16,190 research outputs found
Prediction of protein-protein interaction types using association rule based classification
This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2009 Park et alBackground: Protein-protein interactions (PPI) can be classified according to their characteristics into, for example obligate or transient interactions. The identification and characterization of these PPI types may help in the functional annotation of new protein complexes and in the prediction of protein interaction partners by knowledge driven approaches. Results: This work addresses pattern discovery of the interaction sites for four different interaction types to characterize and uses them for the prediction of PPI types employing Association Rule Based Classification (ARBC) which includes association rule generation and posterior classification. We incorporated domain information from protein complexes in SCOP proteins and identified 354 domain-interaction sites. 14 interface properties were calculated from amino acid and secondary structure composition and then used to generate a set of association rules characterizing these domain-interaction sites employing the APRIORI algorithm. Our results regarding the classification of PPI types based on a set of discovered association rules shows that the discriminative ability of association rules can significantly impact on the prediction power of classification models. We also showed that the accuracy of the classification can be improved through the use of structural domain information and also the use of secondary structure content. Conclusion: The advantage of our approach is that we can extract biologically significant information from the interpretation of the discovered association rules in terms of understandability and interpretability of rules. A web application based on our method can be found at http://bioinfo.ssu.ac.kr/~shpark/picasso/SHP was supported by the Korea Research Foundation Grant funded by the Korean Government(KRF-2005-214-E00050). JAR has been
supported by the Programme Alβan, the European Union Programme of High level Scholarships for Latin America, scholarship E04D034854CL. SK was supported by Soongsil University Research Fund
EuCo2P2: A Model Molecular-Field Helical Heisenberg Antiferromagnet
The metallic compound EuCo2P2 with the body-centered tetragonal ThCr2Si2
structure containing Eu spins 7/2 was previously shown from single-crystal
neutron diffraction measurements to exhibit a helical antiferromagnetic (AFM)
structure below TN = 66.5 K with the helix axis along the c axis and with the
ordered moments aligned within the ab-plane. Here we report crystallography,
electrical resistivity, heat capacity, magnetization and magnetic
susceptibility measurements on single crystals of this compound. We demonstrate
that EuCo2P2 is a model molecular-field helical Heisenberg antiferromagnet from
comparisons of the anisotropic magnetic susceptibility chi, high-field
magnetization and magnetic heat capacity of EuCo2P2 single crystals at
temperature T < TN with the predictions of our recent formulation of molecular
field theory. Values of the Heisenberg exchange interactions between the Eu
spins are derived from the data. The low-T magnetic heat capacity ~ T^3 arising
from spin-wave excitations with no anisotropy gap is calculated and found to be
comparable to the lattice heat capacity. The density of states at the Fermi
energy of EuCo2P2 and the related compound BaCo2P2 are found from the heat
capacity data to be large, 10 and 16 states/eV per formula unit for EuCo2P2 and
BaCo2P2, respectively. These values are enhanced by a factor of ~2.5 above
those found from DFT electronic structure calculations for the two compounds.
The calculations also find ferromagnetic Eu-Eu exchange interactions within the
ab-plane and AFM interactions between nearest- and next-nearest planes, in
agreement with the MFT analysis of chi{ab}(T < TN).Comment: 20 pages, 17 figures, 3 tables, 46 references. This is an extended
replacement of arXiv:1512.02958 with an additional coautho
Bose-Einstein condensation in antiferromagnets close to the saturation field
At zero temperature and strong applied magnetic fields the ground sate of an
anisotropic antiferromagnet is a saturated paramagnet with fully aligned spins.
We study the quantum phase transition as the field is reduced below an upper
critical and the system enters a XY-antiferromagnetic phase. Using a
bond operator representation we consider a model spin-1 Heisenberg
antiferromagnetic with single-ion anisotropy in hyper-cubic lattices under
strong magnetic fields. We show that the transition at can be
interpreted as a Bose-Einstein condensation (BEC) of magnons. The theoretical
results are used to analyze our magnetization versus field data in the organic
compound - (DTN) at very low temperatures. This is the
ideal BEC system to study this transition since is sufficiently low to
be reached with static magnetic fields (as opposed to pulsed fields). The
scaling of the magnetization as a function of field and temperature close to
shows excellent agreement with the theoretical predictions. It allows
to obtain the quantum critical exponents and confirm the BEC nature of the
transition at .Comment: 4 pages, 1 figure. Accepted for publication in PRB
Nongauge bright soliton of the nonlinear Schrodinger (NLS) equation and a family of generalized NLS equations
We present an approach to the bright soliton solution of the NLS equation
from the standpoint of introducing a constant potential term in the equation.
