Histopathologic grading of astrocytic tumors based on current WHO criteria offers a valuable but simplified representation of oncologic reality and is often insufficient to predict clinical outcome. In this study, we report a new astrocytic tumor microarray gene expression data set (n = 65). We have used a simple artificial neural network algorithm to address grading of human astrocytic tumors, derive specific transcriptional signatures from histopathologic subtypes of astrocytic tumors, and asses whether these molecular signatures define survival prognostic subclasses. Fifty-nine classifier genes were identified and found to fall within three distinct functional classes, that is, angiogenesis, cell differentiation, and lower-grade astrocytic tumor discrimination. These gene classes were found to characterize three molecular tumor subtypes denoted ANGIO, INTER, and LOWER. Grading of samples using these subtypes agreed with prior histopathologic grading for both our data set (96.15%) and an ...
Gene co-expression network analysis of transcriptome data has enabled the identification of key genes and important networks underlying complex production and disease traits. This study used weighted gene co-expression network analysis (WGCNA) approach to (1) detect modules or clusters of differentially expressed genes (DEG) with similar expression patterns in calf rumen transcriptome during pre- and post-weaning periods and (2) identify regulatory mechanisms linking gene modules to relevant phenotypes during the pre-weaning period (day 33 [d33]): weight gain (BWT_d33), average daily gain (ADG_d33), blood glucose (Glucose_d33) and β-hydroxybutyrate (BHB_d33) concentrations and post-weaning period (d96): weight gain (BWT_d96), average daily gain (ADG_d96), blood glucose (Glucose_d96) and β-hydroxybutyrate (BHB_d96) concentrations, dry matter intake (DMI_d96) and feed efficiency (FE_d96). Rumen tissues were collected from 16 calves on d33 and another 16 on d96 for whole transcriptome sequencing ...
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This is the eleventh post in an article series about MITs lecture course Introduction to Algorithms. In this post I will review lecture sixteen, which introduces the concept of Greedy Algorithms, reviews Graphs and applies the greedy Prims Algorithm to the Minimum Spanning Tree (MST) Problem.. The previous lecture introduced dynamic programming. Dynamic programming was used for finding solutions to optimization problems. In such problems there can be many possible solutions. Each solution has a value, and we want to find a solution with the optimal (minimum or maximum) value. Greedy algorithms are another set of methods for finding optimal solution. A greedy algorithm always makes the choice that looks best at the moment. That is, it makes a locally optimal choice in the hope that this choice will lead to a globally optimal solution. Greedy algorithms do not always yield optimal solutions, but for many problems they do. In this lecture it is shown that a greedy algorithm gives an optimal ...
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The primary goal of this research project was to demonstrate the feasibility of developing an optimal prediction model for noise-induced hearing loss (NIHL) using a radial basis function neural network (RBFNN). The model was developed to predict noise-induced hearing loss (NIHL) from an archive of animal noise exposure data, which contains 900 chinchillas exposed to various noise environments. The
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TY - JOUR. T1 - Ab initio quantum mechanical/molecular mechanical molecular dynamics simulation of enzyme catalysis. T2 - The case of histone lysine methyltransferase SET7/9. AU - Wang, Shenglong. AU - Hu, Po. AU - Zhang, Yingkai. PY - 2007/4/12. Y1 - 2007/4/12. N2 - To elucidate enzyme catalysis through computer simulation, a prerequisite is to reliably compute free energy barriers for both enzyme and solution reactions. By employing on-the-fly Born-Oppenheimer molecular dynamics simulations with the ab initio quantum mechanical/molecular mechanical approach and the umbrella sampling method, we have determined free energy profiles for the methyl-transfer reaction catalyzed by the histone lysine methyltransferase SET7/9 and its corresponding uncatalyzed reaction in aqueous solution, respectively. Our calculated activation free energy barrier for the enzyme catalyzed reaction is 22.5 kcal/mol, which agrees very well with the experimental value of 20.9 kcal/mol. The difference in potential of mean ...
