Mesoscopic Model for Free Energy Landscape Analysis of DNA sequences

A mesoscopic model which allows us to identify and quantify the strength of binding sites in DNA sequences is proposed. The model is based on the Peyrard-Bishop-Dauxois model for the DNA chain coupled to a Brownian particle which explores the sequence interacting more importantly with open base pairs of the DNA chain. We apply the model to promoter sequences of different organisms. The free energy landscape obtained for these promoters shows a complex structure that is strongly connected to their biological behavior. The analysis method used is able to quantify free energy differences of sites within genome sequences.Comment: 7 pages, 5 figures, 1 tabl

Towards a Semantic Gas Source Localization under Uncertainty

Towards a Semantic Gas Source Localization under Uncertainty.Communications in Computer and Information Science book series (CCIS, volume 855), doi:10.1007/978-3-319-91479-4_42This work addresses the problem of efficiently and coherently locating a gas source in a domestic environment with a mobile robot, meaning efficiently the coverage of the shortest distance as possible and coherently the consideration of different gas sources explaining the gas presence. The main contribution is the exploitation, for the first time, of semantic relationships between the gases detected and the objects present in the environment to face this challenging issue. Our proposal also takes into account both the uncertainty inherent in the gas classification and object recognition processes. These uncertainties are combined through a probabilistic Bayesian framework to provide a priority-ordered list of (previously observed) objects to check. Moreover the proximity of the different candidates to the current robot location is also considered by a cost function, which output is used for planning the robot inspection path. We have conducted an initial demonstration of the suitability of our gas source localization approach by simulating this task within domestic environments for a variable number of objects, and comparing it with an greedy approach.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Self-Consistent Pushing and Cranking Corrections to the Meson Fields of the Chiral Quark-Loop Soliton

We study translational and spin-isospin symmetry restoration for the two-flavor chiral quark-loop soliton. Instead of a static soliton at rest we consider a boosted and rotating hedgehog soliton. Corrected classical meson fields are obtained by minimizing a corrected energy functional which has been derived by semi-classical methods ('variation after projection'). We evaluate corrected meson fields in the region 300 MeV \le M \le 600 MeV of constituent quark masses M and compare them with the uncorrected fields. We study the effect of the corrections on various expectation values of nuclear observables such as the root-mean square radius, the axial-vector coupling constant, magnetic moments and the delta-nucleon mass splitting.Comment: 19 pages, LaTeX, 7 postscript figures included using 'psfig.sty', to appear in Int.J.Mod.Phys.

Invariant Distribution of Promoter Activities in Escherichia coli

Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources

Distinct translatome changes in specific neural populations precede electroencephalographic changes in prion-infected mice

Selective vulnerability is an enigmatic feature of neurodegenerative diseases (NDs), whereby a widely expressed protein causes lesions in specific cell types and brain regions. Using the RiboTag method in mice, translational responses of five neural subtypes to acquired prion disease (PrD) were measured. Pre-onset and disease onset timepoints were chosen based on longitudinal electroencephalography (EEG) that revealed a gradual increase in theta power between 10- and 18-weeks after prion injection, resembling a clinical feature of human PrD. At disease onset, marked by significantly increased theta power and histopathological lesions, mice had pronounced translatome changes in all five cell types despite appearing normal. Remarkably, at a pre-onset stage, prior to EEG and neuropathological changes, we found that 1) translatomes of astrocytes indicated reduced synthesis of ribosomal and mitochondrial components, 2) glutamatergic neurons showed increased expression of cytoskeletal genes, and 3) GABAergic neurons revealed reduced expression of circadian rhythm genes. These data demonstrate that early translatome responses to neurodegeneration emerge prior to conventional markers of disease and are cell type-specific. Therapeutic strategies may need to target multiple pathways in specific populations of cells, early in disease

Development of SimCells as a novel chassis for functional biosensors

This work serves as a proof-of-concept for bacterially derived SimCells (Simple Cells), which contain the cell machinery from bacteria and designed DNA (or potentially a simplified genome) to instruct the cell to carry out novel, specific tasks. SimCells represent a reprogrammable chassis without a native chromosome, which can host designed DNA to perform defined functions. In this paper, the use of Escherichia coli MC1000 ∆minD minicells as a non-reproducing chassis for SimCells was explored, as demonstrated by their ability to act as sensitive biosensors for small molecules. Highly purified minicells derived from E. coli strains containing gene circuits for biosensing were able to transduce the input signals from several small molecules (glucarate, acrylate and arabinose) into the production of green fluorescent protein (GFP). A mathematical model was developed to fit the experimental data for induction of gene expression in SimCells. The intracellular ATP level was shown to be important for SimCell function. A purification and storage protocol was developed to prepare SimCells which could retain their functions for an extended period of time. This study demonstrates that SimCells are able to perform as 'smart bioparticles' controlled by designed gene circuits

Multilevel Deconstruction of the In Vivo Behavior of Looped DNA-Protein Complexes

Protein-DNA complexes with loops play a fundamental role in a wide variety of cellular processes, ranging from the regulation of DNA transcription to telomere maintenance. As ubiquitous as they are, their precise in vivo properties and their integration into the cellular function still remain largely unexplored. Here, we present a multilevel approach that efficiently connects in both directions molecular properties with cell physiology and use it to characterize the molecular properties of the looped DNA-lac repressor complex while functioning in vivo. The properties we uncover include the presence of two representative conformations of the complex, the stabilization of one conformation by DNA architectural proteins, and precise values of the underlying twisting elastic constants and bending free energies. Incorporation of all this molecular information into gene-regulation models reveals an unprecedented versatility of looped DNA-protein complexes at shaping the properties of gene expression.Comment: Open Access article available at http://www.plosone.org/article/fetchArticle.action?articleURI=info%3Adoi%2F10.1371%2Fjournal.pone.000035

Low-Rank Subspace Override for Unsupervised Domain Adaptation

Current supervised learning models cannot generalize well across domain boundaries, which is a known problem in many applications, such as robotics or visual classification. Domain adaptation methods are used to improve these generalization properties. However, these techniques suffer either from being restricted to a particular task, such as visual adaptation, require a lot of computational time and data, which is not always guaranteed, have complex parameterization, or expensive optimization procedures. In this work, we present an approach that requires only a well-chosen snapshot of data to find a single domain invariant subspace. The subspace is calculated in closed form and overrides domain structures, which makes it fast and stable in parameterization. By employing low-rank techniques, we emphasize on descriptive characteristics of data. The presented idea is evaluated on various domain adaptation tasks such as text and image classification against state of the art domain adaptation approaches and achieves remarkable performance across all tasks

Differential (2+1) Jet Event Rates and Determination of alpha_s in Deep Inelastic Scattering at HERA

Events with a (2+1) jet topology in deep-inelastic scattering at HERA are studied in the kinematic range 200 < Q^2< 10,000 GeV^2. The rate of (2+1) jet events has been determined with the modified JADE jet algorithm as a function of the jet resolution parameter and is compared with the predictions of Monte Carlo models. In addition, the event rate is corrected for both hadronization and detector effects and is compared with next-to-leading order QCD calculations. A value of the strong coupling constant of alpha_s(M_Z^2)= 0.118+- 0.002 (stat.)^(+0.007)_(-0.008) (syst.)^(+0.007)_(-0.006) (theory) is extracted. The systematic error includes uncertainties in the calorimeter energy calibration, in the description of the data by current Monte Carlo models, and in the knowledge of the parton densities. The theoretical error is dominated by the renormalization scale ambiguity.Comment: 25 pages, 6 figures, 3 tables, submitted to Eur. Phys.