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See detailPancreatic Fat Is Associated With Metabolic Syndrome and Visceral Fat but Not Beta-Cell Function or Body Mass Index in Pediatric Obesity
Staaf, Johan; Labmayr, Viktor; Paulmichl, Katharina et al

in Pancreas (2017)

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See detailMINERVA—a platform for visualization and curation of molecular interaction networks
Gawron, Piotr; Ostaszewski, Marek UL; Satagopam, Venkata UL et al

in NPJ Systems Biology and Applications (2016)

Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable ... [more ▼]

Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable construction of focused and high-quality molecular interaction networks. Novel tools for curation and exploration of such networks are needed, in order to foster the development of a systems biology environment. In particular, solutions for visualization, annotation and data cross-linking will facilitate usage of network-encoded knowledge in biomedical research. To this end we developed the MINERVA (Molecular Interaction NEtwoRks VisuAlization) platform, a standalone webservice supporting curation, annotation and visualization of molecular interaction networks in Systems Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated content annotation and verification for improved quality control. The end users can explore and interact with hosted networks, and provide direct feedback to content curators. MINERVA enables mapping drug targets or overlaying experimental data on the visualized networks. Extensive export functions enable downloading areas of the visualized networks as SBGN-compliant models for efficient reuse of hosted networks. The software is available under Affero GPL 3.0 as a Virtual Machine snapshot, Debian package and Docker instance at http://r3lab.uni.lu/web/minerva-website/. We believe that MINERVA is an important contribution to systems biology community, as its architecture enables set-up of locally or globally accessible SBGN-oriented repositories of molecular interaction networks. Its functionalities allow overlay of multiple information layers, facilitating exploration of content and interpretation of data. Moreover, annotation and verification workflows of MINERVA improve the efficiency of curation of networks, allowing life-science researchers to better engage in development and use of biomedical knowledge repositories. [less ▲]

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See detailIntegration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases.
Satagopam, Venkata UL; Gu, Wei UL; Eifes, Serge et al

in Big data (2016), 4(2), 97-108

Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process ... [more ▼]

Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services-tranSMART, a Galaxy Server, and a MINERVA platform-are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data. [less ▲]

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See detailReconMap: An interactive visualisation of human metabolism
Noronha, Alberto UL; Danielsdóttir, Anna Dröfn; Jóhannsson, Freyr et al

in Bioinformatics (2016)

A genome-scale reconstruction of human metabolism, Recon 2, is available but no interface exists to interactively visualise its content integrated with omics data and simulation results. We manually drew ... [more ▼]

A genome-scale reconstruction of human metabolism, Recon 2, is available but no interface exists to interactively visualise its content integrated with omics data and simulation results. We manually drew a comprehensive map, ReconMap 2.0, that is consistent with the content of Recon 2. We present it within a web interface that allows content query, visualization of custom datasets and submission of feedback to manual curators. ReconMap can be accessed via http://vmh.uni.lu, with network export in a Systems Biology Graphical Notation compliant format. A Constraint-Based Reconstruction and Analysis (COBRA) Toolbox extension to interact with ReconMap is available via https://github.com/opencobra/cobratoolbox. [less ▲]

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See detailMaking sense of big data in health research: Towards an EU action plan.
Auffray, Charles; Balling, Rudi UL; Barroso, Ines et al

in Genome medicine (2016), 8(1), 71

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation ... [more ▼]

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans. [less ▲]

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See detailBioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders
Hofmann-Apitius, Matin; Ball, Gordon; Gebel, Stephan UL et al

in International Journal of Molecular Sciences (2015), 16(12), 29179-29206

Since the decoding of the Human Genome, techniques from bioinformatics, statistics, and machine learning have been instrumental in uncovering patterns in increasing amounts and types of different data ... [more ▼]