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TY - CONF. T1 - Reward networks changes in the brain of pathological gamblers: a resting state functional magnetic resonance imaging study. AU - Gagliardo, Cesare. AU - La Barbera, Daniele. AU - Piccoli, Tommaso. AU - Marrale, Maurizio. AU - Lagalla, Roberto. AU - Maniaci, Giuseppe. AU - Cannizzaro, Carla. AU - Collura, Giorgio. AU - La Tona, Giuseppe. PY - 2018. Y1 - 2018. N2 - Aims and objectivesTo investigate functional connectivity changes in pathological gamblers (PGs) in comparison to healthy controls (HCs) by means of resting state functional Magnetic Resonance Imaging (RS-fMRI).Methods and materialsThirteen HCs and fourteen PGs were recruited (all right handed males; drugs free; mean age 35.96±9.56). All subjects underwent brain scan using a 1,5T MRI scanner. Activations data of functionally linked brain regions were obtained using a multi-session temporal concatenated Independent Component Analysis (concat-ICA). The resulted components were than matched and compared between groups. ...
... ICGA93 17-22 July, 1993 University of Illinois at Urbana-Champaign PRELIMINARY ANNOUNCEMENT The Fifth International Conference on Genetic Algorithms (ICGA-93), will be held July 17-22, 1993 at the University of Illinois at Urbana-Champaign. This meeting brings together an international community of researchers and practitioners from academia and industry interested in algorithms suggested by the processes of natural evolution. Topics of interest will include the design, analysis, and application of genetic algorithms in optimization and machine learning. Machine learning architectures of interest include classifier systems and connectionist schemes that use genetic algorithms. Papers discussing how genetic algorithms are related to evolving system modeling (e.g., modeling of nervous system evolution, computational ethology, artificial life, economics, etc.) are also encouraged. A formal call for papers for ICGA-93 will be released in the ...
A. Alshekh, Badr Aldwane (2008) Application of superconducting magnetic energy system to damp power system oscillation. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering. A. Aziz, Khairul Azha (2008) Face detection using radial basis function neural networks. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering. A. Latiff, , Liza and Ali, Adel and Fisal, Norsheila and Chia, Ching Ooi (2008) Development of an indoor GPS free self-positioning system for Mobile Ad Hoc Network (MANET). In: Implementation Of Ad Hoc Network In Mobile IP. Penerbit UTM , Johor, pp. 80-96. ISBN 978-983-52-0659-7 A. Rahim, Mohamad Kamal (2008) Design and development of fractal antenna for ultra high frequency band application. Project Report. Faculty of Electrical Engineering, Skudai, Johor. (Unpublished) A. Rahim, Mohamad Kamal (2008) Electromagnetic Band-Gaps Structure In Microwave Device Design. Project Report. Faculty of Electrical Engineering, Skudai, Johor. ...
PURPOSE: Research on the measurement of HIV risk demonstrates that interview mode can affect reporting; however, few studies have applied these findings to assessments of hormonal contraceptive use. This paper examines how audio computer-assisted self-interviewing (ACASI) influenced reports of hormonal contraceptive use and pregnancy among Zimbabwean women.
In a computed protein multiple sequence alignment, the coreness of a column is the fraction of its substitutions that are in so-called core columns of the gold-standard reference alignment of its proteins. In benchmark suites of protein reference alignments, the core columns of the reference alignment are those that can be confidently labeled as correct, usually due to all residues in the column being sufficiently close in the spatial superposition of the known three-dimensional structures of the proteins. Typically the accuracy of a protein multiple sequence alignment that has been computed for a benchmark is only measured with respect to the core columns of the reference alignment. When computing an alignment in practice, however, a reference alignment is not known, so the coreness of its columns can only be predicted. We develop for the first time a predictor of column coreness for protein multiple sequence alignments. This allows us to predict which columns of a computed alignment are core, and
Several stochastic simulation algorithms (SSAs) have been recently proposed for modelling reaction-diffusion processes in cellular and molecular biology. In this talk, two commonly used SSAs will be studied. The first SSA is an on-lattice model described by the reaction-diffusion master equation. The second SSA is an off-lattice model based on the simulation of Brownian motion of individual molecules and their reactive collisions. The connections between SSAs and the deterministic models (based on reaction-diffusion PDEs) will be presented. I will consider chemical reactions both at a surface and in the bulk. I will show how the microscopic parameters should be chosen to achieve the correct macroscopic reaction rate. This choice is found to depend on which SSA is used. I will also present multiscale algorithms which use models with a different level of detail in different parts of the computational domain ...
