108 results match your criteria: "Stockholm Bioinformatics Center[Affiliation]"
Mol Syst Biol
January 2025
Research group "Structural Interactomics", Leibniz Forschungsinstitut für Molekulare Pharmakologie, Robert-Rössle-Str. 10, 13125, Berlin, Germany.
Cross-linking mass spectrometry (XL-MS) allows characterizing protein-protein interactions (PPIs) in native biological systems by capturing cross-links between different proteins (inter-links). However, inter-link identification remains challenging, requiring dedicated data filtering schemes and thorough error control. Here, we benchmark existing data filtering schemes combined with error rate estimation strategies utilizing concatenated target-decoy protein sequence databases.
View Article and Find Full Text PDFInt J Mol Sci
January 2021
Department of Clinical Science and Education, Karolinska Institutet, and Sachs' Children and Youth Hospital, Södersjukhuset, SE-118 83 Stockholm, Sweden.
DNA methylation changes may predispose becoming IgE-sensitized to allergens. We analyzed whether DNA methylation in peripheral blood mononuclear cells (PBMC) is associated with IgE sensitization at 5 years of age (5Y). DNA methylation was measured in 288 PBMC samples from 74 mother/child pairs from the birth cohort ALADDIN (Assessment of Lifestyle and Allergic Disease During INfancy) using the HumanMethylation450BeadChip (Illumina).
View Article and Find Full Text PDFBrief Bioinform
July 2020
Science for Life Laboratory, Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Box 1031, 17121 Solna, Sweden.
The vast amount of experimental data from recent advances in the field of high-throughput biology begs for integration into more complex data structures such as genome-wide functional association networks. Such networks have been used for elucidation of the interplay of intra-cellular molecules to make advances ranging from the basic science understanding of evolutionary processes to the more translational field of precision medicine. The allure of the field has resulted in rapid growth of the number of available network resources, each with unique attributes exploitable to answer different biological questions.
View Article and Find Full Text PDFClin Cancer Res
June 2019
Department of Oncology-Pathology, Cancer Center Karolinska (CCK), Karolinska Institutet, Stockholm, Sweden.
Purpose: Fibroblasts expressing the orphan chemokine CXCL14 have been previously shown to associate with poor breast cancer prognosis and promote cancer growth. This study explores the mechanism underlying the poor survival associations of stromal CXCL14.
Experimental Design: Tumor cell epithelial-to-mesenchymal transition (EMT), invasion, and metastasis were studied in and models together with fibroblasts overexpressing CXCL14.
Bioinformatics
March 2019
Department of Biochemistry and Biophysics, Stockholm Bioinformatics Center, Science for Life Laboratory, Stockholm University, Stockholm, Sweden.
Motivation: Inference of gene regulatory networks (GRNs) from perturbation data can give detailed mechanistic insights of a biological system. Many inference methods exist, but the resulting GRN is generally sensitive to the choice of method-specific parameters. Even though the inferred GRN is optimal given the parameters, many links may be wrong or missing if the data is not informative.
View Article and Find Full Text PDFMethods Appl Fluoresc
April 2018
Science for Life Laboratory, Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Box 1031, 17121 Solna, Sweden.
Huge amounts of data are generated in genome wide experiments, designed to investigate diseases with complex genetic causes. Follow up of all potential leads produced by such experiments is currently cost prohibitive and time consuming. Gene prioritization tools alleviate these constraints by directing further experimental efforts towards the most promising candidate targets.
View Article and Find Full Text PDFSci Rep
January 2018
Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Box 1031, SE-171 21, Solna, Sweden.
Massive amounts of metagenomics data are currently being produced, and in all such projects a sizeable fraction of the resulting data shows no or little homology to known sequences. It is likely that this fraction contains novel viruses, but identification is challenging since they frequently lack homology to known viruses. To overcome this problem, we developed a strategy to detect ORFan protein families in shotgun metagenomics data, using similarity-based clustering and a set of filters to extract bona fide protein families.
View Article and Find Full Text PDFNucleic Acids Res
January 2018
Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Box 1031, 17121 Solna, Sweden.
This release of the FunCoup database (http://funcoup.sbc.su.
View Article and Find Full Text PDFNat Commun
November 2017
Division of Translational Medicine and Chemical Biology, Science for Life Laboratory, Department of Molecular Biochemistry and Biophysics, Karolinska Institutet, Stockholm, 171 65, Sweden.
The NUDIX enzymes are involved in cellular metabolism and homeostasis, as well as mRNA processing. Although highly conserved throughout all organisms, their biological roles and biochemical redundancies remain largely unclear. To address this, we globally resolve their individual properties and inter-relationships.
View Article and Find Full Text PDFBioinformatics
January 2018
Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
The Quest for Orthologs (QfO) is an open collaboration framework for experts in comparative phylogenomics and related research areas who have an interest in highly accurate orthology predictions and their applications. We here report highlights and discussion points from the QfO meeting 2015 held in Barcelona. Achievements in recent years have established a basis to support developments for improved orthology prediction and to explore new approaches.
View Article and Find Full Text PDFPLoS Comput Biol
June 2017
Bioinformatics Unit, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.
Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present large-scale simulation modeling (LASSIM), which is a novel mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE) for gene regulatory networks (GRNs). LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady state and dynamic response expression datasets.
View Article and Find Full Text PDFMol Biosyst
June 2017
Stockholm Bioinformatics Center, Science for Life Laboratory, Sweden.
