868 research outputs found

    Assessing protein similarity with Gene Ontology and its use in subnuclear localization prediction

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    BACKGROUND: The accomplishment of the various genome sequencing projects resulted in accumulation of massive amount of gene sequence information. This calls for a large-scale computational method for predicting protein localization from sequence. The protein localization can provide valuable information about its molecular function, as well as the biological pathway in which it participates. The prediction of localization of a protein at subnuclear level is a challenging task. In our previous work we proposed an SVM-based system using protein sequence information for this prediction task. In this work, we assess protein similarity with Gene Ontology (GO) and then improve the performance of the system by adding a module of nearest neighbor classifier using a similarity measure derived from the GO annotation terms for protein sequences. RESULTS: The performance of the new system proposed here was compared with our previous system using a set of proteins resided within 6 localizations collected from the Nuclear Protein Database (NPD). The overall MCC (accuracy) is elevated from 0.284 (50.0%) to 0.519 (66.5%) for single-localization proteins in leave-one-out cross-validation; and from 0.420 (65.2%) to 0.541 (65.2%) for an independent set of multi-localization proteins. The new system is available at . CONCLUSION: The prediction of protein subnuclear localizations can be largely influenced by various definitions of similarity for a pair of proteins based on different similarity measures of GO terms. Using the sum of similarity scores over the matched GO term pairs for two proteins as the similarity definition produced the best predictive outcome. Substantial improvement in predicting protein subnuclear localizations has been achieved by combining Gene Ontology with sequence information

    Next-to-leading order QCD predictions for Z0H0+jetZ^0 H^0 + {\rm jet} production at LHC

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    We calculate the complete next-to-leading order (NLO) QCD corrections to the Z0H0Z^0H^0 production in association with a jet at the LHC. We study the impacts of the NLO QCD radiative corrections to the integrated and differential cross sections and the dependence of the cross section on the factorization/renormalization scale. We present the transverse momentum distributions of the final Z0Z^0-, Higgs-boson and leading-jet. We find that the NLO QCD corrections significantly modify the physical observables, and obviously reduce the scale uncertainty of the LO cross section. The QCD K-factors can be 1.183 and 1.180 at the s=14TeV\sqrt{s}=14 TeV and s=7TeV\sqrt{s}=7 TeV LHC respectively, when we adopt the inclusive event selection scheme with pT,jcut=50GeVp_{T,j}^{cut}=50 GeV, mH=120GeVm_H=120 GeV and μ=μr=μf=μ01/2(mZ+mH)\mu=\mu_r=\mu_f=\mu_0 \equiv 1/2(m_Z+m_H). Furthermore, we make the comparison between the two scale choices, μ=μ0\mu=\mu_0 and μ=μ1=1/2(ETZ+ETH+jETjet)\mu=\mu_1=1/2(E_{T}^{Z}+E_{T}^{H}+ \sum_{j}E_{T}^{jet}), and find the scale choice μ=μ1\mu=\mu_1 seems to be more appropriate than the fixed scale μ=μ0\mu=\mu_0.Comment: 18 pages, 7 figure

    MHC class I loci of the Bar-Headed goose (Anser indicus)

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    MHC class I proteins mediate functions in anti-pathogen defense. MHC diversity has already been investigated by many studies in model avian species, but here we chose the bar-headed goose, a worldwide migrant bird, as a non-model avian species. Sequences from exons encoding the peptide-binding region (PBR) of MHC class I molecules were isolated from liver genomic DNA, to investigate variation in these genes. These are the first MHC class I partial sequences of the bar-headed goose to be reported. A preliminary analysis suggests the presence of at least four MHC class I genes, which share great similarity with those of the goose and duck. A phylogenetic analysis of bar-headed goose, goose and duck MHC class I sequences using the NJ method supports the idea that they all cluster within the anseriforms clade

    Chinese Americans’ Views and Use of Family Health History: A Qualitative Study

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    Objective Family health history (FHH) plays a significant role in early disease detection and preven- tion. Although Asian Americans are the fastest growing U.S. immigrant group, no data exists regarding Chinese Americans’ (the largest Asian subgroup) views and use of FHH. This study examines this important issue. Methods Forty-nine adults from southern U.S. Chinese American communities participated in this qualitative, semi-structured, in-depth interview study. Interviews were audio recorded, tran- scribed, and analyzed with a content analysis approach. Results Although the majority of participants perceived the importance of collecting FHH, most lacked FHH knowledge and failed to collect FHH information. Barriers affecting FHH collec- tion and discussion among family members included long-distance separation from family members, self-defined “healthy family,� and Chinese cultural beliefs. Lack of doctors’ inqui- ries, never/rarely visiting physicians, self-defined “healthy family,� perceived insignificance of discussing FHH with doctors, and Chinese cultural beliefs were the obstacles in commu- nicating FHH with physicians. Conclusions Chinese Americans had limited usage of their FHH and faced cultural, distance, knowl- edge-, and healthcare system-related barriers that influenced their FHH use. Developing FHH education programs for Chinese Americans is highly recommended

