21,308 research outputs found

    Differentially private partitioned variational inference

    Full text link
    Learning a privacy-preserving model from sensitive data which are distributed across multiple devices is an increasingly important problem. The problem is often formulated in the federated learning context, with the aim of learning a single global model while keeping the data distributed. Moreover, Bayesian learning is a popular approach for modelling, since it naturally supports reliable uncertainty estimates. However, Bayesian learning is generally intractable even with centralised non-private data and so approximation techniques such as variational inference are a necessity. Variational inference has recently been extended to the non-private federated learning setting via the partitioned variational inference algorithm. For privacy protection, the current gold standard is called differential privacy. Differential privacy guarantees privacy in a strong, mathematically clearly defined sense. In this paper, we present differentially private partitioned variational inference, the first general framework for learning a variational approximation to a Bayesian posterior distribution in the federated learning setting while minimising the number of communication rounds and providing differential privacy guarantees for data subjects. We propose three alternative implementations in the general framework, one based on perturbing local optimisation runs done by individual parties, and two based on perturbing updates to the global model (one using a version of federated averaging, the second one adding virtual parties to the protocol), and compare their properties both theoretically and empirically.Comment: Published in TMLR 04/2023: https://openreview.net/forum?id=55Bcghgic

    RAFEN -- Regularized Alignment Framework for Embeddings of Nodes

    Full text link
    Learning representations of nodes has been a crucial area of the graph machine learning research area. A well-defined node embedding model should reflect both node features and the graph structure in the final embedding. In the case of dynamic graphs, this problem becomes even more complex as both features and structure may change over time. The embeddings of particular nodes should remain comparable during the evolution of the graph, what can be achieved by applying an alignment procedure. This step was often applied in existing works after the node embedding was already computed. In this paper, we introduce a framework -- RAFEN -- that allows to enrich any existing node embedding method using the aforementioned alignment term and learning aligned node embedding during training time. We propose several variants of our framework and demonstrate its performance on six real-world datasets. RAFEN achieves on-par or better performance than existing approaches without requiring additional processing steps.Comment: ICCS 202

    Type 2 Diabetes Mellitus and its comorbidity, Alzheimer’s disease: Identifying critical microRNA using machine learning

    Get PDF
    MicroRNAs (miRNAs) are critical regulators of gene expression in healthy and diseased states, and numerous studies have established their tremendous potential as a tool for improving the diagnosis of Type 2 Diabetes Mellitus (T2D) and its comorbidities. In this regard, we computationally identify novel top-ranked hub miRNAs that might be involved in T2D. We accomplish this via two strategies: 1) by ranking miRNAs based on the number of T2D differentially expressed genes (DEGs) they target, and 2) using only the common DEGs between T2D and its comorbidity, Alzheimer’s disease (AD) to predict and rank miRNA. Then classifier models are built using the DEGs targeted by each miRNA as features. Here, we show the T2D DEGs targeted by hsa-mir-1-3p, hsa-mir-16-5p, hsa-mir-124-3p, hsa-mir-34a-5p, hsa-let-7b-5p, hsa-mir-155-5p, hsa-mir-107, hsa-mir-27a-3p, hsa-mir-129-2-3p, and hsa-mir-146a-5p are capable of distinguishing T2D samples from the controls, which serves as a measure of confidence in the miRNAs’ potential role in T2D progression. Moreover, for the second strategy, we show other critical miRNAs can be made apparent through the disease’s comorbidities, and in this case, overall, the hsa-mir-103a-3p models work well for all the datasets, especially in T2D, while the hsa-mir-124-3p models achieved the best scores for the AD datasets. To the best of our knowledge, this is the first study that used predicted miRNAs to determine the features that can separate the diseased samples (T2D or AD) from the normal ones, instead of using conventional non-biology-based feature selection methods

    Évaluation de l'impact du changement climatique sur la défoliation de l'épinette noire par la tordeuse des bourgeons de l'épinette

