that integrates protein annotation with protein family classification and taxonomy. User-defined sets of proteins, protein families, annotation terms or taxonomic groups can be selected and compared in GOTaxExplorer, allowing for the analysis of distribution of biological processes and molecular activities over different taxonomic groups. Additionally, a functional similarity measure implemented in FSST is available for establishing functional relationships between proteins and protein families. FSST is also used by the functional similarity search in Pfam.
Reference: Schlicker, A., Rahnenführer, J., Albrecht, M., Lengauer, T., Domingues, F.S. (2007) GOTax: investigating biological processes and biochemical activities along the taxonomic tree. Genome Biology, 8(3):R33.1-10. (Abstract)


IRECS can predict multiple conformations for all side chains of a target protein. Side-chain conformations are selected according to the flexibility of the respective side chain. IRECS is also able to mutate single side chains or read in alignments to create a homology model of the target protein on a template backbone.
Reference: Hartmann, C.; Antes, I.; Lengauer, T., Docking and scoring with alternative side-chain conformations. Proteins 2009, 74 (3), 712-26


MethMarker ( facilitates the design of DNA methylation assays for COBRA, bisulfite SNuPE, bisulfite pyrosequencing, MethyLight and MSP. It also implements a systematic workflow for design, optimization and (computational) validation of DNA methylation biomarkers. This workflow starts from a preselected differentially methylated region (DMR) and results in an optimized DNA methylation assay that is ready to be tested in a large-scale clinical trial.
Reference: Schüffler, P., et al., MethMarker: User-friendly design and optimization of gene-specific DNA methylation assays. Genome Biol, 2009. 10(10): p. R105.


Mtreemix is a software package to estimate mixture models of mutagenetic trees from observed cross-sectional data. Mutagenetic tree mixtures are probabilistic models that have been designed to describe evolutionary processes that are characterized by the accumulation of genetic changes. Mtreemix has been applied to model the development of drug resistance-associated mutations in the HIV genome and the accumulation of chromosomal gains and losses in tumor development.
Reference: Beerenwinkel, N.; Rahnenführer, J.; Kaiser, R.; Hoffmann, D.; Selbig, J.; Lengauer, T., Mtreemix: a software package for learning and using mixture models of mutagenetic trees. Bioinformatics 2005, 21 (9), 2106-7.


NetworkAnalyzer works as Java plugin for Cytoscape, a free open-source software platform for visualization and analysis of biomolecular networks. This plugin computes parameters describing the network topology and displays their distributions in diagrams.
Reference: Assenov Y, Ramirez F, Schelhorn SE, Lengauer T, & Albrecht M: Computing topological parameters of biological networks. Bioinformatics 2008 24(2):282-284.


NOXclass is a classifier identifying protein-protein interaction types (biological obligate, biological non-obligate and crystal packing) implemented using a support vector machine (SVM) algorithm.
Reference: Zhu, H.; Domingues, F. S.; Sommer, I.; Lengauer, T., NOXclass: prediction of protein-protein interaction types. BMC Bioinformatics 2006, 7 (1), 27.


PSISCOREweb is a web-based client for the PSI Confidence Scoring System (PSISCORE), an architecture for the distributed confidence scoring of molecular interactions. For further information, please visit:
Reference: Bruno Aranda*, Hagen Blankenburg*, Samuel Kerrien, Fiona S L Brinkman, Arnaud Ceol, Emilie Chautard, Jose M Dana, Javier De Las Rivas, Marine Dumousseau, Eugenia Galeota, Anna Gaulton, Johannes Goll, Robert E W Hancock, Ruth Isserlin, Rafael C Jimenez, Jules Kerssemakers, Jyoti Khadake, David J Lynn, Magali Michaut, Gavin O'Kelly, Keiichiro Ono, Sandra Orchard, Carlos Prieto, Sabry Razick, Olga Rigina, Lukasz Salwinski, Milan Simonovic, Sameer Velankar, Andrew Winter, Guanming Wu, Gary D Bader, Gianni Cesareni, Ian M Donaldson, David Eisenberg, Gerard J Kleywegt, John Overington, Sylvie Ricard-Blum, Mike Tyers, Mario Albrecht & Henning Hermjakob. PSICQUIC and PSISCORE: accessing scoring molecular interactions. Nature Methods, 8, 528–529, 2011.


