3,556 research outputs found
Prediction of protein structural classes for low-homology sequences based on predicted secondary structure
<p>Abstract</p> <p>Background</p> <p>Prediction of protein structural classes (<it>α</it>, <it>β</it>, <it>α </it>+ <it>β </it>and <it>α</it>/<it>β</it>) from amino acid sequences is of great importance, as it is beneficial to study protein function, regulation and interactions. Many methods have been developed for high-homology protein sequences, and the prediction accuracies can achieve up to 90%. However, for low-homology sequences whose average pairwise sequence identity lies between 20% and 40%, they perform relatively poorly, yielding the prediction accuracy often below 60%.</p> <p>Results</p> <p>We propose a new method to predict protein structural classes on the basis of features extracted from the predicted secondary structures of proteins rather than directly from their amino acid sequences. It first uses PSIPRED to predict the secondary structure for each protein sequence. Then, the <it>chaos game representation </it>is employed to represent the predicted secondary structure as two time series, from which we generate a comprehensive set of 24 features using <it>recurrence quantification analysis</it>, <it>K-string based information entropy </it>and <it>segment-based analysis</it>. The resulting feature vectors are finally fed into a simple yet powerful Fisher's discriminant algorithm for the prediction of protein structural classes. We tested the proposed method on three benchmark datasets in low homology and achieved the overall prediction accuracies of 82.9%, 83.1% and 81.3%, respectively. Comparisons with ten existing methods showed that our method consistently performs better for all the tested datasets and the overall accuracy improvements range from 2.3% to 27.5%. A web server that implements the proposed method is freely available at <url>http://www1.spms.ntu.edu.sg/~chenxin/RKS_PPSC/</url>.</p> <p>Conclusion</p> <p>The high prediction accuracy achieved by our proposed method is attributed to the design of a comprehensive feature set on the predicted secondary structure sequences, which is capable of characterizing the sequence order information, local interactions of the secondary structural elements, and spacial arrangements of <it>α </it>helices and <it>β </it>strands. Thus, it is a valuable method to predict protein structural classes particularly for low-homology amino acid sequences.</p
Future directions for the management of pain in osteoarthritis.
Osteoarthritis (OA) is the predominant form of arthritis worldwide, resulting in a high degree of functional impairment and reduced quality of life owing to chronic pain. To date, there are no treatments that are known to modify disease progression of OA in the long term. Current treatments are largely based on the modulation of pain, including NSAIDs, opiates and, more recently, centrally acting pharmacotherapies to avert pain. This review will focus on the rationale for new avenues in pain modulation, including inhibition with anti-NGF antibodies and centrally acting analgesics. The authors also consider the potential for structure modification in cartilage/bone using growth factors and stem cell therapies. The possible mismatch between structural change and pain perception will also be discussed, introducing recent techniques that may assist in improved patient phenotyping of pain subsets in OA. Such developments could help further stratify subgroups and treatments for people with OA in future
Microscopics of Extremal Kerr from Spinning M5 Branes
We show that the spinning magnetic one-brane in minimal five-dimensional
supergravity admits a decoupling limit that interpolates smoothly between a
self-dual null orbifold of AdS_3 \times S^2 and the near-horizon limit of the
extremal Kerr black hole times a circle. We use this interpolating solution to
understand the field theory dual to spinning M5 branes as a deformation of the
Discrete Light Cone Quantized (DLCQ) Maldacena-Stominger-Witten (MSW) CFT. In
particular, the conformal weights of the operators dual to the deformation
around AdS_3 \times S^2 are calculated. We present pieces of evidence showing
that a CFT dual to the four-dimensional extremal Kerr can be obtained from the
deformed MSW CFT.Comment: 5 page
Security and Efficiency Analysis of the Hamming Distance Computation Protocol Based on Oblivious Transfer
open access articleBringer et al. proposed two cryptographic protocols for the computation of Hamming distance. Their first scheme uses Oblivious Transfer and provides security in the semi-honest model. The other scheme uses Committed Oblivious Transfer and is claimed to provide full security in the malicious case. The proposed protocols have direct implications to biometric authentication schemes between a prover and a verifier where the verifier has biometric data of the users in plain form.