Since the decoding of the Human Genome, techniques from bioinformatics, statistics, and machine learning have been instrumental in uncovering patterns in increasing amounts and types of different data produced by technical profiling technologies applied to clinical samples, animal models, and cellular systems. Yet, progress on unravelling biological mechanisms, causally driving diseases, has been limited, in part due to the inherent complexity of biological systems. Whereas we have witnessed progress in the areas of cancer, cardiovascular and metabolic diseases, the area of neurodegenerative diseases has proved to be very challenging. This is in part because the aetiology of neurodegenerative diseases such as Alzheimer´s disease or Parkinson´s disease is unknown, rendering it very difficult to discern early causal events. Here we describe a panel of bioinformatics and modeling approaches that have recently been developed to identify candidate mechanisms of neurodegenerative diseases based on publicly available data and knowledge. We identify two complementary strategies-data mining techniques using genetic data as a starting point to be further enriched using other data-types, or alternatively to encode prior knowledge about disease mechanisms in a model based framework supporting reasoning and enrichment analysis. Our review illustrates the challenges entailed in integrating heterogeneous, multiscale and multimodal information in the area of neurology in general and neurodegeneration in particular. We conclude, that progress would be accelerated by increasing efforts on performing systematic collection of multiple data-types over time from each individual suffering from neurodegenerative disease. The work presented here has been driven by project AETIONOMY; a project funded in the course of the Innovative Medicines Initiative (IMI); which is a public-private partnership of the European Federation of Pharmaceutical Industry Associations (EFPIA) and the European Commission (EC). [less ▲]

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See detailShared alterations in the human brain transcriptome during adult aging and in Parkinson's disease
Glaab, Enrico UL; Schneider, Reinhard UL

Poster (2015, June 15)

Aging-related biomolecular changes in the human brain are thought to be associated with an increased risk for neurodegenerative diseases. In particular, aging and Parkinson’s disease (PD) share various ... [more ▼]

Aging-related biomolecular changes in the human brain are thought to be associated with an increased risk for neurodegenerative diseases. In particular, aging and Parkinson’s disease (PD) share various molecular hallmarks, including a gradual decline in dopamine synthesis and increased levels of deleted mitochondrial DNA. While some specific mechanistic links between brain aging and PD have been proposed and investigated previously, systematic analyses of shared molecular alterations at a genome-scale level are required to obtain a better understanding of the affected cellular processes and their interrelations. We present a joint analysis of high-throughput brain transcriptomics data from PD patients and unaffected individuals from different adult age groups using a statistical meta-analysis and a recently published pathway and network analysis approach. Our analyses provide statistical evidence for specific functional associations between molecular network changes in PD and aging, identify new significant joint pathway deregulations and suggest mechanistic explanations for the observed age-dependence of PD risk. [less ▲]

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See detailComparative pathway and network analysis of brain transcriptome changes during adult aging and in Parkinson's disease
Glaab, Enrico UL; Schneider, Reinhard UL

in Neurobiology of Disease (2015), 74

Aging is considered as one of the main factors promoting the risk for Parkinson's disease (PD) and common mechanisms of dopamine neuron degeneration in aging and PD have been proposed in recent years ... [more ▼]

Aging is considered as one of the main factors promoting the risk for Parkinson's disease (PD) and common mechanisms of dopamine neuron degeneration in aging and PD have been proposed in recent years. Here, we use a statistical meta-analysis of human brain transcriptomics data to investigate potential mechanistic relationships between adult brain aging and PD pathogenesis at the pathway and network level. The analyses identify statistically significant shared pathway and network alterations in aging and PD and an enrichment in PD-associated sequence variants from genome-wide association studies among the jointly deregulated genes. We find robust discriminative patterns for groups of functionally related genes with potential applications as combined risk biomarkers to detect aging- and PD-linked oxidative stress, e.g. a consistent over-expression of metallothioneins matching with findings in previous independent studies. Interestingly, analyzing the regulatory network and mouse knockout expression data for the transcription factor NR4A2, previously associated with rare mutations in PD and here found as the most significantly under-expressed gene in PD among the jointly altered genes, suggests that aging-related NR4A2 expression changes may increase PD risk by producing downstream effects similar to disease-linked mutations and to expression changes observed in sporadic PD. Overall, the analyses suggest mechanistic explanations for the age-dependence of PD risk, reveal significant and robust shared process alterations in aging and PD, and examine their potential for biomarker applications in pre-symptomatic risk assessment or early-stage diagnosis. [less ▲]

