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Dive into the research topics where Kristoffer Rapacki is active.

Publication


Featured researches published by Kristoffer Rapacki.


Journal of Molecular Biology | 2002

Prediction of human protein function from post-translational modifications and localization features

Lars Juhl Jensen; Ramneek Gupta; Nikolaj Blom; D. Devos; J. Tamames; Can Keşmir; Henrik Nielsen; Hans-Henrik Stærfeldt; Kristoffer Rapacki; Christopher T. Workman; Claus A. F. Andersen; Steen Knudsen; Anders Krogh; Alfonso Valencia; Søren Brunak

We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from a number of functional attributes that are more directly related to the linear sequence of amino acids, and hence easier to predict, than protein structure. These attributes include features associated with post-translational modifications and protein sorting, but also much simpler aspects such as the length, isoelectric point and composition of the polypeptide chain.


Nucleic Acids Research | 2003

NESbase version 1.0: a database of nuclear export signals

Tanja la Cour; Ramneek Gupta; Kristoffer Rapacki; Karen Skriver; Flemming M. Poulsen; Søren Brunak

Protein export from the nucleus is often mediated by a Leucine-rich Nuclear Export Signal (NES). NESbase is a database of experimentally validated Leucine-rich NESs curated from literature. These signals are not annotated in databases such as SWISS-PROT, PIR or PROSITE. Each NESbase entry contains information of whether NES was shown to be necessary and/or sufficient for export, and whether the export was shown to be mediated by the export receptor CRM1. The compiled information was used to make a sequence logo of the Leucine-rich NESs, displaying the conservation of amino acids within a window of 25 residues. Surprisingly, only 36% of the sequences used for the logo fit the widely accepted NES consensus L-x(2,3)-[LIVFM]-x(2,3)-L-x-[LI]. The database is available online at http://www.cbs.dtu.dk/databases/NESbase/.


Nature Communications | 2015

Novel variation and de novo mutation rates in population-wide de novo assembled Danish trios

Søren Besenbacher; Siyang Liu; Jose M. G. Izarzugaza; Jakob Grove; Kirstine Belling; Jette Bork-Jensen; Shujia Huang; Thomas Damm Als; Shengting Li; Rachita Yadav; Arcadio Rubio-García; Francesco Lescai; Ditte Demontis; Junhua Rao; Weijian Ye; Thomas Mailund; Rune M. Friborg; Christian N. S. Pedersen; Ruiqi Xu; Jihua Sun; Hao Liu; Ou Wang; Xiaofang Cheng; David Flores; Emil Rydza; Kristoffer Rapacki; John Damm Sørensen; Piotr Jaroslaw Chmura; David Westergaard; Piotr Dworzynski

Building a population-specific catalogue of single nucleotide variants (SNVs), indels and structural variants (SVs) with frequencies, termed a national pan-genome, is critical for further advancing clinical and public health genetics in large cohorts. Here we report a Danish pan-genome obtained from sequencing 10 trios to high depth (50 × ). We report 536k novel SNVs and 283k novel short indels from mapping approaches and develop a population-wide de novo assembly approach to identify 132k novel indels larger than 10 nucleotides with low false discovery rates. We identify a higher proportion of indels and SVs than previous efforts showing the merits of high coverage and de novo assembly approaches. In addition, we use trio information to identify de novo mutations and use a probabilistic method to provide direct estimates of 1.27e−8 and 1.5e−9 per nucleotide per generation for SNVs and indels, respectively.


Nature Methods | 2017

A scored human protein-protein interaction network to catalyze genomic interpretation

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 | 2010

The EMBRACE web service collection

Steve Pettifer; Jon Ison; Matúš Kalaš; Dave Thorne; Philip McDermott; Inge Jonassen; Ali Liaquat; José María Fernández; Jose Manuel Rodriguez; David G. Pisano; Christophe Blanchet; Mahmut Uludag; Peter Rice; Edita Bartaseviciute; Kristoffer Rapacki; Maarten L. Hekkelman; Olivier Sand; Heinz Stockinger; Andrew B. Clegg; Erik Bongcam-Rudloff; Jean Salzemann; Vincent Breton; Teresa K. Attwood; Graham Cameron; Gert Vriend

The EMBRACE (European Model for Bioinformatics Research and Community Education) web service collection is the culmination of a 5-year project that set out to investigate issues involved in developing and deploying web services for use in the life sciences. The project concluded that in order for web services to achieve widespread adoption, standards must be defined for the choice of web service technology, for semantically annotating both service function and the data exchanged, and a mechanism for discovering services must be provided. Building on this, the project developed: EDAM, an ontology for describing life science web services; BioXSD, a schema for exchanging data between services; and a centralized registry (http://www.embraceregistry.net) that collects together around 1000 services developed by the consortium partners. This article presents the current status of the collection and its associated recommendations and standards definitions.