A key question in network inference, that has not been properly answered, is what accuracy can be expected for a given biological dataset and inference method. We present GeneSPIDER - a Matlab package for tuning, running, and evaluating inference algorithms that allows independent control of network and data properties to enable data-driven benchmarking. GeneSPIDER is uniquely suited to address this question by first extracting salient properties from the experimental data and then generating simulated networks and data that closely match these properties.
View Article and Find Full Text PDFSci Rep
April 2017
Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Box 1031, 17121 Solna, Sweden.
In order to maximize the use of results from high-throughput experimental studies, e.g. GWAS, for identification and diagnostics of new disease-associated genes, it is important to have properly analyzed and benchmarked gene prioritization tools.
View Article and Find Full Text PDFNucleic Acids Res
January 2017
Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Box 1031, 17121 Solna, Sweden.
HieranoiDB (http://hieranoiDB.sbc.su.
View Article and Find Full Text PDFNucleic Acids Res
January 2017
Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Box 1031, 17121 Solna, Sweden.
Analyzing gene expression patterns is a mainstay to gain functional insights of biological systems. A plethora of tools exist to identify significant enrichment of pathways for a set of differentially expressed genes. Most tools analyze gene overlap between gene sets and are therefore severely hampered by the current state of pathway annotation, yet at the same time they run a high risk of false assignments.
View Article and Find Full Text PDFBioinformatics
September 2016
European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg 69117, Germany.
Motivation: Over the last decades, vast numbers of sequences were deposited in public databases. Bioinformatics tools allow homology and consequently functional inference for these sequences. New profile-based homology search tools have been introduced, allowing reliable detection of remote homologs, but have not been systematically benchmarked.
View Article and Find Full Text PDFBioinformatics
August 2016
Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Solna SE-17121, Sweden.
Unlabelled: We present TreeDom, a web tool for graphically analysing the evolutionary history of domains in multi-domain proteins. Individual domains on the same protein chain may have distinct evolutionary histories, which is important to grasp in order to understand protein function. For instance, it may be important to know whether a domain was duplicated recently or long ago, to know the origin of inserted domains, or to know the pattern of domain loss within a protein family.
View Article and Find Full Text PDFNucleic Acids Res
July 2016
Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Box 1031, 17121 Solna, Sweden
Pathway annotation of gene lists is often used to functionally analyse biomolecular data such as gene expression in order to establish which processes are activated in a given experiment. Databases such as KEGG or GO represent collections of how genes are known to be organized in pathways, and the challenge is to compare a given gene list with the known pathways such that all true relations are identified. Most tools apply statistical measures to the gene overlap between the gene list and pathway.
View Article and Find Full Text PDFNat Methods
May 2016
Department of Genetics, Evolution, and Environment, University College London, London, UK.
Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking.
View Article and Find Full Text PDFBioinformatics
May 2016
Stockholm Bioinformatics Center, SciLifeLab, Swedish E-Science Research Center, Stockholm University, Stockholm, SE, 10691, Sweden and.
Unlabelled: : Accurate topology prediction of transmembrane β-barrels is still an open question. Here, we present BOCTOPUS2, an improved topology prediction method for transmembrane β-barrels that can also identify the barrel domain, predict the topology and identify the orientation of residues in transmembrane β-strands. The major novelty of BOCTOPUS2 is the use of the dyad-repeat pattern of lipid and pore facing residues observed in transmembrane β-barrels.
View Article and Find Full Text PDFNucleic Acids Res
January 2015
Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden.
The InParanoid database (http://InParanoid.sbc.su.
View Article and Find Full Text PDFBioinformatics
November 2014
Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, Swedish eScience Research Center, Stockholm, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain, EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London
Unlabelled: Given the rapid increase of species with a sequenced genome, the need to identify orthologous genes between them has emerged as a central bioinformatics task. Many different methods exist for orthology detection, which makes it difficult to decide which one to choose for a particular application. Here, we review the latest developments and issues in the orthology field, and summarize the most recent results reported at the third 'Quest for Orthologs' meeting.
View Article and Find Full Text PDFNucleic Acids Res
January 2014
HHMI Janelia Farm Research Campus, 19700 Helix Drive, Ashburn, VA 20147 USA, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK, MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3QX, UK, Institute of Biotechnology and Department of Biological and Environmental Sciences, University of Helsinki, PO Box 56 (Viikinkaari 5), 00014 Helsinki, Finland and Stockholm Bioinformatics Center, Swedish eScience Research Center, Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, PO Box 1031, SE-17121 Solna, Sweden.
Pfam, available via servers in the UK (http://pfam.sanger.ac.
View Article and Find Full Text PDFPLoS One
August 2014
KTH Royal Institute of Technology, Stockholm Bioinformatics Center, School of Computer Science and Communication, Stockholm, Sweden.
Genetic markers, defined as variable regions of DNA, can be utilized for distinguishing individuals or populations. As long as markers are independent, it is easy to combine the information they provide. For nonrecombinant sequences like mtDNA, choosing the right set of markers for forensic applications can be difficult and requires careful consideration.
View Article and Find Full Text PDFJ Comput Biol
May 2013
Stockholm Bioinformatics Center, Science for Life Laboratory, Stockholm, Sweden.
Gene regulatory network inference (that is, determination of the regulatory interactions between a set of genes) provides mechanistic insights of central importance to research in systems biology. Most contemporary network inference methods rely on a sparsity/regularization coefficient, which we call ζ (zeta), to determine the degree of sparsity of the network estimates, that is, the total number of links between the nodes. However, they offer little or no advice on how to select this sparsity coefficient, in particular, for biological data with few samples.
View Article and Find Full Text PDF