    Get PDF
    Les modèles écologiques actuels prévoient de profonds effets des changements climatiques sur les régimes de perturbations naturelles des forêts. La tordeuse des bourgeons de l'épinette (Choristoneura fumiferana) (TBE) est le principal insecte défoliateur dans l'est de l'Amérique du Nord. Les épidémies de TBE ont un impact majeur sur la structure et la fonction de la forêt boréale canadienne puisque la défoliation entraîne une diminution de la croissance des arbres, une augmentation de la mortalité et une baisse de la productivité forestière. Les épidémies de TBE sont devenues plus sévères au cours du dernier siècle à cause des changements climatiques; cependant, nous savons peu de choses sur la manière dont l'effet intégré du climat et du TBE modifie la croissance des espèces hôtes. Nous évaluons ici comment l’interaction entre le climat et la gravité de l'épidémie affecte la croissance de l'épinette noire (Picea mariana) pendant l'épidémie de TBE qui a eu lieu entre 1968-1988 et 2006-2017. Nous avons compilé des séries dendrochronologiques (2271 arbres), des données de sévérité de l'épidémie (estimée par la défoliation aérienne observée) et des données climatiques pour 164 sites au Québec, Canada. Nous avons utilisé un modèle linéaire à effets mixtes pour déterminer l'impact des paramètres climatiques, de la défoliation cumulative (des cinq années précédentes) et de leur effet couplé sur la croissance en surface terrière. À la gravité maximale de l'épidémie, la croissance en surface terrière de l'épinette noire a été réduite de 14 à 18 % sur les cinq années en raison de l'effet TBE. Cette croissance a été affectée par le climat : des températures minimales estivales précédentes plus élevées et un indice d'humidité climatique estival plus élevé ont réduit la croissance de 11 % et 4 % respectivement. En revanche, l'effet négatif de la défoliation a été atténué de 9% pour une température minimale plus élevée au printemps précédent et de 7% pour une température maximale plus élevée l'été précédent. Cette étude améliore notre compréhension des effets combinés de la TBE et du climat et aide à prévoir les dommages futurs causés par cet insecte dans les peuplements forestiers afin de soutenir la gestion durable des forêts. Nous recommandons également que les projections des écosystèmes dans la forêt boréale incluent plusieurs classes de défoliation de la TBE et plusieurs scénarios climatiques

    Pollution-induced community tolerance in freshwater biofilms – from molecular mechanisms to loss of community functions