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See detailRepExplore: Addressing technical replicate variance in proteomics and metabolomics data analysis
Glaab, Enrico UL; Schneider, Reinhard UL

in Bioinformatics (2015), 31(13), 2235

High-throughput omics datasets often contain technical replicates, included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using ... [more ▼]

High-throughput omics datasets often contain technical replicates, included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using robust averages may help to reduce the influence of noise on downstream data analysis, the information on the variance across the replicate measurements is lost in the averaging process and therefore typically disregarded in subsequent statistical analyses. We introduce RepExplore, a web-service dedicated to exploit the information captured in the technical replicate variance to provide more reliable and informative differential expression and abundance statistics for omics datasets. The software builds on previously published statistical methods, which have been applied successfully to biomedical omics data but are difficult to use without prior experience in programming or scripting. RepExplore facilitates the analysis by providing a fully automated data processing and interactive ran- king tables, whisker plot, heat map and principal component analysis visualizations to interpret omics data and derived statistics. [less ▲]

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See detailBiomarkers of postoperative delirium and cognitive dysfunction
Androsova, Ganna UL; Krause, Roland UL; Winterer, Georg et al

in Frontiers in Aging Neuroscience (2015), 7(112),

Elderly surgical patients frequently experience postoperative delirium (POD) and the subsequent development of postoperative cognitive dysfunction (POCD). Clinical features include deterioration in ... [more ▼]

Elderly surgical patients frequently experience postoperative delirium (POD) and the subsequent development of postoperative cognitive dysfunction (POCD). Clinical features include deterioration in cognition, disturbance in attention and reduced awareness of the environment and result in higher morbidity, mortality and greater utilization of social financial assistance. The aging Western societies can expect an increase in the incidence of POD and POCD. The underlying pathophysiological mechanisms have been studied on the molecular level albeit with unsatisfying small research efforts given their societal burden. Here, we review the known physiological and immunological changes and genetic risk factors, identify candidates for further studies and integrate the information into a draft network for exploration on a systems level. The pathogenesis of these postoperative cognitive impairments is multifactorial; application of integrated systems biology has the potential to reconstruct the underlying network of molecular mechanisms and help in the identification of prognostic and diagnostic biomarkers. [less ▲]

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See detailA Novel Multi-objectivisation Approach for Optimising the Protein Inverse Folding Problem
Nielsen, Sune Steinbjorn UL; Danoy, Grégoire UL; Jurkowski, Wiktor et al

in Applications of Evolutionary Computation: 18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings (2015)

In biology, the subject of protein structure prediction is of continued interest, not only to chart the molecular map of the living cell, but also to design proteins of new functions. The Inverse Folding ... [more ▼]

In biology, the subject of protein structure prediction is of continued interest, not only to chart the molecular map of the living cell, but also to design proteins of new functions. The Inverse Folding Problem (IFP) is in itself an important research problem, but also at the heart of most rational protein design approaches. In brief, the IFP consists in finding sequences that will fold into a given structure, rather than determining the structure for a given sequence - as in conventional structure prediction. In this work we present a Multi Objective Genetic Algorithm (MOGA) using the diversity-as-objective (DAO) variant of multi-objectivisation, to optimise secondary structure similarity and sequence diversity at the same time, hence pushing the search farther into wide-spread areas of the sequence solution-space. To control the high diversity generated by the DAO approach, we add a novel Quantile Constraint (QC) mechanism to discard an adjustable worst quantile of the population. This DAO-QC approach can efficiently emphasise exploitation rather than exploration to a selectable degree achieving a trade-off producing both better and more diverse sequences than the standard Genetic Algorithm (GA). To validate the final results, a subset of the best sequences was selected for tertiary structure prediction. The super-positioning with the original protein structure demonstrated that meaningful sequences are generated underlining the potential of this work. [less ▲]