In this paper, we show that their protocol is not actually fully secure against malicious adversaries. More precisely, our attack breaks the soundness property of their protocol where a malicious user can compute a Hamming distance which is different from the actual value. For biometric authentication systems, this attack allows a malicious adversary to pass the authentication without knowledge of the honest user's input with at most complexity instead of , where is the input length. We propose an enhanced version of their protocol where this attack is eliminated. The security of our modified protocol is proven using the simulation-based paradigm. Furthermore, as for efficiency concerns, the modified protocol utilizes Verifiable Oblivious Transfer which does not require the commitments to outputs which improves its efficiency significantly
Kinetic Theory Approach to Modeling of Cellular Repair Mechanisms under Genome Stress
Under acute perturbations from outer environment, a normal cell can trigger cellular self-defense mechanism in response to genome stress. To investigate the kinetics of cellular self-repair process at single cell level further, a model of DNA damage generating and repair is proposed under acute Ion Radiation (IR) by using mathematical framework of kinetic theory of active particles (KTAP). Firstly, we focus on illustrating the profile of Cellular Repair System (CRS) instituted by two sub-populations, each of which is made up of the active particles with different discrete states. Then, we implement the mathematical framework of cellular self-repair mechanism, and illustrate the dynamic processes of Double Strand Breaks (DSBs) and Repair Protein (RP) generating, DSB-protein complexes (DSBCs) synthesizing, and toxins accumulating. Finally, we roughly analyze the capability of cellular self-repair mechanism, cellular activity of transferring DNA damage, and genome stability, especially the different fates of a certain cell before and after the time thresholds of IR perturbations that a cell can tolerate maximally under different IR perturbation circumstances
Noiseless Linear Amplification and Distillation of Entanglement
The idea of signal amplification is ubiquitous in the control of physical
systems, and the ultimate performance limit of amplifiers is set by quantum
physics. Increasing the amplitude of an unknown quantum optical field, or more
generally any harmonic oscillator state, must introduce noise. This linear
amplification noise prevents the perfect copying of the quantum state, enforces
quantum limits on communications and metrology, and is the physical mechanism
that prevents the increase of entanglement via local operations. It is known
that non-deterministic versions of ideal cloning and local entanglement
increase (distillation) are allowed, suggesting the possibility of
non-deterministic noiseless linear amplification. Here we introduce, and
experimentally demonstrate, such a noiseless linear amplifier for
continuous-variables states of the optical field, and use it to demonstrate
entanglement distillation of field-mode entanglement. This simple but powerful
circuit can form the basis of practical devices for enhancing quantum
technologies. The idea of noiseless amplification unifies approaches to cloning
and distillation, and will find applications in quantum metrology and
communications.Comment: Submitted 10 June 200
Predicting Transcriptional Activity of Multiple Site p53 Mutants Based on Hybrid Properties
As an important tumor suppressor protein, reactivate mutated p53 was found in many kinds of human cancers and that restoring active p53 would lead to tumor regression. In this work, we developed a new computational method to predict the transcriptional activity for one-, two-, three- and four-site p53 mutants, respectively. With the approach from the general form of pseudo amino acid composition, we used eight types of features to represent the mutation and then selected the optimal prediction features based on the maximum relevance, minimum redundancy, and incremental feature selection methods. The Mathew's correlation coefficients (MCC) obtained by using nearest neighbor algorithm and jackknife cross validation for one-, two-, three- and four-site p53 mutants were 0.678, 0.314, 0.705, and 0.907, respectively. It was revealed by the further optimal feature set analysis that the 2D (two-dimensional) structure features composed the largest part of the optimal feature set and maybe played the most important roles in all four types of p53 mutant active status prediction. It was also demonstrated by the optimal feature sets, especially those at the top level, that the 3D structure features, conservation, physicochemical and biochemical properties of amino acid near the mutation site, also played quite important roles for p53 mutant active status prediction. Our study has provided a new and promising approach for finding functionally important sites and the relevant features for in-depth study of p53 protein and its action mechanism
The Quantum Internet
Quantum networks offer a unifying set of opportunities and challenges across
exciting intellectual and technical frontiers, including for quantum
computation, communication, and metrology. The realization of quantum networks
composed of many nodes and channels requires new scientific capabilities for
the generation and characterization of quantum coherence and entanglement.
Fundamental to this endeavor are quantum interconnects that convert quantum
states from one physical system to those of another in a reversible fashion.
Such quantum connectivity for networks can be achieved by optical interactions
of single photons and atoms, thereby enabling entanglement distribution and
quantum teleportation between nodes.Comment: 15 pages, 6 figures Higher resolution versions of the figures can be
downloaded from the following link:
http://www.its.caltech.edu/~hjkimble/QNet-figures-high-resolutio
An Elementary Quantum Network of Single Atoms in Optical Cavities
Quantum networks are distributed quantum many-body systems with tailored
topology and controlled information exchange. They are the backbone of
distributed quantum computing architectures and quantum communication. Here we
present a prototype of such a quantum network based on single atoms embedded in
optical cavities. We show that atom-cavity systems form universal nodes capable
of sending, receiving, storing and releasing photonic quantum information.
Quantum connectivity between nodes is achieved in the conceptually most
fundamental way: by the coherent exchange of a single photon. We demonstrate
the faithful transfer of an atomic quantum state and the creation of
entanglement between two identical nodes in independent laboratories. The
created nonlocal state is manipulated by local qubit rotation. This efficient
cavity-based approach to quantum networking is particularly promising as it
offers a clear perspective for scalability, thus paving the way towards
large-scale quantum networks and their applications.Comment: 8 pages, 5 figure
- …