    Get PDF
    Exposure to herbicides poses a threat to aquatic biofilms by affecting their community structure, physiology and function. These changes render biofilms to become more tolerant, but on the downside community tolerance has ecologic costs. A concept that addresses induced community tolerance to a pollutant (PICT) was introduced by Blanck and Wängberg (1988). The basic principle of the concept is that microbial communities undergo pollution-induced succession when exposed to a pollutant over a long period of time, which changes communities structurally and functionally and enhancing tolerance to the pollutant exposure. However, the mechanisms of tolerance and the ecologic consequences were hardly studied up to date. This thesis addresses the structural and functional changes in biofilm communities and applies modern molecular methods to unravel molecular tolerance mechanisms. Two different freshwater biofilm communities were cultivated for a period of five weeks, with one of the communities being contaminated with 4 μg L-1 diuron. Subsequently, the communities were characterized for structural and functional differences, especially focusing on their crucial role of photosynthesis. The community structure of the autotrophs was assessed using HPLC-based pigment analysis and their functional alterations were investigated using Imaging-PAM fluorometry to study photosynthesis and community oxygen profiling to determine net primary production. Then, the molecular fingerprints of the communities were measured with meta-transcriptomics (RNA-Seq) and GC-based community metabolomics approaches and analyzed with respect to changes in their molecular functions. The communities were acute exposed to diuron for one hour in a dose-response design, to reveal a potential PICT and uncover related adaptation to diuron exposure. The combination of apical and molecular methods in a dose-response design enabled the linkage of functional effects of diuron exposure and underlying molecular mechanisms based on a sensitivity analysis. Chronic exposure to diuron impaired freshwater biofilms in their biomass accrual. The contaminated communities particularly lost autotrophic biomass, reflected by the decrease in specific chlorophyll a content. This loss was associated with a change in the molecular fingerprint of the communities, which substantiates structural and physiological changes. The decline in autotrophic biomass could be due to a primary loss of sensitive autotrophic organisms caused by the selection of better adapted species in the course of chronic exposure. Related to this hypothesis, an increase in diuron tolerance has been detected in the contaminated communities and molecular mechanisms facilitating tolerance have been found. It was shown that genes of the photosystem, reductive-pentose phosphate cycle and arginine metabolism were differentially expressed among the communities and that an increased amount of potential antioxidant degradation products was found in the contaminated communities. This led to the hypothesis that contaminated communities may have adapted to oxidative stress, making them less sensitive to diuron exposure. Moreover, the photosynthetic light harvesting complex was altered and the photoprotective xanthophyll cycle was increased in the contaminated communities. Despite these adaptation strategies, the loss of autotrophic biomass has been shown to impair primary production. This impairment persisted even under repeated short-term exposure, so that the tolerance mechanisms cannot safeguard primary production as a key function in aquatic systems.:1. The effect of chemicals on organisms and their functions .............................. 1 1.1 Welcome to the anthropocene .......................................................................... 1 1.2 From cellular stress responses to ecosystem resilience ................................... 3 1.2.1 The individual pursuit for homeostasis ....................................................... 3 1.2.2 Stability from diversity ................................................................................. 5 1.3 Community ecotoxicology - a step forward in monitoring the effects of chemical pollution? ................................................................................................................. 6 1.4 Functional ecotoxicological assessment of microbial communities ................... 9 1.5 Molecular tools – the key to a mechanistic understanding of stressor effects from a functional perspective in microbial communities? ...................................... 12 2. Aims and Hypothesis ......................................................................................... 14 2.1 Research question .......................................................................................... 14 2.2 Hypothesis and outline .................................................................................... 15 2.3 Experimental approach & concept .................................................................. 16 2.3.1 Aquatic freshwater biofilms as model community ..................................... 16 2.3.2 Diuron as model herbicide ........................................................................ 17 2.3.3 Experimental design ................................................................................. 18 3. Structural and physiological changes in microbial communities after chronic exposure - PICT and altered functional capacity ................................................. 21 3.1 Introduction ..................................................................................................... 21 3.2 Methods .......................................................................................................... 23 3.2.1 Biofilm cultivation ...................................................................................... 23 3.2.2 Dry weight and autotrophic index ............................................................. 23 3.2.4 Pigment analysis of periphyton ................................................................. 23 3.2.4.1 In-vivo pigment analysis for community characterization ....................... 24 3.2.4.2 In-vivo pigment analysis based on Imaging-PAM fluorometry ............... 24 3.2.4.3 In-vivo pigment fluorescence for tolerance detection ............................. 26 3.2.4.4 Ex-vivo pigment analysis by high-pressure liquid-chromatography ....... 27 3.2.5 Community oxygen metabolism measurements ....................................... 28 3.3 Results and discussion ................................................................................... 29 3.3.1 Comparison of the structural community parameters ............................... 29 3.3.2 Photosynthetic activity and primary production of the communities after selection phase ................................................................................................. 33 3.3.3 Acquisition of photosynthetic tolerance .................................................... 34 3.3.4 Primary production at exposure conditions ............................................... 36 3.3.5 Tolerance detection in primary production ................................................ 37 3.4 Summary and Conclusion ........................................................................... 40 4. Community gene expression analysis by meta-transcriptomics ................... 41 4.1 Introduction to meta-transcriptomics ............................................................... 41 4.2. Methods ......................................................................................................... 43 4.2.1 Sampling and RNA extraction................................................................... 43 4.2.2 RNA sequencing analysis ......................................................................... 44 4.2.3 Data assembly and processing................................................................. 45 4.2.4 Prioritization of contigs and annotation ..................................................... 47 4.2.5 Sensitivity analysis of biological processes .............................................. 48 4.3 Results and discussion ................................................................................... 48 4.3.1 Characterization of the meta-transcriptomic fingerprints .......................... 49 4.3.2 Insights into community stress response mechanisms using trend analysis (DRomic’s) ......................................................................................................... 51 4.3.3 Response pattern in the isoform PS genes .............................................. 63 4.5 Summary and conclusion ................................................................................ 65 5. Community metabolome analysis ..................................................................... 66 5.1 Introduction to community metabolomics ........................................................ 66 5.2 Methods .......................................................................................................... 68 5.2.1 Sampling, metabolite extraction and derivatisation................................... 68 5.2.2 GC-TOF-MS analysis ............................................................................... 69 5.2.3 Data processing and statistical analysis ................................................... 69 5.3 Results and discussion ................................................................................... 70 5.3.1 Characterization of the metabolic fingerprints .......................................... 70 5.3.2 Difference in the metabolic fingerprints .................................................... 71 5.3.3 Differential metabolic responses of the communities to short-term exposure of diuron ............................................................................................................ 73 5.4 Summary and conclusion ................................................................................ 78 6. Synthesis ............................................................................................................. 79 6.1 Approaches and challenges for linking molecular data to functional measurements ...................................................................................................... 79 6.2 Methods .......................................................................................................... 83 6.2.1 Summary on the data ............................................................................... 83 6.2.2 Aggregation of molecular data to index values (TELI and MELI) .............. 83 6.2.3 Functional annotation of contigs and metabolites using KEGG ................ 83 6.3 Results and discussion ................................................................................... 85 6.3.1 Results of aggregation techniques ........................................................... 85 6.3.2 Sensitivity analysis of the different molecular approaches and endpoints 86 6.3.3 Mechanistic view of the molecular stress responses based on KEGG functions ............................................................................................................ 89 6.4 Consolidation of the results – holistic interpretation and discussion ............... 93 6.4.1 Adaptation to chronic diuron exposure - from molecular changes to community effects.............................................................................................. 93 6.4.2 Assessment of the ecological costs of Pollution-induced community tolerance based on primary production ............................................................. 94 6.5 Outlook ............................................................................................................ 9

