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Sample records for predicts functional association

  1. Gene Function Prediction from Functional Association Networks Using Kernel Partial Least Squares Regression

    PubMed Central

    Lehtinen, Sonja; Lees, Jon; Bähler, Jürg; Shawe-Taylor, John; Orengo, Christine

    2015-01-01

    With the growing availability of large-scale biological datasets, automated methods of extracting functionally meaningful information from this data are becoming increasingly important. Data relating to functional association between genes or proteins, such as co-expression or functional association, is often represented in terms of gene or protein networks. Several methods of predicting gene function from these networks have been proposed. However, evaluating the relative performance of these algorithms may not be trivial: concerns have been raised over biases in different benchmarking methods and datasets, particularly relating to non-independence of functional association data and test data. In this paper we propose a new network-based gene function prediction algorithm using a commute-time kernel and partial least squares regression (Compass). We compare Compass to GeneMANIA, a leading network-based prediction algorithm, using a number of different benchmarks, and find that Compass outperforms GeneMANIA on these benchmarks. We also explicitly explore problems associated with the non-independence of functional association data and test data. We find that a benchmark based on the Gene Ontology database, which, directly or indirectly, incorporates information from other databases, may considerably overestimate the performance of algorithms exploiting functional association data for prediction. PMID:26288239

  2. Biological interpretation of genome-wide association studies using predicted gene functions.

    PubMed

    Pers, Tune H; Karjalainen, Juha M; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R; Yang, Jian; Lui, Julian C; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S N; Hirschhorn, Joel N; Franke, Lude

    2015-01-01

    The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. PMID:25597830

  3. Integrated protein function prediction by mining function associations, sequences, and protein–protein and gene–gene interaction networks

    PubMed Central

    Cao, Renzhi; Cheng, Jianlin

    2016-01-01

    Motivations Protein function prediction is an important and challenging problem in bioinformatics and computational biology. Functionally relevant biological information such as protein sequences, gene expression, and protein–protein interactions has been used mostly separately for protein function prediction. One of the major challenges is how to effectively integrate multiple sources of both traditional and new information such as spatial gene–gene interaction networks generated from chromosomal conformation data together to improve protein function prediction. Results In this work, we developed three different probabilistic scores (MIS, SEQ, and NET score) to combine protein sequence, function associations, and protein–protein interaction and spatial gene–gene interaction networks for protein function prediction. The MIS score is mainly generated from homologous proteins found by PSI-BLAST search, and also association rules between Gene Ontology terms, which are learned by mining the Swiss-Prot database. The SEQ score is generated from protein sequences. The NET score is generated from protein–protein interaction and spatial gene–gene interaction networks. These three scores were combined in a new Statistical Multiple Integrative Scoring System (SMISS) to predict protein function. We tested SMISS on the data set of 2011 Critical Assessment of Function Annotation (CAFA). The method performed substantially better than three base-line methods and an advanced method based on protein profile–sequence comparison, profile–profile comparison, and domain co-occurrence networks according to the maximum F-measure. PMID:26370280

  4. Are Executive Functioning Deficits Concurrently and Predictively Associated with Depressive and Anxiety Symptoms in Adolescents?

    PubMed

    Han, Georges; Helm, Jonathan; Iucha, Cornelia; Zahn-Waxler, Carolyn; Hastings, Paul D; Klimes-Dougan, Bonnie

    2016-01-01

    The central objective of the current study was to evaluate how executive functions (EF), and specifically cognitive flexibility, were concurrently and predictively associated with anxiety and depressive symptoms in adolescence. Adolescents (N = 220) and their parents participated in this longitudinal investigation. Adolescents' EF was assessed by the Wisconsin Card Sorting Test (WCST) during the initial assessment, and symptoms of depressive and anxiety disorders were reported by mothers and youths concurrently and 2 years later. Correlational analyses suggested that youths who made more total errors (TE), including both perseverative errors (PE) and nonperseverative errors (NPE), concurrently exhibited significantly more depressive symptoms. Adolescents who made more TE and those who made more NPE tended to have more anxiety symptoms 2 years later. Structural equation modeling analyses accounting for key explanatory variables (e.g., IQ, disruptive behavior disorders, and attention deficit hyperactive disorder) showed that TE was concurrently associated with parent reports of adolescent depressive symptoms. The results suggest internalizing psychopathology is associated with global (TE) and nonspecific (NPE) EF difficulties but not robustly associated with cognitive inflexibility (PE). Future research with the WCST should consider different sources of errors that are posited to reflect divergent underlying neural mechanisms, conferring differential vulnerability for emerging mental health problems. PMID:26042358

  5. Composition and predicted functional ecology of mussel-associated bacteria in Indonesian marine lakes.

    PubMed

    Cleary, Daniel F R; Becking, Leontine E; Polónia, Ana R M; Freitas, Rossana M; Gomes, Newton C M

    2015-03-01

    In the present study, we sampled bacterial communities associated with mussels inhabiting two distinct coastal marine ecosystems in Kalimantan, Indonesia, namely, marine lakes and coastal mangroves. We used 16S rRNA gene pyrosequencing and predicted metagenomic analysis to compare microbial composition and function. Marine lakes are small landlocked bodies of seawater isolated to varying degrees from the open sea environment. They contain numerous endemic taxa and represent natural laboratories of speciation. Our primary goals were to (1) use BLAST search to identify closely related organisms to dominant bacterial OTUs in our mussel dataset and (2) to compare bacterial communities and enrichment in the predicted bacterial metagenome among lakes. Our sequencing effort yielded 3553 OTUs belonging to 44 phyla, 99 classes and 121 orders. Mussels in the largest marine lake (Kakaban) and the coastal mangrove habitat were dominated by bacteria belonging to the phylum Proteobacteria whereas smaller lakes, located on the island of Maratua, were dominated by bacteria belonging to the phyla Firmicutes and Tenericutes. The single most abundant OTU overall was assigned to the genus Mycoplasma. There were several significant differences among locations with respect to metabolic pathways. These included enrichment of xenobiotic biodegradation pathways in the largest marine lake and coastal mangrove. These locations were also the most enriched with respect to nitrogen metabolism. The presence of genes related to isoquinoline alkaloids, polyketides, hydrolases, mono and dioxygenases in the predicted analysis of functional pathways is an indication that the bacterial communities of Brachidontes mussels may be potentially important sources of new marine medicines and enzymes of industrial interest. Future work should focus on measuring how mussel microbial communities influence nutrient dynamics within the marine lake environment and isolating microbes with potential biotechnological

  6. PTMcode: a database of known and predicted functional associations between post-translational modifications in proteins

    PubMed Central

    Minguez, Pablo; Letunic, Ivica; Parca, Luca; Bork, Peer

    2013-01-01

    Post-translational modifications (PTMs) are involved in the regulation and structural stabilization of eukaryotic proteins. The combination of individual PTM states is a key to modulate cellular functions as became evident in a few well-studied proteins. This combinatorial setting, dubbed the PTM code, has been proposed to be extended to whole proteomes in eukaryotes. Although we are still far from deciphering such a complex language, thousands of protein PTM sites are being mapped by high-throughput technologies, thus providing sufficient data for comparative analysis. PTMcode (http://ptmcode.embl.de) aims to compile known and predicted PTM associations to provide a framework that would enable hypothesis-driven experimental or computational analysis of various scales. In its first release, PTMcode provides PTM functional associations of 13 different PTM types within proteins in 8 eukaryotes. They are based on five evidence channels: a literature survey, residue co-evolution, structural proximity, PTMs at the same residue and location within PTM highly enriched protein regions (hotspots). PTMcode is presented as a protein-based searchable database with an interactive web interface providing the context of the co-regulation of nearly 75 000 residues in >10 000 proteins. PMID:23193284

  7. Identification and functional prediction of mitochondrial complex III and IV mutations associated with glioblastoma

    PubMed Central

    Lloyd, Rhiannon E.; Keatley, Kathleen; Littlewood, D. Timothy J.; Meunier, Brigitte; Holt, William V.; An, Qian; Higgins, Samantha C.; Polyzoidis, Stavros; Stephenson, Katie F.; Ashkan, Keyoumars; Fillmore, Helen L.; Pilkington, Geoffrey J.; McGeehan, John E.

    2015-01-01

    Background Glioblastoma (GBM) is the most common primary brain tumor in adults, with a dismal prognosis. Treatment is hampered by GBM's unique biology, including differential cell response to therapy. Although several mitochondrial abnormalities have been identified, how mitochondrial DNA (mtDNA) mutations contribute to GBM biology and therapeutic response remains poorly described. We sought to determine the spectrum of functional complex III and IV mtDNA mutations in GBM. Methods The complete mitochondrial genomes of 10 GBM cell lines were obtained using next-generation sequencing and combined with another set obtained from 32 GBM tissues. Three-dimensional structural mapping and analysis of all the nonsynonymous mutations identified in complex III and IV proteins was then performed to investigate functional importance. Results Over 200 mutations were identified in the mtDNAs, including a significant proportion with very low mutational loads. Twenty-five were nonsynonymous mutations in complex III and IV, 9 of which were predicted to be functional and affect mitochondrial respiratory chain activity. Most of the functional candidates were GBM specific and not found in the general population, and 2 were present in the germ-line. Patient-specific maps reveal that 43% of tumors carry at least one functional candidate. Conclusions We reveal that the spectrum of GBM-associated mtDNA mutations is wider than previously thought, as well as novel structural-functional links between specific mtDNA mutations, abnormal mitochondria, and the biology of GBM. These results could provide tangible new prognostic indicators as well as targets with which to guide the development of patient-specific mitochondrially mediated chemotherapeutic approaches. PMID:25731774

  8. New York Heart Association functional class predicts exercise parameters in the current era

    PubMed Central

    Russell, Stuart D.; Saval, Matthew A.; Robbins, Jennifer L.; Ellestad, Myrvin H.; Gottlieb, Stephen S.; Handberg, Eileen M.; Zhou, Yi; Chandler, Bleakley

    2009-01-01

    The New York Heart Association (NYHA) functional class is a subjective estimate of a patient's functional ability based on symptoms that does not always correlate with the objective estimate of functional capacity, peak oxygen consumption (peak VO2). Additionally, relationships between these two measurements have not been examined in the current medical era when patients are using beta blockers, aldosterone antagonists, and cardiac resynchronization therapy (CRT). Using baseline data from the HF-ACTION (Heart Failure and A Controlled Trial Investigating Outcomes of Exercise TraiNing) study, we examined this relationship. Methods 1758 patients underwent a symptom limited metabolic stress test and stopped exercise due to dyspnea or fatigue. The relationship between NYHA functional class and peak VO2 was examined. Additionally, the effects of beta blockers, aldosterone antagonists, and CRT therapy on these relationships were compared. Results NYHA II patients have a significantly higher peak VO2 (16.1 ± 4.6 vs. 13.0 ± 4.2 ml/kg/min), a lower Ve/VCO2 slope (32.8 ± 7.7 versus 36.8 ± 10.4), and a longer duration of exercise (11.0 ± 3.9 versus 8.0 ± 3.4 minutes) than NYHA III/IV patients. Within each functional class, there is no difference in any of the exercise parameters between patients on or off of beta blockers, aldosterone antagonists, or CRT therapy. Finally, with increasing age a significant difference in peak VO2, Ve/VCO2 slope, and exercise time was found. Conclusion For patients being treated with current medical therapy, there still is a difference in true functional capacity between NYHA functional class II and III/IV patients. However, within each NYHA functional class, the presence or absence or contemporary heart failure therapies does not alter exercise parameters. PMID:19782785

  9. Osteoprotegerin is Associated With Endothelial Function and Predicts Early Carotid Atherosclerosis in Patients With Coronary Artery Disease.

    PubMed

    Morisawa, Taichirou; Nakagomi, Akihiro; Kohashi, Keiichi; Kosugi, Munenori; Kusama, Yoshiki; Atarashi, Hirotsugu; Shimizu, Wataru

    2015-01-01

    Osteoprotegerin (OPG) is a soluble glycoprotein belonging to the tumor necrosis factor receptor superfamily and is linked to vascular atherosclerosis and calcification. The carotid intima-media thickness (CIMT) correlates with carotid atherosclerosis and is a significant predictor of cardiovascular events. The OPG levels are associated with the CIMT in coronary artery disease (CAD) patients. However, the pathophysiological mechanisms underlying this pathway remain unclear. We investigated 114 CAD patients (89 men, 25 women; mean age: 68.7 ± 10.3 years) and measured the Gensini score (a marker of the extent of coronary atherosclerosis), the mean CIMT and the plasma levels of OPG and asymmetric dimethylarginine (ADMA; a marker of endothelial function). Early carotid atherosclerosis was defined as a mean CIMT > 1.0 mm. Only 33 of the 114 patients (28.9%) had early carotid atherosclerosis. Patients with early carotid atherosclerosis had higher OPG levels than those without. The OPG levels were found to be significantly associated with ADMA (r = 0.191, P = 0.046) and the mean CIMT (r = 0.319, P = 0.001), but not with the Gensini score. A receiver operating curve analysis revealed the optimal cut-off value of the OPG levels for predicting early carotid atherosclerosis to be 100 pmol/L. A multivariate logistic regression analysis showed OPG ≥ 100 pmol/L to be significantly and independently associated with early carotid atherosclerosis (odds ratio: 2.98, 95% confidence interval: 1.22-7.20, P = 0.017). These data indicate that OPG is significantly associated with endothelial function and predicts early carotid atherosclerosis in patients with CAD. PMID:26549398

  10. Predicting lncRNA-disease associations and constructing lncRNA functional similarity network based on the information of miRNA

    PubMed Central

    Chen, Xing

    2015-01-01

    Accumulating experimental studies have indicated that lncRNAs play important roles in various critical biological process and their alterations and dysregulations have been associated with many important complex diseases. Developing effective computational models to predict potential disease-lncRNA association could benefit not only the understanding of disease mechanism at lncRNA level, but also the detection of disease biomarkers for disease diagnosis, treatment, prognosis and prevention. However, known experimentally confirmed disease-lncRNA associations are still very limited. In this study, a novel model of HyperGeometric distribution for LncRNA-Disease Association inference (HGLDA) was developed to predict lncRNA-disease associations by integrating miRNA-disease associations and lncRNA-miRNA interactions. Although HGLDA didn’t rely on any known disease-lncRNA associations, it still obtained an AUC of 0.7621 in the leave-one-out cross validation. Furthermore, 19 predicted associations for breast cancer, lung cancer, and colorectal cancer were verified by biological experimental studies. Furthermore, the model of LncRNA Functional Similarity Calculation based on the information of MiRNA (LFSCM) was developed to calculate lncRNA functional similarity on a large scale by integrating disease semantic similarity, miRNA-disease associations, and miRNA-lncRNA interactions. It is anticipated that HGLDA and LFSCM could be effective biological tools for biomedical research. PMID:26278472

  11. Within and between population variation in plant traits predicts ecosystem functions associated with a dominant plant species

    PubMed Central

    Breza, Lauren C; Souza, Lara; Sanders, Nathan J; Classen, Aimée T

    2012-01-01

    Linking intraspecific variation in plant traits to ecosystem carbon uptake may allow us to better predict how shift in populations shape ecosystem function. We investigated whether plant populations of a dominant old-field plant species (Solidago altissima) differed in carbon dynamics and if variation in plant traits among genotypes and between populations predicted carbon dynamics. We established a common garden experiment with 35 genotypes from three populations of S. altissima from either Tennessee (southern populations) or Connecticut (northern populations) to ask whether: (1) southern and northern Solidago populations will differ in aboveground productivity, leaf area, flowering time and duration, and whole ecosystem carbon uptake, (2) intraspecific trait variation (growth and reproduction) will be related to intraspecific variation in gross ecosystem CO2 exchange (GEE) and net ecosystem CO2 exchange (NEE) within and between northern and southern populations. GEE and NEE were 4.8× and 2× greater in southern relative to northern populations. Moreover, southern populations produced 13× more aboveground biomass and 1.4× more inflorescence mass than did northern populations. Flowering dynamics (first- and last-day flowering and flowering duration) varied significantly among genotypes in both the southern and northern populations, but plant performance and ecosystem function did not. Both productivity and inflorescence mass predicted NEE and GEE between S. altissima southern and northern populations. Taken together, our data demonstrate that variation between S. altissima populations in performance and flowering traits are strong predictors of ecosystem function in a dominant old-field species and suggest that populations of the same species might differ substantially in their response to environmental perturbations. PMID:22833791

  12. Effluent Free Radicals are Associated with Residual Renal Function and Predict Technique Failure in Peritoneal Dialysis Patients

    PubMed Central

    Morinaga, Hiroshi; Sugiyama, Hitoshi; Inoue, Tatsuyuki; Takiue, Keiichi; Kikumoto, Yoko; Kitagawa, Masashi; Akagi, Shigeru; Nakao, Kazushi; Maeshima, Yohei; Miyazaki, Ikuko; Asanuma, Masato; Hiramatsu, Makoto; Makino, Hirofumi

    2012-01-01

    ♦ Objective: Residual renal function (RRF) is associated with low oxidative stress in peritoneal dialysis (PD). In the present study, we investigated the relationship between the impact of oxidative stress on RRF and patient outcomes during PD. ♦ Methods: Levels of free radicals (FRs) in effluent from the overnight dwell in 45 outpatients were determined by electron spin resonance spectrometry. The FR levels, clinical parameters, and the level of 8-hydroxy-2′-deoxyguanosine were evaluated at study start. The effects of effluent FR level on technique and patient survival were analyzed in a prospective cohort followed for 24 months. ♦ Results: Levels of effluent FRs showed significant negative correlations with daily urine volume and residual renal Kt/V, and positive correlations with plasma β2-microglobulin and effluent 8-hydroxy-2′-deoxyguanosine. A highly significant difference in technique survival (p < 0.05), but not patient survival, was observed for patients grouped by effluent FR quartile. The effluent FR level was independently associated with technique failure after adjusting for patient age, history of cardiovascular disease, and presence of diabetes mellitus (p < 0.001). The level of effluent FRs was associated with death-censored technique failure in both univariate (p < 0.001) and multivariate (p < 0.01) hazard models. Compared with patients remaining on PD, those withdrawn from the modality had significantly higher levels of effluent FRs (p < 0.005). ♦ Conclusions: Elevated effluent FRs are associated with RRF and technique failure in stable PD patients. These findings highlight the importance of oxidative stress as an unfavorable prognostic factor in PD and emphasize that steps should be taken to minimize oxidative stress in these patients. PMID:22215657

  13. Predicting communities from functional traits.

    PubMed

    Cadotte, Marc W; Arnillas, Carlos A; Livingstone, Stuart W; Yasui, Simone-Louise E

    2015-09-01

    Species traits influence where species live and how they interact. While there have been many advances in describing the functional composition and diversity of communities, only recently do researchers have the ability to predict community composition and diversity. This predictive ability can offer fundamental insights into ecosystem resilience and restoration. PMID:26190136

  14. Plasma neutrophil gelatinase-associated lipocalin as a marker for the prediction of worsening renal function in children hospitalized for acute heart failure.

    PubMed

    Elsharawy, Sahar; Raslan, Lila; Morsy, Saed; Hassan, Basheir; Khalifa, Naglaa

    2016-01-01

    Acute heart failure (AHF) is frequently associated with worsening renal function in adult patients. Neutrophil gelatinase-associated lipocalin (NGAL) serves as an early marker for acute renal tubular injury. To assess the role of plasma NGAL in predicting worsening renal function (WRF) in children with AHF, we studied 30 children hospitalized for AHF; children with history of chronic renal disease or on nephrotoxic drugs were excluded. Twenty age- and sex-matched healthy children were included in the study as a control group. Echocardiographic examination was performed on admission. Blood urea nitrogen (BUN), serum creatinine, estimated glomerular filtration rate (eGFR) and plasma NGAL levels were measured on admission and 72 h later. Seventeen (56.6%) patients developed WRF within the three-day follow-up period. At presentation, plasma NGAL level was significantly elevated in children who developed WRF. Admission plasma NGAL level correlated with renal parameters (BUN, creatinine and eGFR) as well as with left ventricular systolic parameters (ejection fraction and fractional shortening). For prediction of WRF, admission plasma, NGAL level>27.5 μg/L had sensitivity and specificity of 90% and 68%, respectively. The area under the receiver-operator curve was higher for NGAL (0.869) than for BUN (0.569) or eGFR (0.684). We conclude that admission plasma NGAL level can predict WRF in children hospitalized for AHF. PMID:26787566

  15. Load-related brain activation predicts spatial working memory performance in youth aged 9-12 and is associated with executive function at earlier ages.

    PubMed

    Huang, Anna S; Klein, Daniel N; Leung, Hoi-Chung

    2016-02-01

    Spatial working memory is a central cognitive process that matures through adolescence in conjunction with major changes in brain function and anatomy. Here we focused on late childhood and early adolescence to more closely examine the neural correlates of performance variability during this important transition period. Using a modified spatial 1-back task with two memory load conditions in an fMRI study, we examined the relationship between load-dependent neural responses and task performance in a sample of 39 youth aged 9-12 years. Our data revealed that between-subject differences in task performance was predicted by load-dependent deactivation in default network regions, including the ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PCC). Although load-dependent increases in activation in prefrontal and posterior parietal regions were only weakly correlated with performance, increased prefrontal-parietal coupling was associated with better performance. Furthermore, behavioral measures of executive function from as early as age 3 predicted current load-dependent deactivation in vACC and PCC. These findings suggest that both task positive and task negative brain activation during spatial working memory contributed to successful task performance in late childhood/early adolescence. This may serve as a good model for studying executive control deficits in developmental disorders. PMID:26562059

  16. DHCR24 associates strongly with the endoplasmic reticulum beyond predicted membrane domains: implications for the activities of this multi-functional enzyme

    PubMed Central

    Zerenturk, Eser J.; Sharpe, Laura J.; Brown, Andrew J.

    2014-01-01

    Cholesterol synthesis occurs in the ER (endoplasmic reticulum), where most of the cholesterogenic machinery resides. As membrane-bound proteins, their topology is difficult to determine, and thus their structures are largely unknown. To help resolve this, we focused on the final enzyme in cholesterol synthesis, DHCR24 (3β-hydroxysterol Δ24-reductase). Prediction programmes and previous studies have shown conflicting results regarding which regions of DHCR24 are associated with the membrane, although there was general agreement that this was limited to only the N-terminal portion. Here, we present biochemical evidence that in fact the majority of the enzyme is associated with the ER membrane. This has important consequences for the many functions attributed to DHCR24. In particular, those that suggest DHCR24 alters its localization within the cell should be reassessed in light of this new information. Moreover, we propose that the expanding database of post-translational modifications will be a valuable resource for mapping the topology of membrane-associated proteins, such as DHCR24, that is, flagging cytosolic residues accessible to modifying enzymes such as kinases and ubiquitin ligases. PMID:24502685

  17. Integrating Rare-Variant Testing, Function Prediction, and Gene Network in Composite Resequencing-Based Genome-Wide Association Studies (CR-GWAS).

