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  • 1
    Online Resource
    Online Resource
    Evaluation of crowdsourced mortality prediction models as a framework for assessing artificial intelligence in medicine
    Oxford University Press (OUP) ; 2023
    In:  Journal of the American Medical Informatics Association ( 2023-08-18)
    Details
    In: Journal of the American Medical Informatics Association, Oxford University Press (OUP), ( 2023-08-18)
    Abstract: Applications of machine learning in healthcare are of high interest and have the potential to improve patient care. Yet, the real-world accuracy of these models in clinical practice and on different patient subpopulations remains unclear. To address these important questions, we hosted a community challenge to evaluate methods that predict healthcare outcomes. We focused on the prediction of all-cause mortality as the community challenge question. Materials and methods Using a Model-to-Data framework, 345 registered participants, coalescing into 25 independent teams, spread over 3 continents and 10 countries, generated 25 accurate models all trained on a dataset of over 1.1 million patients and evaluated on patients prospectively collected over a 1-year observation of a large health system. Results The top performing team achieved a final area under the receiver operator curve of 0.947 (95% CI, 0.942-0.951) and an area under the precision-recall curve of 0.487 (95% CI, 0.458-0.499) on a prospectively collected patient cohort. Discussion Post hoc analysis after the challenge revealed that models differ in accuracy on subpopulations, delineated by race or gender, even when they are trained on the same data. Conclusion This is the largest community challenge focused on the evaluation of state-of-the-art machine learning methods in a healthcare system performed to date, revealing both opportunities and pitfalls of clinical AI.
    Type of Medium: Online Resource
    ISSN: 1067-5027 , 1527-974X
    URL: Article
    DOI: 10.1093/jamia/ocad159
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 2018371-9
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  • 2
    Online Resource
    Online Resource
    MO081THE INFLUENCE OF VITAMIN D3 ON PODOCYTE DIFFERENTIATION IN SITU AND IN VITRO
    Oxford University Press (OUP) ; 2021
    In:  Nephrology Dialysis Transplantation Vol. 36, No. Supplement_1 ( 2021-05-29)
    Details
    In: Nephrology Dialysis Transplantation, Oxford University Press (OUP), Vol. 36, No. Supplement_1 ( 2021-05-29)
    Abstract: Dedifferentiation of podocytes affects their complex 3 D morphology and is the main initiator for the development of chronic kidney disease (CKD). Unfortunately, there is no causal therapy for CKD until today. Thus, inadequate and late treatment lead to end-stage renal disease which subsequently makes renal replacement therapy inevitable. To address this, new treatment options are of high significance for CKD patients. Recently, vitamin D3 (VitD) became a promising candidate, but it is controversially discussed. In the present study, we investigated the influence of VitD on podocyte differentiation and the related pathways in situ and in vitro. Method We combined a podocyte dedifferentiation model (GlomAssay) with an automated imaging procedure (Aquifer Imaging Machine). We analyzed cultured glomeruli from transgenic mice expressing cyan-fluorescent protein (CFP) under the control of the nephrin promoter which were treated with VitD and its` analogue (calcipotriol). In this model, the decreasing CFP fluorescence is as a read out for podocyte (de)differentiation. Additionally, VitD-, calcipotriol- and VitD receptor (VDR) inhibitor (PS121912)-treated glomeruli were investigated by RNA-Seq and LC-MS/MS to reveal the molecular effects of VitD on podocyte differentiation. Furthermore, we treated cultured murine podocytes with VitD, calcipotriol and PS121912 to elucidate the morphological and molecular changes by immunofluorescence staining, RT-qPCR and Western blot. Results VitD- and calcipotriol-treated glomeruli showed a significantly higher intensity of CFP fluorescence after 9 days, indicating higher level of nephrin compared to the control. This was verified by RT-qPCR and Western blot for nephrin and CFP. Additionally, we found an upregulation of VDR in VitD- and calcipotriol-treated glomeruli compared to controls. By transcriptomic and proteomic analysis, we identified molecular patterns that are specific for the different treated groups. Thus, we observed differential gene expression in VitD- and Wnt-signaling pathway as well as regulated genes that are essential for the actin cytoskeleton, focal adhesion formation and the slit membrane. Beside this, cultured podocytes showed a significant upregulation of the slit membrane protein nephrin, VDR and CYP24A1 by VitD. This is accompanied by an altered morphology of the podocytes due to a reorganization of the actin cytoskeleton. Conclusion Our results show that VitD influences podocyte differentiation in situ and in vitro by the regulation of specific signaling pathways.
