84 research outputs found
Acute Effects of Morning Light on Plasma Glucose and Triglycerides in Healthy Men and Men with Type 2 Diabetes
Sustainable conditions for the development of renewable energy systems : a triple bottom line perspective
Renewable energy systems (RES) have been proposed as an effective solution for sustainable development. However, the impact of municipal contextual conditions on the development of RES is still unclear. One of the literature gaps is the lack of understanding of whether the balanced development of economic, social, and environmental aspects of sustainability – the triple bottom line (TBL) perspective – can support RES policy. We conducted a quantitative analysis of 727 medium- and large-sized German municipalities to understand whether municipalities should create contextual conditions around the TBL dimensions to support RES policy. Furthermore, we applied a cluster analysis to establish the patterns of RES adoption supported by the TBL. Our results document that advanced adopters of RES are more advanced regarding the economic and environmental aspects of the TBL, and their RES development outperforms in the development of a knowledge-base and social cooperation. In contrast, regions with less RES development primarily emphasize reducing energy dependency and increasing social acceptance. As the main contribution, the study provides a novel view on how sustainability and RES development work together by providing details about the connection between specific TBL dimensions and elements with different maturity levels of RES policy implementation
Algebraic Comparison of Partial Lists in Bioinformatics
The outcome of a functional genomics pipeline is usually a partial list of
genomic features, ranked by their relevance in modelling biological phenotype
in terms of a classification or regression model. Due to resampling protocols
or just within a meta-analysis comparison, instead of one list it is often the
case that sets of alternative feature lists (possibly of different lengths) are
obtained. Here we introduce a method, based on the algebraic theory of
symmetric groups, for studying the variability between lists ("list stability")
in the case of lists of unequal length. We provide algorithms evaluating
stability for lists embedded in the full feature set or just limited to the
features occurring in the partial lists. The method is demonstrated first on
synthetic data in a gene filtering task and then for finding gene profiles on a
recent prostate cancer dataset
Reverse Engineering Gene Networks with ANN: Variability in Network Inference Algorithms
Motivation :Reconstructing the topology of a gene regulatory network is one
of the key tasks in systems biology. Despite of the wide variety of proposed
methods, very little work has been dedicated to the assessment of their
stability properties. Here we present a methodical comparison of the
performance of a novel method (RegnANN) for gene network inference based on
multilayer perceptrons with three reference algorithms (ARACNE, CLR, KELLER),
focussing our analysis on the prediction variability induced by both the
network intrinsic structure and the available data.
Results: The extensive evaluation on both synthetic data and a selection of
gene modules of "Escherichia coli" indicates that all the algorithms suffer of
instability and variability issues with regards to the reconstruction of the
topology of the network. This instability makes objectively very hard the task
of establishing which method performs best. Nevertheless, RegnANN shows MCC
scores that compare very favorably with all the other inference methods tested.
Availability: The software for the RegnANN inference algorithm is distributed
under GPL3 and it is available at the corresponding author home page
(http://mpba.fbk.eu/grimaldi/regnann-supmat
DGW: an exploratory data analysis tool for clustering and visualisation of epigenomic marks
Background
Functional genomic and epigenomic research relies fundamentally on sequencing based methods like ChIP-seq for the detection of DNA-protein interactions. These techniques return large, high dimensional data sets with visually complex structures, such as multi-modal peaks extended over large genomic regions. Current tools for visualisation and data exploration represent and leverage these complex features only to a limited extent.
Results
We present DGW, an open source software package for simultaneous alignment and clustering of multiple epigenomic marks. DGW uses Dynamic Time Warping to adaptively rescale and align genomic distances which allows to group regions of interest with similar shapes, thereby capturing the structure of epigenomic marks. We demonstrate the effectiveness of the approach in a simulation study and on a real epigenomic data set from the ENCODE project.
Conclusions
Our results show that DGW automatically recognises and aligns important genomic features such as transcription start sites and splicing sites from histone marks. DGW is available as an open source Python package
A pilot cohort study of cerebral autoregulation and 2-year neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy who received therapeutic hypothermia
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