    PubMed

    Zhu, Chengsong; Li, Xianran; Yu, Jianming

    2011-08-01

    High-density array-based genome-wide association studies (GWAS) are complemented by exome sequencing and whole-genome resequencing-based association studies. Here we present a composite resequencing-based genome-wide association study (CR-GWAS) strategy that systematically exploits collective biological information and analytical tools for a robust analysis. We showcased the utility of this strategy by using Arabidopsis (Arabidopsis thaliana) resequencing data. Bioinformatic predictions of biological function alteration at each locus were integrated into the process of association testing of both common and rare variants for complex traits with a suite of statistics. Significant signals were then filtered with a priori candidate loci generated from genome database and gene network models to obtain a posteriori candidate loci. A probabilistic gene network (AraNet) that interrogates network neighborhoods of genes was then used to expand the filtering power to examine the significant testing signals. Using this strategy, we confirmed the known true positives and identified several new promising associations. Promising genes (AP1, FCA, FRI, FLC, FLM, SPL5, FY, and DCL2) were shown to control for flowering time through either common variants or rare variants within a diverse set of Arabidopsis accessions. Although many of these candidate genes were cloned earlier with mutational studies, identifying their allele variation contribution to overall phenotypic variation among diverse natural accessions is critical. Our rare allele testing established a greater number of connections than previous analyses in which this issue was not addressed. More importantly, our results demonstrated the potential of integrating various biological, statistical, and bioinformatic tools into complex trait dissection. PMID:22384334

  18. Predicting hand function after hemidisconnection.

    PubMed

    Küpper, Hanna; Kudernatsch, Manfred; Pieper, Tom; Groeschel, Samuel; Tournier, Jacques-Donald; Raffelt, David; Winkler, Peter; Holthausen, Hans; Staudt, Martin

    2016-09-01

    Hemidisconnections (i.e. hemispherectomies or hemispherotomies) invariably lead to contralateral hemiparesis. Many patients with a pre-existing hemiparesis, however, experience no deterioration in motor functions, and some can still grasp with their paretic hand after hemidisconnection. The scope of our study was to predict this phenomenon. Hypothesizing that preserved contralateral grasping ability after hemidisconnection can only occur in patients controlling their paretic hands via ipsilateral corticospinal projections already in the preoperative situation, we analysed the asymmetries of the brainstem (by manual magnetic resonance imaging volumetry) and of the structural connectivity of the corticospinal tracts within the brainstem (by magnetic resonance imaging diffusion tractography), assuming that marked hypoplasia or Wallerian degeneration on the lesioned side in patients who can grasp with their paretic hands indicate ipsilateral control. One hundred and two patients who underwent hemidisconnections between 0.8 and 36 years of age were included. Before the operation, contralateral hand function was normal in 3/102 patients, 47/102 patients showed hemiparetic grasping ability and 52/102 patients could not grasp with their paretic hands. After hemidisconnection, 20/102 patients showed a preserved grasping ability, and 5/102 patients began to grasp with their paretic hands only after the operation. All these 25 patients suffered from pre- or perinatal brain lesions. Thirty of 102 patients lost their grasping ability. This group included all seven patients with a post-neonatally acquired or progressive brain lesion who could grasp before the operation, and also all three patients with a preoperatively normal hand function. The remaining 52/102 patients were unable to grasp pre- and postoperatively. On magnetic resonance imaging, the patients with preserved grasping showed significantly more asymmetric brainstem volumes than the patients who lost their grasping

  19. Biological cluster evaluation for gene function prediction.

    PubMed

    Klie, Sebastian; Nikoloski, Zoran; Selbig, Joachim

    2014-06-01

    Recent advances in high-throughput omics techniques render it possible to decode the function of genes by using the "guilt-by-association" principle on biologically meaningful clusters of gene expression data. However, the existing frameworks for biological evaluation of gene clusters are hindered by two bottleneck issues: (1) the choice for the number of clusters, and (2) the external measures which do not take in consideration the structure of the analyzed data and the ontology of the existing biological knowledge. Here, we address the identified bottlenecks by developing a novel framework that allows not only for biological evaluation of gene expression clusters based on existing structured knowledge, but also for prediction of putative gene functions. The proposed framework facilitates propagation of statistical significance at each of the following steps: (1) estimating the number of clusters, (2) evaluating the clusters in terms of novel external structural measures, (3) selecting an optimal clustering algorithm, and (4) predicting gene functions. The framework also includes a method for evaluation of gene clusters based on the structure of the employed ontology. Moreover, our method for obtaining a probabilistic range for the number of clusters is demonstrated valid on synthetic data and available gene expression profiles from Saccharomyces cerevisiae. Finally, we propose a network-based approach for gene function prediction which relies on the clustering of optimal score and the employed ontology. Our approach effectively predicts gene function on the Saccharomyces cerevisiae data set and is also employed to obtain putative gene functions for an Arabidopsis thaliana data set. PMID:20059365

  20. PREDICTION OF NONLINEAR SPATIAL FUNCTIONALS. (R827257)

    EPA Science Inventory

    Spatial statistical methodology can be useful in the arena of environmental regulation. Some regulatory questions may be addressed by predicting linear functionals of the underlying signal, but other questions may require the prediction of nonlinear functionals of the signal. ...

  1. Structure prediction of magnetosome-associated proteins

    PubMed Central

    Nudelman, Hila; Zarivach, Raz

    2014-01-01

    Magnetotactic bacteria (MTB) are Gram-negative bacteria that can navigate along geomagnetic fields. This ability is a result of a unique intracellular organelle, the magnetosome. These organelles are composed of membrane-enclosed magnetite (Fe3O4) or greigite (Fe3S4) crystals ordered into chains along the cell. Magnetosome formation, assembly, and magnetic nano-crystal biomineralization are controlled by magnetosome-associated proteins (MAPs). Most MAP-encoding genes are located in a conserved genomic region – the magnetosome island (MAI). The MAI appears to be conserved in all MTB that were analyzed so far, although the MAI size and organization differs between species. It was shown that MAI deletion leads to a non-magnetic phenotype, further highlighting its important role in magnetosome formation. Today, about 28 proteins are known to be involved in magnetosome formation, but the structures and functions of most MAPs are unknown. To reveal the structure–function relationship of MAPs we used bioinformatics tools in order to build homology models as a way to understand their possible role in magnetosome formation. Here we present a predicted 3D structural models’ overview for all known Magnetospirillum gryphiswaldense strain MSR-1 MAPs. PMID:24523717

  2. Structure prediction of magnetosome-associated proteins.

    PubMed

    Nudelman, Hila; Zarivach, Raz

    2014-01-01

    Magnetotactic bacteria (MTB) are Gram-negative bacteria that can navigate along geomagnetic fields. This ability is a result of a unique intracellular organelle, the magnetosome. These organelles are composed of membrane-enclosed magnetite (Fe3O4) or greigite (Fe3S4) crystals ordered into chains along the cell. Magnetosome formation, assembly, and magnetic nano-crystal biomineralization are controlled by magnetosome-associated proteins (MAPs). Most MAP-encoding genes are located in a conserved genomic region - the magnetosome island (MAI). The MAI appears to be conserved in all MTB that were analyzed so far, although the MAI size and organization differs between species. It was shown that MAI deletion leads to a non-magnetic phenotype, further highlighting its important role in magnetosome formation. Today, about 28 proteins are known to be involved in magnetosome formation, but the structures and functions of most MAPs are unknown. To reveal the structure-function relationship of MAPs we used bioinformatics tools in order to build homology models as a way to understand their possible role in magnetosome formation. Here we present a predicted 3D structural models' overview for all known Magnetospirillum gryphiswaldense strain MSR-1 MAPs. PMID:24523717

  3. Interactions between self-reported alcohol outcome expectancies and cognitive functioning in the prediction of alcohol use and associated problems: a further examination.

    PubMed

    Littlefield, Andrew K; Vergés, Alvaro; McCarthy, Denis M; Sher, Kenneth J

    2011-09-01

    A recent debate regarding the theoretical distinction between explicit and implicit cognitive processes relevant to alcohol-related behaviors was strongly shaped by empirical findings from dual-process models (Moss & Albery, 2009; Wiers & Stacy, 2010; Moss & Albery, 2010). Specifically, as part of a broader discussion, Wiers & Stacy (2010) contended that alcohol-related behaviors are better predicted by self-reported alcohol expectancies for individuals with good executive control and verbal abilities relative to those without such abilities. The purpose of the current paper is to further test whether self-reported alcohol outcome expectancies are moderated by measures of cognitive functioning. Using multiple indices of alcohol use, alcohol-related consequences, self-reported alcohol outcome expectancies, and cognitive functioning, both cross-sectional and longitudinal analyses were conducted in a prospective sample of 489 individuals at varying risk for alcohol use disorders. Results from a series of regression analyses testing interactions between self-reported alcohol expectancies and cognitive functioning showed minimal support for the hypothesized pattern discussed by Wiers and Stacy, 2010 regarding self-reported alcohol outcome expectancies. The overall rates of significance were consistent with Type I error rates and a substantial proportion of the significant interactions were inconsistent with previous findings. Thus, the conclusion that cognitive measures consistently moderate the relation between self-reported alcohol expectancies and alcohol use and outcomes should be tempered. PMID:21443299

  4. The Full Spectrum of Holoprosencephaly-Associated Mutations within the ZIC2 Gene in Humans Predicts Loss-of-Function as the Predominant Disease Mechanism

    PubMed Central

    Roessler, Erich; Lacbawan, Felicitas; Dubourg, Christèle; Paulussen, Aimee; Herbergs, Jos; Hehr, Ute; Bendavid, Claude; Zhou, Nan; Ouspenskaia, Maia; Bale, Sherri; Odent, Sylvie; David, Vèronique; Muenke, Maximilian

    2009-01-01

    Mutations of the ZIC2 transcription factor gene are among the most common heterozygous variations detected in holoprosencephaly (HPE) patients, a patient group who lack critical midline forebrain specification due to defective embryonic signaling during development. Recent studies indicate that complete deficiency of the related murine Zic2 transcription factor can also be a contributing factor to variable midline deficiencies, presenting during mid-gastrulation, that could explain similar forebrain anomalies in this model system. Here we collect and summarize all available mutations in the human ZIC2 gene detected in HPE patients (21 published and 62 novel). Our analysis corroborates this mechanism proposed in mice by predicting loss-of-function as the likely pathogenetic mechanism common to most, if not all, of these mutations in HPE. PMID:19177455

  5. Hierarchical Ensemble Methods for Protein Function Prediction

    PubMed Central

    2014-01-01

    Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

  6. A Dual Role for Prediction Error in Associative Learning

    PubMed Central

    Friston, Karl J.; Daw, Nathaniel D.; McIntosh, Anthony R.; Stephan, Klaas E.

    2009-01-01

    Confronted with a rich sensory environment, the brain must learn statistical regularities across sensory domains to construct causal models of the world. Here, we used functional magnetic resonance imaging and dynamic causal modeling (DCM) to furnish neurophysiological evidence that statistical associations are learnt, even when task-irrelevant. Subjects performed an audio-visual target-detection task while being exposed to distractor stimuli. Unknown to them, auditory distractors predicted the presence or absence of subsequent visual distractors. We modeled incidental learning of these associations using a Rescorla–Wagner (RW) model. Activity in primary visual cortex and putamen reflected learning-dependent surprise: these areas responded progressively more to unpredicted, and progressively less to predicted visual stimuli. Critically, this prediction-error response was observed even when the absence of a visual stimulus was surprising. We investigated the underlying mechanism by embedding the RW model into a DCM to show that auditory to visual connectivity changed significantly over time as a function of prediction error. Thus, consistent with predictive coding models of perception, associative learning is mediated by prediction-error dependent changes in connectivity. These results posit a dual role for prediction-error in encoding surprise and driving associative plasticity. PMID:18820290

  7. Year 2 Report: Protein Function Prediction Platform

    SciTech Connect

    Zhou, C E

    2012-04-27

    Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fully automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.

  8. Quantitative assessment of protein function prediction programs.

    PubMed

    Rodrigues, B N; Steffens, M B R; Raittz, R T; Santos-Weiss, I C R; Marchaukoski, J N

    2015-01-01

    Fast prediction of protein function is essential for high-throughput sequencing analysis. Bioinformatic resources provide cheaper and faster techniques for function prediction and have helped to accelerate the process of protein sequence characterization. In this study, we assessed protein function prediction programs that accept amino acid sequences as input. We analyzed the classification, equality, and similarity between programs, and, additionally, compared program performance. The following programs were selected for our assessment: Blast2GO, InterProScan, PANTHER, Pfam, and ScanProsite. This selection was based on the high number of citations (over 500), fully automatic analysis, and the possibility of returning a single best classification per sequence. We tested these programs using 12 gold standard datasets from four different sources. The gold standard classification of the databases was based on expert analysis, the Protein Data Bank, or the Structure-Function Linkage Database. We found that the miss rate among the programs is globally over 50%. Furthermore, we observed little overlap in the correct predictions from each program. Therefore, a combination of multiple types of sources and methods, including experimental data, protein-protein interaction, and data mining, may be the best way to generate more reliable predictions and decrease the miss rate. PMID:26782400

  9. Protein function prediction based on data fusion and functional interrelationship.

    PubMed

    Meng, Jun; Wekesa, Jael-Sanyanda; Shi, Guan-Li; Luan, Yu-Shi

    2016-04-01

    One of the challenging tasks of bioinformatics is to predict more accurate and confident protein functions from genomics and proteomics datasets. Computational approaches use a variety of high throughput experimental data, such as protein-protein interaction (PPI), protein sequences and phylogenetic profiles, to predict protein functions. This paper presents a method that uses transductive multi-label learning algorithm by integrating multiple data sources for classification. Multiple proteomics datasets are integrated to make inferences about functions of unknown proteins and use a directed bi-relational graph to assign labels to unannotated proteins. Our method, bi-relational graph based transductive multi-label function annotation (Bi-TMF) uses functional correlation and topological PPI network properties on both the training and testing datasets to predict protein functions through data fusion of the individual kernel result. The main purpose of our proposed method is to enhance the performance of classifier integration for protein function prediction algorithms. Experimental results demonstrate the effectiveness and efficiency of Bi-TMF on multi-sources datasets in yeast, human and mouse benchmarks. Bi-TMF outperforms other recently proposed methods. PMID:26869536

  10. Rumination prospectively predicts executive functioning impairments in adolescents

    PubMed Central

    Connolly, Samantha L.; Wagner, Clara A.; Shapero, Benjamin G.; Pendergast, Laura L.; Abramson, Lyn Y.; Alloy, Lauren B.

    2014-01-01

    Background and objectives The current study tested the resource allocation hypothesis, examining whether baseline rumination or depressive symptom levels prospectively predicted deficits in executive functioning in an adolescent sample. The alternative to this hypothesis was also evaluated by testing whether lower initial levels of executive functioning predicted increases in rumination or depressive symptoms at follow-up. Methods A community sample of 200 adolescents (ages 12–13) completed measures of depressive symptoms, rumination, and executive functioning at baseline and at a follow-up session approximately 15 months later. Results Adolescents with higher levels of baseline rumination displayed decreases in selective attention and attentional switching at follow-up. Rumination did not predict changes in working memory or sustained and divided attention. Depressive symptoms were not found to predict significant changes in executive functioning scores at follow-up. Baseline executive functioning was not associated with change in rumination or depression over time. Conclusions Findings partially support the resource allocation hypothesis that engaging in ruminative thoughts consumes cognitive resources that would otherwise be allocated towards difficult tests of executive functioning. Support was not found for the alternative hypothesis that lower levels of initial executive functioning would predict increased rumination or depressive symptoms at follow-up. Our study is the first to find support for the resource allocation hypothesis using a longitudinal design and an adolescent sample. Findings highlight the potentially detrimental effects of rumination on executive functioning during early adolescence. PMID:23978629

  11. A Survey of Computational Intelligence Techniques in Protein Function Prediction

    PubMed Central

    Tiwari, Arvind Kumar; Srivastava, Rajeev

    2014-01-01

    During the past, there was a massive growth of knowledge of unknown proteins with the advancement of high throughput microarray technologies. Protein function prediction is the most challenging problem in bioinformatics. In the past, the homology based approaches were used to predict the protein function, but they failed when a new protein was different from the previous one. Therefore, to alleviate the problems associated with homology based traditional approaches, numerous computational intelligence techniques have been proposed in the recent past. This paper presents a state-of-the-art comprehensive review of various computational intelligence techniques for protein function predictions using sequence, structure, protein-protein interaction network, and gene expression data used in wide areas of applications such as prediction of DNA and RNA binding sites, subcellular localization, enzyme functions, signal peptides, catalytic residues, nuclear/G-protein coupled receptors, membrane proteins, and pathway analysis from gene expression datasets. This paper also summarizes the result obtained by many researchers to solve these problems by using computational intelligence techniques with appropriate datasets to improve the prediction performance. The summary shows that ensemble classifiers and integration of multiple heterogeneous data are useful for protein function prediction. PMID:25574395

  12. Beyond Genotype: Serotonin Transporter Epigenetic Modification Predicts Human Brain Function

    PubMed Central

    Nikolova, Yuliya S.; Koenen, Karestan C.; Galea, Sandro; Wang, Chiou-Miin; Seney, Marianne L.; Sibille, Etienne; Williamson, Douglas E.; Hariri, Ahmad R.

    2014-01-01

    We examined epigenetic regulation in regards to behaviorally and clinically relevant human brain function. Specifically, we found that increased promoter methylation of the serotonin transporter gene predicted increased threat-related amygdala reactivity and decreased mRNA expression in postmortem amygdala tissue. These patterns were independent of functional genetic variation in the same region. Furthermore, the association with amygdala reactivity was replicated in a second cohort and was robust to both sampling methods and age. PMID:25086606

  13. Optimizing nondecomposable loss functions in structured prediction.

    PubMed

    Ranjbar, Mani; Lan, Tian; Wang, Yang; Robinovitch, Steven N; Li, Ze-Nian; Mori, Greg

    2013-04-01

    We develop an algorithm for structured prediction with nondecomposable performance measures. The algorithm learns parameters of Markov Random Fields (MRFs) and can be applied to multivariate performance measures. Examples include performance measures such as Fβ score (natural language processing), intersection over union (object category segmentation), Precision/Recall at k (search engines), and ROC area (binary classifiers). We attack this optimization problem by approximating the loss function with a piecewise linear function. The loss augmented inference forms a Quadratic Program (QP), which we solve using LP relaxation. We apply this approach to two tasks: object class-specific segmentation and human action retrieval from videos. We show significant improvement over baseline approaches that either use simple loss functions or simple scoring functions on the PASCAL VOC and H3D Segmentation datasets, and a nursing home action recognition dataset. PMID:22868650

  14. 47 CFR 69.603 - Association functions.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 3 2011-10-01 2011-10-01 false Association functions. 69.603 Section 69.603... Exchange Carrier Association § 69.603 Association functions. (a) The Association shall not engage in any... untariffed basis shall be deemed to be authorized association activities. (c)-(e) (f) The association...

  15. Graph pyramids for protein function prediction

    PubMed Central

    2015-01-01

    Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

  16. Systematic prediction of gene function in Arabidopsis thaliana using a probabilistic functional gene network

    PubMed Central

    Hwang, Sohyun; Rhee, Seung Y; Marcotte, Edward M; Lee, Insuk

    2012-01-01

    AraNet is a functional gene network for the reference plant Arabidopsis and has been constructed in order to identify new genes associated with plant traits. It is highly predictive for diverse biological pathways and can be used to prioritize genes for functional screens. Moreover, AraNet provides a web-based tool with which plant biologists can efficiently discover novel functions of Arabidopsis genes (http://www.functionalnet.org/aranet/). This protocol explains how to conduct network-based prediction of gene functions using AraNet and how to interpret the prediction results. Functional discovery in plant biology is facilitated by combining candidate prioritization by AraNet with focused experimental tests. PMID:21886106

  17. Executive functions predict conceptual learning of science.

    PubMed

    Rhodes, Sinéad M; Booth, Josephine N; Palmer, Lorna Elise; Blythe, Richard A; Delibegovic, Mirela; Wheate, Nial J

    2016-06-01

    We examined the relationship between executive functions and both factual and conceptual learning of science, specifically chemistry, in early adolescence. Sixty-three pupils in their second year of secondary school (aged 12-13 years) participated. Pupils completed tasks of working memory (Spatial Working Memory), inhibition (Stop-Signal), attention set-shifting (ID/ED), and planning (Stockings of Cambridge), from the CANTAB. They also participated in a chemistry teaching session, practical, and assessment on the topic of acids and alkalis designed specifically for this study. Executive function data were related to (1) the chemistry assessment which included aspects of factual and conceptual learning and (2) a recent school science exam. Correlational analyses between executive functions and both the chemistry assessment and science grades revealed that science achievements were significantly correlated with working memory. Linear regression analysis revealed that visuospatial working memory ability was predictive of chemistry performance. Interestingly, this relationship was observed solely in relation to the conceptual learning condition of the assessment highlighting the role of executive functions in understanding and applying knowledge about what is learned within science teaching. PMID:26751597

  18. Predicting real-world functional milestones in schizophrenia.

    PubMed

    Olsson, Anna-Karin; Hjärthag, Fredrik; Helldin, Lars

    2016-08-30

    Schizophrenia is a severe disorder that often causes impairments in major areas of functioning, and most patients do not achieve expected real-world functional milestones. The aim of this study was to identify which variables of demography, illness activity, and functional capacity predict patients' ability to attain real-world functional milestones. Participants were 235 outpatients, 149 men and 86 women, diagnosed with schizophrenia spectrum disorder. Our results showed that younger patients managed to achieve a higher level of functioning in educational level, marital status, and social contacts. Patients' functional capacity was primarily associated with educational level and housing situation. We also found that women needed less support regarding housing and obtained a higher level of marital status as compared with men. Our findings demonstrate the importance of considering current symptoms, especially negative symptoms, and remission stability over time, together with age, duration of illness, gender, educational level, and current functional capacity, when predicting patients' future real-world functioning. We also conclude that there is an advantage in exploring symptoms divided into positive, negative, and general domains considering their probable impact on functional achievements. PMID:27235985

  19. Visual predictions in the orbitofrontal cortex rely on associative content.

    PubMed

    Chaumon, Maximilien; Kveraga, Kestutis; Barrett, Lisa Feldman; Bar, Moshe

    2014-11-01

    Predicting upcoming events from incomplete information is an essential brain function. The orbitofrontal cortex (OFC) plays a critical role in this process by facilitating recognition of sensory inputs via predictive feedback to sensory cortices. In the visual domain, the OFC is engaged by low spatial frequency (LSF) and magnocellular-biased inputs, but beyond this, we know little about the information content required to activate it. Is the OFC automatically engaged to analyze any LSF information for meaning? Or is it engaged only when LSF information matches preexisting memory associations? We tested these hypotheses and show that only LSF information that could be linked to memory associations engages the OFC. Specifically, LSF stimuli activated the OFC in 2 distinct medial and lateral regions only if they resembled known visual objects. More identifiable objects increased activity in the medial OFC, known for its function in affective responses. Furthermore, these objects also increased the connectivity of the lateral OFC with the ventral visual cortex, a crucial region for object identification. At the interface between sensory, memory, and affective processing, the OFC thus appears to be attuned to the associative content of visual information and to play a central role in visuo-affective prediction. PMID:23771980

  20. Prediction of Postchemotherapy Ovarian Function Using Markers of Ovarian Reserve

    PubMed Central

    Xia, Rong; Schott, Anne F.; McConnell, Daniel; Banerjee, Mousumi; Hayes, Daniel F.

    2014-01-01

    Background. Reproductive-aged women frequently receive both chemotherapy and endocrine therapy as part of their treatment regimen for early stage hormone receptor-positive breast cancer. Chemotherapy results in transient or permanent ovarian failure in the majority of women. The difficulty in determining which patients will recover ovarian function has implications for adjuvant endocrine therapy decision making. We hypothesized that pretreatment serum anti-Müllerian hormone (AMH) and inhibin B concentrations would predict for ovarian function following chemotherapy. Methods. Pre- and perimenopausal women aged 25–50 years with newly diagnosed breast cancer were enrolled. Subjects underwent phlebotomy for assessment of serum AMH, inhibin B, follicle-stimulating hormone, and estradiol prior to chemotherapy and 1 month and 1 year following completion of treatment. Associations among hormone concentrations, clinical factors, and biochemically assessed ovarian function were assessed. Results. Twenty-seven subjects were evaluable for the primary endpoint. Median age was 41. Twenty subjects (74.1%) experienced recovery of ovarian function within 18 months. Of the 26 evaluable subjects assessed prior to chemotherapy, 19 (73.1%) had detectable serum concentrations of AMH. The positive predictive value of a detectable baseline serum AMH concentration for recovery of ovarian function was 94.7%, and the negative predictive value was 85.7%. On univariate analysis, younger age and detectable serum AMH concentration at chemotherapy initiation were predictive of increased likelihood of recovery of ovarian function. Conclusion. Prechemotherapy assessment of serum AMH may be useful for predicting postchemotherapy ovarian function. This finding has implications for decision making about adjuvant endocrine therapy in premenopausal women treated with chemotherapy. PMID:24319018

  1. The Prediction of Scattered Broadband Shock-Associated Noise

    NASA Technical Reports Server (NTRS)

    Miller, Steven A. E.