    Qluster: An easy-to-implement generic workflow for robust clustering of health data

    Get PDF
    The exploration of heath data by clustering algorithms allows to better describe the populations of interest by seeking the sub-profiles that compose it. This therefore reinforces medical knowledge, whether it is about a disease or a targeted population in real life. Nevertheless, contrary to the so-called conventional biostatistical methods where numerous guidelines exist, the standardization of data science approaches in clinical research remains a little discussed subject. This results in a significant variability in the execution of data science projects, whether in terms of algorithms used, reliability and credibility of the designed approach. Taking the path of parsimonious and judicious choice of both algorithms and implementations at each stage, this article proposes Qluster, a practical workflow for performing clustering tasks. Indeed, this workflow makes a compromise between (1) genericity of applications (e.g. usable on small or big data, on continuous, categorical or mixed variables, on database of high-dimensionality or not), (2) ease of implementation (need for few packages, few algorithms, few parameters, ...), and (3) robustness (e.g. use of proven algorithms and robust packages, evaluation of the stability of clusters, management of noise and multicollinearity). This workflow can be easily automated and/or routinely applied on a wide range of clustering projects. It can be useful both for data scientists with little experience in the field to make data clustering easier and more robust, and for more experienced data scientists who are looking for a straightforward and reliable solution to routinely perform preliminary data mining. A synthesis of the literature on data clustering as well as the scientific rationale supporting the proposed workflow is also provided. Finally, a detailed application of the workflow on a concrete use case is provided, along with a practical discussion for data scientists. An implementation on the Dataiku platform is available upon request to the authors

    Computational modeling of locoregional recurrence with spatial structure identifies tissue-specific carcinogenic profiles

    Get PDF
    IntroductionLocal and regional recurrence after surgical intervention is a significant problem in cancer management. The multistage theory of carcinogenesis precisely places the presence of histologically normal but mutated premalignant lesions surrounding the tumor - field cancerization, as a significant cause of cancer recurrence. The relationship between tissue dynamics, cancer initiation and cancer recurrence in multistage carcinogenesis is not well known.MethodsThis study constructs a computational model for cancer initiation and recurrence by combining the Moran and branching processes in which cells requires 3 or more mutations to become malignant. In addition, a spatial structure-setting is included in the model to account for positional relativity in cell turnover towards malignant transformation. The model consists of a population of normal cells with no mutation; several populations of premalignant cells with varying number of mutations and a population of malignant cells. The model computes a stage of cancer detection and surgery to eliminate malignant cells but spares premalignant cells and then estimates the time for malignant cells to re-emerge.ResultsWe report the cellular conditions that give rise to different patterns of cancer initiation and the conditions favoring a shorter cancer recurrence by analyzing premalignant cell types at the time of surgery. In addition, the model is fitted to disease-free clinical data of 8,957 patients in 27 different cancer types; From this fitting, we estimate the turnover rate per month, relative fitness of premalignant cells, growth rate and death rate of cancer cells in each cancer type.DiscussionOur study provides insights into how to identify patients who are likely to have a shorter recurrence and where to target the therapeutic intervention