Recco analyzes alignments of sequences that evolved subject to recombination and mutation. The analysis provides evidence as to whether a dataset contains recombination, which sequence is a recombinant and where the recombination breakpoints are. The analysis is based on explaining one sequence with all other sequences in the alignment using mutation and recombination. A parametric analysis of the parameter alpha, which weights recombination cost against mutation cost, yields additional information as to which sequence might be recombinant.
Reference: Maydt, J.; Lengauer, T., Recco: recombination analysis using cost optimization. Bioinformatics 2006, 22 (9), 1064-71.


RINalyzer is a Java plugin for Cytoscape, a free open-source software platform for visualization and analysis of biomolecular networks. This plugin allows the simultaneous visualization and interactive analysis of residue interaction networks (RINs) together with the corresponding 3D protein structures displayed in UCSF Chimera. It also provides a comprehensive set of topological centrality measures to gain additional insights into the structural and functional role of interacting residues.
Reference: Doncheva, N.T., Klein, K., Domingues, F.S., Albrecht, M. (2011): Analyzing and visualizing residue networks of protein structures. Trends in Biochemical Sciences, 36(4): 179-182.


RnBeads is an R package for the comprehensive analysis of bisulfite sequencing and microarray methylation data. The analysis modules include Loading and Normalization, Quality Control, Filtering, Batch Effects, Methylation Profiling, Differential Methylation and Data Export. Supported input formats include BED files, IDAT files, methylation value and sample annotation tables in text files, as well as GEO series matrix files. The analysis results are presented in comprehensive and interpretable reports in HTML format.


ROC graphs, sensitivity/specificity curves, lift charts, and precision/recall plots are popular examples of trade-off visualizations for specific pairs of performance measures. ROCR is a flexible tool for creating cutoff-parametrized 2D performance curves by freely combining two from over 25 performance measures (new performance measures can be added using a standard interface). Curves from different cross-validation or bootstrapping runs can be averaged by different methods, and standard deviations, standard errors or box plots can be used to visualize the variability across the runs. The parametrization can be visualized by printing cutoff values at the corresponding curve positions, or by coloring the curve according to cutoff. All components of a performance plot can be quickly adjusted using a flexible parameter dispatching mechanism. Despite its flexibility, ROCR is easy to use, with only three commands and reasonable default values for all optional parameters.
Reference: Sing, T., et al., ROCR: visualizing classifier performance in R. Bioinformatics, 2005. 21(20): p. 3940-1.


Alternative structural models, determined by X-ray crystallography or NMR spectroscopy, are frequently available for a given protein. These models can present significant structural dissimilarity. STRuster is a method for clustering alternative structural models corresponding to different structure determination experiments. The structures are classified according to backbone structure similarity.
Reference: Domingues, F. S.; Rahnenfuhrer, J.; Lengauer, T., Conformational analysis of alternative protein structures. Bioinformatics 2007, 23 (23), 3131-8.


topGO (topology-based Gene Ontology scoring) is a software package for calculating the significance of biological terms from gene expression data. It implements various standard and advanced new algorithms for determining the relevance of Gene Ontology groups from microarrays. A specific feature of the advanced algorithms is the exploitation of the hierarchical graph structure of the GO annotation for coping with the large number of GO groups. Often, related biological terms are scored with a similar statistical significance. Dependencies between GO terms can be de-correlated by accounting for the neighborhood of a GO node when calculating its significance. The new algorithms better detect significant GO terms from gene expression data.
Reference: Alexa, A.; Rahnenführer, J.; Lengauer, T., Improved scoring of functional groups from gene expression data by decorrelating GO graph structure. Bioinformatics 2006, 22 (13), 1600-7.