Rasmus Wernersson
Technical University of Denmark
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Publication
Featured researches published by Rasmus Wernersson.
Nucleic Acids Research | 2005
Rasmus Wernersson; Henrik Bjørn Nielsen
OligoWiz 2.0 is a powerful tool for microarray probe design that allows for integration of sequence annotation, such as exon/intron structure, untranslated regions (UTRs), transcription start site, etc. In addition to probe selection according to a series of probe quality parameters, cross-hybridization, Tm, position in transcript, probe folding and low-complexity, the program facilitates automatic placement of probes relative to the sequence annotation. The program also supports automatic placement of multiple probes per transcript. Together these facilities make advanced probe design feasible for scientists inexperienced in computerized information management. Furthermore, we show that probes designed using OligoWiz 2.0 give rise to consistent hybridization results ().
Nucleic Acids Research | 2003
Henrik Bjørn Nielsen; Rasmus Wernersson; Steen Knudsen
Optimal design of oligonucleotides for microarrays involves tedious and laborious work evaluating potential oligonucleotides relative to a series of parameters. The currently available tools for this purpose are limited in their flexibility and do not present the oligonucleotide designer with an overview of these parameters. We present here a flexible tool named OligoWiz for designing oligonucleotides for multiple purposes. OligoWiz presents a set of parameter scores in a graphical interface to facilitate an overview for the user. Additional custom parameter scores can easily be added to the program to extend the default parameters: homology, DeltaTm, low-complexity, position and GATC-only. Furthermore we present an analysis of the limitations in designing oligonucleotide sets that can detect transcripts from multiple organisms. OligoWiz is available at www.cbs.dtu.dk/services/OligoWiz/.
Genome Biology | 2007
Jan Gorodkin; Susanna Cirera; Jakob Hedegaard; Michael J. Gilchrist; Frank Panitz; Claus Jørgensen; Karsten Scheibye-Knudsen; Troels Arvin; Steen Lumholdt; Milena Sawera; Trine Green; Bente Nielsen; Jakob Hull Havgaard; Carina Rosenkilde; Jun-Jun Wang; Heng Li; Ruiqiang Li; Bin Liu; Songnian Hu; Wei Dong; Wei Li; Jun Qing Yu; Jian Wang; Hans-Henrik Stærfeldt; Rasmus Wernersson; Lone Madsen; Bo Thomsen; Henrik Hornshøj; Zhan Bujie; Xuegang Wang
BackgroundKnowledge of the structure of gene expression is essential for mammalian transcriptomics research. We analyzed a collection of more than one million porcine expressed sequence tags (ESTs), of which two-thirds were generated in the Sino-Danish Pig Genome Project and one-third are from public databases. The Sino-Danish ESTs were generated from one normalized and 97 non-normalized cDNA libraries representing 35 different tissues and three developmental stages.ResultsUsing the Distiller package, the ESTs were assembled to roughly 48,000 contigs and 73,000 singletons, of which approximately 25% have a high confidence match to UniProt. Approximately 6,000 new porcine gene clusters were identified. Expression analysis based on the non-normalized libraries resulted in the following findings. The distribution of cluster sizes is scaling invariant. Brain and testes are among the tissues with the greatest number of different expressed genes, whereas tissues with more specialized function, such as developing liver, have fewer expressed genes. There are at least 65 high confidence housekeeping gene candidates and 876 cDNA library-specific gene candidates. We identified differential expression of genes between different tissues, in particular brain/spinal cord, and found patterns of correlation between genes that share expression in pairs of libraries. Finally, there was remarkable agreement in expression between specialized tissues according to Gene Ontology categories.ConclusionThis EST collection, the largest to date in pig, represents an essential resource for annotation, comparative genomics, assembly of the pig genome sequence, and further porcine transcription studies.
Nucleic Acids Research | 2006
Rasmus Wernersson
Virtual Ribosome is a DNA translation tool with two areas of focus. (i) Providing a strong translation tool in its own right, with an integrated ORF finder, full support for the IUPAC degenerate DNA alphabet and all translation tables defined by the NCBI taxonomy group, including the use of alternative start codons. (ii) Integration of sequences feature annotation—in particular, native support for working with files containing intron/exon structure annotation. The software is available for both download and online use at .
Nature Protocols | 2007
Rasmus Wernersson; Agnieszka Sierakowska Juncker; Henrik Bjørn Nielsen
Nucleotide abundance measurements using DNA microarray technology are possible only if appropriate probes complementary to the target nucleotides can be identified. Here we present a protocol for selecting DNA probes for microarrays using the OligoWiz application. OligoWiz is a client–server application that offers a detailed graphical interface and real-time user interaction on the client side, and massive computer power and a large collection of species databases (400, summer 2007) on the server side. Probes are selected according to five weighted scores: cross-hybridization, ΔTm, folding, position and low-complexity; and probes can be placed with respect to sequence annotation using regular expressions. This protocol provides recommendations related to the design and parameter settings, and it also offers a comprehensive walkthrough of the design steps. The protocol requires limited computer skills and can be executed from any Internet-connected computer. The probe selection procedure for a standard microarray design targeting all yeast transcripts can be completed in 1 h.