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Markov Chain Monte Carlo simulation has received considerable attention within the past decade as reportedly one of the most powerful techniques for the first passage probability estimation of dynamic systems. A very popular method in this direction capable of estimating probability of rare events with low computation cost is the subset simulation (SS). The idea of the method is to break a rare event into a sequence of more probable events which are easy to be estimated based on the conditional simulation techniques. Recently, two algorithms have been proposed in order to increase the efficiency of the method by modifying the conditional sampler. In this paper, applicability of the original SS is compared to the recently introduced modifications of the method on a wind turbine model. The model incorporates a PID pitch controller which aims at keeping the rotational speed of the wind turbine rotor equal to its nominal value. Finally Monte Carlo simulations are performed which allow assessment of ...
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In this paper we propose an energy-efficient object tracking algorithm in wireless sensor networks (WSNs). Such sensor networks have to be designed to achieve energy-efficient object tracking for any given arbitrary topology. We consider in particular the bi-directional moving objects with given frequencies for each pair of sensor nodes and link transmission cost. This problem is formulated as a 0/1 integer-programming problem. A Lagrangean relaxation-based (LR-based) heuristic algorithm is proposed for solving the optimization problem. Experimental results showed that the proposed algorithm achieves near optimization in energy-efficient object tracking. Furthermore, the algorithm is very efficient and scalable in terms of the solution time.
A method of writing servo signals on a magnetic tape which comprises irradiating one end of an optical fiber bundle (12) comprising a plurality of optical fibers (11) arrayed in parallel with each other with laser light, transmitting the laser light (24) emitted from the other end as an output light source through a condensing lens (13), and irradiating a site of a magnetic tape running at a prescribed speed, the site being capable of forming servo tracks, with the laser light passed through the condensing lens (13) to form real images (25) equal to or smaller in size than the output light source to cause the site to change physically or chemically thereby forming a plurality of servo track patterns (S) in the longitudinal direction of the tape at a smaller pitch than the pitch of the optical fibers (11) arrayed in the optical fiber bundle (12).
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A Monte Carlo study of the transient response of single photon absorption in X-ray pixel detectors is presented. The simulation results have been combined with Monte Carlo simulation of the X-ray photon transport and absorption, and used to estimate the image properties of a detector system, including the pixel array and readout electronics. The study includes several different simulation challenges, such as full band Monte Carlo simulation of charge transport in large devices (300 mu m * 100 mu m), modelling of three-dimensional electrostatic effects using cylindrical coordinates, Monte Carlo simulation of photon transport and absorption, and a system level Monte Carlo simulation of the entire pixel detector and readout. ...
TY - JOUR. T1 - Artificial intelligence to detect tympanic membrane perforations. AU - Habib, A.-R.. AU - Wong, E.. AU - Sacks, R.. AU - Singh, N.. PY - 2020/4/1. Y1 - 2020/4/1. N2 - Objective. To explore the feasibility of constructing a proof-of-concept artificial intelligence algorithm to detect tympanic membrane perforations, for future application in under-resourced rural settings. Methods A retrospective review was conducted of otoscopic images analysed using transfer learning with Googles Inception-V3 convolutional neural network architecture. The gold standard ground truth was defined by otolaryngologists. Perforation size was categorised as less than one-third (small), one-third to two-thirds (medium), or more than two-thirds (large) of the total tympanic membrane diameter. Results A total of 233 tympanic membrane images were used (183 for training, 50 for testing). The algorithm correctly identified intact and perforated tympanic membranes (overall accuracy = 76.0 per cent, 95 per ...
The terahertz (THz) spectra in the range of 0.2-1.6 THz (6.6-52.8 cm−1) of wheat grains with various degrees of deterioration (normal, worm-eaten, moldy, and sprouting wheat grains) were investigated by terahertz time domain spectroscopy. Principal component analysis (PCA) was employed to extract feature data according to the cumulative contribution rates; the top four principal components were selected, and then a support vector machine (SVM) method was applied. Several selection kernels (linear, polynomial, and radial basis functions) were applied to identify the four types of wheat grain. The results showed that the materials were identified with an accuracy of nearly 95%. Furthermore, this approach was compared with others (principal component regression, partial least squares regression, and back-propagation neural networks). The comparisons showed that PCA-SVM outperformed the others and also indicated that the proposed method of THz technology combined with PCA-SVM is efficient and ...
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Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimers, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to ...