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See detailsiRNA screen identifies QPCT as a druggable target for Huntington's disease.
Jimenez-Sanchez, Maria; Lam, Wun; Hannus, Michael et al

in Nature chemical biology (2015), 11(5), 347354

Huntington's disease (HD) is a currently incurable neurodegenerative condition caused by an abnormally expanded polyglutamine tract in huntingtin (HTT). We identified new modifiers of mutant HTT toxicity ... [more ▼]

Huntington's disease (HD) is a currently incurable neurodegenerative condition caused by an abnormally expanded polyglutamine tract in huntingtin (HTT). We identified new modifiers of mutant HTT toxicity by performing a large-scale 'druggable genome' siRNA screen in human cultured cells, followed by hit validation in Drosophila. We focused on glutaminyl cyclase (QPCT), which had one of the strongest effects on mutant HTT-induced toxicity and aggregation in the cell-based siRNA screen and also rescued these phenotypes in Drosophila. We found that QPCT inhibition induced the levels of the molecular chaperone alphaB-crystallin and reduced the aggregation of diverse proteins. We generated new QPCT inhibitors using in silico methods followed by in vitro screening, which rescued the HD-related phenotypes in cell, Drosophila and zebrafish HD models. Our data reveal a new HD druggable target affecting mutant HTT aggregation and provide proof of principle for a discovery pipeline from druggable genome screen to drug development. [less ▲]

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See detailSystems genomics evaluation of the SH-SY5Y neuroblastoma cell line as a model for Parkinson’s disease
Krishna, Abhimanyu UL; Biryukov, Maria UL; Trefois, Christophe UL et al

in BMC Genomics (2014), 15(1154),

Background: The human neuroblastoma cell line, SH-SY5Y, is a commonly used cell line in studies related to neurotoxicity, oxidative stress, and neurodegenerative diseases. Although this cell line is often ... [more ▼]

Background: The human neuroblastoma cell line, SH-SY5Y, is a commonly used cell line in studies related to neurotoxicity, oxidative stress, and neurodegenerative diseases. Although this cell line is often used as a cellular model for Parkinson’s disease, the relevance of this cellular model in the context of Parkinson’s disease (PD) and other neurodegenerative diseases has not yet been systematically evaluated. Results: We have used a systems genomics approach to characterize the SH-SY5Y cell line using whole-genome sequencing to determine the genetic content of the cell line and used transcriptomics and proteomics data to determine molecular correlations. Further, we integrated genomic variants using a network analysis approach to evaluate the suitability of the SH-SY5Y cell line for perturbation experiments in the context of neurodegenerative diseases, including PD. Conclusions: The systems genomics approach showed consistency across different biological levels (DNA, RNA and protein concentrations). Most of the genes belonging to the major Parkinson’s disease pathways and modules were intact in the SH-SY5Y genome. Specifically, each analysed gene related to PD has at least one intact copy in SH-SY5Y. The disease-specific network analysis approach ranked the genetic integrity of SH-SY5Y as higher for PD than for Alzheimer’s disease but lower than for Huntington’s disease and Amyotrophic Lateral Sclerosis for loss of function perturbation experiments. [less ▲]

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See detailReproducible Research Results R3
Trefois, Christophe UL; Jarosz, Yohan UL; Gu, Wei UL et al

Poster (2014, December)

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See detailBioTextQuest+: a knowledge integration platform for literature mining and concept discovery
Papanikolaou, Nikolas; Pavlopoulos, Georgios A.; Pafilis, Evangelos et al

in Bioinformatics (2014)