Nucleic Acids Research | 2016

Tools and data services registry: a community effort to document bioinformatics resources

Jon Ison; Kristoffer Rapacki; Hervé Ménager; Matúš Kalaš; Emil Rydza; Piotr Jaroslaw Chmura; Christian Anthon; Niall Beard; Karel Berka; Dan Bolser; Tim Booth; Anthony Bretaudeau; Jan Brezovsky; Rita Casadio; Gianni Cesareni; Frederik Coppens; Michael Cornell; Gianmauro Cuccuru; Kristian Davidsen; Gianluca Della Vedova; Tunca Doğan; Olivia Doppelt-Azeroual; Laura Emery; Elisabeth Gasteiger; Thomas Gatter; Tatyana Goldberg; Marie Grosjean; Björn Grüning; Manuela Helmer-Citterich; Hans Ienasescu

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand. Here we present a community-driven curation effort, supported by ELIXIR—the European infrastructure for biological information—that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners. As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.


european conference on computational biology | 2010

BioXSD: the common data-exchange format for everyday bioinformatics web services

Matúš Kalaš; Pæl Puntervoll; Alexandre Joseph; Edita Bartaševičiūtė; Armin Töpfer; Prabakar Venkataraman; Steve Pettifer; Jan Christian Bryne; Jon Ison; Christophe Blanchet; Kristoffer Rapacki; Inge Jonassen

Motivation: The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types. Results: BioXSD has been developed as a candidate for standard, canonical exchange format for basic bioinformatics data. BioXSD is represented by a dedicated XML Schema and defines syntax for biological sequences, sequence annotations, alignments and references to resources. We have adapted a set of web services to use BioXSD as the input and output format, and implemented a test-case workflow. This demonstrates that the approach is feasible and provides smooth interoperability. Semantics for BioXSD is provided by annotation with the EDAM ontology. We discuss in a separate section how BioXSD relates to other initiatives and approaches, including existing standards and the Semantic Web. Availability: The BioXSD 1.0 XML Schema is freely available at http://www.bioxsd.org/BioXSD-1.0.xsd under the Creative Commons BY-ND 3.0 license. The http://bioxsd.org web page offers documentation, examples of data in BioXSD format, example workflows with source codes in common programming languages, an updated list of compatible web services and tools and a repository of feature requests from the community. Contact: [email protected]; [email protected]; [email protected]


Nucleic Acids Research | 2006

FeatureMap3D—a tool to map protein features and sequence conservation onto homologous structures in the PDB

Rasmus Wernersson; Kristoffer Rapacki; Hans Henrik Stærfeldt; Peter Wad Sackett; Anne Mølgaard

FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) for structures of homologous proteins. The results are displayed both as an annotated sequence alignment, where the user-provided annotations as well as the sequence conservation between the query and the target sequence are displayed, and also as a publication-quality image of the 3D protein structure with the selected features and sequence conservation enhanced. The results are also returned in a readily parsable text format as well as a PyMol () script file, which allows the user to easily modify the protein structure image to suit a specific purpose. FeatureMap3D can also be used without sequence annotation, to evaluate the quality of the alignment of the input sequences to the most homologous structures in the PDB, through the sequence conservation colored 3D structure visualization tool. FeatureMap3D is available at: .


International Journal on Software Tools for Technology Transfer | 2016

Using registries to integrate bioinformatics tools and services into workbench environments

Hervé Ménager; Matúš Kalaš; Kristoffer Rapacki; Jon Ison

The diversity and complexity of bioinformatics resources presents significant challenges to their localisation, deployment and use, creating a need for reliable systems that address these issues. Meanwhile, users demand increasingly usable and integrated ways to access and analyse data, especially within convenient, integrated “workbench” environments. Resource descriptions are the core element of registry and workbench systems, which are used to both help the user find and comprehend available software tools, data resources, and Web Services, and to localise, execute and combine them. The descriptions are, however, hard and expensive to create and maintain, because they are volatile and require an exhaustive knowledge of the described resource, its applicability to biological research, and the data model and syntax used to describe it. We present here the Workbench Integration Enabler, a software component that will ease the integration of bioinformatics resources in a workbench environment, using their description provided by the existing ELIXIR Tools and Data Services Registry.


Frontiers in Microbiology | 2017

FurIOS: a web-based tool for identification of Vibrionaceae species using the fur gene

Henrique Machado; João Gonçalo Rocha Cardoso; Sonia Giubergia; Kristoffer Rapacki; Lone Gram

Gene based methods for identification of species from the Vibrionaceae family have been developed during the last decades to address the limitations of the commonly used 16S rRNA gene phylogeny. Recently, we found that the ferric-uptake regulator gene (fur) can be used as a single identification marker providing species discrimination, consistent with multi-locus sequencing analyses and whole genome phylogenies. To allow for broader and easy use of this marker, we have developed an online prediction service that allows the identification of Vibrionaceae species based on their fur-sequence. The input is a DNA sequence that can be uploaded on the web service; the output is a table containing the strain identifier, e-value, and percentage of identity for each of the matches with rows colored in green for hits with high probability of being the same species. The service is available on the web at: http://www.cbs.dtu.dk/services/furIOS-1.0/. The fur-sequences can be derived either from genome sequences or from PCR-amplification of the genomic region encoding the fur gene. We have used 191 strains identified as Vibrionaceae based on 16S rRNA gene sequence to test the PCR method and the web service on a large dataset. We were able to classify 171 of 191 strains at the species level and 20 strains remained unclassified. Furthermore, the fur phylogenetics and subsequent in silico DNA-DNA hybridization demonstrated that two strains (ATCC 33789 and ZS-139) previously identified as Vibrio splendidus are more closely related to V. tasmaniensis and V. cyclitrophicus, respectively. FurIOS is an easy-to-use online service that allows the identification of bacteria from the Vibrionaceae family at the species level using the fur gene as a single marker. Its simplistic design and straightforward pipeline makes it suitable for any research environment, from academia to industry.

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Jon Ison

Technical University of Denmark

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Søren Brunak

University of Copenhagen

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Steve Pettifer

University of Manchester

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Rodrigo Lopez

European Bioinformatics Institute

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