    2015-01-01

    A mathematical model is developed for the prediction of scattered broadband shock-associated noise. Model arguments are dependent on the vector Green's function of the linearized Euler equations, steady Reynolds-averaged Navier-Stokes solutions, and the two-point cross-correlation of the equivalent source. The equivalent source is dependent on steady Reynolds-averaged Navier-Stokes solutions of the jet flow, that capture the nozzle geometry and airframe surface. Contours of the time-averaged streamwise velocity component and turbulent kinetic energy are examined with varying airframe position relative to the nozzle exit. Propagation effects are incorporated by approximating the vector Green's function of the linearized Euler equations. This approximation involves the use of ray theory and an assumption that broadband shock-associated noise is relatively unaffected by the refraction of the jet shear layer. A non-dimensional parameter is proposed that quantifies the changes of the broadband shock-associated noise source with varying jet operating condition and airframe position. Scattered broadband shock-associated noise possesses a second set of broadband lobes that are due to the effect of scattering. Presented predictions demonstrate relatively good agreement compared to a wide variety of measurements.

  2. Spinal meningiomas: clinicoradiological factors predicting recurrence and functional outcome.

    PubMed

    Maiti, Tanmoy K; Bir, Shyamal C; Patra, Devi Prasad; Kalakoti, Piyush; Guthikonda, Bharat; Nanda, Anil

    2016-08-01

    OBJECTIVE Spinal meningiomas are benign tumors with a wide spectrum of clinical and radiological features at presentation. The authors analyzed multiple clinicoradiological factors to predict recurrence and functional outcome in a cohort with a mean follow-up of more than 4 years. The authors also discuss the results of clinical studies regarding spinal meningiomas in the last 15 years. METHODS The authors retrospectively reviewed the clinical and radiological details of patients who underwent surgery for spinal tumors between 2001 and 2015 that were histopathologically confirmed as meningiomas. Demographic parameters, such as age, sex, race, and association with neurofibromatosis Type 2, were considered. Radiological parameters, such as tumor size, signal changes of spinal cord, spinal level, number of levels, location of tumor attachment, shape of tumor, and presence of dural tail/calcification, were noted. These factors were analyzed to predict recurrence and functional outcome. Furthermore, a pooled analysis was performed from 13 reports of spinal meningiomas in the last 15 years. RESULTS A total of 38 patients were included in this study. Male sex and tumors with radiological evidence of a dural tail were associated with an increased risk of recurrence at a mean follow-up of 51.2 months. Ventral or ventrolateral location, large tumors, T2 cord signal changes, and poor preoperative functional status were associated with poor functional outcome at 1-year follow-up. CONCLUSIONS Spine surgeons must be aware of the natural history and risk factors of spinal meningiomas to establish a prognosis for their patients. PMID:27476848

  3. Predicting Protein Function via Semantic Integration of Multiple Networks.

    PubMed

    Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

    2016-01-01

    Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically i ntegrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet. PMID:26800544

  4. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function.

    PubMed

    Warde-Farley, David; Donaldson, Sylva L; Comes, Ovi; Zuberi, Khalid; Badrawi, Rashad; Chao, Pauline; Franz, Max; Grouios, Chris; Kazi, Farzana; Lopes, Christian Tannus; Maitland, Anson; Mostafavi, Sara; Montojo, Jason; Shao, Quentin; Wright, George; Bader, Gary D; Morris, Quaid

    2010-07-01

    GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. Six organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens and Saccharomyces cerevisiae) and hundreds of data sets have been collected from GEO, BioGRID, Pathway Commons and I2D, as well as organism-specific functional genomics data sets. Users can select arbitrary subsets of the data sets associated with an organism to perform their analyses and can upload their own data sets to analyze. The GeneMANIA algorithm performs as well or better than other gene function prediction methods on yeast and mouse benchmarks. The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make GeneMANIA a useful tool for any biologist. PMID:20576703

  5. Exponential generating functions for the associated Bessel functions

    NASA Astrophysics Data System (ADS)

    Fakhri, H.; Mojaveri, B.; Gomshi Nobary, M. A.

    2008-09-01

    Similar to the associated Legendre functions, the differential equation for the associated Bessel functions Bl,m(x) is introduced so that its form remains invariant under the transformation l → -l - 1. A Rodrigues formula for the associated Bessel functions as squared integrable solutions in both regions l < 0 and l >= 0 is presented. The functions with the same m but with different positive and negative values of l are not independent of each other, while the functions with the same l + m (l - m) but with different values of l and m are independent of each other. So, all the functions Bl,m(x) may be taken into account as the union of the increasing (decreasing) infinite sequences with respect to l. It is shown that two new different types of exponential generating functions are attributed to the associated Bessel functions corresponding to these rearranged sequences.

  6. Habitual fat intake predicts memory function in younger women

    PubMed Central

    Gibson, E. Leigh; Barr, Suzanne; Jeanes, Yvonne M.

    2013-01-01

    High intakes of fat have been linked to greater cognitive decline in old age, but such associations may already occur in younger adults. We tested memory and learning in 38 women (25 to 45 years old), recruited for a larger observational study in women with polycystic ovary syndrome. These women varied in health status, though not significantly between cases (n = 23) and controls (n = 15). Performance on tests sensitive to medial temporal lobe function (CANTABeclipse, Cambridge Cognition Ltd, Cambridge, UK), i.e., verbal memory, visuo-spatial learning, and delayed pattern matching (DMS), were compared with intakes of macronutrients from 7-day diet diaries and physiological indices of metabolic syndrome. Partial correlations were adjusted for age, activity, and verbal IQ (National Adult Reading Test). Greater intakes of saturated and trans fats, and higher saturated to unsaturated fat ratio (Sat:UFA), were associated with more errors on the visuo-spatial task and with poorer word recall and recognition. Unexpectedly, higher UFA intake predicted poorer performance on the word recall and recognition measures. Fasting insulin was positively correlated with poorer word recognition only, whereas higher blood total cholesterol was associated only with visuo-spatial learning errors. None of these variables predicted performance on a DMS test. The significant nutrient–cognition relationships were tested for mediation by total energy intake: saturated and trans fat intakes, and Sat:UFA, remained significant predictors specifically of visuo-spatial learning errors, whereas total fat and UFA intakes now predicted only poorer word recall. Examination of associations separately for monounsaturated (MUFA) and polyunsaturated fats suggested that only MUFA intake was predictive of poorer word recall. Saturated and trans fats, and fasting insulin, may already be associated with cognitive deficits in younger women. The findings need extending but may have important implications for

  7. "Reverse Genomics" Predicts Function of Human Conserved Noncoding Elements.

    PubMed

    Marcovitz, Amir; Jia, Robin; Bejerano, Gill

    2016-05-01

    Evolutionary changes in cis-regulatory elements are thought to play a key role in morphological and physiological diversity across animals. Many conserved noncoding elements (CNEs) function as cis-regulatory elements, controlling gene expression levels in different biological contexts. However, determining specific associations between CNEs and related phenotypes is a challenging task. Here, we present a computational "reverse genomics" approach that predicts the phenotypic functions of human CNEs. We identify thousands of human CNEs that were lost in at least two independent mammalian lineages (IL-CNEs), and match their evolutionary profiles against a diverse set of phenotypes recently annotated across multiple mammalian species. We identify 2,759 compelling associations between human CNEs and a diverse set of mammalian phenotypes. We discuss multiple CNEs, including a predicted ear element near BMP7, a pelvic CNE in FBN1, a brain morphology element in UBE4B, and an aquatic adaptation forelimb CNE near EGR2, and provide a full list of our predictions. As more genomes are sequenced and more traits are annotated across species, we expect our method to facilitate the interpretation of noncoding mutations in human disease and expedite the discovery of individual CNEs that play key roles in human evolution and development. PMID:26744417

  8. Metabolic Syndrome Biomarkers Predict Lung Function Impairment

    PubMed Central

    Naveed, Bushra; Weiden, Michael D.; Kwon, Sophia; Gracely, Edward J.; Comfort, Ashley L.; Ferrier, Natalia; Kasturiarachchi, Kusali J.; Cohen, Hillel W.; Aldrich, Thomas K.; Rom, William N.; Kelly, Kerry; Prezant, David J.

    2012-01-01

    Rationale: Cross-sectional studies demonstrate an association between metabolic syndrome and impaired lung function. Objectives: To define if metabolic syndrome biomarkers are risk factors for loss of lung function after irritant exposure. Methods: A nested case-control study of Fire Department of New York personnel with normal pre–September 11th FEV1 and who presented for subspecialty pulmonary evaluation before March 10, 2008. We correlated metabolic syndrome biomarkers obtained within 6 months of World Trade Center dust exposure with subsequent FEV1. FEV1 at subspecialty pulmonary evaluation within 6.5 years defined disease status; cases had FEV1 less than lower limit of normal, whereas control subjects had FEV1 greater than or equal to lower limit of normal. Measurements and Main Results: Clinical data and serum sampled at the first monitoring examination within 6 months of September 11, 2001, assessed body mass index, heart rate, serum glucose, triglycerides and high-density lipoprotein (HDL), leptin, pancreatic polypeptide, and amylin. Cases and control subjects had significant differences in HDL less than 40 mg/dl with triglycerides greater than or equal to 150 mg/dl, heart rate greater than or equal to 66 bpm, and leptin greater than or equal to 10,300 pg/ml. Each increased the odds of abnormal FEV1 at pulmonary evaluation by more than twofold, whereas amylin greater than or equal to 116 pg/ml decreased the odds by 84%, in a multibiomarker model adjusting for age, race, body mass index, and World Trade Center arrival time. This model had a sensitivity of 41%, a specificity of 86%, and a receiver operating characteristic area under the curve of 0.77. Conclusions: Abnormal triglycerides and HDL and elevated heart rate and leptin are independent risk factors of greater susceptibility to lung function impairment after September 11, 2001, whereas elevated amylin is protective. Metabolic biomarkers are predictors of lung disease, and may be useful for assessing

  9. GAPIT: genome association and prediction integrated tool

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Advances in high throughput sequencing have improved the detection of genes underlying important traits as well as the prediction accuracy of disease risk and breeding value of crop or livestock. Software programs developed to perform statistical genetic analysis that support these activities should...

  10. Text Mining Improves Prediction of Protein Functional Sites

    PubMed Central

    Cohn, Judith D.; Ravikumar, Komandur E.

    2012-01-01

    We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

  11. A Prediction Model of the Capillary Pressure J-Function.

    PubMed

    Xu, W S; Luo, P Y; Sun, L; Lin, N

    2016-01-01

    The capillary pressure J-function is a dimensionless measure of the capillary pressure of a fluid in a porous medium. The function was derived based on a capillary bundle model. However, the dependence of the J-function on the saturation Sw is not well understood. A prediction model for it is presented based on capillary pressure model, and the J-function prediction model is a power function instead of an exponential or polynomial function. Relative permeability is calculated with the J-function prediction model, resulting in an easier calculation and results that are more representative. PMID:27603701

  12. Remote sensing of vegetation ecophysiological function for improved hydrologic prediction

    NASA Astrophysics Data System (ADS)

    Drewry, D.; Ruddell, B. L.

    2014-12-01

    Land surface hydrology in vegetated landscapes is strongly controlled by ecophysiological function. The coupling between photosynthesis, stomatal dynamics and leaf energy balance fundamentally links the hydrologic and carbon cycles, and provides a basis for examining the utility of observations of functional plant traits for hydrologic prediction. Here we explore the potential of solar induced fluorescence (SIF) and thermal infrared (TIR) remote sensing observations to improve the accuracy and reduce the uncertainty in hydrologic prediction. While SIF represents an emission of radiation associated with photosynthesis, TIR provides information on foliage temperature and is related to stomatal function and water stress. A set of remote observing system simulation experiments are conducted to quantify the value of remotely sensed observations of SIF and TIR when assimilated into a detailed vegetation biophysical model. The MLCan model discretizes a dense plant canopy to resolve vertical variation in photosynthesis, water vapor and energy exchange. Here we present extensions to MLCan that allow for direct computation of the canopy emission of both SIF and TIR. The detailed representation of the physical environment and biological functioning of structurally complex canopies makes MLCan an ideal simulation tool for exploring the impact of these two unique, and potentially synergistic observables. This work specifically addresses remote sensing capabilities on both recently launched (OCO-2) and near-term (ECOSTRESS) satellite platforms. We contrast the information gained through the assimilation of SIF and TIR observations to that of the assimilation of data related to physical states such as soil moisture and leaf area index.

  13. Electrocortical indices of selective attention predict adolescent executive functioning.

    PubMed

    Lackner, Christine L; Santesso, Diane L; Dywan, Jane; Wade, Terrance J; Segalowitz, Sidney J

    2013-05-01

    Executive functioning is considered a powerful predictor of behavioral and mental health outcomes during adolescence. Our question was whether executive functioning skills, normally considered "top-down" processes, are related to automatic aspects of selective attention. Event-related potentials (ERPs) were recorded from typically-developing 12-14-year-old adolescents as they responded to tones presented in attended and unattended channels in an auditory selective attention task. Examining these ERPs in relation to parental reports on the Behavior Rating Inventory of Executive Function (BRIEF) revealed that an early frontal positivity (EFP) elicited by to-be-ignored/unattended tones was larger in those with poorer executive functions, driven by scores on the BRIEF Metacognition Index. As is traditionally found, N1 amplitudes were more negative for the to-be-attended rather than unattended tones. Additionally, N1 latencies to unattended tones correlated with parent-ratings on the BRIEF Behavior Regulation Index, where shorter latencies predicted better executive functions. Results suggest that the ability to disengage attention from distractor information in the early stages of stimulus processing is associated with adolescent executive functioning skills. PMID:23528784

  14. Predicted vibrational spectra from anharmonic potential functions

    SciTech Connect

    Dunn, K.M.

    1986-01-01

    The dissertation develops a procedure for predicting vibrational spectra of polyatomic molecules from a combination of theoretical and experimental information. Ab initio quantum chemical calculations provide anharmonic force constants including cubics and diagonal quartics. A variational procedure analogous to configuration interaction is then used to compute eigenvalues of the pure vibrational Hamiltonian. The diagonal quadratic force constants are then adjusted until the calculated fundamental frequencies agree with experiment. The resulting theoretical-experimental force field may then be used to predict the energies of vibrationally excited states. The method is applied to three molecules: hydrogen cyanide, ammonia, and methyl fluoride. For hydrogen cyanide, the dissertation presents predicted energies for all of the vibrationally excited states with up to four quanta of excitation distributed among the four modes. The root-mean-square error is 8.7 cm{sup {minus}1} for the states below 11,000 cm{sup {minus}1}. The force constants for ammonia are adjusted to reproduce the fundamental frequencies of ND{sub 3}. The force constants then predict the energies of states below 7000 cm{sup {minus}1} with an rms error of 5.8 cm{sup {minus}1} for ND{sub 3} and 16.7 cm{sup {minus}1} for NH{sub 3}. Finally, the adjusted force constants for methyl fluoride predict the energies of states below 4100 cm{sup {minus}1} with an rms error of 4.3 cm{sup {minus}1}. These force constants are also used to predict the CH stretching overtone region of CH{sub 3}F and the first, second and third overtone regions of CD{sub 2}FH for which experimental information is not available.

  15. Models for predicting objective function weights in prostate cancer IMRT

    SciTech Connect

    Boutilier, Justin J. Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.

    2015-04-15

    Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

  16. Network-based prediction of protein function

    PubMed Central

    Sharan, Roded; Ulitsky, Igor; Shamir, Ron

    2007-01-01

    Functional annotation of proteins is a fundamental problem in the post-genomic era. The recent availability of protein interaction networks for many model species has spurred on the development of computational methods for interpreting such data in order to elucidate protein function. In this review, we describe the current computational approaches for the task, including direct methods, which propagate functional information through the network, and module-assisted methods, which infer functional modules within the network and use those for the annotation task. Although a broad variety of interesting approaches has been developed, further progress in the field will depend on systematic evaluation of the methods and their dissemination in the biological community. PMID:17353930

  17. A survey of the broadband shock associated noise prediction methods

    NASA Technical Reports Server (NTRS)

    Kim, Chan M.; Krejsa, Eugene A.; Khavaran, Abbas

    1992-01-01

    Several different prediction methods to estimate the broadband shock associated noise of a supersonic jet are introduced and compared with experimental data at various test conditions. The nozzle geometries considered for comparison include a convergent and a convergent-divergent nozzle, both axisymmetric. Capabilities and limitations of prediction methods in incorporating the two nozzle geometries, flight effect, and temperature effect are discussed. Predicted noise field shows the best agreement for a convergent nozzle geometry under static conditions. Predicted results for nozzles in flight show larger discrepancies from data and more dependable flight data are required for further comparison. Qualitative effects of jet temperature, as observed in experiment, are reproduced in predicted results.

  18. Critical evidence for the prediction error theory in associative learning

    PubMed Central

    Terao, Kanta; Matsumoto, Yukihisa; Mizunami, Makoto

    2015-01-01

    In associative learning in mammals, it is widely accepted that the discrepancy, or error, between actual and predicted reward determines whether learning occurs. Complete evidence for the prediction error theory, however, has not been obtained in any learning systems: Prediction error theory stems from the finding of a blocking phenomenon, but blocking can also be accounted for by other theories, such as the attentional theory. We demonstrated blocking in classical conditioning in crickets and obtained evidence to reject the attentional theory. To obtain further evidence supporting the prediction error theory and rejecting alternative theories, we constructed a neural model to match the prediction error theory, by modifying our previous model of learning in crickets, and we tested a prediction from the model: the model predicts that pharmacological intervention of octopaminergic transmission during appetitive conditioning impairs learning but not formation of reward prediction itself, and it thus predicts no learning in subsequent training. We observed such an “auto-blocking”, which could be accounted for by the prediction error theory but not by other competitive theories to account for blocking. This study unambiguously demonstrates validity of the prediction error theory in associative learning. PMID:25754125

  19. Critical evidence for the prediction error theory in associative learning.

    PubMed

    Terao, Kanta; Matsumoto, Yukihisa; Mizunami, Makoto

    2015-01-01

    In associative learning in mammals, it is widely accepted that the discrepancy, or error, between actual and predicted reward determines whether learning occurs. Complete evidence for the prediction error theory, however, has not been obtained in any learning systems: Prediction error theory stems from the finding of a blocking phenomenon, but blocking can also be accounted for by other theories, such as the attentional theory. We demonstrated blocking in classical conditioning in crickets and obtained evidence to reject the attentional theory. To obtain further evidence supporting the prediction error theory and rejecting alternative theories, we constructed a neural model to match the prediction error theory, by modifying our previous model of learning in crickets, and we tested a prediction from the model: the model predicts that pharmacological intervention of octopaminergic transmission during appetitive conditioning impairs learning but not formation of reward prediction itself, and it thus predicts no learning in subsequent training. We observed such an "auto-blocking", which could be accounted for by the prediction error theory but not by other competitive theories to account for blocking. This study unambiguously demonstrates validity of the prediction error theory in associative learning. PMID:25754125

  20. MASS FUNCTION PREDICTIONS BEYOND {Lambda}CDM

    SciTech Connect

    Bhattacharya, Suman; Lukic, Zarija; Habib, Salman; Heitmann, Katrin; White, Martin; Wagner, Christian

    2011-05-10

    The statistics of dark matter halos is an essential component of precision cosmology. The mass distribution of halos, as specified by the halo mass function, is a key input for several cosmological probes. The sizes of N-body simulations are now such that, for the most part, results need no longer be statistics-limited, but are still subject to various systematic uncertainties. Discrepancies in the results of simulation campaigns for the halo mass function remain in excess of statistical uncertainties and of roughly the same size as the error limits set by near-future observations; we investigate and discuss some of the reasons for these differences. Quantifying error sources and compensating for them as appropriate, we carry out a high-statistics study of dark matter halos from 67 N-body simulations to investigate the mass function and its evolution for a reference {Lambda}CDM cosmology and for a set of wCDM cosmologies. For the reference {Lambda}CDM cosmology (close to WMAP5), we quantify the breaking of universality in the form of the mass function as a function of redshift, finding an evolution of as much as 10% away from the universal form between redshifts z = 0 and z = 2. For cosmologies very close to this reference we provide a fitting formula to our results for the (evolving) {Lambda}CDM mass function over a mass range of 6 x 10{sup 11}-3 x 10{sup 15} M{sub sun} to an estimated accuracy of about 2%. The set of wCDM cosmologies is taken from the Coyote Universe simulation suite. The mass functions from this suite (which includes a {Lambda}CDM cosmology and others with w {approx_equal} -1) are described by the fitting formula for the reference {Lambda}CDM case at an accuracy level of 10%, but with clear systematic deviations. We argue that, as a consequence, fitting formulae based on a universal form for the mass function may have limited utility in high-precision cosmological applications.

  1. Mass Function Predictions Beyond ΛCDM

    NASA Astrophysics Data System (ADS)

    Bhattacharya, Suman; Heitmann, Katrin; White, Martin; Lukić, Zarija; Wagner, Christian; Habib, Salman

    2011-05-01

    The statistics of dark matter halos is an essential component of precision cosmology. The mass distribution of halos, as specified by the halo mass function, is a key input for several cosmological probes. The sizes of N-body simulations are now such that, for the most part, results need no longer be statistics-limited, but are still subject to various systematic uncertainties. Discrepancies in the results of simulation campaigns for the halo mass function remain in excess of statistical uncertainties and of roughly the same size as the error limits set by near-future observations; we investigate and discuss some of the reasons for these differences. Quantifying error sources and compensating for them as appropriate, we carry out a high-statistics study of dark matter halos from 67 N-body simulations to investigate the mass function and its evolution for a reference ΛCDM cosmology and for a set of wCDM cosmologies. For the reference ΛCDM cosmology (close to WMAP5), we quantify the breaking of universality in the form of the mass function as a function of redshift, finding an evolution of as much as 10% away from the universal form between redshifts z = 0 and z = 2. For cosmologies very close to this reference we provide a fitting formula to our results for the (evolving) ΛCDM mass function over a mass range of 6 × 1011-3 × 1015 M sun to an estimated accuracy of about 2%. The set of wCDM cosmologies is taken from the Coyote Universe simulation suite. The mass functions from this suite (which includes a ΛCDM cosmology and others with w ~= -1) are described by the fitting formula for the reference ΛCDM case at an accuracy level of 10%, but with clear systematic deviations. We argue that, as a consequence, fitting formulae based on a universal form for the mass function may have limited utility in high-precision cosmological applications.