    Type of Medium: Online Resource
    ISSN: 0931-0509 , 1460-2385
    URL: Article
    DOI: 10.1093/ndt/gfab078.0017
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 1465709-0
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  • 3
    Online Resource
    Online Resource
    Cohort Profile Update: The Study of Health in Pomerania (SHIP)
    Oxford University Press (OUP) ; 2022
    In:  International Journal of Epidemiology Vol. 51, No. 6 ( 2022-12-13), p. e372-e383
    Details
    In: International Journal of Epidemiology, Oxford University Press (OUP), Vol. 51, No. 6 ( 2022-12-13), p. e372-e383
    Type of Medium: Online Resource
    ISSN: 0300-5771 , 1464-3685
    URL: Article
    DOI: 10.1093/ije/dyac034
    RVK:
    XF 4100
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 1494592-7
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  • 4
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    Online Resource
    Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research
    Oxford University Press (OUP) ; 2021
    In:  Briefings in Bioinformatics Vol. 22, No. 2 ( 2021-03-22), p. 642-663
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 22, No. 2 ( 2021-03-22), p. 642-663
    Abstract: SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbaa232
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2036055-1
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  • 5
    Online Resource
    Online Resource
    Selecting signature oligonucleotides to identify organisms using DNA arrays
    Oxford University Press (OUP) ; 2002
    In:  Bioinformatics Vol. 18, No. 10 ( 2002-10-01), p. 1340-1349
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 18, No. 10 ( 2002-10-01), p. 1340-1349
    Abstract: Motivation: DNA arrays are a very useful tool to quickly identify biological agents present in some given sample, e.g. to identify viruses causing disease, for quality control in the food industry, or to determine bacteria contaminating drinking water. The selection of specific oligos to attach to the array surface is a relevant problem in the experiment design process. Given a set S of genomic sequences (the target sequences), the task is to find at least one oligonucleotide, called probe, for each sequence in S. This probe will be attached to the array surface, and must be chosen in a way that it will not hybridize to any other sequence but the intended target. Furthermore, all probes on the array must hybridize to their intended targets under the same reaction conditions, most importantly at the temperature T at which the experiment is conducted. Results: We present an efficient algorithm for the probe design problem. Melting temperatures are calculated for all possible probe–target interactions using an extended nearest-neighbor model, allowing for both non-Watson–Crick base-pairing and unpaired bases within a duplex. To compute temperatures efficiently, a combination of suffix trees and dynamic programming based alignment algorithms is introduced. Additional filtering steps during preprocessing increase the speed of the computation. The practicability of the algorithms is demonstrated by two case studies: The identification of HIV-1 subtypes, and of 28S rDNA sequences from ≥400 organisms. Availability: The software is available on request. Contact: kaderali@zpr.uni-koeln.de * To whom correspondence should be addressed.
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    URL: Article
    DOI: 10.1093/bioinformatics/18.10.1340
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2002
    detail.hit.zdb_id: 1468345-3
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  • 6
    Online Resource
    Online Resource
    Retrospective survival analysis of 237 consecutive patients with multiple pulmonary metastases from advanced renal cell carcinoma exclusively resected by a 1318-nm laser
    Oxford University Press (OUP) ; 2015
    In:  Interactive CardioVascular and Thoracic Surgery Vol. 21, No. 2 ( 2015-08), p. 211-217
    Details
    In: Interactive CardioVascular and Thoracic Surgery, Oxford University Press (OUP), Vol. 21, No. 2 ( 2015-08), p. 211-217
    Type of Medium: Online Resource
    ISSN: 1569-9293 , 1569-9285
    URL: Article
    DOI: 10.1093/icvts/ivv120
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2015
    detail.hit.zdb_id: 2096257-5
    detail.hit.zdb_id: 3167862-2
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  • 7
    Online Resource
    Online Resource
    Reconstructing signaling pathways from RNAi data using probabilistic Boolean threshold networks
    Oxford University Press (OUP) ; 2009
    In:  Bioinformatics Vol. 25, No. 17 ( 2009-09-01), p. 2229-2235
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 25, No. 17 ( 2009-09-01), p. 2229-2235
    Abstract: Motivation: The reconstruction of signaling pathways from gene knockdown data is a novel research field enabled by developments in RNAi screening technology. However, while RNA interference is a powerful technique to identify genes related to a phenotype of interest, their placement in the corresponding pathways remains a challenging problem. Difficulties are aggravated if not all pathway components can be observed after each knockdown, but readouts are only available for a small subset. We are then facing the problem of reconstructing a network from incomplete data. Results: We infer pathway topologies from gene knockdown data using Bayesian networks with probabilistic Boolean threshold functions. To deal with the problem of underdetermined network parameters, we employ a Bayesian learning approach, in which we can integrate arbitrary prior information on the network under consideration. Missing observations are integrated out. We compute the exact likelihood function for smaller networks, and use an approximation to evaluate the likelihood for larger networks. The posterior distribution is evaluated using mode hopping Markov chain Monte Carlo. Distributions over topologies and parameters can then be used to design additional experiments. We evaluate our approach on a small artificial dataset, and present inference results on RNAi data from the Jak/Stat pathway in a human hepatoma cell line. Availability: Software is available on request. Contact:  lars.kaderali@bioquant.uni-heidelberg.de Supplementary information:  Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    URL: Article
    DOI: 10.1093/bioinformatics/btp375
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2009
    detail.hit.zdb_id: 1468345-3
