Low power in the cosmic microwave background and its implications for the topology of the universe

Imperial Users onl

Predicting and analyzing topological correlations in the CMB

The Cosmic Microwave Background (CMB) power spectrum derived from the first year WMAP data demonstrates an intriguing lack of power at large scales that cannot be accounted for within the framework of the standard cosmological model. We explore the possibility that this anomaly could be explained by waiving the implicit assumption of a simply connected topology, rather than modifying the physics of the standard model. In particular, we assume that the Universe is slightly closed and its spatial section can be described by one of the simplest spherical multi-connected manifolds (the quaternionic, the octahedral, the truncated cube and the Poincare space). We discuss the implications for the CMB in each case.Comment: 5 pages, 4 figures. To appear in the proceedings of the 7th astronomy conference of the Hellenic Astronomical Society (8-11 September 2005

Large-scale power in the CMB and new physics: An analysis using Bayesian model comparison

Published versio

Low power in the cosmic microwave background and its implications for the topology of the universe

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

C-PAmP: large scale analysis and database construction containing high scoring computationally predicted antimicrobial peptides for all the available plant species.

BACKGROUND: Antimicrobial peptides are a promising alternative to conventional antibiotics. Plants are an important source of such peptides; their pharmacological properties are known since antiquity. Access to relevant information, however, is not straightforward, as there are practically no major repositories of experimentally validated and/or predicted plant antimicrobial peptides. PhytAMP is the only database dedicated to plant peptides with confirmed antimicrobial action, holding 273 entries. Data on such peptides can be otherwise retrieved from generic repositories. DESCRIPTION: We present C-PAmP, a database of computationally predicted plant antimicrobial peptides. C-PAmP contains 15,174,905 peptides, 5-100 amino acids long, derived from 33,877 proteins of 2,112 plant species in UniProtKB/Swiss-Prot. Its web interface allows queries based on peptide/protein sequence, protein accession number and species. Users can view the corresponding predicted peptides along with their probability score, their classification according to the Collection of Anti-Microbial Peptides (CAMP), and their PhytAMP id where applicable. Moreover, users can visualise protein regions with a high concentration of predicted antimicrobial peptides. In order to identify potential antimicrobial peptides we used a classification algorithm, based on a modified version of the pseudo amino acid concept. The classifier tested all subsequences ranging from 5 to 100 amino acids of the plant proteins in UniProtKB/Swiss-Prot and stored those classified as antimicrobial with a high probability score (>90%). Its performance measures across a 10-fold cross-validation are more than satisfactory (accuracy: 0.91, sensitivity: 0.93, specificity: 0.90) and it succeeded in classifying 99.5% of the PhytAMP peptides correctly. CONCLUSIONS: We have compiled a major repository of predicted plant antimicrobial peptides using a highly performing classification algorithm. Our repository is accessible from the web and supports multiple querying options to optimise data retrieval. We hope it will greatly benefit drug design research by significantly limiting the range of plant peptides to be experimentally tested for antimicrobial activity

Large-scale power in the CMB and new physics: an analysis using Bayesian model comparison, Phys

One of the most tantalizing results from the Wilkinson Microwave Anisotropy Probe ͑WMAP͒ experiment is the suggestion that the power at large scales is anomalously low when compared to the prediction of the ''standard'' ⌳ cold dark matter ͑CDM͒ model. The same anomaly, although with somewhat larger uncertainty, was also previously noted in the COBE data. In this work we discuss possible alternate models that give better fits on large scales and apply a model-comparison technique to select amongst them. We find that models with a cutoff in the power spectrum at large scales are indeed preferred by data, but only by a factor of 3.6, at most, in the likelihood ratio, corresponding to about ''1.6'' if interpreted in the traditional manner. Using the same technique, we have also examined the possibility of a systematic error in the measurement or prediction of the large-scale power. Ignoring other evidence that the large-scale modes are properly measured and predicted, we find this possibility somewhat more likely, with roughly a 2.75 evidence

Snapshots from the C-PAmP Database.

<p>Snapshots from the C-PAmP Database.</p

Statistics of the predicted plant antimicrobial peptides.

<p>Statistics of the predicted plant antimicrobial peptides.</p

Comparative overview of other antimicrobial peptide studies.

<p>Comparative overview of other antimicrobial peptide studies.</p

Maximum, minimum and average values of Accuracy, Sensitivity, Specificity and Matthews Correlation Coefficient (MCC) for a 10-fold cross-validation.

<p>Maximum, minimum and average values of Accuracy, Sensitivity, Specificity and Matthews Correlation Coefficient (MCC) for a 10-fold cross-validation.</p