We discuss a `nongauge' bright soliton for which both the envelope and the
phase depend only on the traveling variable. We also construct a family of
generalized NLS equations with solitonic sech^p solutions in the traveling
variable and find an exact equivalence with other nonlinear equations, such as
the Korteveg-de Vries and Benjamin-Bona-Mahony equations when p=2Comment: ~4 pages, 3 figures, 16 references, published versio
The onset of solar cycle 24: What global acoustic modes are telling us
We study the response of the low-degree, solar p-mode frequencies to the
unusually extended minimum of solar surface activity since 2007. A total of
4768 days of observations collected by the space-based, Sun-as-a-star
helioseismic GOLF instrument are analyzed. A multi-step iterative
maximum-likelihood fitting method is applied to subseries of 365 days and 91.25
days to extract the p-mode parameters. Temporal variations of the l=0, 1, and 2
p-mode frequencies are then obtained from April 1996 to May 2009. While the
p-mode frequency shifts are closely correlated with solar surface activity
proxies during the past solar cycles, the frequency shifts of the l=0 and l=2
modes show an increase from the second half of 2007, when no significant
surface activity is observable. On the other hand, the l=1 modes follow the
general decreasing trend of the solar surface activity. The different
behaviours between the l=0 and l=2 modes and the l=1 modes can be interpreted
as different geometrical responses to the spatial distribution of the solar
magnetic field beneath the surface of the Sun. The analysis of the low-degree,
solar p-mode frequency shifts indicates that the solar activity cycle 24
started late 2007, despite the absence of activity on the solar surface.Comment: To be accepted by A&A (with minor revisions), 4 pages, 3 figures, 1
tabl
Inferring Networks of Substitutable and Complementary Products
In a modern recommender system, it is important to understand how products
relate to each other. For example, while a user is looking for mobile phones,
it might make sense to recommend other phones, but once they buy a phone, we
might instead want to recommend batteries, cases, or chargers. These two types
of recommendations are referred to as substitutes and complements: substitutes
are products that can be purchased instead of each other, while complements are
products that can be purchased in addition to each other.
Here we develop a method to infer networks of substitutable and complementary
products. We formulate this as a supervised link prediction task, where we
learn the semantics of substitutes and complements from data associated with
products. The primary source of data we use is the text of product reviews,
though our method also makes use of features such as ratings, specifications,
prices, and brands. Methodologically, we build topic models that are trained to
automatically discover topics from text that are successful at predicting and
explaining such relationships. Experimentally, we evaluate our system on the
Amazon product catalog, a large dataset consisting of 9 million products, 237
million links, and 144 million reviews.Comment: 12 pages, 6 figure
Renormalization Constants of Quark Operators for the Non-Perturbatively Improved Wilson Action
We present the results of an extensive lattice calculation of the
renormalization constants of bilinear and four-quark operators for the
non-perturbatively O(a)-improved Wilson action. The results are obtained in the
quenched approximation at four values of the lattice coupling by using the
non-perturbative RI/MOM renormalization method. Several sources of systematic
uncertainties, including discretization errors and final volume effects, are
examined. The contribution of the Goldstone pole, which in some cases may
affect the extrapolation of the renormalization constants to the chiral limit,
is non-perturbatively subtracted. The scale independent renormalization
constants of bilinear quark operators have been also computed by using the
lattice chiral Ward identities approach and compared with those obtained with
the RI-MOM method. For those renormalization constants the non-perturbative
estimates of which have been already presented in the literature we find an
agreement which is typically at the level of 1%.Comment: 36 pages, 13 figures. Minor changes in the text and in one figure.
Accepted for publication on JHE
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