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  • 8
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    Online Resource
    CASPAR: a hierarchical bayesian approach to predict survival times in cancer from gene expression data
    Oxford University Press (OUP) ; 2006
    In:  Bioinformatics Vol. 22, No. 12 ( 2006-06-15), p. 1495-1502
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 22, No. 12 ( 2006-06-15), p. 1495-1502
    Abstract: Motivation: DNA microarrays allow the simultaneous measurement of thousands of gene expression levels in any given patient sample. Gene expression data have been shown to correlate with survival in several cancers, however, analysis of the data is difficult, since typically at most a few hundred patients are available, resulting in severely underdetermined regression or classification models. Several approaches exist to classify patients in different risk classes, however, relatively little has been done with respect to the prediction of actual survival times. We introduce CASPAR, a novel method to predict true survival times for the individual patient based on microarray measurements. CASPAR is based on a multivariate Cox regression model that is embedded in a Bayesian framework. A hierarchical prior distribution on the regression parameters is specifically designed to deal with high dimensionality (large number of genes) and low sample size settings, that are typical for microarray measurements. This enables CASPAR to automatically select small, most informative subsets of genes for prediction. Results: Validity of the method is demonstrated on two publicly available datasets on diffuse large B-cell lymphoma (DLBCL) and on adenocarcinoma of the lung. The method successfully identifies long and short survivors, with high sensitivity and specificity. We compare our method with two alternative methods from the literature, demonstrating superior results of our approach. In addition, we show that CASPAR can further refine predictions made using clinical scoring systems such as the International Prognostic Index (IPI) for DLBCL and clinical staging for lung cancer, thus providing an additional tool for the clinician. An analysis of the genes identified confirms previously published results, and furthermore, new candidate genes correlated with survival are identified. Availability: The software is available upon request from the authors. Contact:  kaderali@zpr.uni-koeln.de Supplementary information:  
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    URL: Article
    DOI: 10.1093/bioinformatics/btl103
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2006
    detail.hit.zdb_id: 1468345-3
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  • 9
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    Online Resource
    RNAither, an automated pipeline for the statistical analysis of high-throughput RNAi screens
    Oxford University Press (OUP) ; 2009
    In:  Bioinformatics Vol. 25, No. 5 ( 2009-03-01), p. 678-679
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 25, No. 5 ( 2009-03-01), p. 678-679
    Abstract: Summary: We present RNAither, a package for the free statistical environment R which performs an analysis of high-throughput RNA interference (RNAi) knock-down experiments, generating lists of relevant genes and pathways out of raw experimental data. The library provides a quality assessment of the signal intensities, as well as a broad range of options for data normalization, different statistical tests for the identification of significant siRNAs, and a significance analysis of the biological processes involving corresponding genes. The results of the analysis are presented as a set of HTML pages. Additionally, all values and plots are available as either text files or pdf and png files. Availability:  http://bioconductor.org/ Contact:  RNAither@gmx.de
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    URL: Article
    DOI: 10.1093/bioinformatics/btp014
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2009
    detail.hit.zdb_id: 1468345-3
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  • 10
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    Online Resource
    Detecting host factors involved in virus infection by observing the clustering of infected cells in siRNA screening images
    Oxford University Press (OUP) ; 2010
    In:  Bioinformatics Vol. 26, No. 18 ( 2010-09-15), p. i653-i658
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 26, No. 18 ( 2010-09-15), p. i653-i658
    Abstract: Motivation: Detecting human proteins that are involved in virus entry and replication is facilitated by modern high-throughput RNAi screening technology. However, hit lists from different laboratories have shown only little consistency. This may be caused by not only experimental discrepancies, but also not fully explored possibilities of the data analysis. We wanted to improve reliability of such screens by combining a population analysis of infected cells with an established dye intensity readout. Results: Viral infection is mainly spread by cell–cell contacts and clustering of infected cells can be observed during spreading of the infection in situ and in vivo. We employed this clustering feature to define knockdowns which harm viral infection efficiency of human Hepatitis C Virus. Images of knocked down cells for 719 human kinase genes were analyzed with an established point pattern analysis method (Ripley's K-function) to detect knockdowns in which virally infected cells did not show any clustering and therefore were hindered to spread their infection to their neighboring cells. The results were compared with a statistical analysis using a common intensity readout of the GFP-expressing viruses and a luciferase-based secondary screen yielding five promising host factors which may suit as potential targets for drug therapy. Conclusion: We report of an alternative method for high-throughput imaging methods to detect host factors being relevant for the infection efficiency of viruses. The method is generic and has the potential to be used for a large variety of different viruses and treatments being screened by imaging techniques. Contact:  r.eils@dkfz.de; r.koenig@dkfz.de Supplementary information:  Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    URL: Article
    DOI: 10.1093/bioinformatics/btq398
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2010
    detail.hit.zdb_id: 1468345-3
    SSG: 12
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