  2. Early executive function predicts reasoning development.

    PubMed

    Richland, Lindsey E; Burchinal, Margaret R

    2013-01-01

    Analogical reasoning is a core cognitive skill that distinguishes humans from all other species and contributes to general fluid intelligence, creativity, and adaptive learning capacities. Yet its origins are not well understood. In the study reported here, we analyzed large-scale longitudinal data from the Study of Early Child Care and Youth Development to test predictors of growth in analogical-reasoning skill from third grade to adolescence. Our results suggest an integrative resolution to the theoretical debate regarding contributory factors arising from smaller-scale, cross-sectional experiments on analogy development. Children with greater executive-function skills (both composite and inhibitory control) and vocabulary knowledge in early elementary school displayed higher scores on a verbal analogies task at age 15 years, even after adjusting for key covariates. We posit that knowledge is a prerequisite to analogy performance, but strong executive-functioning resources during early childhood are related to long-term gains in fundamental reasoning skills. PMID:23184588

  3. Sexual abuse predicts functional somatic symptoms: an adolescent population study.

    PubMed

    Bonvanie, Irma J; van Gils, Anne; Janssens, Karin A M; Rosmalen, Judith G M

    2015-08-01

    The main aim of this study was to investigate the effect of childhood sexual abuse on medically not well explained or functional somatic symptoms (FSSs) in adolescents. We hypothesized that sexual abuse predicts higher levels of FSSs and that anxiety and depression contribute to this relationship. In addition, we hypothesized that more severe abuse is associated with higher levels of FSSs and that sexual abuse is related to gastrointestinal FSSs in particular. This study was part of the Tracking Adolescents' Individual Lives Survey (TRAILS): a general population cohort which started in 2001 (N=2,230; 50.8% girls, mean age 11.1 years). The current study uses data of 1,680 participants over four assessment waves (75% of baseline, mean duration of follow-up: 8 years). FSSs were measured by the Somatic Complaints subscale of the Youth Self-Report at all waves. Sexual abuse before the age of sixteen was assessed retrospectively with a questionnaire at T4. To test the hypotheses linear mixed models were used adjusted for age, sex, socioeconomic status, anxiety and depression. Sexual abuse predicted higher levels of FSSs after adjustment for age sex and socioeconomic status (B=.06) and after additional adjustment for anxiety and depression (B=.03). While sexual abuse involving physical contact significantly predicted the level of FSSs (assault; B=.08, rape; B=.05), non-contact sexual abuse was not significantly associated with FSSs (B=.04). Sexual abuse was not a stronger predictor of gastrointestinal FSSs (B=.06) than of all FSSs. Further research is needed to clarify possible mechanisms underlying relationship between sexual abuse and FSSs. PMID:26142915

  4. Probabilistic Protein Function Prediction from Heterogeneous Genome-Wide Data

    PubMed Central

    Nariai, Naoki; Kolaczyk, Eric D.; Kasif, Simon

    2007-01-01

    Dramatic improvements in high throughput sequencing technologies have led to a staggering growth in the number of predicted genes. However, a large fraction of these newly discovered genes do not have a functional assignment. Fortunately, a variety of novel high-throughput genome-wide functional screening technologies provide important clues that shed light on gene function. The integration of heterogeneous data to predict protein function has been shown to improve the accuracy of automated gene annotation systems. In this paper, we propose and evaluate a probabilistic approach for protein function prediction that integrates protein-protein interaction (PPI) data, gene expression data, protein motif information, mutant phenotype data, and protein localization data. First, functional linkage graphs are constructed from PPI data and gene expression data, in which an edge between nodes (proteins) represents evidence for functional similarity. The assumption here is that graph neighbors are more likely to share protein function, compared to proteins that are not neighbors. The functional linkage graph model is then used in concert with protein domain, mutant phenotype and protein localization data to produce a functional prediction. Our method is applied to the functional prediction of Saccharomyces cerevisiae genes, using Gene Ontology (GO) terms as the basis of our annotation. In a cross validation study we show that the integrated model increases recall by 18%, compared to using PPI data alone at the 50% precision. We also show that the integrated predictor is significantly better than each individual predictor. However, the observed improvement vs. PPI depends on both the new source of data and the functional category to be predicted. Surprisingly, in some contexts integration hurts overall prediction accuracy. Lastly, we provide a comprehensive assignment of putative GO terms to 463 proteins that currently have no assigned function. PMID:17396164

  5. Functional prediction of hypothetical proteins in human adenoviruses.

    PubMed

    Dorden, Shane; Mahadevan, Padmanabhan

    2015-01-01

    Assigning functional information to hypothetical proteins in virus genomes is crucial for gaining insight into their proteomes. Human adenoviruses are medium sized viruses that cause a range of diseases. Their genomes possess proteins with uncharacterized function known as hypothetical proteins. Using a wide range of protein function prediction servers, functional information was obtained about these hypothetical proteins. A comparison of functional information obtained from these servers revealed that some of them produced functional information, while others provided little functional information about these human adenovirus hypothetical proteins. The PFP, ESG, PSIPRED, 3d2GO, and ProtFun servers produced the most functional information regarding these hypothetical proteins. PMID:26664031

  6. Predicting Transfer Performance: A Comparison of Competing Function Learning Models

    ERIC Educational Resources Information Center

    McDaniel, Mark A.; Dimperio, Eric; Griego, Jacqueline A.; Busemeyer, Jerome R.

    2009-01-01

    The population of linear experts (POLE) model suggests that function learning and transfer are mediated by activation of a set of prestored linear functions that together approximate the given function (Kalish, Lewandowsky, & Kruschke, 2004). In the extrapolation-association (EXAM) model, an exemplar-based architecture associates trained input…

  7. Using search engine technology for protein function prediction.

    PubMed

    Chen, Ziyang; Cai, Zhao; Li, Min; Liu, Binbin

    2011-01-01

    Prediction of protein function is one of the most challenging problems in the post-genomic era. In this paper, we propose a novel algorithm Improved ProteinRank (IPR) for protein function prediction, which is based on the search engine technology and the preferential attachment criteria. In addition, an improved algorithm IPRW is developed from IPR to be used in the weighted protein?protein interaction (PPI) network. The proposed algorithms IPR and IPRW are applied to the PPI network of S.cerevisiae. The experimental results show that both IPR and IPRW outweigh the previous methods for the prediction of protein functions. PMID:21441099

  8. Predicting individual brain maturity using dynamic functional connectivity

    PubMed Central

    Qin, Jian; Chen, Shan-Guang; Hu, Dewen; Zeng, Ling-Li; Fan, Yi-Ming; Chen, Xiao-Ping; Shen, Hui

    2015-01-01

    Neuroimaging-based functional connectivity (FC) analyses have revealed significant developmental trends in specific intrinsic connectivity networks linked to cognitive and behavioral maturation. However, knowledge of how brain functional maturation is associated with FC dynamics at rest is limited. Here, we examined age-related differences in the temporal variability of FC dynamics with data publicly released by the Nathan Kline Institute (NKI; n = 183, ages 7–30) and showed that dynamic inter-region interactions can be used to accurately predict individual brain maturity across development. Furthermore, we identified a significant age-dependent trend underlying dynamic inter-network FC, including increasing variability of the connections between the visual network, default mode network (DMN) and cerebellum as well as within the cerebellum and DMN and decreasing variability within the cerebellum and between the cerebellum and DMN as well as the cingulo-opercular network. Overall, the results suggested significant developmental changes in dynamic inter-network interaction, which may shed new light on the functional organization of typical developmental brains. PMID:26236224

  9. Dopamine neurons share common response function for reward prediction error

    PubMed Central

    Eshel, Neir; Tian, Ju; Bukwich, Michael; Uchida, Naoshige

    2016-01-01

    Dopamine neurons are thought to signal reward prediction error, or the difference between actual and predicted reward. How dopamine neurons jointly encode this information, however, remains unclear. One possibility is that different neurons specialize in different aspects of prediction error; another is that each neuron calculates prediction error in the same way. We recorded from optogenetically-identified dopamine neurons in the lateral ventral tegmental area (VTA) while mice performed classical conditioning tasks. Our tasks allowed us to determine the full prediction error functions of dopamine neurons and compare them to each other. We found striking homogeneity among individual dopamine neurons: their responses to both unexpected and expected rewards followed the same function, just scaled up or down. As a result, we could describe both individual and population responses using just two parameters. Such uniformity ensures robust information coding, allowing each dopamine neuron to contribute fully to the prediction error signal. PMID:26854803

  10. Polyamines: Predictive Biomarker for HIV-Associated Neurocognitive Disorders

    PubMed Central

    Merali, Salim; Barrero, Carlos A.; Sacktor, Ned C.; Haughey, Norman J.; Datta, Prasun K.; Langford, Dianne; Khalili, Kamel

    2014-01-01

    Objectives Spermidine/spermine-N1-acetytransferase (SSAT) is the key enzyme in the catabolism of polyamines that are involved in regulating NMDA functioning. Over expression of SSAT leads to abnormal metabolic cycling and may disrupt NMDA receptor signaling. In fact, the HIV protein Tat induces neurotoxicity involving polyamine/NMDA receptor interactions. Thus, we investigated abnormal polyamine cycling in HIV+ participants with varying degrees of HIV-associated neurocognitive disorders. Methods Acetyl-polyamine (SSAT products) levels were assessed by HPLC in CSF from 99 HIV-infected participants (no cognitive impairment (NCI, n=25), asymptomatic neurocognitive impairment (ANI, n=25), mild cognitive and motor disorders (MCMD, n=24), and HIV-associated dementia (HAD, n=25)). Polyamine levels in brain tissues from a subset of participants (uninfected (n=3), NCI (n=3), and MNCD (n=3)) were also assessed. Human primary astrocytes expressing HIV Tat were assessed for levels of the SSAT activity. Results Activation of the polyamine catabolic enzyme, SSAT increases polyamine flux in brain and CSF of HIV infected individuals with HIV-associated neurocognitive disorders. CSF levels of acetylated polyamine increase with the degree of HAND severity as indicated by significantly increased acetylpolyamine levels in HAD participants compared to NCI and ANI (p<0.0001) and between MCMD and NCI and ANI (p<0.0001). In vitro studies suggest that the HIV protein Tat may be responsible in part for astrocyte-derived acetyl polyamine release. Interpretation Our data suggest that polyamine metabolism may play a pivotal role in the neurodegeneration process among HAND patients. Changes in polyamine flux may serve as a potential predictive diagnostic biomarker for different severities of HAND. PMID:25893137

  11. A new protein structure representation for efficient protein function prediction.

    PubMed

    Maghawry, Huda A; Mostafa, Mostafa G M; Gharib, Tarek F

    2014-12-01

    One of the challenging problems in bioinformatics is the prediction of protein function. Protein function is the main key that can be used to classify different proteins. Protein function can be inferred experimentally with very small throughput or computationally with very high throughput. Computational methods are sequence based or structure based. Structure-based methods produce more accurate protein function prediction. In this article, we propose a new protein structure representation for efficient protein function prediction. The representation is based on three-dimensional patterns of protein residues. In the analysis, we used protein function based on enzyme activity through six mechanistically diverse enzyme superfamilies: amidohydrolase, crotonase, haloacid dehalogenase, isoprenoid synthase type I, and vicinal oxygen chelate. We applied three different classification methods, naïve Bayes, k-nearest neighbors, and random forest, to predict the enzyme superfamily of a given protein. The prediction accuracy using the proposed representation outperforms a recently introduced representation method that is based only on the distance patterns. The results show that the proposed representation achieved prediction accuracy up to 98%, with improvement of about 10% on average. PMID:25343279

  12. Genome-environment associations in sorghum landraces predict adaptive traits.

    PubMed

    Lasky, Jesse R; Upadhyaya, Hari D; Ramu, Punna; Deshpande, Santosh; Hash, C Tom; Bonnette, Jason; Juenger, Thomas E; Hyma, Katie; Acharya, Charlotte; Mitchell, Sharon E; Buckler, Edward S; Brenton, Zachary; Kresovich, Stephen; Morris, Geoffrey P

    2015-07-01

    Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these could be used to predict phenotypic variation for adaptive traits. We tested this proposition in the global food crop Sorghum bicolor, characterizing 1943 georeferenced landraces at 404,627 SNPs and quantifying allelic associations with bioclimatic and soil gradients. Environment explained a substantial portion of SNP variation, independent of geographical distance, and genic SNPs were enriched for environmental associations. Further, environment-associated SNPs predicted genotype-by-environment interactions under experimental drought stress and aluminum toxicity. Our results suggest that genomic signatures of environmental adaptation may be useful for crop improvement, enhancing germplasm identification and marker-assisted selection. Together, genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation. PMID:26601206

  13. Genome-environment associations in sorghum landraces predict adaptive traits

    PubMed Central

    Lasky, Jesse R.; Upadhyaya, Hari D.; Ramu, Punna; Deshpande, Santosh; Hash, C. Tom; Bonnette, Jason; Juenger, Thomas E.; Hyma, Katie; Acharya, Charlotte; Mitchell, Sharon E.; Buckler, Edward S.; Brenton, Zachary; Kresovich, Stephen; Morris, Geoffrey P.

    2015-01-01

    Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these could be used to predict phenotypic variation for adaptive traits. We tested this proposition in the global food crop Sorghum bicolor, characterizing 1943 georeferenced landraces at 404,627 SNPs and quantifying allelic associations with bioclimatic and soil gradients. Environment explained a substantial portion of SNP variation, independent of geographical distance, and genic SNPs were enriched for environmental associations. Further, environment-associated SNPs predicted genotype-by-environment interactions under experimental drought stress and aluminum toxicity. Our results suggest that genomic signatures of environmental adaptation may be useful for crop improvement, enhancing germplasm identification and marker-assisted selection. Together, genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation. PMID:26601206

  14. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

    EPA Science Inventory

    We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

  15. Gene function prediction with knowledge from gene ontology.

    PubMed

    Shen, Ying; Zhang, Lin

    2015-01-01

    Gene function prediction is an important problem in bioinformatics. Due to the inherent noise existing in the gene expression data, the attempt to improve the prediction accuracy resorting to new classification techniques is limited. With the emergence of Gene Ontology (GO), extra knowledge about the gene products can be extracted from GO and facilitates solving the gene function prediction problem. In this paper, we propose a new method which utilises GO information to improve the classifiers' performance in gene function prediction. Specifically, our method learns a distance metric under the supervision of the GO knowledge using the distance learning technique. Compared with the traditional distance metrics, the learned one produces a better performance and consequently classification accuracy can be improved. The effectiveness of our proposed method has been corroborated by the extensive experimental results. PMID:26529907

  16. Empirical sediment transport function predicting seepage erosion undercutting for cohesive bank failure prediction

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Seepage erosion is an important factor in hillslope instability and failure. However, predicting erosion by subsurface flow or seepage and incorporating its effects into stability models remains a challenge. Limitations exist with all existing seepage erosion sediment transport functions, including ...

  17. Preschool Executive Functioning Abilities Predict Early Mathematics Achievement

    ERIC Educational Resources Information Center

    Clark, Caron A. C.; Pritchard, Verena E.; Woodward, Lianne J.

    2010-01-01

    Impairments in executive function have been documented in school-age children with mathematical learning difficulties. However, the utility and specificity of preschool executive function abilities in predicting later mathematical achievement are poorly understood. This study examined linkages between children's developing executive function…

  18. A Unitary Executive Function Predicts Intelligence in Children

    ERIC Educational Resources Information Center

    Brydges, Christopher R.; Reid, Corinne L.; Fox, Allison M.; Anderson, Mike

    2012-01-01

    Executive functions (EF) and intelligence are of critical importance to success in many everyday tasks. Working memory, or updating, which is one latent variable identified in confirmatory factor analytic models of executive functions, predicts intelligence (both fluid and crystallised) in adults, but inhibition and shifting do not (Friedman et…

  19. INTEGRATING COMPUTATIONAL PROTEIN FUNCTION PREDICTION INTO DRUG DISCOVERY INITIATIVES

    PubMed Central

    Grant, Marianne A.

    2014-01-01

    Pharmaceutical researchers must evaluate vast numbers of protein sequences and formulate innovative strategies for identifying valid targets and discovering leads against them as a way of accelerating drug discovery. The ever increasing number and diversity of novel protein sequences identified by genomic sequencing projects and the success of worldwide structural genomics initiatives have spurred great interest and impetus in the development of methods for accurate, computationally empowered protein function prediction and active site identification. Previously, in the absence of direct experimental evidence, homology-based protein function annotation remained the gold-standard for in silico analysis and prediction of protein function. However, with the continued exponential expansion of sequence databases, this approach is not always applicable, as fewer query protein sequences demonstrate significant homology to protein gene products of known function. As a result, several non-homology based methods for protein function prediction that are based on sequence features, structure, evolution, biochemical and genetic knowledge have emerged. Herein, we review current bioinformatic programs and approaches for protein function prediction/annotation and discuss their integration into drug discovery initiatives. The development of such methods to annotate protein functional sites and their application to large protein functional families is crucial to successfully utilizing the vast amounts of genomic sequence information available to drug discovery and development processes. PMID:25530654

  20. A large-scale evaluation of computational protein function prediction

    PubMed Central

    Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    2013-01-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

  1. A large-scale evaluation of computational protein function prediction.

    PubMed

    Radivojac, Predrag; Clark, Wyatt T; Oron, Tal Ronnen; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kaßner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Boehm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas A; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    2013-03-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools. PMID:23353650

  2. Protein Structure and Function Prediction Using I-TASSER

    PubMed Central

    Yang, Jianyi; Zhang, Yang

    2016-01-01

    I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. PMID:26678386

  3. Relating Phylogenetic and Functional Diversity among Denitrifiers and Quantifying their Capacity to Predict Community Functioning

    PubMed Central

    Salles, Joana Falcão; Le Roux, Xavier; Poly, Franck

    2012-01-01

    Genetic diversity of phylogenetic or functional markers is widely used as a proxy of microbial diversity. However, it remains unclear to what extent functional diversity (FD), gene sequence diversity and community functioning are linked. For a range of denitrifying bacteria, we analyzed the relationships between (i) the similarity of functional traits evaluated from metabolic profiles (BIOLOG plates) or from N2O accumulation patterns on different carbon sources and (ii) the similarity of phylogenetic (16S rRNA gene) or functional (nir gene) markers. We also calculated different proxies for the diversity of denitrifier community based on taxa richness, phylogenetic (16S rRNA gene) or functional similarities (based either on metabolic profiles or N2O accumulation patterns), and evaluated their performance in inferring the functioning of assembled denitrifying communities. For individual strains, the variation in the 16S rRNA gene sequence was weakly correlated with the variation in metabolic patterns (ρ = 0.35) and was not related to N2O accumulation. The latter was correlated with the similarity of nitrite reductase residues. When nir genes were analyzed separately, the similarity in amino acids coded by the nirS genes was highly correlated with the observed patterns of N2O accumulation (ρ = 0.62), whereas nirK amino acid residues were unrelated to N2O accumulation. For bacterial assemblages, phylogenetic diversity (average similarity among species in a community) and mean community dissimilarity (average distance between species) calculated using 16S rRNA gene sequences, and FD measures associated with metabolic profiles, poorly predicted the variation in the functioning of assembled communities (≤15%). In contrast, the proxies of FD based on N2O accumulation patterns performed better and explained from 23 to 42% of the variation in denitrification. Amongst those, community niche was the best metric, indicating the importance of complementarity for

  4. Beyond GWASs: Illuminating the Dark Road from Association to Function

    PubMed Central

    Edwards, Stacey L.; Beesley, Jonathan; French, Juliet D.; Dunning, Alison M.

    2013-01-01

    Genome-wide association studies (GWASs) have enabled the discovery of common genetic variation contributing to normal and pathological traits and clinical drug responses, but recognizing the precise targets of these associations is now the major challenge. Here, we review recent approaches to the functional follow-up of GWAS loci, including fine mapping of GWAS signal(s), prioritization of putative functional SNPs by the integration of genetic epidemiological and bioinformatic methods, and in vitro and in vivo experimental verification of predicted molecular mechanisms for identifying the targeted genes. The majority of GWAS-identified variants fall in noncoding regions of the genome. Therefore, this review focuses on strategies for assessing likely mechanisms affected by noncoding variants; such mechanisms include transcriptional regulation, noncoding RNA function, and epigenetic regulation. These approaches have already accelerated progress from genetic studies to biological knowledge and might ultimately guide the development of prognostic, preventive, and therapeutic measures. PMID:24210251

  5. Ladder operators for the associated Laguerre functions

    NASA Astrophysics Data System (ADS)

    Fakhri, H.; Chenaghlou, A.

    2004-07-01

    Introducing the associated Laguerre functions in terms of two non-negative integers, we obtain simultaneously and separately realization of the laddering equations with respect to each of the integers by means of two pairs of ladder operators. Besides, two different types of shape-invariance symmetries are realized. This approach leads to a derivation of shape-invariance equations of third type which are realized by two simultaneous raising and lowering operators of two parameters.

  6. Curved Saccade Trajectories Reveal Conflicting Predictions in Associative Learning

    ERIC Educational Resources Information Center

    Koenig, Stephan; Lachnit, Harald

    2011-01-01

    We report how the trajectories of saccadic eye movements are affected by memory interference acquired during associative learning. Human participants learned to perform saccadic choice responses based on the presentation of arbitrary central cues A, B, AC, BC, AX, BY, X, and Y that were trained to predict the appearance of a peripheral target…

  7. Revisiting the prediction of protein function at CASP6.

    PubMed

    Pellegrini-Calace, Marialuisa; Soro, Simonetta; Tramontano, Anna

    2006-07-01

    The ability to predict the function of a protein, given its sequence and/or 3D structure, is an essential requirement for exploiting the wealth of data made available by genomics and structural genomics projects and is therefore raising increasing interest in the computational biology community. To foster developments in the area as well as to establish the state of the art of present methods, a function prediction category was tentatively introduced in the 6th edition of the Critical Assessment of Techniques for Protein Structure Prediction (CASP) worldwide experiment. The assessment of the performance of the methods was made difficult by at least two factors: (a) the experimentally determined function of the targets was not available at the time of assessment; (b) the experiment is run blindly, preventing verification of whether the convergence of different predictions towards the same functional annotation was due to the similarity of the methods or to a genuine signal detectable by different methodologies. In this work, we collected information about the methods used by the various predictors and revisited the results of the experiment by verifying how often and in which cases a convergent prediction was obtained by methods based on different rationale. We propose a method for classifying the type and redundancy of the methods. We also analyzed the cases in which a function for the target protein has become available. Our results show that predictions derived from a consensus of different methods can reach an accuracy as high as 80%. It follows that some of the predictions submitted to CASP6, once reanalyzed taking into account the type of converging methods, can provide very useful information to researchers interested in the function of the target proteins. PMID:16759228

  8. Functional Analysis of Variance for Association Studies

    PubMed Central

    Vsevolozhskaya, Olga A.; Zaykin, Dmitri V.; Greenwood, Mark C.; Wei, Changshuai; Lu, Qing

    2014-01-01

    While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. In this paper, we propose a functional analysis of variance (FANOVA) method for testing an association of sequence variants in a genomic region with a qualitative trait. The FANOVA has a number of advantages: (1) it tests for a joint effect of gene variants, including both common and rare; (2) it fully utilizes linkage disequilibrium and genetic position information; and (3) allows for either protective or risk-increasing causal variants. Through simulations, we show that FANOVA outperform two popularly used methods – SKAT and a previously proposed method based on functional linear models (FLM), – especially if a sample size of a study is small and/or sequence variants have low to moderate effects. We conduct an empirical study by applying three methods (FANOVA, SKAT and FLM) to sequencing data from Dallas Heart Study. While SKAT and FLM respectively detected ANGPTL 4 and ANGPTL 3 associated with obesity, FANOVA was able to identify both genes associated with obesity. PMID:25244256

  9. Executive function does not predict coping with symptoms in stable patients with a diagnosis of schizophrenia

    PubMed Central

    Bak, Maarten; Krabbendam, Lydia; Delespaul, Philippe; Huistra, Karola; Walraven, Wil; van Os, Jim

    2008-01-01

    Background Associations between coping with and control over psychotic symptoms were examined using the Maastricht Assessment of Coping Strategies-24, testing the hypothesis that the cognitive domain of executive functioning predicted quality and quantity of coping. Methods MACS-24 was administered to 32 individuals with a diagnosis of schizophrenia. For each of 24 symptoms, experience of distress, type of coping and the resulting degree of perceived control were assessed. Coping types were reduced to two contrasting coping categories: symptomatic coping (SC) and non-symptomatic coping (NSC; combining active problem solving, passive illness behaviour, active problem avoiding, and passive problem avoiding). Cognitive functioning was assessed using the GIT (Groninger Intelligence Test), the Zoo map (BADS: Behavioural Assessment of Dysexecutive function), Stroop-test and Trail making. Results Cognitive function was not associated with frequency of coping, nor did cognitive function differentially predict SC or NSC. Cognitive function similarly was not associated with symptom distress or level of perceived control over the symptom. Conclusion There was no evidence that cognitive function predicts quantity or quality of coping with symptoms in people with a diagnosis of schizophrenia. Variation in the realm of emotion regulation and social cognition may be more predictive of coping with psychotic symptoms. PMID:18510757

  10. Inductive matrix completion for predicting gene–disease associations

    PubMed Central

    Natarajan, Nagarajan; Dhillon, Inderjit S.

