26 research outputs found
Theory of Bose-Einstein condensation in trapped gases
The phenomenon of Bose-Einstein condensation of dilute gases in traps is
reviewed from a theoretical perspective. Mean-field theory provides a framework
to understand the main features of the condensation and the role of
interactions between particles. Various properties of these systems are
discussed, including the density profiles and the energy of the ground state
configurations, the collective oscillations and the dynamics of the expansion,
the condensate fraction and the thermodynamic functions. The thermodynamic
limit exhibits a scaling behavior in the relevant length and energy scales.
Despite the dilute nature of the gases, interactions profoundly modify the
static as well as the dynamic properties of the system; the predictions of
mean-field theory are in excellent agreement with available experimental
results. Effects of superfluidity including the existence of quantized vortices
and the reduction of the moment of inertia are discussed, as well as the
consequences of coherence such as the Josephson effect and interference
phenomena. The review also assesses the accuracy and limitations of the
mean-field approach.Comment: revtex, 69 pages, 38 eps figures, new version with more references,
new figures, various changes and corrections, for publ. in Rev. Mod. Phys.,
available also at http://www-phys.science.unitn.it/bec/BEC.htm
NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data
Background: Biomedical applications of high-throughput sequencing methods generate a vast amount of data in which numerous chromatin features are mapped along the genome. The results are frequently analysed by creating binary data sets that link the presence/absence of a given feature to specific genomic loci. However, the nucleosome occupancy or chromatin accessibility landscape is essentially continuous. It is currently a challenge in the field to cope with continuous distributions of deep sequencing chromatin readouts and to integrate the different types of discrete chromatin features to reveal linkages between them. Results: Here we introduce the NucTools suite of Perl scripts as well as MATLAB- and R-based visualization programs for a nucleosome-centred downstream analysis of deep sequencing data. NucTools accounts for the continuous distribution of nucleosome occupancy. It allows calculations of nucleosome occupancy profiles averaged over several replicates, comparisons of nucleosome occupancy landscapes between different experimental conditions, and the estimation of the changes of integral chromatin properties such as the nucleosome repeat length. Furthermore, NucTools facilitates the annotation of nucleosome occupancy with other chromatin features like binding of transcription factors or architectural proteins, and epigenetic marks like histone modifications or DNA methylation. The applications of NucTools are demonstrated for the comparison of several datasets for nucleosome occupancy in mouse embryonic stem cells (ESCs) and mouse embryonic fibroblasts (MEFs). Conclusions: The typical workflows of data processing and integrative analysis with NucTools reveal information on the interplay of nucleosome positioning with other features such as for example binding of a transcription factor CTCF, regions with stable and unstable nucleosomes, and domains of large organized chromatin K9me2 modifications (LOCKs). As potential limitations and problems we discuss how inter-replicate variability of MNase-seq experiments can be addressed
Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition
A majority of the studies examining the molecular regulation of human labor have
been conducted using single gene approaches. While the technology to produce
multi-dimensional datasets is readily available, the means for facile analysis
of such data are limited. The objective of this study was to develop a systems
approach to infer regulatory mechanisms governing global gene expression in
cytokine-challenged cells in vitro, and to apply these methods
to predict gene regulatory networks (GRNs) in intrauterine tissues during term
parturition. To this end, microarray analysis was applied to human amnion
mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially
expressed transcripts were subjected to hierarchical clustering, temporal
expression profiling, and motif enrichment analysis, from which a GRN was
constructed. These methods were then applied to fetal membrane specimens
collected in the absence or presence of spontaneous term labor. Analysis of
cytokine-responsive genes in AMCs revealed a sterile immune response signature,
with promoters enriched in response elements for several inflammation-associated
transcription factors. In comparison to the fetal membrane dataset, there were
34 genes commonly upregulated, many of which were part of an acute inflammation
gene expression signature. Binding motifs for nuclear factor-κB were
prominent in the gene interaction and regulatory networks for both datasets;
however, we found little evidence to support the utilization of
pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens
were also enriched for transcripts governed by hypoxia-inducible factor. The
approach presented here provides an uncomplicated means to infer global
relationships among gene clusters involved in cellular responses to
labor-associated signals