21,416 research outputs found
Statistical mechanics of complex networks
Complex networks describe a wide range of systems in nature and society, much
quoted examples including the cell, a network of chemicals linked by chemical
reactions, or the Internet, a network of routers and computers connected by
physical links. While traditionally these systems were modeled as random
graphs, it is increasingly recognized that the topology and evolution of real
networks is governed by robust organizing principles. Here we review the recent
advances in the field of complex networks, focusing on the statistical
mechanics of network topology and dynamics. After reviewing the empirical data
that motivated the recent interest in networks, we discuss the main models and
analytical tools, covering random graphs, small-world and scale-free networks,
as well as the interplay between topology and the network's robustness against
failures and attacks.Comment: 54 pages, submitted to Reviews of Modern Physic
Techniques for clustering gene expression data
Many clustering techniques have been proposed for the analysis of gene expression data obtained from microarray experiments. However, choice of suitable method(s) for a given experimental dataset is not straightforward. Common approaches do not translate well and fail to take account of the data profile. This review paper surveys state of the art applications which recognises these limitations and implements procedures to overcome them. It provides a framework for the evaluation of clustering in gene expression analyses. The nature of microarray data is discussed briefly. Selected examples are presented for the clustering methods considered
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MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis.
Data-independent acquisition (DIA) in liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) provides comprehensive untargeted acquisition of molecular data. We provide an open-source software pipeline, which we call MS-DIAL, for DIA-based identification and quantification of small molecules by mass spectral deconvolution. For a reversed-phase LC-MS/MS analysis of nine algal strains, MS-DIAL using an enriched LipidBlast library identified 1,023 lipid compounds, highlighting the chemotaxonomic relationships between the algal strains
Parameters for apple quality: and an outline for a new quality concept - part 1 report
In real life it is hard to distinguish between the two life processes, growth and differentiation. We cannot expect one measured parameter to represent only one aspect of vital quality. But for most parameters we can recognise emphases on one or more aspects of the vital quality concept. We made this prelimary classification both by thinking about the concept and by looking at the experimental results. Also the conventional parameters are interpreted as a result of these processes in a more holistic way than usual.
We realise that various parameters all concerning the same aspect of our quality concept can show different levels of the aspect. To belong to the same aspect of the quality concept does not automatically mean that their correlation (see annex 14.2) must be high. We still have to get a lot of more experience to validate the parametersâ character. Here we present our first research on this topic, including the unanswered questions and realise that more experimental series will bring more and more certainty.
After this first project we cannot say which parameters are so similar that it makes the other redundant. Until now we learned something from every parameter to develop our quality concept. Most inspiring for the new quality concept were the crystallisations, the delayed luminescence and the Bovis-value
Quantumlike Chaos in the Frequency Distributions of the Bases A, C, G, T in Drosophila DNA
Continuous periodogram power spectral analyses of fractal fluctuations of
frequency distributions of bases A, C, G, T in Drosophila DNA show that the
power spectra follow the universal inverse power-law form of the statistical
normal distribution. Inverse power-law form for power spectra of space-time
fluctuations is generic to dynamical systems in nature and is identified as
self-organized criticality. The author has developed a general systems theory,
which provides universal quantification for observed self-organized criticality
in terms of the statistical normal distribution. The long-range correlations
intrinsic to self-organized criticality in macro-scale dynamical systems are a
signature of quantumlike chaos. The fractal fluctuations self-organize to form
an overall logarithmic spiral trajectory with the quasiperiodic Penrose tiling
pattern for the internal structure. Power spectral analysis resolves such a
spiral trajectory as an eddy continuum with embedded dominant wavebands. The
dominant peak periodicities are functions of the golden mean. The observed
fractal frequency distributions of the Drosophila DNA base sequences exhibit
quasicrystalline structure with long-range spatial correlations or
self-organized criticality. Modification of the DNA base sequence structure at
any location may have significant noticeable effects on the function of the DNA
molecule as a whole. The presence of non-coding introns may not be redundant,
but serve to organize the effective functioning of the coding exons in the DNA
molecule as a complete unit.Comment: 46 pages, 9 figure
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