Institution
Katholieke Universiteit Leuven
Education•Leuven, Belgium•
About: Katholieke Universiteit Leuven is a education organization based out in Leuven, Belgium. It is known for research contribution in the topics: Population & Transplantation. The organization has 61109 authors who have published 176584 publications receiving 6210872 citations.
Topics: Population, Transplantation, CMOS, European union, Stars
Papers published on a yearly basis
Papers
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TL;DR: A bioinformatics approach, together with a freely accessible, interactive and flexible software termed Endeavour, to prioritize candidate genes underlying biological processes or diseases, based on their similarity to known genes involved in these phenomena, offers an alternative integrative method for gene discovery.
Abstract: The identification of genes involved in health and disease remains a challenge. We describe a bioinformatics approach, together with a freely accessible, interactive and flexible software termed Endeavour, to prioritize candidate genes underlying biological processes or diseases, based on their similarity to known genes involved in these phenomena. Unlike previous approaches, ours generates distinct prioritizations for multiple heterogeneous data sources, which are then integrated, or fused, into a global ranking using order statistics. In addition, it offers the flexibility of including additional data sources. Validation of our approach revealed it was able to efficiently prioritize 627 genes in disease data sets and 76 genes in biological pathway sets, identify candidates of 16 mono- or polygenic diseases, and discover regulatory genes of myeloid differentiation. Furthermore, the approach identified a novel gene involved in craniofacial development from a 2-Mb chromosomal region, deleted in some patients with DiGeorge-like birth defects. The approach described here offers an alternative integrative method for gene discovery.
803 citations
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University of Paris1, Medical University of Vienna2, Leiden University3, Paris Descartes University4, University of Leeds5, Ruhr University Bochum6, Charité7, University College Dublin8, Halmstad University9, Katholieke Universiteit Leuven10, University of Münster11, University of Glasgow12, Charles University in Prague13, University of Erlangen-Nuremberg14, Ghent University Hospital15
TL;DR: These recommendations provide stakeholders with an updated consensus on the pharmacological treatment of PsA and strategies to reach optimal outcomes in PsA, based on a combination of evidence and expert opinion.
Abstract: Background Since the publication of the European League Against Rheumatism recommendations for the pharmacological treatment of psoriatic arthritis (PsA) in 2012, new evidence and new therapeutic agents have emerged. The objective was to update these recommendations. Methods A systematic literature review was performed regarding pharmacological treatment in PsA. Subsequently, recommendations were formulated based on the evidence and the expert opinion of the 34 Task Force members. Levels of evidence and strengths of recommendations were allocated. Results The updated recommendations comprise 5 overarching principles and 10 recommendations, covering pharmacological therapies for PsA from non-steroidal anti-inflammatory drugs (NSAIDs), to conventional synthetic (csDMARD) and biological (bDMARD) disease-modifying antirheumatic drugs, whatever their mode of action, taking articular and extra-articular manifestations of PsA into account, but focusing on musculoskeletal involvement. The overarching principles address the need for shared decision-making and treatment objectives. The recommendations address csDMARDs as an initial therapy after failure of NSAIDs and local therapy for active disease, followed, if necessary, by a bDMARD or a targeted synthetic DMARD (tsDMARD). The first bDMARD would usually be a tumour necrosis factor (TNF) inhibitor. bDMARDs targeting interleukin (IL)12/23 (ustekinumab) or IL-17 pathways (secukinumab) may be used in patients for whom TNF inhibitors are inappropriate and a tsDMARD such as a phosphodiesterase 4-inhibitor (apremilast) if bDMARDs are inappropriate. If the first bDMARD strategy fails, any other bDMARD or tsDMARD may be used. Conclusions These recommendations provide stakeholders with an updated consensus on the pharmacological treatment of PsA and strategies to reach optimal outcomes in PsA, based on a combination of evidence and expert opinion.
802 citations
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Charité1, Lawrence Berkeley National Laboratory2, Wellcome Trust Sanger Institute3, Cambridge University Hospitals NHS Foundation Trust4, Paul Sabatier University5, University of Manchester6, Newcastle University7, University of Toronto8, Leeds Teaching Hospitals NHS Trust9, Katholieke Universiteit Leuven10, University of Kiel11, University College London12, Drexel University13, University of Cambridge14, Geisinger Medical Center15, St George’s University Hospitals NHS Foundation Trust16, University of Bristol17, Columbia University18, University of Oxford19, Radboud University Nijmegen20, University of Oregon21, Aberystwyth University22, Max Planck Society23
TL;DR: The updated HPO database is described, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO, allowing integration of existing datasets and interoperability with multiple biomedical resources.
Abstract: The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.
801 citations
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TL;DR: This classification is the first to categorize the articles of the VRP literature to this level of detail and is based on an adapted version of an existing comprehensive taxonomy.
800 citations
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TL;DR: This paper considers logistics network design in a reverse logistics context with a generic facility location model and uses this model to analyze the impact of product return flows on logistics networks.
Abstract: Efficient implementation of closed-loop supply chains requires setting up appropriate logistics structures for the arising flows of used and recovered products. In this paper we consider logistics network design in a reverse logistics context. We present a generic facility location model and discuss differences with traditional logistics settings. Moreover, we use our model to analyze the impact of product return flows on logistics networks. We show that the influence of product recovery is very much context dependent. While product recovery may efficiently be integrated in existing logistics structures in many cases, other examples require a more comprehensive approach redesigning a company's logistics network in an integral way
800 citations
Authors
Showing all 61602 results
Name | H-index | Papers | Citations |
---|---|---|---|
Eugene Braunwald | 230 | 1711 | 264576 |
Joseph L. Goldstein | 207 | 556 | 149527 |
Rakesh K. Jain | 200 | 1467 | 177727 |
Stefan Schreiber | 178 | 1233 | 138528 |
Masayuki Yamamoto | 171 | 1576 | 123028 |
Jun Wang | 166 | 1093 | 141621 |
David R. Jacobs | 165 | 1262 | 113892 |
Klaus Müllen | 164 | 2125 | 140748 |
Peter Carmeliet | 164 | 844 | 122918 |
Hua Zhang | 163 | 1503 | 116769 |
William J. Sandborn | 162 | 1317 | 108564 |
Elliott M. Antman | 161 | 716 | 179462 |
Tobin J. Marks | 159 | 1621 | 111604 |
Ian A. Wilson | 158 | 971 | 98221 |
Johan Auwerx | 158 | 653 | 95779 |