    Bayesian Reconstruction of Magnetic Resonance Images using Gaussian Processes

    Full text link
    A central goal of modern magnetic resonance imaging (MRI) is to reduce the time required to produce high-quality images. Efforts have included hardware and software innovations such as parallel imaging, compressed sensing, and deep learning-based reconstruction. Here, we propose and demonstrate a Bayesian method to build statistical libraries of magnetic resonance (MR) images in k-space and use these libraries to identify optimal subsampling paths and reconstruction processes. Specifically, we compute a multivariate normal distribution based upon Gaussian processes using a publicly available library of T1-weighted images of healthy brains. We combine this library with physics-informed envelope functions to only retain meaningful correlations in k-space. This covariance function is then used to select a series of ring-shaped subsampling paths using Bayesian optimization such that they optimally explore space while remaining practically realizable in commercial MRI systems. Combining optimized subsampling paths found for a range of images, we compute a generalized sampling path that, when used for novel images, produces superlative structural similarity and error in comparison to previously reported reconstruction processes (i.e. 96.3% structural similarity and <0.003 normalized mean squared error from sampling only 12.5% of the k-space data). Finally, we use this reconstruction process on pathological data without retraining to show that reconstructed images are clinically useful for stroke identification

    Examples of works to practice staccato technique in clarinet instrument

    Get PDF
    Klarnetin staccato tekniğini güçlendirme aşamaları eser çalışmalarıyla uygulanmıştır. Staccato geçişlerini hızlandıracak ritim ve nüans çalışmalarına yer verilmiştir. Çalışmanın en önemli amacı sadece staccato çalışması değil parmak-dilin eş zamanlı uyumunun hassasiyeti üzerinde de durulmasıdır. Staccato çalışmalarını daha verimli hale getirmek için eser çalışmasının içinde etüt çalışmasına da yer verilmiştir. Çalışmaların üzerinde titizlikle durulması staccato çalışmasının ilham verici etkisi ile müzikal kimliğe yeni bir boyut kazandırmıştır. Sekiz özgün eser çalışmasının her aşaması anlatılmıştır. Her aşamanın bir sonraki performans ve tekniği güçlendirmesi esas alınmıştır. Bu çalışmada staccato tekniğinin hangi alanlarda kullanıldığı, nasıl sonuçlar elde edildiği bilgisine yer verilmiştir. Notaların parmak ve dil uyumu ile nasıl şekilleneceği ve nasıl bir çalışma disiplini içinde gerçekleşeceği planlanmıştır. Kamış-nota-diyafram-parmak-dil-nüans ve disiplin kavramlarının staccato tekniğinde ayrılmaz bir bütün olduğu saptanmıştır. Araştırmada literatür taraması yapılarak staccato ile ilgili çalışmalar taranmıştır. Tarama sonucunda klarnet tekniğin de kullanılan staccato eser çalışmasının az olduğu tespit edilmiştir. Metot taramasında da etüt çalışmasının daha çok olduğu saptanmıştır. Böylelikle klarnetin staccato tekniğini hızlandırma ve güçlendirme çalışmaları sunulmuştur. Staccato etüt çalışmaları yapılırken, araya eser çalışmasının girmesi beyni rahatlattığı ve istekliliği daha arttırdığı gözlemlenmiştir. Staccato çalışmasını yaparken doğru bir kamış seçimi üzerinde de durulmuştur. Staccato tekniğini doğru çalışmak için doğru bir kamışın dil hızını arttırdığı saptanmıştır. Doğru bir kamış seçimi kamıştan rahat ses çıkmasına bağlıdır. Kamış, dil atma gücünü vermiyorsa daha doğru bir kamış seçiminin yapılması gerekliliği vurgulanmıştır. Staccato çalışmalarında baştan sona bir eseri yorumlamak zor olabilir. Bu açıdan çalışma, verilen müzikal nüanslara uymanın, dil atış performansını rahatlattığını ortaya koymuştur. Gelecek nesillere edinilen bilgi ve birikimlerin aktarılması ve geliştirici olması teşvik edilmiştir. Çıkacak eserlerin nasıl çözüleceği, staccato tekniğinin nasıl üstesinden gelinebileceği anlatılmıştır. Staccato tekniğinin daha kısa sürede çözüme kavuşturulması amaç edinilmiştir. Parmakların yerlerini öğrettiğimiz kadar belleğimize de çalışmaların kaydedilmesi önemlidir. Gösterilen azmin ve sabrın sonucu olarak ortaya çıkan yapıt başarıyı daha da yukarı seviyelere çıkaracaktır
    corecore