    2014-01-01

    Motivation: Most existing methods for predicting causal disease genes rely on specific type of evidence, and are therefore limited in terms of applicability. More often than not, the type of evidence available for diseases varies—for example, we may know linked genes, keywords associated with the disease obtained by mining text, or co-occurrence of disease symptoms in patients. Similarly, the type of evidence available for genes varies—for example, specific microarray probes convey information only for certain sets of genes. In this article, we apply a novel matrix-completion method called Inductive Matrix Completion to the problem of predicting gene-disease associations; it combines multiple types of evidence (features) for diseases and genes to learn latent factors that explain the observed gene–disease associations. We construct features from different biological sources such as microarray expression data and disease-related textual data. A crucial advantage of the method is that it is inductive; it can be applied to diseases not seen at training time, unlike traditional matrix-completion approaches and network-based inference methods that are transductive. Results: Comparison with state-of-the-art methods on diseases from the Online Mendelian Inheritance in Man (OMIM) database shows that the proposed approach is substantially better—it has close to one-in-four chance of recovering a true association in the top 100 predictions, compared to the recently proposed Catapult method (second best) that has <15% chance. We demonstrate that the inductive method is particularly effective for a query disease with no previously known gene associations, and for predicting novel genes, i.e. genes that are previously not linked to diseases. Thus the method is capable of predicting novel genes even for well-characterized diseases. We also validate the novelty of predictions by evaluating the method on recently reported OMIM associations and on associations recently

  11. Differential association between chronic cannabis use and brain function deficits.

    PubMed

    Soueif, M I

    1976-01-01

    To summarize, 12 objective tests that generated 16 test variables were administered to 850 male regular cannabis users and 839 nonusers. The tests were designed to assess various modalities, including speed of psychomotor performance, distance estimation, time estimation, immediate memory, and visuomotor coordination. Most of the test variables differentiated significantly between consumers and controls. At the same time, a significant second-order interaction emerged in most cases. This interaction meant that, under certain conditions that relate to the two dimensions "literacy-illiteracy" and/or "urbanism-ruralism," the superiority of controls over cannabis users became impressive, whereas under other conditions it almost disappeared. To account for this complex pattern of results, a working hypothesis was presented to the effect that "other conditions being equal, the lower the nondrug level of proficiency on tests of cognitive and psychomotor performance the smaller the size of function deficit associated with drug usage." For an empirical examination of the hypothesis, six predictions were formulated. Three predictions defined specific relationships between level of performance, on one hand, and each of three organismic variables, on the other: literacy, urbanism, and age. The remaining predictions delineated relationships to be expected between size of function deficit and the three organismic variables. All our predictions were confirmed, showing less function impairment to be contingent with cannabis usage among the illiterates, rurals, and older subjects. Level of cortical arousal was suggested as the central process associated with the three organismic variables. Because the version of our working hypothesis was formulated with reference to chronic material, the possibility of a transposition of the paradign to research on the acute effects of the drug was discussed. The suggestion was made that our working hypothesis, in either version, is capable of

  12. Prediction of Functional Outcome in Axonal Guillain-Barre Syndrome

    PubMed Central

    2016-01-01

    Objective To identify the factors that could predict the functional outcome in patients with the axonal type of Guillain-Barre syndrome (GBS). Methods Two hundred and two GBS patients admitted to our university hospital between 2003 and 2014 were reviewed retrospectively. We defined a good outcome as being "able to walk independently at 1 month after onset" and a poor outcome as being "unable to walk independently at 1 month after onset". We evaluated the factors that differed between the good and poor outcome groups. Results Twenty-four patients were classified into the acute motor axonal neuropathy type. There was a statistically significant difference between the good and poor outcome groups in terms of the GBS disability score at admission, and GBS disability score and Medical Research Council sum score at 1 month after admission. In an electrophysiologic analysis, the good outcome group showed greater amplitude of median, ulnar, deep peroneal, and posterior tibial nerve compound muscle action potentials (CMAP) and greater amplitude of median, ulnar, and superficial peroneal sensory nerve action potentials (SNAP) than the poor outcome group. Conclusion A lower GBS disability score at admission, high amplitude of median, ulnar, deep peroneal, and posterior tibial CMAPs, and high amplitude of median, ulnar, and superficial peroneal SNAPs were associated with being able to walk at 1 month in patients with axonal GBS. PMID:27446785

  13. PredictProtein—an open resource for online prediction of protein structural and functional features

    PubMed Central

    Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

    2014-01-01

    PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431

  14. PHARM – Association Rule Mining for Predictive Health

    PubMed Central

    Cheng, Chih-Wen; Martin, Greg S.; Wu, Po-Yen; Wang, May D.

    2016-01-01

    Predictive health is a new and innovative healthcare model that focuses on maintaining health rather than treating diseases. Such a model may benefit from computer-based decision support systems, which provide more quantitative health assessment, enabling more objective advice and action plans from predictive health providers. However, data mining for predictive health is more challenging compared to that for diseases. This is a reason why there are relatively fewer predictive health decision support systems embedded with data mining. The purpose of this study is to research and develop an interactive decision support system, called PHARM, in conjunction with Emory Center for Health Discovery and Well Being (CHDWB®). PHARM adopts association rule mining to generate quantitative and objective rules for health assessment and prediction. A case study results in 12 rules that predict mental illness based on five psychological factors. This study shows the value and usability of the decision support system to prevent the development of potential illness and to prioritize advice and action plans for reducing disease risks.

  15. Biochemical functional predictions for protein structures of unknown or uncertain function

    PubMed Central

    Mills, Caitlyn L.; Beuning, Penny J.; Ondrechen, Mary Jo

    2015-01-01

    With the exponential growth in the determination of protein sequences and structures via genome sequencing and structural genomics efforts, there is a growing need for reliable computational methods to determine the biochemical function of these proteins. This paper reviews the efforts to address the challenge of annotating the function at the molecular level of uncharacterized proteins. While sequence- and three-dimensional-structure-based methods for protein function prediction have been reviewed previously, the recent trends in local structure-based methods have received less attention. These local structure-based methods are the primary focus of this review. Computational methods have been developed to predict the residues important for catalysis and the local spatial arrangements of these residues can be used to identify protein function. In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function. Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function. These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations. PMID:25848497

  16. Can infant lung function predict respiratory morbidity during the first year of life in preterm infants?

    PubMed

    Proietti, Elena; Riedel, Thomas; Fuchs, Oliver; Pramana, Isabelle; Singer, Florian; Schmidt, Anne; Kuehni, Claudia; Latzin, Philipp; Frey, Urs

    2014-06-01

    Compared with term-born infants, preterm infants have increased respiratory morbidity in the first year of life. We investigated whether lung function tests performed near term predict subsequent respiratory morbidity during the first year of life and compared this to standard clinical parameters in preterms. The prospective birth cohort included randomly selected preterm infants with and without bronchopulmonary dysplasia. Lung function (tidal breathing and multiple-breath washout) was measured at 44 weeks post-menstrual age during natural sleep. We assessed respiratory morbidity (wheeze, hospitalisation, inhalation and home oxygen therapy) after 1 year using a standardised questionnaire. We first assessed the association between lung function and subsequent respiratory morbidity. Secondly, we compared the predictive power of standard clinical predictors with and without lung function data. In 166 preterm infants, tidal volume, time to peak tidal expiratory flow/expiratory time ratio and respiratory rate were significantly associated with subsequent wheeze. In comparison with standard clinical predictors, lung function did not improve the prediction of later respiratory morbidity in an individual child. Although associated with later wheeze, noninvasive infant lung function shows large physiological variability and does not add to clinically relevant risk prediction for subsequent respiratory morbidity in an individual preterm. PMID:24696112

  17. Exploring Function Prediction in Protein Interaction Networks via Clustering Methods

    PubMed Central

    Trivodaliev, Kire; Bogojeska, Aleksandra; Kocarev, Ljupco

    2014-01-01

    Complex networks have recently become the focus of research in many fields. Their structure reveals crucial information for the nodes, how they connect and share information. In our work we analyze protein interaction networks as complex networks for their functional modular structure and later use that information in the functional annotation of proteins within the network. We propose several graph representations for the protein interaction network, each having different level of complexity and inclusion of the annotation information within the graph. We aim to explore what the benefits and the drawbacks of these proposed graphs are, when they are used in the function prediction process via clustering methods. For making this cluster based prediction, we adopt well established approaches for cluster detection in complex networks using most recent representative algorithms that have been proven as efficient in the task at hand. The experiments are performed using a purified and reliable Saccharomyces cerevisiae protein interaction network, which is then used to generate the different graph representations. Each of the graph representations is later analysed in combination with each of the clustering algorithms, which have been possibly modified and implemented to fit the specific graph. We evaluate results in regards of biological validity and function prediction performance. Our results indicate that the novel ways of presenting the complex graph improve the prediction process, although the computational complexity should be taken into account when deciding on a particular approach. PMID:24972109

  18. The Prediction of Ego Functioning in Adolescence. Final Report.

    ERIC Educational Resources Information Center

    Taube, Irvin; Vreeland, Rebecca

    The object of this study was to predict ego functioning in college among a group of successful high school graduates. Two hundred and seventy-one graduates of Phillips Exeter Academy who had been admitted to Harvard University during 4 consecutive years were studied. Three types of previously collected data were used: (1) teacher reports on the…

  19. Human transfer functions used to predict system performance parameters

    NASA Technical Reports Server (NTRS)

    1966-01-01

    Automatic, parameter-tracking, model-matching technique compares the responses of a human operator with those of an analog computer model of a human operator to predict and analyze the performance of mechanical or electromechanical systems prior to construction. Transfer functions represent the input-output relation of an operator controlling a closed-loop system.

  20. Protein side chain conformation predictions with an MMGBSA energy function.

    PubMed

    Gaillard, Thomas; Panel, Nicolas; Simonson, Thomas

    2016-06-01

    The prediction of protein side chain conformations from backbone coordinates is an important task in structural biology, with applications in structure prediction and protein design. It is a difficult problem due to its combinatorial nature. We study the performance of an "MMGBSA" energy function, implemented in our protein design program Proteus, which combines molecular mechanics terms, a Generalized Born and Surface Area (GBSA) solvent model, with approximations that make the model pairwise additive. Proteus is not a competitor to specialized side chain prediction programs due to its cost, but it allows protein design applications, where side chain prediction is an important step and MMGBSA an effective energy model. We predict the side chain conformations for 18 proteins. The side chains are first predicted individually, with the rest of the protein in its crystallographic conformation. Next, all side chains are predicted together. The contributions of individual energy terms are evaluated and various parameterizations are compared. We find that the GB and SA terms, with an appropriate choice of the dielectric constant and surface energy coefficients, are beneficial for single side chain predictions. For the prediction of all side chains, however, errors due to the pairwise additive approximation overcome the improvement brought by these terms. We also show the crucial contribution of side chain minimization to alleviate the rigid rotamer approximation. Even without GB and SA terms, we obtain accuracies comparable to SCWRL4, a specialized side chain prediction program. In particular, we obtain a better RMSD than SCWRL4 for core residues (at a higher cost), despite our simpler rotamer library. Proteins 2016; 84:803-819. © 2016 Wiley Periodicals, Inc. PMID:26948696

  1. WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.

    PubMed

    Chen, Xing; Yan, Chenggang Clarence; Zhang, Xu; You, Zhu-Hong; Deng, Lixi; Liu, Ying; Zhang, Yongdong; Dai, Qionghai

    2016-01-01

    Increasing evidences have indicated that microRNAs (miRNAs) are functionally associated with the development and progression of various complex human diseases. However, the roles of miRNAs in multiple biological processes or various diseases and their underlying molecular mechanisms still have not been fully understood yet. Predicting potential miRNA-disease associations by integrating various heterogeneous biological datasets is of great significance to the biomedical research. Computational methods could obtain potential miRNA-disease associations in a short time, which significantly reduce the experimental time and cost. Considering the limitations in previous computational methods, we developed the model of Within and Between Score for MiRNA-Disease Association prediction (WBSMDA) to predict potential miRNAs associated with various complex diseases. WBSMDA could be applied to the diseases without any known related miRNAs. The AUC of 0.8031 based on Leave-one-out cross validation has demonstrated its reliable performance. WBSMDA was further applied to Colon Neoplasms, Prostate Neoplasms, and Lymphoma for the identification of their potential related miRNAs. As a result, 90%, 84%, and 80% of predicted miRNA-disease pairs in the top 50 prediction list for these three diseases have been confirmed by recent experimental literatures, respectively. It is anticipated that WBSMDA would be a useful resource for potential miRNA-disease association identification. PMID:26880032

  2. Cardiorespiratory function associated with dietary nitrate supplementation.

    PubMed

    Bond, Vernon; Curry, Bryan H; Adams, Richard G; Millis, Richard M; Haddad, Georges E

    2014-02-01

    The advent of medical nutrition therapy and nutritional physiology affords the opportunity to link diet to specific cardiovascular mechanisms, suggesting novel treatments for cardiovascular disease. This study tests the hypothesis that beetroot juice increases the plasma nitric oxide (NO) concentration, which is associated with improvements in cardiorespiratory function at rest and during submaximal aerobic exercise. The subjects were 12 healthy, young adult, normotensive African-American females, with a body mass of 61 ± 2 kg, body fat of 28% ± 4%, and peak oxygen consumption of 26 ± 3 mL·kg(-1)·min(-1). The subjects were studied at rest and during cycle ergometer exercise at 40%, 60%, and 80% of peak oxygen consumption. Plasma NO concentration, respiratory quotient (RQ), minute ventilation, systolic and diastolic blood pressure (SBP and DBP), heart rate, and oxygen consumption were compared between isocaloric, isovolumetric placebo control orange juice and experimental beetroot juice treatments on separate days. The beetroot juice treatment increased plasma NO concentration and decreased oxygen consumption, SBP, and the heart rate-SBP product at rest and at 40%, 60%, and 80% of peak oxygen consumption in the absence of significant effects on RQ, minute ventilation, heart rate, and DBP. These findings suggest that, in healthy subjects, beetroot juice treatments increase plasma NO concentration and decrease cardiac afterload and myocardial oxygen demand at rest and during 3 submaximal levels of aerobic exercise. Future studies should determine the cellular and molecular mechanisms responsible for the improvement in cardiorespiratory function associated with dietary nitrate supplementation and whether they translate into better cardiovascular function and exercise tolerance in individuals with a compromised cardiovascular system. PMID:24476472

  3. Cardiorespiratory function associated with dietary nitrate supplementation

    PubMed Central

    Bond, Vernon; Curry, Bryan H.; Adams, Richard G.; Millis, Richard M.; Haddad, Georges E.

    2014-01-01

    The advent of medical nutrition therapy and nutritional physiology affords the opportunity to link diet to specific cardiovascular mechanisms, suggesting novel treatments for cardiovascular disease. This study tests the hypothesis that beetroot juice increases the plasma nitric oxide (NO) concentration, which is associated with improvements in cardiorespiratory function at rest and during submaximal aerobic exercise. The subjects were 12 healthy, young adult, normotensive African-American females, with a body mass of 61 ± 2 kg, body fat of 28% ± 4%, and peak oxygen consumption of 26 ± 3 mL·kg−1·min−1. The subjects were studied at rest and during cycle ergometer exercise at 40%, 60%, and 80% of peak oxygen consumption. Plasma NO concentration, respiratory quotient (RQ), minute ventilation, systolic and diastolic blood pressure (SBP and DBP), heart rate, and oxygen consumption were compared between isocaloric, isovolumetric placebo control orange juice and experimental beetroot juice treatments on separate days. The beetroot juice treatment increased plasma NO concentration and decreased oxygen consumption, SBP, and the heart rate-SBP product at rest and at 40%, 60%, and 80% of peak oxygen consumption in the absence of significant effects on RQ, minute ventilation, heart rate, and DBP. These findings suggest that, in healthy subjects, beetroot juice treatments increase plasma NO concentration and decrease cardiac afterload and myocardial oxygen demand at rest and during 3 submaximal levels of aerobic exercise. Future studies should determine the cellular and molecular mechanisms responsible for the improvement in cardiorespiratory function associated with dietary nitrate supplementation and whether they translate into better cardiovascular function and exercise tolerance in individuals with a compromised cardiovascular system. PMID:24476472

  4. Analysis and Functional Prediction of Reactive Cysteine Residues*

    PubMed Central

    Marino, Stefano M.; Gladyshev, Vadim N.

    2012-01-01

    Cys is much different from other common amino acids in proteins. Being one of the least abundant residues, Cys is often observed in functional sites in proteins. This residue is reactive, polarizable, and redox-active; has high affinity for metals; and is particularly responsive to the local environment. A better understanding of the basic properties of Cys is essential for interpretation of high-throughput data sets and for prediction and classification of functional Cys residues. We provide an overview of approaches used to study Cys residues, from methods for investigation of their basic properties, such as exposure and pKa, to algorithms for functional prediction of different types of Cys in proteins. PMID:22157013

  5. Pattern recognition methods for protein functional site prediction.

    PubMed

    Yang, Zheng Rong; Wang, Lipo; Young, Natasha; Trudgian, Dave; Chou, Kuo-Chen

    2005-10-01

    Protein functional site prediction is closely related to drug design, hence to public health. In order to save the cost and the time spent on identifying the functional sites in sequenced proteins in biology laboratory, computer programs have been widely used for decades. Many of them are implemented using the state-of-the-art pattern recognition algorithms, including decision trees, neural networks and support vector machines. Although the success of this effort has been obvious, advanced and new algorithms are still under development for addressing some difficult issues. This review will go through the major stages in developing pattern recognition algorithms for protein functional site prediction and outline the future research directions in this important area. PMID:16248799

  6. Predicting plants -modeling traits as a function of environment

    NASA Astrophysics Data System (ADS)

    Franklin, Oskar

    2016-04-01

    A central problem in understanding and modeling vegetation dynamics is how to represent the variation in plant properties and function across different environments. Addressing this problem there is a strong trend towards trait-based approaches, where vegetation properties are functions of the distributions of functional traits rather than of species. Recently there has been enormous progress in in quantifying trait variability and its drivers and effects (Van Bodegom et al. 2012; Adier et al. 2014; Kunstler et al. 2015) based on wide ranging datasets on a small number of easily measured traits, such as specific leaf area (SLA), wood density and maximum plant height. However, plant function depends on many other traits and while the commonly measured trait data are valuable, they are not sufficient for driving predictive and mechanistic models of vegetation dynamics -especially under novel climate or management conditions. For this purpose we need a model to predict functional traits, also those not easily measured, and how they depend on the plants' environment. Here I present such a mechanistic model based on fitness concepts and focused on traits related to water and light limitation of trees, including: wood density, drought response, allocation to defense, and leaf traits. The model is able to predict observed patterns of variability in these traits in relation to growth and mortality, and their responses to a gradient of water limitation. The results demonstrate that it is possible to mechanistically predict plant traits as a function of the environment based on an eco-physiological model of plant fitness. References Adier, P.B., Salguero-Gómez, R., Compagnoni, A., Hsu, J.S., Ray-Mukherjee, J., Mbeau-Ache, C. et al. (2014). Functional traits explain variation in plant lifehistory strategies. Proc. Natl. Acad. Sci. U. S. A., 111, 740-745. Kunstler, G., Falster, D., Coomes, D.A., Hui, F., Kooyman, R.M., Laughlin, D.C. et al. (2015). Plant functional traits

  7. Nanoparticles-cell association predicted by protein corona fingerprints.

    PubMed

    Palchetti, S; Digiacomo, L; Pozzi, D; Peruzzi, G; Micarelli, E; Mahmoudi, M; Caracciolo, G

    2016-07-01

    In a physiological environment (e.g., blood and interstitial fluids) nanoparticles (NPs) will bind proteins shaping a "protein corona" layer. The long-lived protein layer tightly bound to the NP surface is referred to as the hard corona (HC) and encodes information that controls NP bioactivity (e.g. cellular association, cellular signaling pathways, biodistribution, and toxicity). Decrypting this complex code has become a priority to predict the NP biological outcomes. Here, we use a library of 16 lipid NPs of varying size (Ø≈ 100-250 nm) and surface chemistry (unmodified and PEGylated) to investigate the relationships between NP physicochemical properties (nanoparticle size, aggregation state and surface charge), protein corona fingerprints (PCFs), and NP-cell association. We found out that none of the NPs' physicochemical properties alone was exclusively able to account for association with human cervical cancer cell line (HeLa). For the entire library of NPs, a total of 436 distinct serum proteins were detected. We developed a predictive-validation modeling that provides a means of assessing the relative significance of the identified corona proteins. Interestingly, a minor fraction of the HC, which consists of only 8 PCFs were identified as main promoters of NP association with HeLa cells. Remarkably, identified PCFs have several receptors with high level of expression on the plasma membrane of HeLa cells. PMID:27279572

  8. Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction

    PubMed Central

    Shoichet, Brian K.; Gillis, Jesse

    2016-01-01

    The expansion of protein-ligand annotation databases has enabled large-scale networking of proteins by ligand similarity. These ligand-based protein networks, which implicitly predict the ability of neighboring proteins to bind related ligands, may complement biologically-oriented gene networks, which are used to predict functional or disease relevance. To quantify the degree to which such ligand-based protein associations might complement functional genomic associations, including sequence similarity, physical protein-protein interactions, co-expression, and disease gene annotations, we calculated a network based on the Similarity Ensemble Approach (SEA: sea.docking.org), where protein neighbors reflect the similarity of their ligands. We also measured the similarity with functional genomic networks over a common set of 1,131 genes, and found that the networks had only small overlaps, which were significant only due to the large scale of the data. Consistent with the view that the networks contain different information, combining them substantially improved Molecular Function prediction within GO (from AUROC~0.63–0.75 for the individual data modalities to AUROC~0.8 in the aggregate). We investigated the boost in guilt-by-association gene function prediction when the networks are combined and describe underlying properties that can be further exploited. PMID:27467773

  9. Nanoparticles-cell association predicted by protein corona fingerprints

    NASA Astrophysics Data System (ADS)

    Palchetti, S.; Digiacomo, L.; Pozzi, D.; Peruzzi, G.; Micarelli, E.; Mahmoudi, M.; Caracciolo, G.

