Stacking classifiers for anti-spam filtering of e-mail

We evaluate empirically a scheme for combining classifiers, known as stacked generalization, in the context of anti-spam filtering, a novel cost-sensitive application of text categorization. Unsolicited commercial e-mail, or "spam", floods mailboxes, causing frustration, wasting bandwidth, and exposing minors to unsuitable content. Using a public corpus, we show that stacking can improve the efficiency of automatically induced anti-spam filters, and that such filters can be used in real-life applications

Optimization of Patterned Surfaces for Improved Superhydrophobicity Through Cost-Effective Large-Scale Computations

The growing need for creating surfaces with specific wetting properties, such as superhyrdophobic behavior, asks for novel methods for their efficient design. In this work, a fast computational method for the evaluation of patterned superhyrdophobic surfaces is introduced. The hydrophobicity of a surface is quantified in energy terms through an objective function. The increased computational cost led to the parallelization of the method with the Message Passing Interface (MPI) communication protocol that enables calculations on distributed memory systems allowing for parametric investigations at acceptable time frames. The method is demonstrated for a surface consisting of an array of pillars with inverted conical (frustum) geometry. The parallel speedup achieved allows for low cost parametric investigations on the effect of the fine features (curvature and slopes) of the pillars on the superhydophobicity of the surface and consequently for the optimization of superhyrdophobic surfaces.Comment: 18 pages, 18 figure

A Hidden Markov Model method, capable of predicting and discriminating β-barrel outer membrane proteins

BACKGROUND: Integral membrane proteins constitute about 20–30% of all proteins in the fully sequenced genomes. They come in two structural classes, the α-helical and the β-barrel membrane proteins, demonstrating different physicochemical characteristics, structure and localization. While transmembrane segment prediction for the α-helical integral membrane proteins appears to be an easy task nowadays, the same is much more difficult for the β-barrel membrane proteins. We developed a method, based on a Hidden Markov Model, capable of predicting the transmembrane β-strands of the outer membrane proteins of gram-negative bacteria, and discriminating those from water-soluble proteins in large datasets. The model is trained in a discriminative manner, aiming at maximizing the probability of correct predictions rather than the likelihood of the sequences. RESULTS: The training has been performed on a non-redundant database of 14 outer membrane proteins with structures known at atomic resolution; it has been tested with a jacknife procedure, yielding a per residue accuracy of 84.2% and a correlation coefficient of 0.72, whereas for the self-consistency test the per residue accuracy was 88.1% and the correlation coefficient 0.824. The total number of correctly predicted topologies is 10 out of 14 in the self-consistency test, and 9 out of 14 in the jacknife. Furthermore, the model is capable of discriminating outer membrane from water-soluble proteins in large-scale applications, with a success rate of 88.8% and 89.2% for the correct classification of outer membrane and water-soluble proteins respectively, the highest rates obtained in the literature. That test has been performed independently on a set of known outer membrane proteins with low sequence identity with each other and also with the proteins of the training set. CONCLUSION: Based on the above, we developed a strategy, that enabled us to screen the entire proteome of E. coli for outer membrane proteins. The results were satisfactory, thus the method presented here appears to be suitable for screening entire proteomes for the discovery of novel outer membrane proteins. A web interface available for non-commercial users is located at: , and it is the only freely available HMM-based predictor for β-barrel outer membrane protein topology

The normal field instability under side-wall effects: comparison of experiments and computations

We consider a single spike of ferrofluid, arising in a small cylindrical container, when a vertically oriented magnetic field is applied. The height of the spike as well as the surface topography is measured experimentally by two different technologies and calculated numerically using the finite element method. As a consequence of the finite size of the container, the numerics uncovers an imperfect bifurcation to a single spike solution, which is forward. This is in contrast to the standard transcritical bifurcation to hexagons, common for rotational symmetric systems with broken up-down symmetry. The numerical findings are corroborated in the experiments. The small hysteresis observed is explained in terms of a hysteretic wetting of the side wall.Comment: accepted to New Journal of Physic

