Evolution of Music by Public Choice

Music evolves as composers, performers, and consumers favor some musical variants over others. To investigate the role of consumer selection, we constructed a Darwinian music engine consisting of a population of short audio loops that sexually reproduce and mutate. This population evolved for 2,513 generations under the selective influence of 6,931 consumers who rated the loops’ aesthetic qualities. We found that the loops quickly evolved into music attributable, in part, to the evolution of aesthetically pleasing chords and rhythms. Later, however, evolution slowed. Applying the Price equation, a general description of evolutionary processes, we found that this stasis was mostly attributable to a decrease in the fidelity of transmission. Our experiment shows how cultural dynamics can be explained in terms of competing evolutionary forces

Improved alignment quality by combining evolutionary information, predicted secondary structure and self-organizing maps

BACKGROUND: Protein sequence alignment is one of the basic tools in bioinformatics. Correct alignments are required for a range of tasks including the derivation of phylogenetic trees and protein structure prediction. Numerous studies have shown that the incorporation of predicted secondary structure information into alignment algorithms improves their performance. Secondary structure predictors have to be trained on a set of somewhat arbitrarily defined states (e.g. helix, strand, coil), and it has been shown that the choice of these states has some effect on alignment quality. However, it is not unlikely that prediction of other structural features also could provide an improvement. In this study we use an unsupervised clustering method, the self-organizing map, to assign sequence profile windows to "structural states" and assess their use in sequence alignment. RESULTS: The addition of self-organizing map locations as inputs to a profile-profile scoring function improves the alignment quality of distantly related proteins slightly. The improvement is slightly smaller than that gained from the inclusion of predicted secondary structure. However, the information seems to be complementary as the two prediction schemes can be combined to improve the alignment quality by a further small but significant amount. CONCLUSION: It has been observed in many studies that predicted secondary structure significantly improves the alignments. Here we have shown that the addition of self-organizing map locations can further improve the alignments as the self-organizing map locations seem to contain some information that is not captured by the predicted secondary structure

Automatic discovery of cross-family sequence features associated with protein function

BACKGROUND: Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomics. Until now, this problem has been approached using machine learning techniques that attempt to predict membership, or otherwise, to predefined functional categories or subcellular locations. A potential drawback of this approach is that the human-designated functional classes may not accurately reflect the underlying biology, and consequently important sequence-to-function relationships may be missed. RESULTS: We show that a self-supervised data mining approach is able to find relationships between sequence features and functional annotations. No preconceived ideas about functional categories are required, and the training data is simply a set of protein sequences and their UniProt/Swiss-Prot annotations. The main technical aspect of the approach is the co-evolution of amino acid-based regular expressions and keyword-based logical expressions with genetic programming. Our experiments on a strictly non-redundant set of eukaryotic proteins reveal that the strongest and most easily detected sequence-to-function relationships are concerned with targeting to various cellular compartments, which is an area already well studied both experimentally and computationally. Of more interest are a number of broad functional roles which can also be correlated with sequence features. These include inhibition, biosynthesis, transcription and defence against bacteria. Despite substantial overlaps between these functions and their corresponding cellular compartments, we find clear differences in the sequence motifs used to predict some of these functions. For example, the presence of polyglutamine repeats appears to be linked more strongly to the "transcription" function than to the general "nuclear" function/location. CONCLUSION: We have developed a novel and useful approach for knowledge discovery in annotated sequence data. The technique is able to identify functionally important sequence features and does not require expert knowledge. By viewing protein function from a sequence perspective, the approach is also suitable for discovering unexpected links between biological processes, such as the recently discovered role of ubiquitination in transcription

An expression map for Anopheles gambiae

<p>Abstract</p> <p>Background</p> <p>Quantitative transcriptome data for the malaria-transmitting mosquito <it>Anopheles gambiae </it>covers a broad range of biological and experimental conditions, including development, blood feeding and infection. Web-based summaries of differential expression for individual genes with respect to these conditions are a useful tool for the biologist, but they lack the context that a visualisation of <it>all </it>genes with respect to <it>all </it>conditions would give. For most organisms, including <it>A. gambiae</it>, such a systems-level view of gene expression is not yet available.</p> <p>Results</p> <p>We have clustered microarray-based gene-averaged expression values, available from VectorBase, for 10194 genes over 93 experimental conditions using a self-organizing map. Map regions corresponding to known biological events, such as egg production, are revealed. Many individual gene clusters (nodes) on the map are highly enriched in biological and molecular functions, such as protein synthesis, protein degradation and DNA replication. Gene families, such as odorant binding proteins, can be classified into distinct functional groups based on their expression and evolutionary history. Immunity-related genes are non-randomly distributed in several distinct regions on the map, and are generally distant from genes with house-keeping roles. Each immunity-rich region appears to represent a distinct biological context for pathogen recognition and clearance (e.g. the humoral and gut epithelial responses). Several immunity gene families, such as peptidoglycan recognition proteins (PGRPs) and defensins, appear to be specialised for these distinct roles, while three genes with physically interacting protein products (LRIM1/APL1C/TEP1) are found in close proximity.</p> <p>Conclusions</p> <p>The map provides the first genome-scale, multi-experiment overview of gene expression in <it>A. gambiae </it>and should also be useful at the gene-level for investigating potential interactions. A web interface is available through the VectorBase website <url>http://www.vectorbase.org/</url>. It is regularly updated as new experimental data becomes available.</p