    2016-06-01

    In a physiological environment (e.g., blood and interstitial fluids) nanoparticles (NPs) will bind proteins shaping a ``protein corona'' layer. The long-lived protein layer tightly bound to the NP surface is referred to as the hard corona (HC) and encodes information that controls NP bioactivity (e.g. cellular association, cellular signaling pathways, biodistribution, and toxicity). Decrypting this complex code has become a priority to predict the NP biological outcomes. Here, we use a library of 16 lipid NPs of varying size (Ø ~ 100-250 nm) and surface chemistry (unmodified and PEGylated) to investigate the relationships between NP physicochemical properties (nanoparticle size, aggregation state and surface charge), protein corona fingerprints (PCFs), and NP-cell association. We found out that none of the NPs' physicochemical properties alone was exclusively able to account for association with human cervical cancer cell line (HeLa). For the entire library of NPs, a total of 436 distinct serum proteins were detected. We developed a predictive-validation modeling that provides a means of assessing the relative significance of the identified corona proteins. Interestingly, a minor fraction of the HC, which consists of only 8 PCFs were identified as main promoters of NP association with HeLa cells. Remarkably, identified PCFs have several receptors with high level of expression on the plasma membrane of HeLa cells.In a physiological environment (e.g., blood and interstitial fluids) nanoparticles (NPs) will bind proteins shaping a ``protein corona'' layer. The long-lived protein layer tightly bound to the NP surface is referred to as the hard corona (HC) and encodes information that controls NP bioactivity (e.g. cellular association, cellular signaling pathways, biodistribution, and toxicity). Decrypting this complex code has become a priority to predict the NP biological outcomes. Here, we use a library of 16 lipid NPs of varying size (Ø ~ 100-250 nm) and surface

  10. Scoring functions for prediction of protein-ligand interactions.

    PubMed

    Wang, Jui-Chih; Lin, Jung-Hsin

    2013-01-01

    The scoring functions for protein-ligand interactions plays central roles in computational drug design, virtual screening of chemical libraries for new lead identification, and prediction of possible binding targets of small chemical molecules. An ideal scoring function for protein-ligand interactions is expected to be able to recognize the native binding pose of a ligand on the protein surface among decoy poses, and to accurately predict the binding affinity (or binding free energy) so that the active molecules can be discriminated from the non-active ones. Due to the empirical nature of most, if not all, scoring functions for protein-ligand interactions, the general applicability of empirical scoring functions, especially to domains far outside training sets, is a major concern. In this review article, we will explore the foundations of different classes of scoring functions, their possible limitations, and their suitable application domains. We also provide assessments of several scoring functions on weakly-interacting protein-ligand complexes, which will be useful information in computational fragment-based drug design or virtual screening. PMID:23016847

  11. Accurate perception of negative emotions predicts functional capacity in schizophrenia.

    PubMed

    Abram, Samantha V; Karpouzian, Tatiana M; Reilly, James L; Derntl, Birgit; Habel, Ute; Smith, Matthew J

    2014-04-30

    Several studies suggest facial affect perception (FAP) deficits in schizophrenia are linked to poorer social functioning. However, whether reduced functioning is associated with inaccurate perception of specific emotional valence or a global FAP impairment remains unclear. The present study examined whether impairment in the perception of specific emotional valences (positive, negative) and neutrality were uniquely associated with social functioning, using a multimodal social functioning battery. A sample of 59 individuals with schizophrenia and 41 controls completed a computerized FAP task, and measures of functional capacity, social competence, and social attainment. Participants also underwent neuropsychological testing and symptom assessment. Regression analyses revealed that only accurately perceiving negative emotions explained significant variance (7.9%) in functional capacity after accounting for neurocognitive function and symptoms. Partial correlations indicated that accurately perceiving anger, in particular, was positively correlated with functional capacity. FAP for positive, negative, or neutral emotions were not related to social competence or social attainment. Our findings were consistent with prior literature suggesting negative emotions are related to functional capacity in schizophrenia. Furthermore, the observed relationship between perceiving anger and performance of everyday living skills is novel and warrants further exploration. PMID:24524947

  12. Bisphenol A Exposure is Associated with Decreased Lung Function

    PubMed Central

    Spanier, Adam J.; Fiorino, Elizabeth K.; Trasande, Leonardo

    2014-01-01

    Objective To examine the associations of bisphenol A (BPA) exposure with lung function measures and exhaled nitric oxide (FeNO) in children. Study design We performed a cross-sectional analysis of a subsample of US children age 6–19 years who participated in the 2007–2010 National Health and Nutrition Examination Survey. We assessed univariate and multivariable associations of urinary BPA concentration with the predicted pulmonary function measures for age, sex, race/ethnicity and height (forced expiratory function in 1 second – FEV1, forced vital capacity – FVC, forced expiratory flow 25–75% – FEF2575, and FEV1/FVC) and with FeNO. Results Exposure and outcome data were available for 661 children. Median BPA was 2.4 ng/ml (IQR: 1.3, 4.1). In multivariable analysis a larger urinary BPA concentration was associated with significantly decreased %FEF2575 (3.7%, 95% CI 1.0, 6.5) and %FEV1/FVC (0.8%, 95% CI 0.1, 1.7) but not %FEV1, %FVC, or FeNO. A child in the top quartile of BPA compared with the bottom quartile had a 10% decrease in %FEF2575 (95% CI −1, −19) and 3% decrease in %FEV1/FVC (95% CI −1, −5). Conclusions BPA exposure was associated with a modest decrease in %FEF2575 (small airway function) and %FEV1/FVC (pulmonary obstruction) but not FEV1, FVC, or FeNO. Explanations of the association cannot rule out the possibility of reverse causality. PMID:24657123

  13. Association Between a Prognostic Gene Signature and Functional Gene Sets

    PubMed Central

    Hummel, Manuela; Metzeler, Klaus H.; Buske, Christian; Bohlander, Stefan K.; Mansmann, Ulrich

    2008-01-01

    Background The development of expression-based gene signatures for predicting prognosis or class membership is a popular and challenging task. Besides their stringent validation, signatures need a functional interpretation and must be placed in a biological context. Popular tools such as Gene Set Enrichment have drawbacks because they are restricted to annotated genes and are unable to capture the information hidden in the signature’s non-annotated genes. Methodology We propose concepts to relate a signature with functional gene sets like pathways or Gene Ontology categories. The connection between single signature genes and a specific pathway is explored by hierarchical variable selection and gene association networks. The risk score derived from an individual patient’s signature is related to expression patterns of pathways and Gene Ontology categories. Global tests are useful for these tasks, and they adjust for other factors. GlobalAncova is used to explore the effect on gene expression in specific functional groups from the interaction of the score and selected mutations in the patient’s genome. Results We apply the proposed methods to an expression data set and a corresponding gene signature for predicting survival in Acute Myeloid Leukemia (AML). The example demonstrates strong relations between the signature and cancer-related pathways. The signature-based risk score was found to be associated with development-related biological processes. Conclusions Many authors interpret the functional aspects of a gene signature by linking signature genes to pathways or relevant functional gene groups. The method of gene set enrichment is preferred to annotating signature genes to specific Gene Ontology categories. The strategies proposed in this paper go beyond the restriction of annotation and deepen the insights into the biological mechanisms reflected in the information given by a signature. PMID:19812786

  14. COMBREX-DB: an experiment centered database of protein function: knowledge, predictions and knowledge gaps.

    PubMed

    Chang, Yi-Chien; Hu, Zhenjun; Rachlin, John; Anton, Brian P; Kasif, Simon; Roberts, Richard J; Steffen, Martin

    2016-01-01

    The COMBREX database (COMBREX-DB; combrex.bu.edu) is an online repository of information related to (i) experimentally determined protein function, (ii) predicted protein function, (iii) relationships among proteins of unknown function and various types of experimental data, including molecular function, protein structure, and associated phenotypes. The database was created as part of the novel COMBREX (COMputational BRidges to EXperiments) effort aimed at accelerating the rate of gene function validation. It currently holds information on ∼ 3.3 million known and predicted proteins from over 1000 completely sequenced bacterial and archaeal genomes. The database also contains a prototype recommendation system for helping users identify those proteins whose experimental determination of function would be most informative for predicting function for other proteins within protein families. The emphasis on documenting experimental evidence for function predictions, and the prioritization of uncharacterized proteins for experimental testing distinguish COMBREX from other publicly available microbial genomics resources. This article describes updates to COMBREX-DB since an initial description in the 2011 NAR Database Issue. PMID:26635392

  15. Associations between Markers of Glucose and Insulin Function and Cognitive Function in Healthy African American Elders

    PubMed Central

    Skinner, Jeannine S.; Morgan, Amy; Hernandez-Saucedo, Hector; Hansen, Angela; Corbett, Selena; Arbuckle, Matthew; Leverenz, James BA; Wilkins, Consuelo H.; Craft, Suzanne; Baker, Laura D.

    2015-01-01

    Background Glucose and insulin are important moderators of cognitive function. African Americans have poorer glycemic control across the glycemic spectrum and are at increased risk for type 2 diabetes and poor cognitive health. It is unclear which glucoregulatory markers predict cognitive function in this at-risk population. The purpose of this study was to examine the association between cognitive function and common markers of glucoregulation in non-diabetic African Americans elders. Methods Thirty-four, community-dwelling African Americans, aged 50-75 years completed cognitive testing and blood collection as part of a health screening assessment. Cognitive outcomes were composite scores derived from neuropsychological tests of executive function and verbal memory. Linear regression was used to examine relationships between cognitive composite scores and fasting blood levels of glucose, insulin, and hemoglobin A1C, with adjustments for age, education, body mass index, and antihypertensive medication use. Results Fasting plasma glucose was negatively associated with executive function (β=−0.41, p=0.03). There was a trend of an association between fasting plasma glucose and verbal memory (β=−0.34, p=0.06). Fasting insulin and hemoglobin A1c were not associated with cognitive function. Conclusion High non-diabetic fasting glucose levels were associated with poorer executive function and verbal memory. These results provide preliminary support for proactive glucose control in older African Americans even before glycemic criteria for type 2 diabetes are met. Our findings suggests that high-normal FPG levels may represent an early red-flag to signify increased risk of cognitive impairment or decline. PMID:26798567

  16. Computational predictions of energy materials using density functional theory

    NASA Astrophysics Data System (ADS)

    Jain, Anubhav; Shin, Yongwoo; Persson, Kristin A.

    2016-01-01

    In the search for new functional materials, quantum mechanics is an exciting starting point. The fundamental laws that govern the behaviour of electrons have the possibility, at the other end of the scale, to predict the performance of a material for a targeted application. In some cases, this is achievable using density functional theory (DFT). In this Review, we highlight DFT studies predicting energy-related materials that were subsequently confirmed experimentally. The attributes and limitations of DFT for the computational design of materials for lithium-ion batteries, hydrogen production and storage materials, superconductors, photovoltaics and thermoelectric materials are discussed. In the future, we expect that the accuracy of DFT-based methods will continue to improve and that growth in computing power will enable millions of materials to be virtually screened for specific applications. Thus, these examples represent a first glimpse of what may become a routine and integral step in materials discovery.

  17. Plant functional traits predict green roof ecosystem services.

    PubMed

    Lundholm, Jeremy; Tran, Stephanie; Gebert, Luke

    2015-02-17

    Plants make important contributions to the services provided by engineered ecosystems such as green roofs. Ecologists use plant species traits as generic predictors of geographical distribution, interactions with other species, and ecosystem functioning, but this approach has been little used to optimize engineered ecosystems. Four plant species traits (height, individual leaf area, specific leaf area, and leaf dry matter content) were evaluated as predictors of ecosystem properties and services in a modular green roof system planted with 21 species. Six indicators of ecosystem services, incorporating thermal, hydrological, water quality, and carbon sequestration functions, were predicted by the four plant traits directly or indirectly via their effects on aggregate ecosystem properties, including canopy density and albedo. Species average height and specific leaf area were the most useful traits, predicting several services via effects on canopy density or growth rate. This study demonstrates that easily measured plant traits can be used to select species to optimize green roof performance across multiple key services. PMID:25599106

  18. Optimizing Non-Decomposable Loss Functions in Structured Prediction

    PubMed Central

    Ranjbar, Mani; Lan, Tian; Wang, Yang; Robinovitch, Steven N.; Li, Ze-Nian; Mori, Greg

    2012-01-01

    We develop an algorithm for structured prediction with non-decomposable performance measures. The algorithm learns parameters of Markov random fields and can be applied to multivariate performance measures. Examples include performance measures such as Fβ score (natural language processing), intersection over union (object category segmentation), Precision/Recall at k (search engines) and ROC area (binary classifiers). We attack this optimization problem by approximating the loss function with a piecewise linear function. The loss augmented inference forms a quadratic program (QP), which we solve using LP relaxation. We apply this approach to two tasks: object class-specific segmentation and human action retrieval from videos. We show significant improvement over baseline approaches that either use simple loss functions or simple scoring functions on the PASCAL VOC and H3D Segmentation datasets, and a nursing home action recognition dataset. PMID:22868650

  19. Rapid D-Affine Biventricular Cardiac Function with Polar Prediction

    PubMed Central

    Gilbert, Kathleen; Cowan, Brett; Suinesiaputra, Avan; Occleshaw, Christopher; Young, Alistair

    2014-01-01

    Although many solutions have been proposed for left ventricular functional analysis of the heart, right and left (bi-) ventricular function has been problematic due to the complex geometry and large motions. Biventricular function is particularly important in congenital heart disease, the most common type of birth defects. We describe a rapid interactive analysis tool for biventricular function which incorporates 1) a 3D+ time finite element model of biventricular geometry, 2) a fast prediction step which estimates an initial geometry in a polar coordinate system, and 3) a Cartesian update which penalizes deviations from affine transformations (D-Affine) from a prior. Solution times were very rapid, enabling interaction in real time using guide point modeling. The method was applied to 13 patients with congenital heart disease and compared with the clinical gold standard of manual tracing. Results between the methods showed good correlation (R2 > 0.9) and good precision (volume<17ml; mass<11g) for both chambers. PMID:25485422

  20. High Precision Prediction of Functional Sites in Protein Structures

    PubMed Central

    Buturovic, Ljubomir; Wong, Mike; Tang, Grace W.; Altman, Russ B.; Petkovic, Dragutin

    2014-01-01

    We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta. PMID:24632601

  1. Functional brain imaging predicts public health campaign success.

    PubMed

    Falk, Emily B; O'Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

    2016-02-01

    Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a 'self-localizer' defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400,000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R(2) up to 0.65) and (ii) this relationship depends on message content-self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns. PMID:26400858

  2. Large-scale de novo prediction of physical protein-protein association.

    PubMed

    Elefsinioti, Antigoni; Saraç, Ömer Sinan; Hegele, Anna; Plake, Conrad; Hubner, Nina C; Poser, Ina; Sarov, Mihail; Hyman, Anthony; Mann, Matthias; Schroeder, Michael; Stelzl, Ulrich; Beyer, Andreas

    2011-11-01

    Information about the physical association of proteins is extensively used for studying cellular processes and disease mechanisms. However, complete experimental mapping of the human interactome will remain prohibitively difficult in the near future. Here we present a map of predicted human protein interactions that distinguishes functional association from physical binding. Our network classifies more than 5 million protein pairs predicting 94,009 new interactions with high confidence. We experimentally tested a subset of these predictions using yeast two-hybrid analysis and affinity purification followed by quantitative mass spectrometry. Thus we identified 462 new protein-protein interactions and confirmed the predictive power of the network. These independent experiments address potential issues of circular reasoning and are a distinctive feature of this work. Analysis of the physical interactome unravels subnetworks mediating between different functional and physical subunits of the cell. Finally, we demonstrate the utility of the network for the analysis of molecular mechanisms of complex diseases by applying it to genome-wide association studies of neurodegenerative diseases. This analysis provides new evidence implying TOMM40 as a factor involved in Alzheimer's disease. The network provides a high-quality resource for the analysis of genomic data sets and genetic association studies in particular. Our interactome is available via the hPRINT web server at: www.print-db.org. PMID:21836163

  3. Large-scale De Novo Prediction of Physical Protein-Protein Association*

    PubMed Central

    Elefsinioti, Antigoni; Saraç, Ömer Sinan; Hegele, Anna; Plake, Conrad; Hubner, Nina C.; Poser, Ina; Sarov, Mihail; Hyman, Anthony; Mann, Matthias; Schroeder, Michael; Stelzl, Ulrich; Beyer, Andreas

    2011-01-01

    Information about the physical association of proteins is extensively used for studying cellular processes and disease mechanisms. However, complete experimental mapping of the human interactome will remain prohibitively difficult in the near future. Here we present a map of predicted human protein interactions that distinguishes functional association from physical binding. Our network classifies more than 5 million protein pairs predicting 94,009 new interactions with high confidence. We experimentally tested a subset of these predictions using yeast two-hybrid analysis and affinity purification followed by quantitative mass spectrometry. Thus we identified 462 new protein-protein interactions and confirmed the predictive power of the network. These independent experiments address potential issues of circular reasoning and are a distinctive feature of this work. Analysis of the physical interactome unravels subnetworks mediating between different functional and physical subunits of the cell. Finally, we demonstrate the utility of the network for the analysis of molecular mechanisms of complex diseases by applying it to genome-wide association studies of neurodegenerative diseases. This analysis provides new evidence implying TOMM40 as a factor involved in Alzheimer's disease. The network provides a high-quality resource for the analysis of genomic data sets and genetic association studies in particular. Our interactome is available via the hPRINT web server at: www.print-db.org. PMID:21836163

  4. Predictions of Geospace Drivers By the Probability Distribution Function Model

    NASA Astrophysics Data System (ADS)

    Bussy-Virat, C.; Ridley, A. J.

    2014-12-01

    Geospace drivers like the solar wind speed, interplanetary magnetic field (IMF), and solar irradiance have a strong influence on the density of the thermosphere and the near-Earth space environment. This has important consequences on the drag on satellites that are in low orbit and therefore on their position. One of the basic problems with space weather prediction is that these drivers can only be measured about one hour before they affect the environment. In order to allow for adequate planning for some members of the commercial, military, or civilian communities, reliable long-term space weather forecasts are needed. The study presents a model for predicting geospace drivers up to five days in advance. This model uses the same general technique to predict the solar wind speed, the three components of the IMF, and the solar irradiance F10.7. For instance, it uses Probability distribution functions (PDFs) to relate the current solar wind speed and slope to the future solar wind speed, as well as the solar wind speed to the solar wind speed one solar rotation in the future. The PDF Model has been compared to other models for predictions of the speed. It has been found that it is better than using the current solar wind speed (i.e., persistence), and better than the Wang-Sheeley-Arge Model for prediction horizons of 24 hours. Once the drivers are predicted, and the uncertainty on the drivers are specified, the density in the thermosphere can be derived using various models of the thermosphere, such as the Global Ionosphere Thermosphere Model. In addition, uncertainties on the densities can be estimated, based on ensembles of simulations. From the density and uncertainty predictions, satellite positions, as well as the uncertainty in those positions can be estimated. These can assist operators in determining the probability of collisions between objects in low Earth orbit.

  5. [Falls and renal function: a dangerous association].

    PubMed

    De Giorgi, Alfredo; Fabbian, Fabio; Pala, Marco; Mallozzi Menegatti, Alessandra; Misurati, Elisa; Manfredini, Roberto

    2012-01-01

    Falls are an important health problem and the risk of falling increases with age. The costs due to falls are related to the progressive decline of patients' clinical conditions, with functional inability inducing increasing social costs, morbidity and mortality. Renal dysfunction is mostly present in elderly people who often have several comorbidities. Risk factors for falls have been classified as intrinsic and extrinsic, and renal dysfunction is included among the former. Chronic kidney disease per se is an important risk factor for falls, and the risk correlates negatively with creatinine clearance. Vitamin D deficiency, dysfunction of muscles and bones, nerve degeneration, cognitive decline, electrolyte imbalance, anemia, and metabolic acidosis have been reported to be associated with falls. Falls seem to be very frequent in dialysis patients: 44% of subjects on hemodialysis fall at least once a year with a 1-year mortality due to fractures of 64%. Male sex, comorbidities, predialysis hypotension, and a history of previous falls are the main risk factors, together with events directly related to renal replacement therapy such as biocompatibility of the dialysis membrane, arrhythmias, fluid overload and length of dialysis treatment. Peripheral nerve degeneration and demyelination as well as altered nerve conduction resulting in muscular weakness and loss of peripheral sensitivity are frequent when the glomerular filtration rate is less than 12 mL/min. Moreover, depression and sleep disorders can also increase the risk of falls. Kidney function is an important parameter to consider when evaluating the risk of falls in the elderly, and the development of specific guidelines for preventing falls in the uremic population should be considered. PMID:22718453

  6. Association between lung function and airway wall density

    NASA Astrophysics Data System (ADS)

    Leader, J. Ken; Zheng, Bin; Fuhrman, Carl R.; Tedrow, John; Park, Sang C.; Tan, Jun; Pu, Jiantao; Drescher, John M.; Gur, David; Sciurba, Frank C.

    2009-02-01

    Computed tomography (CT) examination is often used to quantify the relation between lung function and airway remodeling in chronic obstructive pulmonary disease (COPD). In this preliminary study, we examined the association between lung function and airway wall computed attenuation ("density") in 200 COPD screening subjects. Percent predicted FVC (FVC%), percent predicted FEV1 (FEV1%), and the ratio of FEV1 to FVC as a percentage (FEV1/FVC%) were measured post-bronchodilator. The apical bronchus of the right upper lobe was manually selected from CT examinations for evaluation. Total airway area, lumen area, wall area, lumen perimeter and wall area as fraction of the total airway area were computed. Mean HU (meanHU) and maximum HU (maxHU) values were computed across pixels assigned membership in the wall and with a HU value greater than -550. The Pearson correlation coefficients (PCC) between FVC%, FEV1%, and FEV1/FVC% and meanHU were -0.221 (p = 0.002), -0.175 (p = 0.014), and -0.110 (p = 0.123), respectively. The PCCs for maxHU were only significant for FVC%. The correlations between lung function and the airway morphometry parameters were slightly stronger compared to airway wall density. MeanHU was significantly correlated with wall area (PCC = 0.720), airway area (0.498) and wall area percent (0.611). This preliminary work demonstrates that airway wall density is associated with lung function. Although the correlations in our study were weaker than a recent study, airway wall density initially appears to be an important parameter in quantitative CT analysis of COPD.

  7. The use of copula functions for predictive analysis of correlations between extreme storm tides

    NASA Astrophysics Data System (ADS)

    Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

    2014-11-01

    In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

  8. Resting amygdala and medial prefrontal metabolism predicts functional activation of the fear extinction circuit

    PubMed Central

    Linnman, Clas; Zeidan, Mohamed A.; Furtak, Sharon C.; Pitman, Roger K.; Quirk, Gregory J.; Milad, Mohammed R.

    2014-01-01

    Objective Individual differences in ability to control fear have been linked to activation of dorsal anterior cingulate cortex, ventromedial prefrontal cortex, and amygdala. This study investigated whether functional variance in this network can be predicted by resting metabolism in these same regions. Methods Healthy subject volunteers were studied with positron emission tomography using [18F]-deoxyglucose to measure resting brain metabolism. This was followed by a two-day fear conditioning and extinction training paradigm in a functional magnetic resonance imaging scanner to measure brain activation during fear extinction and its recall. Skin conductance response was used to index conditioned responding. Resting metabolism in amygdala, dorsal anterior cingulate cortex and ventromedial prefrontal cortex were used to predict responses during fear extinction and extinction recall. Results During extinction training, resting amygdala metabolism positively predicted ventromedial prefrontal cortex, and negatively predicted dorsal anterior cingulate cortex, activation. In contrast, during extinction recall, resting amygdala metabolism negatively predicted ventromedial prefrontal cortex, and positively predicted dorsal anterior cingulate cortex, activation. Resting dorsal anterior cingulate cortex metabolism predicted fear expression (skin conductance response) during extinction recall. Conclusions Brain metabolism at rest predicts neuronal reactivity and skin conductance changes associated with recall of the fear extinction memory. PMID:22318762

  9. Multitrophic functional diversity predicts ecosystem functioning in experimental assemblages of estuarine consumers.

    PubMed

    Lefcheck, Jonathan S; Duffy, J Emmett

    2015-11-01

    The use of functional traits to explain how biodiversity affects ecosystem functioning has attracted intense interest, yet few studies have a priori altered functional diversity, especially in multitrophic communities. Here, we manipulated multivariate functional diversity of estuarine grazers and predators within multiple levels of species richness to test how species richness and functional diversity predicted ecosystem functioning in a multitrophic food web. Community functional diversity was a better predictor than species richness for the majority of ecosystem properties, based on generalized linear mixed-effects models. Combining inferences from eight traits into a single multivariate index increased prediction accuracy of these models relative to any individual trait. Structural equation modeling revealed that functional diversity of both grazers and predators was important in driving final biomass within trophic levels, with stronger effects observed for predators. We also show that different species drove different ecosystem responses, with evidence for both sampling effects and complementarity. Our study extends experimental investigations of functional trait diversity to a multilevel food web, and demonstrates that functional diversity can be more accurate and effective than species richness in predicting community biomass in a food web context. PMID:27070016

  10. Network-based auto-probit modeling for protein function prediction.

    PubMed

    Jiang, Xiaoyu; Gold, David; Kolaczyk, Eric D

    2011-09-01

    Predicting the functional roles of proteins based on various genome-wide data, such as protein-protein association networks, has become a canonical problem in computational biology. Approaching this task as a binary classification problem, we develop a network-based extension of the spatial auto-probit model. In particular, we develop a hierarchical Bayesian probit-based framework for modeling binary network-indexed processes, with a latent multivariate conditional autoregressive Gaussian process. The latter allows for the easy incorporation of protein-protein association network topologies-either binary or weighted-in modeling protein functional similarity. We use this framework to predict protein functions, for functions defined as terms in the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functionality. Furthermore, we show how a natural extension of this framework can be used to model and correct for the high percentage of false negative labels in training data derived from GO, a serious shortcoming endemic to biological databases of this type. Our method performance is evaluated and compared with standard algorithms on weighted yeast protein-protein association networks, extracted from a recently developed integrative database called Search Tool for the Retrieval of INteracting Genes/proteins (STRING). Results show that our basic method is competitive with these other methods, and that the extended method-incorporating the uncertainty in negative labels among the training data-can yield nontrivial improvements in predictive accuracy. PMID:21133881

  11. Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets.