Author(s): Connolly, CG; Wu, J; Ho, TC; Hoeft, F; Wolkowitz, O; Eisendrath, S; Frank, G; Hendren, R; Max, JE; Paulus, MP; Tapert, SF; Banerjee, D; Simmons, AN; Yang, TT | Abstract: Background Very few studies have been performed to understand the underlying neural substrates of adolescent major depressive disorder (MDD). Studies in depressed adults have demonstrated that the subgenual anterior cingulate cortex (sgACC) plays a pivotal role in depression and have revealed aberrant patterns of resting-state functional connectivity (RSFC). Here, we examine the RSFC of the sgACC in medication-naïve first-episode adolescents with MDD. Methods Twenty-three adolescents with MDD and 36 well-matched control subjects underwent functional magnetic resonance imaging to assess the RSFC of the sgACC. Results We observed elevated connectivity between the sgACC and the insula and between the sgACC and the amygdala in the MDD group compared with the control subjects. Decreased connectivity between the sgACC and the
HIGHLIGHTS. All accepted papers will be published by Springer and made available through Springer-Link Digital Library, one of the worlds largest scientific libraries.. CONFERENCE TOPICS. INTELLIGENT COMPUTING AND APPLICATIONS: Artificial intelligence, Quantum computing, Artificial Neural Networks, Self - Organizing, Fuzzy logic, Membrane computing, Evolutionary computation, Learning theory, Probabilistic methods, Image processing Computer vision, Speech recognition, Big data, Evolutionary algorithm, Randomness Monte Carlo methods, Algorithmic probability, Chaos theory, Cryptography, Game theory, Information theory, Pattern recognition, Natural computing, Evolutionary robotics Knowledge-based system, Machine learning, Unsupervised learning, Computational finance, Computational economics, and DNA computing. OPTIMIZATION AND APPLICATIONS: Ant colony optimization, Artificial bee colony, Artificial immune systems, Artificial neural networks, Automatic computing, Bacterial foraging, Biological ...
International Conference on Computer Graphics Theory and Applications 2015. GRAPP 2015 is part of 10th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.
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Deep neural networks have recently been applied to the study of brain disorders such as autism spectrum disorder (ASD) with great success. However, the internal logics of these networks are difficult to interpret, especially with regard to how specific network architecture decisions are made. In this paper, we study an interpretable neural network model as a method to identify ASD participants from functional magnetic resonance imaging (fMRI) data and interpret results of the model in a precise and consistent manner. First, we propose an interpretable fully connected neural network (FCNN) to classify two groups, ASD versus healthy controls (HC), based on input data from resting-state functional connectivity (rsFC) between regions of interests (ROIs). The proposed FCNN model is a piecewise linear neural network (PLNN) which uses piecewise linear function LeakyReLU as its activation function. We experimentally compared the FCNN model against widely used classification models including support vector
Title: A Research on Bioinformatics Prediction of Protein Subcellular Localization. VOLUME: 4 ISSUE: 3. Author(s):Gang Fang, Guirong Tao and Shemin Zhang. Affiliation:Department of Life Science, Xian University of Arts and Science, Xian 710065, China.. Keywords:Bioinformatics, prediction, protein subcellular localization, localizome, proteomics, database. Abstract: Protein subcellular localization is one of the key characteristic to understand its biological function. Proteins are transported to specific organelles and suborganelles after they are synthesized. They take part in cell activity and function efficiently when correctly localized. Inaccurate subcellular localization will have great impact on cellular function. Prediction of protein subcellular localization is one of the important areas in protein function research. Now it becomes the hot issue in bioinformatics. In this review paper, the recent progress on bioinformatics research of protein subcellular localization and its prospect ...
Chronic insomnia which can cause daytime function impairments like abnormal emotion and hypomnesis is important risk factors for developing cardiovascular disease, neurological disorders or mental disorders. Acupuncture is a widely recognized therapy to treat chronic insomnia in clinical practice. Previous researches presented that sleep-wake dysfunction of patients with chronic insomnia have strong correlation with abnormal of the default mode network and salience network. The project present acupuncture may improve sleep quality by adjusting the abnormal default mode network and the salience network in patients with chronic insomnia.. The investigators are assigned the ninety eligible participants in three groups: thirty chronic insomnia patients by true acupuncture treatment (Zhoushi coordinated points), thirty chronic insomnia patients by sham acupuncture stimulation (non-acupoint points) and thirty healthy subjects, Treatment will be given 3 times per week for 3 months. Additionally, two ...