A database for G proteins and their interaction with GPCRs

BACKGROUND: G protein-coupled receptors (GPCRs) transduce signals from extracellular space into the cell, through their interaction with G proteins, which act as switches forming hetero-trimers composed of different subunits (α,β,γ). The α subunit of the G protein is responsible for the recognition of a given GPCR. Whereas specialised resources for GPCRs, and other groups of receptors, are already available, currently, there is no publicly available database focusing on G Proteins and containing information about their coupling specificity with their respective receptors. DESCRIPTION: gpDB is a publicly accessible G proteins/GPCRs relational database. Including species homologs, the database contains detailed information for 418 G protein monomers (272 Gα, 87 Gβ and 59 Gγ) and 2782 GPCRs sequences belonging to families with known coupling to G proteins. The GPCRs and the G proteins are classified according to a hierarchy of different classes, families and sub-families, based on extensive literature searchs. The main innovation besides the classification of both G proteins and GPCRs is the relational model of the database, describing the known coupling specificity of the GPCRs to their respective α subunit of G proteins, a unique feature not available in any other database. There is full sequence information with cross-references to publicly available databases, references to the literature concerning the coupling specificity and the dimerization of GPCRs and the user may submit advanced queries for text search. Furthermore, we provide a pattern search tool, an interface for running BLAST against the database and interconnectivity with PRED-TMR, PRED-GPCR and TMRPres2D. CONCLUSIONS: The database will be very useful, for both experimentalists and bioinformaticians, for the study of G protein/GPCR interactions and for future development of predictive algorithms. It is available for academics, via a web browser at the URL

PLEISTOCENE PALAEOCLIMATIC EVOLUTION FROM AGIOS GEORGIOS CAVE SPELEOTHEM (KILKIS, N. GREECE)

Palaeoclimatic reconstruction in N. Greece has been investigated in this study, using stable isotope analyses and U/Th dating of a speleothem (stalactite) from the cave of Agios Georgios (Kilkis). Sampling sequence was followed in detail in order to obtain high resolution analysis of the proxy. Speleothem δ18O entirely depends on two factors: changes in the δ18O of the percolation waters (a proxy for local rainfall δ18O) and the temperature of water-calcite fractionation inside the cave (a proxy for outside air temperatures). During periods of relatively stable temperatures, δ13C shifts are caused principally by variations in soil CO2 input and physico-chemical processes inside the cave. More important processes affect the δ13C signal of speleothem inside the cave are length of flow path and rates of CO2 degassing.The lower δ13C calcite values indicate greater respiratory activity of soils under wetter conditions. The stalagmite layers were dated through U/Th geochronological method, which places the carbonate precipitation in Middle Pleistocene (630-300ka BP). The isotopic composition of the layers was used in combination with the dating results to reconstruct the evolution of the area of Kilkis. Correlation with global climatic records shows that major climatic transitions that influenced northern hemisphere seem to have also affected the region of N. Greece

PLEISTOCENE PALAEOCLIMATIC EVOLUTION FROM AGIOS GEORGIOS CAVE SPELEOTHEM (KILKIS, N. GREECE)

Palaeoclimatic reconstruction in N. Greece has been investigated in this study, using stable isotope analyses and U/Th dating of a speleothem (stalactite) from the cave of Agios Georgios (Kilkis). Sampling sequence was followed in detail in order to obtain high resolution analysis of the proxy. Speleothem δ18O entirely depends on two factors: changes in the δ18O of the percolation waters (a proxy for local rainfall δ18O) and the temperature of water-calcite fractionation inside the cave (a proxy for outside air temperatures). During periods of relatively stable temperatures, δ13C shifts are caused principally by variations in soil CO2 input and physico-chemical processes inside the cave. More important processes affect the δ13C signal of speleothem inside the cave are length of flow path and rates of CO2 degassing.The lower δ13C calcite values indicate greater respiratory activity of soils under wetter conditions. The stalagmite layers were dated through U/Th geochronological method, which places the carbonate precipitation in Middle Pleistocene (630-300ka BP). The isotopic composition of the layers was used in combination with the dating results to reconstruct the evolution of the area of Kilkis. Correlation with global climatic records shows that major climatic transitions that influenced northern hemisphere seem to have also affected the region of N. Greece