    Exact score distribution computation for ontological similarity searches

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    <p>Abstract</p> <p>Background</p> <p>Semantic similarity searches in ontologies are an important component of many bioinformatic algorithms, e.g., finding functionally related proteins with the Gene Ontology or phenotypically similar diseases with the Human Phenotype Ontology (HPO). We have recently shown that the performance of semantic similarity searches can be improved by ranking results according to the probability of obtaining a given score at random rather than by the scores themselves. However, to date, there are no algorithms for computing the exact distribution of semantic similarity scores, which is necessary for computing the exact <it>P</it>-value of a given score.</p> <p>Results</p> <p>In this paper we consider the exact computation of score distributions for similarity searches in ontologies, and introduce a simple null hypothesis which can be used to compute a <it>P</it>-value for the statistical significance of similarity scores. We concentrate on measures based on Resnik's definition of ontological similarity. A new algorithm is proposed that collapses subgraphs of the ontology graph and thereby allows fast score distribution computation. The new algorithm is several orders of magnitude faster than the naive approach, as we demonstrate by computing score distributions for similarity searches in the HPO. It is shown that exact <it>P</it>-value calculation improves clinical diagnosis using the HPO compared to approaches based on sampling.</p> <p>Conclusions</p> <p>The new algorithm enables for the first time exact <it>P</it>-value calculation via exact score distribution computation for ontology similarity searches. The approach is applicable to any ontology for which the annotation-propagation rule holds and can improve any bioinformatic method that makes only use of the raw similarity scores. The algorithm was implemented in Java, supports any ontology in OBO format, and is available for non-commercial and academic usage under: <url>https://compbio.charite.de/svn/hpo/trunk/src/tools/significance/</url></p

    Intervention to enhance skilled arm and hand movements after stroke: A feasibility study using a new virtual reality system

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    <p>Abstract</p> <p>Background</p> <p>Rehabilitation programs designed to develop skill in upper extremity (UE) function after stroke require progressive practice that engage and challenge the learner. Virtual realty (VR) provides a unique environment where the presentation of stimuli can be controlled systematically for optimal challenge by adapting task difficulty as performance improves. We describe four VR tasks that were developed and tested to improve arm and hand movement skills for individuals with hemiparesis.</p> <p>Methods</p> <p>Two participants with chronic post-stroke paresis and different levels of motor severity attended 12 training sessions lasting 1 to 2 hours each over a 3-week period. Behavior measures and questionnaires were administered pre-, mid-, and post-training.</p> <p>Results</p> <p>Both participants improved VR task performance across sessions. The less impaired participant averaged more time on task, practiced a greater number of blocks per session, and progressed at a faster rate over sessions than the more impaired participant. Impairment level did not change but both participants improved functional ability after training. The less impaired participant increased the number of blocks moved on the Box & Blocks test while the more impaired participant achieved 4 more items on the Functional Test of the Hemiparetic UE.</p> <p>Conclusion</p> <p>Two participants with differing motor severity were able to engage in VR based practice and improve performance over 12 training sessions. We were able to successfully provide individualized, progressive practice based on each participant's level of movement ability and rate of performance improvement.</p

    Search for the standard model Higgs boson in the H to ZZ to 2l 2nu channel in pp collisions at sqrt(s) = 7 TeV

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    A search for the standard model Higgs boson in the H to ZZ to 2l 2nu decay channel, where l = e or mu, in pp collisions at a center-of-mass energy of 7 TeV is presented. The data were collected at the LHC, with the CMS detector, and correspond to an integrated luminosity of 4.6 inverse femtobarns. No significant excess is observed above the background expectation, and upper limits are set on the Higgs boson production cross section. The presence of the standard model Higgs boson with a mass in the 270-440 GeV range is excluded at 95% confidence level.Comment: Submitted to JHE

    Measurements of fiducial and differential cross sections for Higgs boson production in the diphoton decay channel at s√=8 TeV with ATLAS

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    Measurements of fiducial and differential cross sections are presented for Higgs boson production in proton-proton collisions at a centre-of-mass energy of s√=8 TeV. The analysis is performed in the H → γγ decay channel using 20.3 fb−1 of data recorded by the ATLAS experiment at the CERN Large Hadron Collider. The signal is extracted using a fit to the diphoton invariant mass spectrum assuming that the width of the resonance is much smaller than the experimental resolution. The signal yields are corrected for the effects of detector inefficiency and resolution. The pp → H → γγ fiducial cross section is measured to be 43.2 ±9.4(stat.) − 2.9 + 3.2 (syst.) ±1.2(lumi)fb for a Higgs boson of mass 125.4GeV decaying to two isolated photons that have transverse momentum greater than 35% and 25% of the diphoton invariant mass and each with absolute pseudorapidity less than 2.37. Four additional fiducial cross sections and two cross-section limits are presented in phase space regions that test the theoretical modelling of different Higgs boson production mechanisms, or are sensitive to physics beyond the Standard Model. Differential cross sections are also presented, as a function of variables related to the diphoton kinematics and the jet activity produced in the Higgs boson events. The observed spectra are statistically limited but broadly in line with the theoretical expectations
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