The iterative process of finding relevant information in biomedical literature and performing bioinformatics analyses might result in an endless loop for an inexperienced user, considering the exponential ... [more ▼]

The iterative process of finding relevant information in biomedical literature and performing bioinformatics analyses might result in an endless loop for an inexperienced user, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed® and related biological databases. Herein, we describe BioTextQuest+, a web-based interactive knowledge exploration platform with significant advances to its predecessor (BioTextQuest), aiming to bridge processes such as bioentity recognition, functional annotation, document clustering and data integration towards literature mining and concept discovery. BioTextQuest+ enables PubMed and OMIM querying, retrieval of abstracts related to a targeted request and optimal detection of genes, proteins, molecular functions, pathways and biological processes within the retrieved documents. The front-end interface facilitates the browsing of document clustering per subject, the analysis of term co-occurrence, the generation of tag clouds containing highly represented terms per cluster and at-a-glance popup windows with information about relevant genes and proteins. Moreover, to support experimental research, BioTextQuest+ addresses integration of its primary functionality with biological repositories and software tools able to deliver further bioinformatics services. The Google-like interface extends beyond simple use by offering a range of advanced parameterization for expert users. We demonstrate the functionality of BioTextQuest+ through several exemplary research scenarios including author disambiguation, functional term enrichment, knowledge acquisition and concept discovery linking major human diseases, such as obesity and ageing. [less ▲]

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See detailPredictProtein--an open resource for online prediction of protein structural and functional features
Yachdav, Guy; Kloppman; Kajan et al

in Nucleic Acid Research (2014), 42(8),

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence ... [more ▼]

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. [less ▲]

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See detailAddressing Technical Replicate Variance in Omics Data Analysis
Glaab, Enrico UL; Schneider, Reinhard UL

Poster (2014)

High-throughput omics datasets often contain technical replicates, included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using ... [more ▼]

High-throughput omics datasets often contain technical replicates, included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using robust averages may help to reduce the influence of noise on downstream data analysis, the information on the variance across the replicate measurements is lost in the averaging process and therefore typically disregarded in subsequent statistical analyses. We introduce RepExplore, a web-service dedicated to exploit the information captured in the technical replicate variance to provide more reliable and informative differential expression and abundance statistics for omics datasets. The software builds on previously published statistical methods, which have been applied successfully to biomedical omics data but are difficult to use without prior experience in programming or scripting. RepExplore facilitates the analysis by providing a fully automated data processing and interactive ranking tables, whisker plot, heat map and principal component analysis visualizations to interpret omics data and derived statistics. The web-based software is freely available at http://www.repexplore.tk. [less ▲]

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See detailCOMPARTMENTS: unification and visualization of protein subcellular localization evidence.
Binder, Janos X. UL; Pletscher-Frankild, Sune; Tsafou, Kalliopi et al

in Database : the journal of biological databases and curation (2014), 2014

Information on protein subcellular localization is important to understand the cellular functions of proteins. Currently, such information is manually curated from the literature, obtained from high ... [more ▼]

Information on protein subcellular localization is important to understand the cellular functions of proteins. Currently, such information is manually curated from the literature, obtained from high-throughput microscopy-based screens and predicted from primary sequence. To get a comprehensive view of the localization of a protein, it is thus necessary to consult multiple databases and prediction tools. To address this, we present the COMPARTMENTS resource, which integrates all sources listed above as well as the results of automatic text mining. The resource is automatically kept up to date with source databases, and all localization evidence is mapped onto common protein identifiers and Gene Ontology terms. We further assign confidence scores to the localization evidence to facilitate comparison of different types and sources of evidence. To further improve the comparability, we assign confidence scores based on the type and source of the localization evidence. Finally, we visualize the unified localization evidence for a protein on a schematic cell to provide a simple overview. Database URL: http://compartments.jensenlab.org. [less ▲]

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