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Background The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test
TY - JOUR. T1 - Effects of Naltrexone on Large-Scale Network Interactions in Methamphetamine Use Disorder. AU - Kohno, Milky. AU - Morales, Angelica M.. AU - Dennis, Laura E.. AU - McCready, Holly. AU - Hoffman, William F.. AU - Korthuis, P. Todd. PY - 2019/9/3. Y1 - 2019/9/3. N2 - Naltrexone attenuates craving, and the subjective effects of methamphetamine and extended-release naltrexone (XR-NTX) reduces functional connectivity between regions of the striatum and limbic cortex. Naltrexone modulates neural activity at dopaminergic synapses; however, it is unclear whether naltrexone has an effect on large-scale brain networks. Functional networks interact to coordinate behavior, and as substance-use disorders are associated with an imbalance between reward and cognitive control networks, treatment approaches that target interactive brain systems underlying addiction may be a useful adjunct for behavioral therapies. The objective of this study was to examine the effect of XR-NTX on large-scale ...
Molecular dynamics simulations were used to investigate trends in noble gas (Ar, Kr, Xe) diffusion in the metal-organic frameworks HKUST-1 and ZIF-8. Diffusion occurs primarily through inter-cage jump events, with much greater diffusion of guest atoms in HKUST-1 compared to ZIF-8 due to the larger cage and window sizes in the former. We compare diffusion coefficients calculated for both rigid and flexible frameworks. For rigid framework simulations, in which the framework atoms were held at their crystallographic or geometry optimized coordinates, sometimes dramatic differences in guest diffusion were seen depending on the initial framework structure or the choice of framework force field parameters. When framework flexibility effects were included, argon and krypton diffusion increased significantly compared to rigid-framework simulations using general force field parameters. Additionally, for argon and krypton in ZIF-8, guest diffusion increased with loading, demonstrating that guest-guest ...
Task-based fMRI has been used to study the effects of experimental inflammation on the human brain, but it remains unknown whether intrinsic connectivity in the brain at rest changes during a sickness response. Here, we investigated the effect of experimental inflammation on connectivity between areas relevant for monitoring of bodily states, motivation, and subjective symptoms of sickness. In a double blind randomized controlled trial, 52 healthy volunteers were injected with 0.6 ng/kg LPS (lipopolysaccharide) or placebo, and participated in a resting state fMRI experiment after approximately 2h 45 minutes. Resting state fMRI data were available from 48 participants, of which 28 received LPS and 20 received placebo. Bilateral anterior and bilateral posterior insula sections were used as seed regions and connectivity with bilateral orbitofrontal and cingulate (anterior and middle) cortices was investigated. Back pain, headache and global sickness increased significantly after as compared to ...
Research of the Section for Artificial Intelligence and Decision Support (AID) focusses on Artificial Intelligence technology and computer-based decison support and its use in the medical domain. This includes the development of software systems for intelligent data analysis, knowledge-based systems technology for decision support and therapy planning, and natural language processing which deals with automatic processing of text and speech.. The department offers lectures in Artificial Intelligence on an introductory as well as an advanced level. With regard to particular study programmes, we offer courses for students of Medicine and of Medical Informatics, as well as for students of the Middle European Master Programme in Cognitive Science. Courses are also offered for computer science students in a cooperation with the University of Vienna.. The department was founded in 1977 as an institute of the Medical Faculty of the University of Vienna. In 2004, it became part of the Center for Brain ...
