Bioinformatics Software

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Bioinformatics group currently offers 20 software applications. For details and download click on the title.
PINTA (2011) PINTA is a gene prioritization tool that identifies the most promising candidates within a region when only sparse information about the phenotype is available by replacing this knowledge by experimental data on differential gene expression between affected and healthy individuals. Considering the problem from the perspective of a gene/protein network, it assesses the relevance of a candidate gene by considering the level of differential expression in its network neighborhood under the assumption that strong candidates tend to be surrounded by differentially expressed neighbors.	ModuleMiner (2008) ModuleMiner is a tool to detect similar cis-regulatory modules (CRMs) in a set of co-regulated or co-expressed genes. The algorithm takes as input a set of genes thought to have similar regulatory elements in their upstream regions (under the form of Ensembl gene IDs), and detects these similar CRMs. Apart from the CRMs near the given genes, the algorithm also creates a model of these similar CRMs and uses this model to find new target genes in the whole genome. The algorithm is available as an online tool that emails the results when ready. Both a web interface and a standalone version are available.
aBandApart (2007) Biomedical literature provides a rich but unstructured source of associations between chromosomal regions and biomedical concepts. By mining MEDLINE abstracts, we annotate the human genome at the level of cytogenetic bands. Our method creates a set of chromosomal aberration maps that associate cytogenetic bands to biomedical concepts from a variety of controlled vocabularies, including disease, dysmorphology, anatomy, development, and Gene Ontology branches. The association between a band (e.g., 4p16.3) and a concept (e.g., microcephaly) is assessed by the statistical overrepresentation of this concept in the abstracts relating to this band. Our method is validated using existing genome annotation resources and known chromosomal aberration maps, and is further illustrated through a case study on heart disease. Our chromosomal aberration maps provide diagnostics support to clinical geneticists, aid cytogeneticists to interpret and report cytogenetic findings, and support researchers interested in human gene function	Bioconductor package "CALIB" (2007) “CALIB” is a new Bioconductor package which is for normalization of two-color microarray data. This approach is based on the measurements of external controls and estimates an absolute target level for each gene and condition pair, as opposed to working with log-ratios as a relative measure of expression. Moreover, this method makes no assumptions regarding the distribution of gene expression divergence.
CGHGate (2007) As Microarray-CGH is introduced into the clinical practice for the identification of submicroscopic genomic aberrations, tools to handle related data become essential for clinical geneticists. CGHGate is a web application that combines a constitutional cytogenetics database and tools for search, visualisation, genome annotation and data mining. CGHGate is a database tool for storage, reporting and mining Array CGH Case reports in a clinical setting. It features a constitutional cytogenetics patient database, allows genome annotation, data mining, literature search, it identifies candidate genes for patient phenotypes in deletion and duplication regions, it generates clinical reports, ...	LOOP (2007) LOOP is a tool to analyze arrayCGH loop designs in which three patients are placed in a loop design, which is advantageous over the classical dye-swap approach. ArrayCGH is a microarray technology that can be used to detect aberrations in the ploidy of DNA segments in the genome of patients with congenital anomalies.
ReMoDiscovery (2006) ReMoDiscovery is an intuitive algorithm to correlate regulatory programs with regulators and corresponding motifs to a set of co-expressed genes. It exploits in a concurrent way three independent data sources: ChIP-chip data, motif information and gene expression profiles.	SynTReN (2006) A Generator of synthetic gene expression data for design and analysis of structure learning algorithms. The software is provided as an executable jar file.
biomaRt (2005) The package provides and API in R to query BioMart databases such as Ensembl, a software system which produces and maintains automatic annotation on metazoan genomes.	BlockAligner (2005) The BlockAligner uses a local ungapped alignment strategy based on dynamic programming to mutually compare conserved promoter regions (i.e. blocks) represented by their respective motif models.
BlockSampler (2005) The BlockSampler is used to find conserved blocks in the upstream region of sets of orthologous genes.	Endeavour (2005) ENDEAVOUR is a software application for the computational prioritisation of `test genes', based on a set of `training genes'. The ranking of a test gene is based on its similarity with the training genes, using different information sources such as MEDLINE abstracts and LocusLink textual descriptions, Gene Ontology annotation, BIND protein interactions, BIND protein interactions, Transcription factor binding sites (TFBS) and other.
M@cBETH (2005) The M@CBETH (a MicroArray Classification BEnchmarking Tool on a Host server) web service offers the microarray community a simple tool for making optimal two-class predictions. M@CBETH aims at finding the best prediction among different classification methods by using randomizations of the benchmarking dataset.	RMAGEML (2004) The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments. AVAILABILITY: http://www.bioconductor.org. Open Source.
TOUCAN2 (2004) TOUCAN is a workbench for regulatory sequence analysis on metazoan genomes: comparative genomics, detection of significant transcription factor binding sites, and detection of cis-regulatory modules (combinations of binding sites) in sets of coexpressed/coregulated genes. It is a platform independent, standalone Java application that is tightly linked with Ensembl, and was built using the BioJava package. SOAP web services are used to remotely access multiple algorithms for comparative genomics, motif detection, and module detection.	TXTGate (2004) TXTGate is a literature index database and is part of an experimental platform to evaluate (combinations of) information extraction and indexing from a variety of biological annotation databases. It is designed towards the summarization and analysis of groups of genes based on text.
INCLUSive (2003) INCLUSive is a suit of algorithms and tools for the analysis of gene expression data and the discovery of cis-regulatory sequence elements. The tools allow for normalization, filtering and clustering of microarray data, functional scoring of gene clusters, sequence retrieval and detection of known and unknown regulatory elements. All tools are available via different web pages and as web services.	Adaptive Quality-based Clustering (AQBC) (2002) AQBC is a heuristic, iterative two-step algorithm to cluster gene expression data. First, we find in the high-dimensional representation of the data a sphere where the ‘density’ of expression profiles is locally maximal. In a second step, we derive an optimal radius of the cluster (adaptive approach) so that only the significantly coexpressed genes are included in the cluster. By inferring the radius from the data itself, the biologist is freed from finding an optimal value for this radius by trial-and-error.
Maran (2002) Microarray Analysis using ANOVA	MotifSampler (2001) MotifSampler tries to find over-represented motifs in the upstream region of a set of co-regulated genes. This motif finding algorithm uses an extended version of Gibbs sampling to find the position probability matrix that represents the motif. The main extension are the use of higher-order background models to improve the robustness of the motif finding and a probabilistic framework to estimate the number of motif occurrences in a sequences. Both a web interface and a standalone version are available.