Collaborative denoising autoencoder for high glycated haemoglobin prediction.

A pioneering study is presented demonstrating that the presence of high glycated haemoglobin (HbA1c) levels in a patient’s blood can be reliably predicted from routinely collected clinical data. This paves the way for performing early detection of Type-2 Diabetes Mellitus (T2DM). This will save healthcare providers a major cost associated with the administration and assessment of clinical tests for HbA1c. A novel collaborative denoising autoencoder framework is used to address this challenge. The framework builds an independent denoising autoencoder model for the high and low HbA1c level, which extracts feature representations in the latent space. A baseline model using just three features: patient age together with triglycerides and glucose level achieves 76% F1-score with an SVM classifier. The collaborative denoising autoencoder uses 78 features and can predict HbA1c level with 81% F1-score

Robust probabilistic superposition and comparison of protein structures

<p>Abstract</p> <p>Background</p> <p>Protein structure comparison is a central issue in structural bioinformatics. The standard dissimilarity measure for protein structures is the root mean square deviation (RMSD) of representative atom positions such as α-carbons. To evaluate the RMSD the structures under comparison must be superimposed optimally so as to minimize the RMSD. How to evaluate optimal fits becomes a matter of debate, if the structures contain regions which differ largely - a situation encountered in NMR ensembles and proteins undergoing large-scale conformational transitions.</p> <p>Results</p> <p>We present a probabilistic method for robust superposition and comparison of protein structures. Our method aims to identify the largest structurally invariant core. To do so, we model non-rigid displacements in protein structures with outlier-tolerant probability distributions. These distributions exhibit heavier tails than the Gaussian distribution underlying standard RMSD minimization and thus accommodate highly divergent structural regions. The drawback is that under a heavy-tailed model analytical expressions for the optimal superposition no longer exist. To circumvent this problem we work with a scale mixture representation, which implies a weighted RMSD. We develop two iterative procedures, an Expectation Maximization algorithm and a Gibbs sampler, to estimate the local weights, the optimal superposition, and the parameters of the heavy-tailed distribution. Applications demonstrate that heavy-tailed models capture differences between structures undergoing substantial conformational changes and can be used to assess the precision of NMR structures. By comparing Bayes factors we can automatically choose the most adequate model. Therefore our method is parameter-free.</p> <p>Conclusions</p> <p>Heavy-tailed distributions are well-suited to describe large-scale conformational differences in protein structures. A scale mixture representation facilitates the fitting of these distributions and enables outlier-tolerant superposition.</p

Kinetic modelling of competition and depletion of shared miRNAs by competing endogenous RNAs

Non-conding RNAs play a key role in the post-transcriptional regulation of mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact with their target RNAs through protein-mediated, sequence-specific binding, giving rise to extended and highly heterogeneous miRNA-RNA interaction networks. Within such networks, competition to bind miRNAs can generate an effective positive coupling between their targets. Competing endogenous RNAs (ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk. Albeit potentially weak, ceRNA interactions can occur both dynamically, affecting e.g. the regulatory clock, and at stationarity, in which case ceRNA networks as a whole can be implicated in the composition of the cell's proteome. Many features of ceRNA interactions, including the conditions under which they become significant, can be unraveled by mathematical and in silico models. We review the understanding of the ceRNA effect obtained within such frameworks, focusing on the methods employed to quantify it, its role in the processing of gene expression noise, and how network topology can determine its reach.Comment: review article, 29 pages, 7 figure

PROMPT: a protein mapping and comparison tool

BACKGROUND: Comparison of large protein datasets has become a standard task in bioinformatics. Typically researchers wish to know whether one group of proteins is significantly enriched in certain annotation attributes or sequence properties compared to another group, and whether this enrichment is statistically significant. In order to conduct such comparisons it is often required to integrate molecular sequence data and experimental information from disparate incompatible sources. While many specialized programs exist for comparisons of this kind in individual problem domains, such as expression data analysis, no generic software solution capable of addressing a wide spectrum of routine tasks in comparative proteomics is currently available. RESULTS: PROMPT is a comprehensive bioinformatics software environment which enables the user to compare arbitrary protein sequence sets, revealing statistically significant differences in their annotation features. It allows automatic retrieval and integration of data from a multitude of molecular biological databases as well as from a custom XML format. Similarity-based mapping of sequence IDs makes it possible to link experimental information obtained from different sources despite discrepancies in gene identifiers and minor sequence variation. PROMPT provides a full set of statistical procedures to address the following four use cases: i) comparison of the frequencies of categorical annotations between two sets, ii) enrichment of nominal features in one set with respect to another one, iii) comparison of numeric distributions, and iv) correlation of numeric variables. Analysis results can be visualized in the form of plots and spreadsheets and exported in various formats, including Microsoft Excel. CONCLUSION: PROMPT is a versatile, platform-independent, easily expandable, stand-alone application designed to be a practical workhorse in analysing and mining protein sequences and associated annotation. The availability of the Java Application Programming Interface and scripting capabilities on one hand, and the intuitive Graphical User Interface with context-sensitive help system on the other, make it equally accessible to professional bioinformaticians and biologically-oriented users. PROMPT is freely available for academic users from