Nature Methods | 2017
Taibo Li; Rasmus Wernersson; Rasmus Borup Hansen; Heiko Horn; Johnathan Mercer; Grzegorz Slodkowicz; Christopher T. Workman; Olga Rigina; Kristoffer Rapacki; Hans Henrik Stærfeldt; Søren Brunak; Thomas Skøt Jensen; Kasper Lage
Genome-scale human protein–protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein–protein interaction network (InWeb_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism.
Nucleic Acids Research | 2007
Nicholas Paul Gauthier; Malene Erup Larsen; Rasmus Wernersson; Ulrik de Lichtenberg; Lars Juhl Jensen; Søren Brunak; Thomas Skøt Jensen
The past decade has seen the publication of a large number of cell-cycle microarray studies and many more are in the pipeline. However, data from these experiments are not easy to access, combine and evaluate. We have developed a centralized database with an easy-to-use interface, Cyclebase.org, for viewing and downloading these data. The user interface facilitates searches for genes of interest as well as downloads of genome-wide results. Individual genes are displayed with graphs of expression profiles throughout the cell cycle from all available experiments. These expression profiles are normalized to a common timescale to enable inspection of the combined experimental evidence. Furthermore, state-of-the-art computational analyses provide key information on both individual experiments and combined datasets such as whether or not a gene is periodically expressed and, if so, the time of peak expression. Cyclebase is available at http://www.cyclebase.org.
Yeast | 2005
Ulrik de Lichtenberg; Rasmus Wernersson; Thomas Skøt Jensen; Henrik Bjørn Nielsen; Anders Fausbøll; Peer Schmidt; Flemming Bryde Hansen; Steen Knudsen; Søren Brunak
We present an approach combining bioinformatics prediction with experimental microarray validation to identify new cell cycle‐regulated genes in Saccharomyces cerevisiae. We identify in the order of 100 new cell cycle‐regulated genes and show by independent data that these genes in general tend to be more weakly expressed than the genes identified hitherto. Among the genes not previously suggested to be periodically expressed we find genes linked to DNA repair, cell size monitoring and transcriptional control, as well as a number of genes of unknown function. Several of the gene products are believed to be phosphorylated by Cdc28. For many of these new genes, homologues exist in Schizosaccharomyces pombe and Homo sapiens for which the expression also varies with cell cycle progression. Copyright
Nucleic Acids Research | 2010
Nicholas Paul Gauthier; Lars Juhl Jensen; Rasmus Wernersson; Søren Brunak; Thomas Skøt Jensen
Cell division involves a complex series of events orchestrated by thousands of molecules. To study this process, researchers have employed mRNA expression profiling of synchronously growing cell cultures progressing through the cell cycle. These experiments, which have been carried out in several organisms, are not easy to access, combine and evaluate. Complicating factors include variation in interdivision time between experiments and differences in relative duration of each cell-cycle phase across organisms. To address these problems, we created Cyclebase, an online resource of cell-cycle-related experiments. This database provides an easy-to-use web interface that facilitates visualization and download of genome-wide cell-cycle data and analysis results. Data from different experiments are normalized to a common timescale and are complimented with key cell-cycle information and derived analysis results. In Cyclebase version 2.0, we have updated the entire database to reflect changes to genome annotations, included information on cyclin-dependent kinase (CDK) substrates, predicted degradation signals and loss-of-function phenotypes from genome-wide screens. The web interface has been improved and provides a single, gene-centric graph summarizing the available cell-cycle experiments. Finally, key information and links to orthologous and paralogous genes are now included to further facilitate comparison of cell-cycle regulation across species. Cyclebase version 2.0 is available at http://www.cyclebase.org.
Nucleic Acids Research | 2015
Alberto Santos; Rasmus Wernersson; Lars Juhl Jensen
The eukaryotic cell division cycle is a highly regulated process that consists of a complex series of events and involves thousands of proteins. Researchers have studied the regulation of the cell cycle in several organisms, employing a wide range of high-throughput technologies, such as microarray-based mRNA expression profiling and quantitative proteomics. Due to its complexity, the cell cycle can also fail or otherwise change in many different ways if important genes are knocked out, which has been studied in several microscopy-based knockdown screens. The data from these many large-scale efforts are not easily accessed, analyzed and combined due to their inherent heterogeneity. To address this, we have created Cyclebase—available at http://www.cyclebase.org—an online database that allows users to easily visualize and download results from genome-wide cell-cycle-related experiments. In Cyclebase version 3.0, we have updated the content of the database to reflect changes to genome annotation, added new mRNA and protein expression data, and integrated cell-cycle phenotype information from high-content screens and model-organism databases. The new version of Cyclebase also features a new web interface, designed around an overview figure that summarizes all the cell-cycle-related data for a gene.