    PubMed

    Swanton, Charles; Larkin, James M; Gerlinger, Marco; Eklund, Aron C; Howell, Michael; Stamp, Gordon; Downward, Julian; Gore, Martin; Futreal, P Andrew; Escudier, Bernard; Andre, Fabrice; Albiges, Laurence; Beuselinck, Benoit; Oudard, Stephane; Hoffmann, Jens; Gyorffy, Balázs; Torrance, Chris J; Boehme, Karen A; Volkmer, Hansjuergen; Toschi, Luisella; Nicke, Barbara; Beck, Marlene; Szallasi, Zoltan

    2010-01-01

    The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding

  12. Mini-review: Prediction errors, attention and associative learning.

    PubMed

    Holland, Peter C; Schiffino, Felipe L

    2016-05-01

    Most modern theories of associative learning emphasize a critical role for prediction error (PE, the difference between received and expected events). One class of theories, exemplified by the Rescorla-Wagner (1972) model, asserts that PE determines the effectiveness of the reinforcer or unconditioned stimulus (US): surprising reinforcers are more effective than expected ones. A second class, represented by the Pearce-Hall (1980) model, argues that PE determines the associability of conditioned stimuli (CSs), the rate at which they may enter into new learning: the surprising delivery or omission of a reinforcer enhances subsequent processing of the CSs that were present when PE was induced. In this mini-review we describe evidence, mostly from our laboratory, for PE-induced changes in the associability of both CSs and USs, and the brain systems involved in the coding, storage and retrieval of these altered associability values. This evidence favors a number of modifications to behavioral models of how PE influences event processing, and suggests the involvement of widespread brain systems in animals' responses to PE. PMID:26948122

  13. High-throughput functional testing of ENCODE segmentation predictions

    PubMed Central

    Kwasnieski, Jamie C.; Fiore, Christopher; Chaudhari, Hemangi G.

    2014-01-01

    The histone modification state of genomic regions is hypothesized to reflect the regulatory activity of the underlying genomic DNA. Based on this hypothesis, the ENCODE Project Consortium measured the status of multiple histone modifications across the genome in several cell types and used these data to segment the genome into regions with different predicted regulatory activities. We measured the cis-regulatory activity of more than 2000 of these predictions in the K562 leukemia cell line. We tested genomic segments predicted to be Enhancers, Weak Enhancers, or Repressed elements in K562 cells, along with other sequences predicted to be Enhancers specific to the H1 human embryonic stem cell line (H1-hESC). Both Enhancer and Weak Enhancer sequences in K562 cells were more active than negative controls, although surprisingly, Weak Enhancer segmentations drove expression higher than did Enhancer segmentations. Lower levels of the covalent histone modifications H3K36me3 and H3K27ac, thought to mark active enhancers and transcribed gene bodies, associate with higher expression and partly explain the higher activity of Weak Enhancers over Enhancer predictions. While DNase I hypersensitivity (HS) is a good predictor of active sequences in our assay, transcription factor (TF) binding models need to be included in order to accurately identify highly expressed sequences. Overall, our results show that a significant fraction (∼26%) of the ENCODE enhancer predictions have regulatory activity, suggesting that histone modification states can reflect the cis-regulatory activity of sequences in the genome, but that specific sequence preferences, such as TF-binding sites, are the causal determinants of cis-regulatory activity. PMID:25035418

  14. Predictive factors associated with hepatitis C antiviral therapy response.

    PubMed

    Cavalcante, Lourianne Nascimento; Lyra, André Castro

    2015-06-28

    Hepatitis C virus (HCV) infection may lead to significant liver injury, and viral, environmental, host, immunologic and genetic factors may contribute to the differences in the disease expression and treatment response. In the early 2000s, dual therapy using a combination of pegylated interferon plus ribavirin (PR) became the standard of care for HCV treatment. In this PR era, predictive factors of therapy response related to virus and host have been identified. In 2010/2011, therapeutic regimens for HCV genotype 1 patients were modified, and the addition of NS3/4a protease inhibitors (boceprevir or telaprevir) to dual therapy increased the effectiveness and chances of sustained virologic response (SVR). Nevertheless, the first-generation triple therapy is associated with many adverse events, some of which are serious and associated with death, particularly in cirrhotic patients. This led to the need to identify viral and host predictive factors that might influence the SVR rate to triple therapy and avoid unnecessary exposure to these drugs. Over the past four years, hepatitis C treatment has been rapidly changing with the development of new therapies and other developments. Currently, with the more recent generations of pangenotipic antiviral therapies, there have been higher sustained virologic rates, and prognostic factors may not have the same importance and strength as before. Nonetheless, some variables may still be consistent with the low rates of non-response with regimens that include sofosbuvir, daclatasvir and ledipasvir. In this manuscript, we review the predictive factors of therapy response across the different treatment regimens over the last decade including the new antiviral drugs. PMID:26140082

  15. Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations.

    PubMed

    Shah, Sonia; Bonder, Marc J; Marioni, Riccardo E; Zhu, Zhihong; McRae, Allan F; Zhernakova, Alexandra; Harris, Sarah E; Liewald, Dave; Henders, Anjali K; Mendelson, Michael M; Liu, Chunyu; Joehanes, Roby; Liang, Liming; Levy, Daniel; Martin, Nicholas G; Starr, John M; Wijmenga, Cisca; Wray, Naomi R; Yang, Jian; Montgomery, Grant W; Franke, Lude; Deary, Ian J; Visscher, Peter M

    2015-07-01

    We tested whether DNA-methylation profiles account for inter-individual variation in body mass index (BMI) and height and whether they predict these phenotypes over and above genetic factors. Genetic predictors were derived from published summary results from the largest genome-wide association studies on BMI (n ∼ 350,000) and height (n ∼ 250,000) to date. We derived methylation predictors by estimating probe-trait effects in discovery samples and tested them in external samples. Methylation profiles associated with BMI in older individuals from the Lothian Birth Cohorts (LBCs, n = 1,366) explained 4.9% of the variation in BMI in Dutch adults from the LifeLines DEEP study (n = 750) but did not account for any BMI variation in adolescents from the Brisbane Systems Genetic Study (BSGS, n = 403). Methylation profiles based on the Dutch sample explained 4.9% and 3.6% of the variation in BMI in the LBCs and BSGS, respectively. Methylation profiles predicted BMI independently of genetic profiles in an additive manner: 7%, 8%, and 14% of variance of BMI in the LBCs were explained by the methylation predictor, the genetic predictor, and a model containing both, respectively. The corresponding percentages for LifeLines DEEP were 5%, 9%, and 13%, respectively, suggesting that the methylation profiles represent environmental effects. The differential effects of the BMI methylation profiles by age support previous observations of age modulation of genetic contributions. In contrast, methylation profiles accounted for almost no variation in height, consistent with a mainly genetic contribution to inter-individual variation. The BMI results suggest that combining genetic and epigenetic information might have greater utility for complex-trait prediction. PMID:26119815

  16. Prediction of Broadband Shock-Associated Noise Including Propagation Effects Originating NASA

    NASA Technical Reports Server (NTRS)

    Miller, Steven; Morris, Philip J.

    2012-01-01

    An acoustic analogy is developed based on the Euler equations for broadband shock-associated noise (BBSAN) that directly incorporates the vector Green s function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) to describe the mean flow. The vector Green s function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation rate. An adjoint vector Green s function solver is implemented to determine the vector Green s function based on a locally parallel mean flow at different streamwise locations. The newly developed acoustic analogy can be simplified to one that uses the Green s function associated with the Helmholtz equation, which is consistent with a previous formulation by the authors. A large number of predictions are generated using three different nozzles over a wide range of fully-expanded jet Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise experimental facilities. In addition, two models for the so-called fine-scale mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include propagation effects.

  17. Do Early-Life Conditions Predict Functional Health Status in Adulthood? The Case of Mexico

    PubMed Central

    Huang, Cheng; Soldo, Beth J; Elo, Irma T

    2010-01-01

    Relatively few researchers have investigated early antecedents of adult functional limitations in developing countries. In this study, we assessed associations between childhood conditions and adult lower-body functional limitations (LBFL) as well as the potential mediating role of adult socioeconomic status, smoking, body mass index, and chronic diseases or symptoms. Based on data from the Mexican Health and Aging Study (MHAS) of individuals born prior to 1951 and contacted in 2001 and 2003, we found that childhood nutritional deprivation, serious health problems, and family background predict adult LBFL in Mexico. Adjustment for the potential mediators in adulthood attenuates these associations only to a modest degree. PMID:21074924

  18. Simple topological properties predict functional misannotations in a metabolic network

    PubMed Central

    Liberal, Rodrigo; Pinney, John W.

    2013-01-01

    Motivation: Misannotation in sequence databases is an important obstacle for automated tools for gene function annotation, which rely extensively on comparison with sequences with known function. To improve current annotations and prevent future propagation of errors, sequence-independent tools are, therefore, needed to assist in the identification of misannotated gene products. In the case of enzymatic functions, each functional assignment implies the existence of a reaction within the organism’s metabolic network; a first approximation to a genome-scale metabolic model can be obtained directly from an automated genome annotation. Any obvious problems in the network, such as dead end or disconnected reactions, can, therefore, be strong indications of misannotation. Results: We demonstrate that a machine-learning approach using only network topological features can successfully predict the validity of enzyme annotations. The predictions are tested at three different levels. A random forest using topological features of the metabolic network and trained on curated sets of correct and incorrect enzyme assignments was found to have an accuracy of up to 86% in 5-fold cross-validation experiments. Further cross-validation against unseen enzyme superfamilies indicates that this classifier can successfully extrapolate beyond the classes of enzyme present in the training data. The random forest model was applied to several automated genome annotations, achieving an accuracy of in most cases when validated against recent genome-scale metabolic models. We also observe that when applied to draft metabolic networks for multiple species, a clear negative correlation is observed between predicted annotation quality and phylogenetic distance to the major model organism for biochemistry (Escherichia coli for prokaryotes and Homo sapiens for eukaryotes). Contact: j.pinney@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID

  19. Platelet Serotonin Transporter Function Predicts Default-Mode Network Activity

    PubMed Central

    Kasess, Christian H.; Meyer, Bernhard M.; Hofmaier, Tina; Diers, Kersten; Bartova, Lucie; Pail, Gerald; Huf, Wolfgang; Uzelac, Zeljko; Hartinger, Beate; Kalcher, Klaudius; Perkmann, Thomas; Haslacher, Helmuth; Meyer-Lindenberg, Andreas; Kasper, Siegfried; Freissmuth, Michael; Windischberger, Christian; Willeit, Matthäus; Lanzenberger, Rupert; Esterbauer, Harald; Brocke, Burkhard; Moser, Ewald; Sitte, Harald H.; Pezawas, Lukas

    2014-01-01

    Background The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence. Methods A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (Vmax) was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA) to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD) activity and platelet Vmax. Results The present study demonstrates that increases in platelet Vmax significantly predict default-mode network (DMN) suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet Vmax is related to global DMN activation and not intrinsic DMN connectivity. Conclusion This study provides evidence that platelet Vmax predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal Vmax coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation. PMID:24667541

  20. iPFPi: A System for Improving Protein Function Prediction through Cumulative Iterations.

    PubMed

    Taha, Kamal; Yoo, Paul D; Alzaabi, Mohammed

    2015-01-01

    We propose a classifier system called iPFPi that predicts the functions of un-annotated proteins. iPFPi assigns an un-annotated protein P the functions of GO annotation terms that are semantically similar to P. An un-annotated protein P and a GO annotation term T are represented by their characteristics. The characteristics of P are GO terms found within the abstracts of biomedical literature associated with P. The characteristics of Tare GO terms found within the abstracts of biomedical literature associated with the proteins annotated with the function of T. Let F and F/ be the important (dominant) sets of characteristic terms representing T and P, respectively. iPFPi would annotate P with the function of T, if F and F/ are semantically similar. We constructed a novel semantic similarity measure that takes into consideration several factors, such as the dominance degree of each characteristic term t in set F based on its score, which is a value that reflects the dominance status of t relative to other characteristic terms, using pairwise beats and looses procedure. Every time a protein P is annotated with the function of T, iPFPi updates and optimizes the current scores of the characteristic terms for T based on the weights of the characteristic terms for P. Set F will be updated accordingly. Thus, the accuracy of predicting the function of T as the function of subsequent proteins improves. This prediction accuracy keeps improving over time iteratively through the cumulative weights of the characteristic terms representing proteins that are successively annotated with the function of T. We evaluated the quality of iPFPi by comparing it experimentally with two recent protein function prediction systems. Results showed marked improvement. PMID:26357323

  1. The Association Between Urinary Phthalates and Lung Function

    PubMed Central

    Cakmak, Sabit; Hebbern, Chris; Saravanabhavan, Gurusankar

    2014-01-01

    Objective: To investigate the influence of phthalate exposure on lung function in the Canadian population. Methods: We tested the association between 1-second forced expiratory volume (FEVl), forced vital capacity (FVC), and urinary phthalate metabolite levels in a nationally representative sample of 3147, from 6 to 49 years old. Results: An interquartile increase in mono-n-butyl phthalate was associated with decreases in percent predicted FEV1 of 0.8% (95% confidence interval = 0.3 to 1.4) and in FVC of 0.9% (95% confidence interval = 0.3 to 1.5). Results were similar for mono-3-carboxypropyl phthalate, mono-benzyl phthalate, and di(2-ethylhexyl) phthalate metabolites, but significant effects of the latter were only seen in males and those at least 17 years old. Conclusions: These results provide evidence that phthalate exposure may adversely affect lung function in the Canadian population. Given that these chemicals are ubiquitous, the population health burden may be significant if the associations were causal. PMID:24709763

  2. Associations between static and functional measures of joint function in the foot and ankle.

    PubMed

    Wrobel, James S; Connolly, John E; Beach, Michael L

    2004-01-01

    Clinicians have traditionally assessed range of motion of the first metatarsophalangeal and ankle joints in a static position. It is unclear, however, if these measurements accurately reflect functional sagittal plane limitations of these joints during gait. For 50 patients (100 feet), we assessed available dorsiflexion at the first metatarsophalangeal and ankle joints, as well as the presence of pinch callus. We then compared these findings with 11 functional gait parameters, as measured using a pressure sensor system. After adjusting for age, weight, smoking status, glycosylated hemoglobin, and insensitivity to monofilament, we found that patients with pinch callus demonstrated statistically significant compensatory gait patterns in 7 of 11 measures. Hallux limitus and equinus patients demonstrated six and three statistically significant associations, respectively. Pinch callus seems to be as predictive of functional gait alterations as static first metatarsophalangeal joint and ankle dorsiflexion. PMID:15547120

  3. Contrast sensitivity function calibration based on image quality prediction

    NASA Astrophysics Data System (ADS)

    Han, Yu; Cai, Yunze

    2014-11-01

    Contrast sensitivity functions (CSFs) describe visual stimuli based on their spatial frequency. However, CSF calibration is limited by the size of the sample collection and this remains an open issue. In this study, we propose an approach for calibrating CSFs that is based on the hypothesis that a precise CSF model can accurately predict image quality. Thus, CSF calibration is regarded as the inverse problem of image quality prediction according to our hypothesis. A CSF could be calibrated by optimizing the performance of a CSF-based image quality metric using a database containing images with known quality. Compared with the traditional method, this would reduce the work involved in sample collection dramatically. In the present study, we employed three image databases to optimize some existing CSF models. The experimental results showed that the performance of a three-parameter CSF model was better than that of other models. The results of this study may be helpful in CSF and image quality research.

  4. Prediction of functional residues in water channels and related proteins.

    PubMed Central

    Froger, A.; Tallur, B.; Thomas, D.; Delamarche, C.

    1998-01-01

    In this paper, we present an updated classification of the ubiquitous MIP (Major Intrinsic Protein) family proteins, including 153 fully or partially sequenced members available in public databases. Presently, about 30 of these proteins have been functionally characterized, exhibiting essentially two distinct types of channel properties: (1) specific water transport by the aquaporins, and (2) small neutral solutes transport, such as glycerol by the glycerol facilitators. Sequence alignments were used to predict amino acids and motifs discriminant in channel specificity. The protein sequences were also analyzed using statistical tools (comparisons of means and correspondence analysis). Five key positions were clearly identified where the residues are specific for each functional subgroup and exhibit high dissimilar physico-chemical properties. Moreover, we have found that the putative channels for small neutral solutes clearly differ from the aquaporins by the amino acid content and the length of predicted loop regions, suggesting a substrate filter function for these loops. From these results, we propose a signature pattern for water transport. PMID:9655351

  5. Does human presynaptic striatal dopamine function predict social conformity?

    PubMed

    Stokes, Paul R A; Benecke, Aaf; Puraite, Julita; Bloomfield, Michael A P; Shotbolt, Paul; Reeves, Suzanne J; Lingford-Hughes, Anne R; Howes, Oliver; Egerton, Alice

    2014-03-01

    Socially desirable responding (SDR) is a personality trait which reflects either a tendency to present oneself in an overly positive manner to others, consistent with social conformity (impression management (IM)), or the tendency to view one's own behaviour in an overly positive light (self-deceptive enhancement (SDE)). Neurochemical imaging studies report an inverse relationship between SDR and dorsal striatal dopamine D₂/₃ receptor availability. This may reflect an association between SDR and D₂/₃ receptor expression, synaptic dopamine levels or a combination of the two. In this study, we used a [¹⁸F]-DOPA positron emission tomography (PET) image database to investigate whether SDR is associated with presynaptic dopamine function. Striatal [¹⁸F]-DOPA uptake, (k(i)(cer), min⁻¹), was determined in two independent healthy participant cohorts (n=27 and 19), by Patlak analysis using a cerebellar reference region. SDR was assessed using the revised Eysenck Personality Questionnaire (EPQ-R) Lie scale, and IM and SDE were measured using the Paulhus Deception Scales. No significant associations were detected between Lie, SDE or IM scores and striatal [¹⁸F]-DOPA k(i)(cer). These results indicate that presynaptic striatal dopamine function is not associated with social conformity and suggests that social conformity may be associated with striatal D₂/₃ receptor expression rather than with synaptic dopamine levels. PMID:24257812

  6. The Evolutionary Legacy of Diversification Predicts Ecosystem Function.

    PubMed

    Yguel, Benjamin; Jactel, Hervé; Pearse, Ian S; Moen, Daniel; Winter, Marten; Hortal, Joaquin; Helmus, Matthew R; Kühn, Ingolf; Pavoine, Sandrine; Purschke, Oliver; Weiher, Evan; Violle, Cyrille; Ozinga, Wim; Brändle, Martin; Bartish, Igor; Prinzing, Andreas

    2016-10-01

    Theory suggests that the structure of evolutionary history represented in a species community may affect its functioning, but phylogenetic diversity metrics do not allow for the identification of major differences in this structure. Here we propose a new metric, ELDERness (for Evolutionary Legacy of DivERsity) to estimate evolutionary branching patterns within communities by fitting a polynomial function to lineage-through-time (LTT) plots. We illustrate how real and simulated community branching patterns can be more correctly described by ELDERness and can successfully predict ecosystem functioning. In particular, the evolutionary history of branching patterns can be encapsulated by the parameters of third-order polynomial functions and further measured through only two parameters, the "ELDERness surfaces." These parameters captured variation in productivity of a grassland community better than existing phylogenetic diversity or diversification metrics and independent of species richness or presence of nitrogen fixers. Specifically, communities with small ELDERness surfaces (constant accumulation of lineages through time in LTT plots) were more productive, consistent with increased productivity resulting from complementary lineages combined with niche filling within lineages. Overall, while existing phylogenetic diversity metrics remain useful in many contexts, we suggest that our ELDERness approach better enables testing hypotheses that relate complex patterns of macroevolutionary history represented in local communities to ecosystem functioning. PMID:27622874

  7. Do dissociated or associated phoria predict the comfortable prism?

    PubMed Central

    Otto, Joanna M. N.; Kromeier, Miriam; Bach, Michael

    2008-01-01

    Background Dissociated and associated phoria are measures of latent strabismus under artificial viewing conditions. We examined to what extent dissociated and associated phoria predict the “comfortable prism”, i.e. the prism that appears most comfortable under natural viewing conditions. Methods For associated phoria, a configuration resembling the Mallett test was employed: both eyes were presented with a fixation cross, surrounded by fusionable objects. Nonius lines served as monocular markers. For dissociated phoria, the left eye was presented with all the Mallett elements, while only a white spot was presented to the right eye. To determine the comfortable prism, all the Mallett elements, including the Nonius lines, were shown to both eyes. In each of the three tests, the observer had to adjust a pair of counterrotating prisms. To avoid any (possibly prejudiced) influence of the experimenter, the prismatic power was recorded with a potentiometer. Twenty non-strabismic subjects with a visual acuity of ≥1.0 in each eye were examined. Results The range of the intertrial mean was for dissociated phoria from +9.3 eso to −5.9 cm/m exo, for associated phoria from +11.2 eso to −3.3 cm/m exo, and for the comfortable prism from +4.8 eso to −4.1 cm/m exo (cm/m = prism dioptre). In most observers, the phoria parameters differed greatly from the comfortable prism. On average, the phoria values were shifted about 2 cm/m towards the eso direction in relation to the comfortable prism (associated phoria not less than dissociated phoria). Conclusions The deviation of both, dissociated and associated phoria, from the comfortable prism suggests that the abnormal viewing conditions under which the phoria parameters are determined induce artefacts. Accordingly, the findings cast doubt on current textbook recommendations to use dissociated or associated phoria as a basis for therapeutic prisms. Rather, patients should be allowed to determine their comfortable prism

  8. Structural and functional protein network analyses predict novel signaling functions for rhodopsin

    PubMed Central

    Kiel, Christina; Vogt, Andreas; Campagna, Anne; Chatr-aryamontri, Andrew; Swiatek-de Lange, Magdalena; Beer, Monika; Bolz, Sylvia; Mack, Andreas F; Kinkl, Norbert; Cesareni, Gianni; Serrano, Luis; Ueffing, Marius

    2011-01-01

    Orchestration of signaling, photoreceptor structural integrity, and maintenance needed for mammalian vision remain enigmatic. By integrating three proteomic data sets, literature mining, computational analyses, and structural information, we have generated a multiscale signal transduction network linked to the visual G protein-coupled receptor (GPCR) rhodopsin, the major protein component of rod outer segments. This network was complemented by domain decomposition of protein–protein interactions and then qualified for mutually exclusive or mutually compatible interactions and ternary complex formation using structural data. The resulting information not only offers a comprehensive view of signal transduction induced by this GPCR but also suggests novel signaling routes to cytoskeleton dynamics and vesicular trafficking, predicting an important level of regulation through small GTPases. Further, it demonstrates a specific disease susceptibility of the core visual pathway due to the uniqueness of its components present mainly in the eye. As a comprehensive multiscale network, it can serve as a basis to elucidate the physiological principles of photoreceptor function, identify potential disease-associated genes and proteins, and guide the development of therapies that target specific branches of the signaling pathway. PMID:22108793

  9. Inter-individual differences in the experience of negative emotion predict variations in functional brain architecture.

    PubMed

    Petrican, Raluca; Saverino, Cristina; Shayna Rosenbaum, R; Grady, Cheryl

    2015-12-01

    Current evidence suggests that two spatially distinct neuroanatomical networks, the dorsal attention network (DAN) and the default mode network (DMN), support externally and internally oriented cognition, respectively, and are functionally regulated by a third, frontoparietal control network (FPC). Interactions among these networks contribute to normal variations in cognitive functioning and to the aberrant affective profiles present in certain clinical conditions, such as major depression. Nevertheless, their links to non-clinical variations in affective functioning are still poorly understood. To address this issue, we used fMRI to measure the intrinsic functional interactions among these networks in a sample of predominantly younger women (N=162) from the Human Connectome Project. Consistent with the previously documented dichotomous motivational orientations (i.e., withdrawal versus approach) associated with sadness versus anger, we hypothesized that greater sadness would predict greater DMN (rather than DAN) functional dominance, whereas greater anger would predict the opposite. Overall, there was evidence of greater DAN (rather than DMN) functional dominance, but this pattern was modulated by current experience of specific negative emotions, as well as subclinical depressive and anxiety symptoms. Thus, greater levels of currently experienced sadness and subclinical depression independently predicted weaker DAN functional dominance (i.e., weaker DAN-FPC functional connectivity), likely reflecting reduced goal-directed attention towards the external perceptual environment. Complementarily, greater levels of currently experienced anger and subclinical anxiety predicted greater DAN functional dominance (i.e., greater DAN-FPC functional connectivity and, for anxiety only, also weaker DMN-FPC coupling). Our findings suggest that distinct affective states and subclinical mood symptoms have dissociable neural signatures, reflective of the symbiotic relationship

  10. Utility functions predict variance and skewness risk preferences in monkeys

    PubMed Central

    Genest, Wilfried; Stauffer, William R.; Schultz, Wolfram

    2016-01-01

    Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals’ preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals’ preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys’ choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences. PMID:27402743

  11. miRDB: an online resource for microRNA target prediction and functional annotations.

