Biomedical subjects

Hilmar Lapp

Publications and source records attributed to Hilmar Lapp.

7 recordsLinked to original sources

PubMed2006

Open source tools and toolkits for bioinformatics: significance, and where are we?

This review summarizes important work in open-source bioinformatics software that has occurred over the past couple of years. The survey is intended to illustrate how programs and toolkits whose source code has been developed or released under an Open Source license have changed informatics-heavy areas of life science research. Rather than creating a comprehensive list of all tools developed over the last 2-3 years, we use a few selected projects encompassing toolkit libraries, analysis tools, data analysis environments and interoperability standards to show how freely available and modifiable open-source software can serve as the foundation for building important applications, analysis workflows and resources.

Algorithms↗

PubMed2006

Data and animal management software for large-scale phenotype screening.

The mouse N-ethyl-N-nitrosourea (ENU) mutagenesis program at the Genomics Institute of the Novartis Research Foundation (GNF) uses MouseTRACS to analyze phenotype screens and manage animal husbandry. MouseTRACS is a Web-based laboratory informatics system that electronically records and organizes mouse colony operations, prints cage cards, tracks inventory, manages requests, and reports Institutional Animal Care and Use Committee (IACUC) protocol usage. For efficient phenotype screening, MouseTRACS identifies mutants, visualizes data, and maps mutations. It displays and integrates phenotype and genotype data using likelihood odds ratio (LOD) plots of genetic linkage between genotype and phenotype. More detailed mapping intervals show individual single nucleotide polymorphism (SNP) markers in the context of phenotype. In addition, dynamically generated pedigree diagrams and inventory reports linked to screening results summarize the inheritance pattern and the degree of penetrance. MouseTRACS displays screening data in tables and uses standard charts such as box plots, histograms, scatter plots, and customized charts looking at clustered mice or cross pedigree comparisons. In summary, MouseTRACS enables the efficient screening, analysis, and management of thousands of animals to find mutant mice and identify novel gene functions. MouseTRACS is available under an open source license at http://www.mousetracs.sourceforge.net.

Animals↗

PubMed2005

Large-scale profiling of Rab GTPase trafficking networks: the membrome.

Rab GTPases and SNARE fusion proteins direct cargo trafficking through the exocytic and endocytic pathways of eukaryotic cells. We have used steady state mRNA expression profiling and computational hierarchical clustering methods to generate a global overview of the distribution of Rabs, SNAREs, and coat machinery components, as well as their respective adaptors, effectors, and regulators in 79 human and 61 mouse nonredundant tissues. We now show that this systems biology approach can be used to define building blocks for membrane trafficking based on Rab-centric protein activity hubs. These Rab-regulated hubs provide a framework for an integrated coding system, the membrome network, which regulates the dynamics of the specialized membrane architecture of differentiated cells. The distribution of Rab-regulated hubs illustrates a number of facets that guides the overall organization of subcellular compartments of cells and tissues through the activity of dynamic protein interaction networks. An interactive website for exploring datasets comprising components of the Rab-regulated hubs that define the membrome of different cell and organ systems in both human and mouse is available at http://www.membrome.org/.

Animals↗

PubMed2005

Exploring trafficking GTPase function by mRNA expression profiling: use of the SymAtlas web-application and the Membrome datasets.

Despite complete sequencing of the human and mouse genomes, functional annotation of novel gene function still remains a major challenge in mammalian biology. Emerging strategies to help elucidate unknown gene function include the analysis of tissue-specific patterns of mRNA expression. A recent study investigated the steady-state mRNA expression profiling of the vast majority of protein-encoding human and mouse genes across a panel of 79 human and 61 mouse nonredundant tissues. The microarray data from this study constitutes the Genomics Institute of Novartis Foundation (GNF) Human and Mouse Gene Atlases and is publicly available for exploration through the SymAtlas web-application (http://symatlas.gnf.org/). We have recently reported the use of these data and hierarchical clustering algorithms to generate a global overview of the distribution of Rabs, SNAREs, and coat machinery components, as well as their respective adaptors, effectors, and regulators. This systems biology approach led us to propose Rab-centric protein activity hubs as a framework for an integrated coding system, the membrome network, which orchestrates the dynamics of specialized membrane architecture of differentiated cells. Here, we describe the use of the SymAtlas web-application and the Membrome datasets to help explore trafficking GTPase function. The human and mouse membrome datasets are available through the Membrome homepage (http://www.membrome.org/) and correspond to subsets of the SymAtlas content restricted to known membrane trafficking components. Considering the fragmentary nature of the current reductionist approaches in elucidating trafficking component functions, the membrome datasets provide a more focused systems biology perspective that not only complements our current understanding of transport in complex tissues but also provides an integrated perspective of Rab activity in controlling membrane architecture.

Animals↗

PubMed2004

A gene atlas of the mouse and human protein-encoding transcriptomes.

The tissue-specific pattern of mRNA expression can indicate important clues about gene function. High-density oligonucleotide arrays offer the opportunity to examine patterns of gene expression on a genome scale. Toward this end, we have designed custom arrays that interrogate the expression of the vast majority of protein-encoding human and mouse genes and have used them to profile a panel of 79 human and 61 mouse tissues. The resulting data set provides the expression patterns for thousands of predicted genes, as well as known and poorly characterized genes, from mice and humans. We have explored this data set for global trends in gene expression, evaluated commonly used lines of evidence in gene prediction methodologies, and investigated patterns indicative of chromosomal organization of transcription. We describe hundreds of regions of correlated transcription and show that some are subject to both tissue and parental allele-specific expression, suggesting a link between spatial expression and imprinting.

Animals↗

PubMed2004

Applications of a rat multiple tissue gene expression data set.

With the sequencing and assembly of the rat genome comes the difficult task of assigning functions to genes. Tissue localization of gene expression gives some information about the potential role of a gene in physiology. Various examples of the utility of multiple tissue gene expression data sets are illustrated here. First, we highlight their use in finding genes that might play an important role in a particular tissue on the basis of exclusive expression in that tissue or coexpression with a gene or genes with known function. Second, we show how this data might be used to explain known phenotypic differences between strains. Third, we show how expression patterns of genes in a genomic interval might identify candidate genes in quantitative trait loci (QTL) mapping studies. Lastly, we show how multiple tissue and species data can help researchers prioritize follow up studies to microarray experiments. All of these applications of multiple tissue gene expression data sets will play a role in functionally annotating the rat genome.

Animals↗

PubMed2002

The Bioperl toolkit: Perl modules for the life sciences.

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.

Algorithms↗