Морфологічні зміни підщелепної слинної залози при гіпертонічній хворобі

Вступ. Значна увага приділяється питанням, пов'язаним з дисциркуляторними змінами в різних органах, пов’язаних з артеріальною гіпертензією і, зокрема, у великих слинних залозах. Доступна література містить недостатньо інформації про морфологічні зміни в підщелепних слинних залозах людини при гіпертонічній хворобі. Метою роботи є вивчення морфофункціональних змін внутрішньоорганних судин і тканин підщелепної слинної залози у хворих на гіпертонічну хворобу

Expansion of Foxp3+ T-cell populations by Candida albicans enhances both Th17-cell responses and fungal dissemination after intravenous challenge

Research Funding Wellcome Trust, UK. Grant Numbers: 086827, 080088 NIH. Grant Number: DE022550Peer reviewedPublisher PD

Magnifying transmitter

The magnifying transmitter was intended by Nicola Tesla for the wireless transmission of electrical energy. It is a high power harmonic oscillator, an air-core, multiple-resonant transformer that can generate very high voltages. In normal operation the magnifying transmitter is relatively silent, generating a high power electric field, but if the output voltage exceeds the design voltage of the elevated terminal, high-voltage sparks will strike out from the electrode into the air. In his autobiography, Tesla stated that "...I feel certain that of all my inventions, the Magnifying Transmitter will prove most important and valuable to future generations.

VectorBase: improvements to a bioinformatics resource for invertebrate vector genomics.

VectorBase (http://www.vectorbase.org) is a NIAID-supported bioinformatics resource for invertebrate vectors of human pathogens. It hosts data for nine genomes: mosquitoes (three Anopheles gambiae genomes, Aedes aegypti and Culex quinquefasciatus), tick (Ixodes scapularis), body louse (Pediculus humanus), kissing bug (Rhodnius prolixus) and tsetse fly (Glossina morsitans). Hosted data range from genomic features and expression data to population genetics and ontologies. We describe improvements and integration of new data that expand our taxonomic coverage. Releases are bi-monthly and include the delivery of preliminary data for emerging genomes. Frequent updates of the genome browser provide VectorBase users with increasing options for visualizing their own high-throughput data. One major development is a new population biology resource for storing genomic variations, insecticide resistance data and their associated metadata. It takes advantage of improved ontologies and controlled vocabularies. Combined, these new features ensure timely release of multiple types of data in the public domain while helping overcome the bottlenecks of bioinformatics and annotation by engaging with our user community

On the Back Reaction Problem for Gravitational Perturbations

We derive the effective energy-momentum tensor for cosmological perturbations and prove its gauge-invariance. The result is applied to study the influence of perturbations on the behaviour of the Friedmann background in inflationary Universe scenarios. We found that the back reaction of cosmological perturbations on the background can become important already at energies below the self-reproduction scale.Comment: 4 pages, uses LATE

Applications of a New Proposal for Solving the "Problem of Time" to Some Simple Quantum Cosmological Models

We apply a recent proposal for defining states and observables in quantum gravity to simple models. First, we consider a Klein-Gordon particle in an ex- ternal potential in Minkowski space and compare our proposal to the theory ob- tained by deparametrizing with respect to a time slicing prior to quantiza- tion. We show explicitly that the dynamics of the deparametrization approach depends on the time slicing. Our proposal yields a dynamics independent of the choice of time slicing at intermediate times but after the potential is turned off, the dynamics does not return to the free particle dynamics. Next we apply our proposal to the closed Robertson-Walker quantum cosmology with a massless scalar field with the size of the universe as our time variable, so the only dynamical variable is the scalar field. We show that the resulting theory has the semi-classical behavior up to the classical turning point from expansion to contraction, i.e., given a classical solution which expands for much longer than the Planck time, there is a quantum state whose dynamical evolution closely approximates this classical solution during the expansion. However, when the "time" gets larger than the classical maximum, the scalar field be- comes "frozen" at its value at the maximum expansion. We also obtain similar results in the Taub model. In an Appendix we derive the form of the Wheeler- DeWitt equation for the Bianchi models by performing a proper quantum reduc- tion of the momentum constraints; this equation differs from the usual one ob- tained by solving the momentum constraints classically, prior to quantization.Comment: 30 pages, LaTeX 3 figures (postscript file or hard copy) available upon request, BUTP-94/1