Measuring the functional sequence complexity of proteins

<p>Abstract</p> <p>Background</p> <p>Abel and Trevors have delineated three aspects of sequence complexity, Random Sequence Complexity (RSC), Ordered Sequence Complexity (OSC) and Functional Sequence Complexity (FSC) observed in biosequences such as proteins. In this paper, we provide a method to measure functional sequence complexity.</p> <p>Methods and Results</p> <p>We have extended Shannon uncertainty by incorporating the data variable with a functionality variable. The resulting measured unit, which we call Functional bit (Fit), is calculated from the sequence data jointly with the defined functionality variable. To demonstrate the relevance to functional bioinformatics, a method to measure functional sequence complexity was developed and applied to 35 protein families. Considerations were made in determining how the measure can be used to correlate functionality when relating to the whole molecule and sub-molecule. In the experiment, we show that when the proposed measure is applied to the aligned protein sequences of ubiquitin, 6 of the 7 highest value sites correlate with the binding domain.</p> <p>Conclusion</p> <p>For future extensions, measures of functional bioinformatics may provide a means to evaluate potential evolving pathways from effects such as mutations, as well as analyzing the internal structural and functional relationships within the 3-D structure of proteins.</p

Adequacy of Diabetes Care for Older U.S. Rural Adults: A Cross-sectional Population Based Study Using 2009 BRFSS Data

Background: In the U.S. diabetes prevalence estimates for adults ≥ 65 years exceed 20%. Rural communities have higher proportions of older individuals and health disparities associated with rural residency place rural communities at risk for a higher burden from diabetes. This study examined the adequacy of care received by older rural adults for their diabetes to determine if older rural adults differed in the receipt of adequate diabetes care when compared to their non-rural counterparts. Methods: Cross-sectional data from the 2009 Behavioral Risk Factor Surveillance Survey were examined using bivariate and multivariate analytical techniques. Results: Logistic regression analysis revealed that older rural adults with diabetes were more likely to receive less than adequate care when compared to their non-rural counterparts (OR = 1.465, 95% CI: 1.454-1.475). Older rural adults receiving less than adequate care for their diabetes were more likely to be: male, non-Caucasian, less educated, unmarried, economically poorer, inactive, a smoker. They were also more likely to: have deferred medical care because of cost, not have a personal health care provider, and not have had a routine medical check-up within the last 12 months. Conclusion: There are gaps between what is recommended for diabetes management and the management that older individuals receive. Older adults with diabetes living in rural communities are at greater risk for less than adequate care when compared to their non-rural counterparts. These results suggest the need to develop strategies to improve diabetes care for older adults with diabetes and to target those at highest risk

DreamTel; Diabetes risk evaluation and management tele-monitoring study protocol

<p>Abstract</p> <p>Background</p> <p>The rising prevalence of type 2 diabetes underlines the importance of secondary strategies for the prevention of target organ damage. While access to diabetes education centers and diabetes intensification management has been shown to improve blood glucose control, these services are not available to all that require them, particularly in rural and northern areas. The provision of these services through the Home Care team is an advance that can overcome these barriers. Transfer of blood glucose data electronically from the home to the health care provider may improve diabetes management.</p> <p>Methods and design</p> <p>The study population will consist of patients with type 2 diabetes with uncontrolled A1c levels living on reserve in the Battlefords region of Saskatchewan, Canada. This pilot study will take place over three phases. In the first phase over three months the impact of the introduction of the Bluetooth enabled glucose monitor will be assessed. In the second phase over three months, the development of guidelines based treatment algorithms for diabetes intensification will be completed. In the third phase lasting 18 months, study subjects will have diabetes intensification according to the algorithms developed.</p> <p>Discussion</p> <p>The first phase will determine if the use of the Bluetooth enabled blood glucose devices which can transmit results electronically will lead to changes in A1c levels. It will also determine the feasibility of recruiting subjects to use this technology. The rest of the Diabetes Risk Evaluation and Management Tele-monitoring (DreamTel) study will determine if the delivery of a diabetes intensification management program by the Home Care team supported by the Bluetooth enabled glucose meters leads to improvements in diabetes management.</p> <p>Trial Registration</p> <p>Protocol NCT00325624</p

Search for lepton flavor violating decays of a heavy neutral particle in p-pbar collisions at root(s)=1.8 TeV

We report on a search for a high mass, narrow width particle that decays directly to e+mu, e+tau, or mu+tau. We use approximately 110 pb^-1 of data collected with the Collider Detector at Fermilab from 1992 to 1995. No evidence of lepton flavor violating decays is found. Limits are set on the production and decay of sneutrinos with R-parity violating interactions.Comment: Figure 2 fixed. Reference 4 fixed. Minor changes to tex

Search for Kaluza-Klein Graviton Emission in ppˉp\bar{p} Collisions at s=1.8\sqrt{s}=1.8 TeV using the Missing Energy Signature

We report on a search for direct Kaluza-Klein graviton production in a data sample of 84 ${pb}^{-1}$ of \ppb collisions at $\sqrt{s}$ = 1.8 TeV, recorded by the Collider Detector at Fermilab. We investigate the final state of large missing transverse energy and one or two high energy jets. We compare the data with the predictions from a $3+1+n$-dimensional Kaluza-Klein scenario in which gravity becomes strong at the TeV scale. At 95% confidence level (C.L.) for $n$=2, 4, and 6 we exclude an effective Planck scale below 1.0, 0.77, and 0.71 TeV, respectively.Comment: Submitted to PRL, 7 pages 4 figures/Revision includes 5 figure