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Ornithine cyclodeaminase (OCD) is an NAD+-dependent deaminase that is found in bacterial species such as Pseudomonas putida. Importantly, it catalyzes the direct conversion of the amino acid L-ornithine to L-proline. Using molecular dynamics (MD) and a hybrid quantum mechanics/molecular mechanics (QM/MM) method in the ONIOM formalism, the catalytic mechanism of OCD has been examined. The rate limiting step is calculated to be the initial step in the overall mechanism: hydride transfer from the L-ornithines Cα-H group to the NAD+ cofactor with concomitant formation of a Cα=NH2+ Schiff base with a barrier of 90.6 kJ mol−1. Importantly, no water is observed within the active site during the MD simulations suitably positioned to hydrolyze the Cα=NH2+ intermediate to form the corresponding carbonyl. Instead, the reaction proceeds via a non-hydrolytic mechanism involving direct nucleophilic attack of the δ-amine at the Cα-position. This is then followed by cleavage and loss of the α-NH2 group to give
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OVERNIGHT CLOSED-LOOP INSULIN DELIVERY WITH MODEL PREDICTIVE CONTROL AND GLUCOSE MEASUREMENT ERROR MODEL - A closed-loop system for insulin infusion overnight uses a model predictive control algorithm ("MPC"). Used with the MPC is a glucose measurement error model which was derived from actual glucose sensor error data. That sensor error data included both a sensor artifacts component, including dropouts, and a persistent error component, including calibration error, all of which was obtained experimentally from living subjects. The MPC algorithm advised on insulin infusion every fifteen minutes. Sensor glucose input to the MPC was obtained by combining model-calculated, noise-free interstitial glucose with experimentally-derived transient and persistent sensor artifacts associated with the FreeStyle Navigator® Continuous Glucose Monitor System ("FSN"). The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during simulated overnight closed-loop control ...
Objective: Vestibular signals are involved in higher cortical functions like spatial orientation and its disorders. Vestibular dysfunction contributes, for example, to spatial neglect which can be transiently improved by caloric stimulation. The exact roles and mechanisms of the vestibular and visual systems for the recovery of neglect are not yet known. Methods: Resting-state functional connectivity (fc) magnetic resonance imaging was recorded in a patient with hemispatial neglect during the acute phase and after recovery 6 months later following a right middle cerebral artery infarction before and after caloric vestibular stimulation. Seeds in the vestibular [parietal operculum (OP2)], the parietal [posterior parietal cortex (PPC);7A, hIP3], and the visual cortex (VC) were used for the analysis. Results: During the acute stage after caloric stimulation the fc of the right OP2 to the left OP2, the anterior cingulum, and the para/hippocampus was increased bilaterally (i.e., the vestibular ...
The combination of gene expression profiling with linkage analysis has become a powerful paradigm for mapping gene expression quantitative trait loci (eQTL). To date, most studies have searched for eQTL by analyzing gene expression traits one at a time. As thousands of expression traits are typically analyzed, this can reduce power because of the need to correct for the number of hypothesis tests performed. In addition, gene expression traits exhibit a complex correlation structure, which is ignored when analyzing traits individually. To address these issues, we applied two different multivariate dimension reduction techniques, the Singular Value Decomposition (SVD) and Independent Component Analysis (ICA) to gene expression traits derived from a cross between two strains of Saccharomyces cerevisiae. Both methods decompose the data into a set of meta-traits, which are linear combinations of all the expression traits. The meta-traits were enriched for several Gene Ontology categories including metabolic
Aromatase is a member of the cytochrome P450 family responsible for catalyzing the rate-limiting conversion of androgens to estrogens. In the pursuit of robust aromatase inhibitors, quantitative structure-activity relationship (QSAR) and classification structure-activity relationship (CSAR) studies were performed on a non-redundant set of 63 flavonoids using multiple linear regression, artificial neural network, support vector machine and decision tree approaches. Easy-to-interpret descriptors providing comprehensive coverage on general characteristics of molecules (i.e., molecular size, flexibility, polarity, solubility, charge and electronic properties) were employed to describe the unique physicochemical properties of the investigated flavonoids. QSAR models provided good predictive performance as observed from their statistical parameters with Q values in the range of 0.8014 and 0.9870 for the cross-validation set and Q values in the range of 0.8966 and 0.9943 for the external test set. ...
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The topics of interest to the conference include, but are not limited to:. Computer Science: Information Technology, Green Computing, Machine Learning, Smart Computing, Predictive Analysis, Mobile Programming, big data, Computer architecture, Computational & Synthetic Biology, Computer Graphics, Vision, Animation, Game Science, Computing for Development, Data Management, Human Computer Interaction, Natural Language Processing, Programming Languages and Software Engineering, Robotics, Security & Privacy, Systems and Networking, Theory of Computation, Ubiquitous Computing, Wireless and Sensor Systems, Using IT to reduce carbon emissions, Energy-aware computing, Smart grid and micro grids, Sustainable computing.. Optimization: Mathematical Programming, Continues optimization, Combinatorial optimization, Discreet optimization, Ant colony optimization, Fuzzy logic, Genetic algorithm, Genetic programming, variable neighbourhood search, Support vector machine, Cuckoo search, Simulated annealing, Bat ...
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