    PubMed

    Wong, Nathan; Wang, Xiaowei

    2015-01-01

    MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB. PMID:25378301

  12. Weaknesses in executive functioning predict the initiating of adolescents' alcohol use.

    PubMed

    Peeters, Margot; Janssen, Tim; Monshouwer, Karin; Boendermaker, Wouter; Pronk, Thomas; Wiers, Reinout; Vollebergh, Wilma

    2015-12-01

    Recently, it has been suggested that impairments in executive functioning might be risk factors for the onset of alcohol use rather than a result of heavy alcohol use. In the present study, we examined whether two aspects of executive functioning, working memory and response inhibition, predicted the first alcoholic drink and first binge drinking episode in young adolescents using discrete survival analyses. Adolescents were selected from several Dutch secondary schools including both mainstream and special education (externalizing behavioral problems). Participants were 534 adolescents between 12 and 14 years at baseline. Executive functioning and alcohol use were assessed four times over a period of two years. Working memory uniquely predicted the onset of first drink (p=.01) and first binge drinking episode (p=.04) while response inhibition only uniquely predicted the initiating of the first drink (p=.01). These results suggest that the association of executive functioning and alcohol consumption found in former studies cannot simply be interpreted as an effect of alcohol consumption, as weaknesses in executive functioning, found in alcohol naïve adolescents, predict the initiating of (binge) drinking. Though, prolonged and heavy alcohol use might further weaken already existing deficiencies. PMID:25936585

  13. Predicting activity approach based on new atoms similarity kernel function.

    PubMed

    Abu El-Atta, Ahmed H; Moussa, M I; Hassanien, Aboul Ella

    2015-07-01

    Drug design is a high cost and long term process. To reduce time and costs for drugs discoveries, new techniques are needed. Chemoinformatics field implements the informational techniques and computer science like machine learning and graph theory to discover the chemical compounds properties, such as toxicity or biological activity. This is done through analyzing their molecular structure (molecular graph). To overcome this problem there is an increasing need for algorithms to analyze and classify graph data to predict the activity of molecules. Kernels methods provide a powerful framework which combines machine learning with graph theory techniques. These kernels methods have led to impressive performance results in many several chemoinformatics problems like biological activity prediction. This paper presents a new approach based on kernel functions to solve activity prediction problem for chemical compounds. First we encode all atoms depending on their neighbors then we use these codes to find a relationship between those atoms each other. Then we use relation between different atoms to find similarity between chemical compounds. The proposed approach was compared with many other classification methods and the results show competitive accuracy with these methods. PMID:26117822

  14. Parent Emotional Expressiveness and Children's Self-Regulation: Associations with Abused Children's School Functioning

    ERIC Educational Resources Information Center

    Haskett, Mary E.; Stelter, Rebecca; Proffit, Katie; Nice, Rachel

    2012-01-01

    Objective: Identifying factors associated with school functioning of abused children is important in prevention of long-term negative outcomes associated with school failure. The purpose of this study was to examine the degree to which parent emotional expressiveness and children's self-regulation predicted early school behavior of abused…

  15. Genome-wide association study identifies five loci associated with lung function

    PubMed Central

    Repapi, Emmanouela; Sayers, Ian; Wain, Louise V; Burton, Paul R; Johnson, Toby; Obeidat, Ma’en; Zhao, Jing Hua; Ramasamy, Adaikalavan; Zhai, Guangju; Vitart, Veronique; Huffman, Jennifer E; Igl, Wilmar; Albrecht, Eva; Deloukas, Panos; Henderson, John; Granell, Raquel; McArdle, Wendy L; Rudnicka, Alicja R; Barroso, Inês; Loos, Ruth J F; Wareham, Nicholas J; Mustelin, Linda; Rantanen, Taina; Surakka, Ida; Imboden, Medea; Wichmann, H Erich; Grkovic, Ivica; Jankovic, Stipan; Zgaga, Lina; Hartikainen, Anna-Liisa; Peltonen, Leena; Gyllensten, Ulf; Johansson, Åsa; Zaboli, Ghazal; Campbell, Harry; Wild, Sarah H; Wilson, James F; Gläser, Sven; Homuth, Georg; Völzke, Henry; Mangino, Massimo; Soranzo, Nicole; Spector, Tim D; Polašek, Ozren; Rudan, Igor; Wright, Alan F; Heliövaara, Markku; Ripatti, Samuli; Pouta, Anneli; Naluai, Åsa Torinsson; Olin, Anna-Carin; Torén, Kjell; Cooper, Matthew N; James, Alan L; Palmer, Lyle J; Hingorani, Aroon D; Wannamethee, S Goya; Whincup, Peter H; Smith, George Davey; Ebrahim, Shah; McKeever, Tricia M; Pavord, Ian D; MacLeod, Andrew K; Morris, Andrew D; Porteous, David J; Cooper, Cyrus; Dennison, Elaine; Shaheen, Seif; Karrasch, Stefan; Schnabel, Eva; Schulz, Holger; Grallert, Harald; Bouatia-Naji, Nabila; Delplanque, Jérôme; Froguel, Philippe; Blakey, John D; Britton, John R; Morris, Richard W; Holloway, John W; Lawlor, Debbie A; Hui, Jennie; Nyberg, Fredrik; Jarvelin, Marjo-Riitta; Jackson, Cathy; Kähönen, Mika; Kaprio, Jaakko; Probst-Hensch, Nicole M; Koch, Beate; Hayward, Caroline; Evans, David M; Elliott, Paul; Strachan, David P; Hall, Ian P; Tobin, Martin D

    2010-01-01

    Pulmonary function measures are heritable traits that predict morbidity and mortality and define chronic obstructive pulmonary disease (COPD). We tested genome-wide association with forced expiratory volume in 1 s (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) in the SpiroMeta consortium (n = 20,288 individuals of European ancestry). We conducted a meta-analysis of top signals with data from direct genotyping (n ≤ 32,184 additional individuals) and in silico summary association data from the CHARGE Consortium (n = 21,209) and the Health 2000 survey (n ≤ 883). We confirmed the reported locus at 4q31 and identified associations with FEV1 or FEV1/FVC and common variants at five additional loci: 2q35 in TNS1 (P = 1.11 × 10−12), 4q24 in GSTCD (2.18 × 10−23), 5q33 in HTR4 (P = 4.29 × 10−9), 6p21 in AGER (P = 3.07 × 10−15) and 15q23 in THSD4 (P = 7.24 × 10−15). mRNA analyses showed expression of TNS1, GSTCD, AGER, HTR4 and THSD4 in human lung tissue. These associations offer mechanistic insight into pulmonary function regulation and indicate potential targets for interventions to alleviate respiratory disease. PMID:20010834

  16. 47 CFR 69.603 - Association functions.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... proportion to the revenues associated with each component. The first component (“Category I.A Expenses”) shall be in proportion to the Universal Service Fund and Lifeline Assistance revenues. The second component (“Category I.B Expenses”) shall be in proportion to the sum of the association End User...

  17. Predicting clinical responses in major depression using intrinsic functional connectivity.

    PubMed

    Qin, Jian; Shen, Hui; Zeng, Ling-Li; Jiang, Weixiong; Liu, Li; Hu, Dewen

    2015-08-19

    There has been increasing interest in multivariate pattern analysis (MVPA) as a means of distinguishing psychiatric patients from healthy controls using brain imaging. However, it remains unclear whether MVPA methods can accurately estimate the medication status of psychiatric patients. This study aims to develop an MVPA approach to accurately predict the antidepressant medication status of individuals with major depression on the basis of whole-brain resting-state functional connectivity MRI (rs-fcMRI). We investigated data from rs-fcMRI of 24 medication-naive depressed patients, 16 out of whom subsequently underwent antidepressant treatment and achieved clinical recovery, and 29 demographically similar controls. By training a linear support vector machine classifier and combining it with principal component analysis, the medication-naive patients were identified from the healthy controls with 100% accuracy. In addition, we found reliable correlations between MVPA prediction scores and clinical symptom severity. Moreover, the most discriminative functional connections were located within or across the cerebellum and default mode, affective, and sensorimotor networks, indicating that these networks may play important roles in major depression. Most importantly, only ∼30% of these discriminative connections were normalized in clinically recovered patients after antidepressant treatment. The current study may not only show the feasibility of estimating medication status by MVPA of whole-brain rs-fcMRI data in major depression but also shed new light on the pathological mechanism of this disorder. PMID:26164454

  18. Prediction of a stable associated liquid of short amyloidogenic peptides.

    PubMed

    Luiken, Jurriaan A; Bolhuis, Peter G

    2015-04-28

    Amyloid fibril formation is believed to be a nucleation-controlled process. Depending on the nature of peptide sequence, fibril nucleation can occur in one step, straight from a dilute solution, or in multiple steps via oligomers or disordered aggregates. What determines this process is poorly understood. Since the fibril formation kinetics is driven by thermodynamic forces, knowledge of the phase behavior is crucial. Here, we investigated the phase behavior of three short peptide sequences of varying side-chain hydrophobicity. Replica exchange molecular dynamics simulations of a mid-resolution model indicate that the weakly hydrophobic peptide forms fibrils directly from solution, whereas the most hydrophobic peptide forms a dense liquid phase before crystallizing into ordered fibrils at low temperatures. For the medium hydrophobic peptide we found evidence of a novel additional transition to a liquid phase consisting of clusters of aligned peptides, implying a three-step nucleation process. We tested the robustness of this prediction by applying Wertheim's theory and statistical associating fluid theory to a hard-sphere model dressed with isotropic and anisotropic attractions. We found that the ratio of interaction strengths strongly affects the phase behavior, and under certain conditions indeed gives rise to a stable polymerized liquid phase. The peptide clusters in the associated liquid tend to be slow and long-lived, which may give the oligomer droplet more time to act as a toxic oligomer, before turning into a fibril. PMID:25804723

  19. Predicting habitat associations of five intertidal crab species among estuaries

    NASA Astrophysics Data System (ADS)

    Vermeiren, Peter; Sheaves, Marcus

    2014-08-01

    Intertidal crab assemblages that are active on the sediment surface of tropical estuaries during tidal exposure play an important role in many fundamental ecosystem processes. Consequently, they are critical contributors to a wide range of estuarine goods and services. However, a lack of understanding of their spatial organization within a large landscape context prevents the inclusion of intertidal crabs into generally applicable ecological models and management applications. We investigated spatial distribution patterns of intertidal crabs within and among eight dry tropical estuaries spread across a 160 km stretch of coast in North East Queensland, Australia. Habitat associations were modelled for five species based on photographic sampling in 40-80 sites per estuarine up- and downstream component: Uca seismella occurred in sites with little structure, bordered by low intertidal vegetation; Macrophthalmus japonicus occupied flat muddy sites with no structure or vegetation; Metopograpsus frontalis and Metopograpsus latifrons occupied sites covered with structure in more than 10% and 25% respectively. Finally, both Metopograpsus spp. and Metopograpsus thukuhar occupied rock walls. Habitat associations were predictable among estuaries with moderate to high sensitivity and low percentages of false positives indicating that simple, physical factors were adequate to explain the spatial distribution pattern of intertidal crabs. Results provide a necessary first step in developing generally applicable understanding of the fundamental mechanisms driving spatial niche organization of intertidal crabs within a landscape context.

  20. The functions of contexts in associative learning

    PubMed Central

    Urcelay, Gonzalo P.; Miller, Ralph R.

    2014-01-01

    Although contexts play many roles during training and also during testing, over the last four decades theories of learning have predominantly focused on one or the other of two families of functions served by contexts. In this selective review, we summarize recent data concerning these two functions and their interrelationship. The first function is similar to that of discrete cues, and allows contexts to elicit conditioned responses and compete with discrete events for behavioral control. The second function is modulatory, and similar to that of discrete occasion setters in that in this role contexts do not elicit conditioned responses by themselves, but rather modulate instrumental responding or responding to Pavlovian cues. We first present evidence for these two functions, and then suggest that the spacing of trials, amount of training, and contiguity are three determinants of the degree to which the context will play each function. We also conclude that these two functions are not mutually exclusive, and that future research would benefit from identifying the conditions under which their functions dominate behavioral control. We close by discussing some misconceptions concerning contexts. PMID:24614400

  1. Prediction of functional aerobic capacity without exercise testing

    NASA Technical Reports Server (NTRS)

    Jackson, A. S.; Blair, S. N.; Mahar, M. T.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.

    1990-01-01

    The purpose of this study was to develop functional aerobic capacity prediction models without using exercise tests (N-Ex) and to compare the accuracy with Astrand single-stage submaximal prediction methods. The data of 2,009 subjects (9.7% female) were randomly divided into validation (N = 1,543) and cross-validation (N = 466) samples. The validation sample was used to develop two N-Ex models to estimate VO2peak. Gender, age, body composition, and self-report activity were used to develop two N-Ex prediction models. One model estimated percent fat from skinfolds (N-Ex %fat) and the other used body mass index (N-Ex BMI) to represent body composition. The multiple correlations for the developed models were R = 0.81 (SE = 5.3 ml.kg-1.min-1) and R = 0.78 (SE = 5.6 ml.kg-1.min-1). This accuracy was confirmed when applied to the cross-validation sample. The N-Ex models were more accurate than what was obtained from VO2peak estimated from the Astrand prediction models. The SEs of the Astrand models ranged from 5.5-9.7 ml.kg-1.min-1. The N-Ex models were cross-validated on 59 men on hypertensive medication and 71 men who were found to have a positive exercise ECG. The SEs of the N-Ex models ranged from 4.6-5.4 ml.kg-1.min-1 with these subjects.(ABSTRACT TRUNCATED AT 250 WORDS).

  2. Ongoing dynamics in large-scale functional connectivity predict perception

    PubMed Central

    Sadaghiani, Sepideh; Poline, Jean-Baptiste; Kleinschmidt, Andreas; D’Esposito, Mark

    2015-01-01

    Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22–40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency. PMID:26106164

  3. Functional imaging in tumor-associated lymphatics

    NASA Astrophysics Data System (ADS)

    Kwon, Sunkuk; Sevick-Muraca, Eva M.

    2011-03-01

    The lymphatic system plays an important role in cancer cell dissemination; however whether lymphatic drainage pathways and function change during tumor progression and metastasis remains to be elucidated. In this report, we employed a non-invasive, dynamic near-infrared (NIR) fluorescence imaging technique for functional lymphatic imaging. Indocyanine green (ICG) was intradermally injected into tumor-free mice and mice bearing C6/LacZ rat glioma tumors in the tail or hindlimb. Our imaging data showed abnormal lymphatic drainage pathways and reduction/loss of lymphatic contractile function in mice with lymph node (LN) metastasis, indicating that cancer metastasis to the draining LNs is accompanied by transient changes of the lymphatic architectural network and its function. Therefore, functional lymphatic imaging may provide a role in the clinical staging of cancer.

  4. Fibrosis with Inflammation at One Year Predicts Transplant Functional Decline

    PubMed Central

    Park, Walter D.; Griffin, Matthew D.; Cornell, Lynn D.; Cosio, Fernando G.

    2010-01-01

    Lack of knowledge regarding specific causes for late loss of kidney transplants hampers improvements in long-term allograft survival. Kidney transplants with both interstitial fibrosis and subclinical inflammation but not fibrosis alone after 1 year have reduced survival. This study tested whether fibrosis with inflammation at 1 year associates with decline of renal function in a low-risk cohort and characterized the nature of the inflammation. We studied 151 living-donor, tacrolimus/mycophenolate-treated recipients without overt risk factors for reduced graft survival. Transplants with normal histology (n = 86) or fibrosis alone (n = 45) on 1-year protocol biopsy had stable renal function between 1 and 5 years, whereas those with both fibrosis and inflammation (n = 20) exhibited a decline in GFR and reduced graft survival. Immunohistochemistry confirmed increased interstitial T cells and macrophages/dendritic cells in the group with both fibrosis and inflammation, and there was increased expression of transcripts related to innate and cognate immunity. Pathway- and pathologic process–specific analyses of microarray profiles revealed that potentially damaging immunologic activities were enriched among the overexpressed transcripts (e.g., Toll-like receptor signaling, antigen presentation/dendritic cell maturation, IFN-γ–inducible response, cytotoxic T lymphocyte–associated and acute rejection–associated genes). Therefore, the combination of fibrosis and inflammation in 1-year protocol biopsies associates with reduced graft function and survival as well as a rejection-like gene expression signature, even among recipients with no clinical risk factors for poor outcomes. Early interventions aimed at altering rejection-like inflammation may improve long-term survival of kidney allografts. PMID:20813870

  5. How and when should interactome-derived clusters be used to predict functional modules and protein function?

    PubMed Central

    Song, Jimin; Singh, Mona

    2009-01-01

    Motivation: Clustering of protein–protein interaction networks is one of the most common approaches for predicting functional modules, protein complexes and protein functions. But, how well does clustering perform at these tasks? Results: We develop a general framework to assess how well computationally derived clusters in physical interactomes overlap functional modules derived via the Gene Ontology (GO). Using this framework, we evaluate six diverse network clustering algorithms using Saccharomyces cerevisiae and show that (i) the performances of these algorithms can differ substantially when run on the same network and (ii) their relative performances change depending upon the topological characteristics of the network under consideration. For the specific task of function prediction in S.cerevisiae, we demonstrate that, surprisingly, a simple non-clustering guilt-by-association approach outperforms widely used clustering-based approaches that annotate a protein with the overrepresented biological process and cellular component terms in its cluster; this is true over the range of clustering algorithms considered. Further analysis parameterizes performance based on the number of annotated proteins, and suggests when clustering approaches should be used for interactome functional analyses. Overall our results suggest a re-examination of when and how clustering approaches should be applied to physical interactomes, and establishes guidelines by which novel clustering approaches for biological networks should be justified and evaluated with respect to functional analysis. Contact: msingh@cs.princeton.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19770263

  6. LncDisease: a sequence based bioinformatics tool for predicting lncRNA-disease associations

    PubMed Central

    Wang, Junyi; Ma, Ruixia; Ma, Wei; Chen, Ji; Yang, Jichun; Xi, Yaguang; Cui, Qinghua

    2016-01-01

    LncRNAs represent a large class of noncoding RNA molecules that have important functions and play key roles in a variety of human diseases. There is an urgent need to develop bioinformatics tools as to gain insight into lncRNAs. This study developed a sequence-based bioinformatics method, LncDisease, to predict the lncRNA-disease associations based on the crosstalk between lncRNAs and miRNAs. Using LncDisease, we predicted the lncRNAs associated with breast cancer and hypertension. The breast-cancer-associated lncRNAs were studied in two breast tumor cell lines, MCF-7 and MDA-MB-231. The qRT-PCR results showed that 11 (91.7%) of the 12 predicted lncRNAs could be validated in both breast cancer cell lines. The hypertension-associated lncRNAs were further evaluated in human vascular smooth muscle cells (VSMCs) stimulated with angiotensin II (Ang II). The qRT-PCR results showed that 3 (75.0%) of the 4 predicted lncRNAs could be validated in Ang II-treated human VSMCs. In addition, we predicted 6 diseases associated with the lncRNA GAS5 and validated 4 (66.7%) of them by literature mining. These results greatly support the specificity and efficacy of LncDisease in the study of lncRNAs in human diseases. The LncDisease software is freely available on the Software Page: http://www.cuilab.cn/. PMID:26887819

  7. LncDisease: a sequence based bioinformatics tool for predicting lncRNA-disease associations.

    PubMed

    Wang, Junyi; Ma, Ruixia; Ma, Wei; Chen, Ji; Yang, Jichun; Xi, Yaguang; Cui, Qinghua

    2016-05-19

    LncRNAs represent a large class of noncoding RNA molecules that have important functions and play key roles in a variety of human diseases. There is an urgent need to develop bioinformatics tools as to gain insight into lncRNAs. This study developed a sequence-based bioinformatics method, LncDisease, to predict the lncRNA-disease associations based on the crosstalk between lncRNAs and miRNAs. Using LncDisease, we predicted the lncRNAs associated with breast cancer and hypertension. The breast-cancer-associated lncRNAs were studied in two breast tumor cell lines, MCF-7 and MDA-MB-231. The qRT-PCR results showed that 11 (91.7%) of the 12 predicted lncRNAs could be validated in both breast cancer cell lines. The hypertension-associated lncRNAs were further evaluated in human vascular smooth muscle cells (VSMCs) stimulated with angiotensin II (Ang II). The qRT-PCR results showed that 3 (75.0%) of the 4 predicted lncRNAs could be validated in Ang II-treated human VSMCs. In addition, we predicted 6 diseases associated with the lncRNA GAS5 and validated 4 (66.7%) of them by literature mining. These results greatly support the specificity and efficacy of LncDisease in the study of lncRNAs in human diseases. The LncDisease software is freely available on the Software Page: http://www.cuilab.cn/. PMID:26887819

  8. The Mutational Spectrum of Holoprosencephaly-Associated Changes within the SHH Gene in Humans Predicts Loss-of-Function Through Either Key Structural Alterations of the Ligand or Its Altered Synthesis

    PubMed Central

    Roessler, Erich; El-Jaick, Kenia B.; Dubourg, Christèle; Vélez, Jorge I.; Solomon, Benjamin D.; Pineda-Álvarez, Daniel E.; Lacbawan, Felicitas; Zhou, Nan; Ouspenskaia, Maia; Paulussen, Aimée; Smeets, Hubert J.; Hehr, Ute; Bendavid, Claude; Bale, Sherri; Odent, Sylvie; David, Véronique; Muenke, Maximilian

    2009-01-01

    Mutations within either the SHH gene or its related pathway components are the most common, and best understood, pathogenetic changes observed in holoprosencephaly patients; this fact is consistent with the essential functions of this gene during forebrain development and patterning. Here we summarize the nature and types of deleterious sequence alterations among over one hundred distinct mutations in the SHH gene (64 novel mutations) and compare these to over a dozen mutations in disease-related Hedgehog family members IHH and DHH. This combined structural analysis suggests that dysfunction of Hedgehog signaling in human forebrain development can occur through truncations or major structural changes to the signaling domain, SHH-N, as well as due to defects in the processing of the mature ligand from its pre-pro-precursor or defective post-translation bi-lipid modifications with palmitate and cholesterol PMID:19603532

  9. Predicting Gene-Regulation Functions: Lessons from Temperate Bacteriophages

    PubMed Central

    Teif, Vladimir B.

    2010-01-01

    Gene-regulation functions (GRF) provide a unique characteristic of a cis-regulatory module (CRM), relating the concentrations of transcription factors (input) to the promoter activities (output). The challenge is to predict GRFs from the sequence. Here we systematically consider the lysogeny-lysis CRMs of different temperate bacteriophages such as the Lactobacillus casei phage A2, Escherichia coli phages λ, and 186 and Lactococcal phage TP901-1. This study allowed explaining a recent experimental puzzle on the role of Cro protein in the lambda switch. Several general conclusions have been drawn: 1), long-range interactions, multilayer assembly and DNA looping may lead to complex GRFs that cannot be described by linear functions of binding site occupancies; 2), in general, GRFs cannot be described by the Boolean logic, whereas a three-state non-Boolean logic suffices for the studied examples; 3), studied CRMs of the intact phages seemed to have a similar GRF topology (the number of plateaus and peaks corresponding to different expression regimes); we hypothesize that functionally equivalent CRMs might have topologically equivalent GRFs for a larger class of genetic systems; and 4) within a given GRF class, a set of mechanistic-to-mathematical transformations has been identified, which allows shaping the GRF before carrying out a system-level analysis. PMID:20371324

  10. Functional traits predict relationship between plant abundance dynamic and long-term climate warming.

    PubMed

    Soudzilovskaia, Nadejda A; Elumeeva, Tatiana G; Onipchenko, Vladimir G; Shidakov, Islam I; Salpagarova, Fatima S; Khubiev, Anzor B; Tekeev, Dzhamal K; Cornelissen, Johannes H C

    2013-11-01

    Predicting climate change impact on ecosystem structure and services is one of the most important challenges in ecology. Until now, plant species response to climate change has been described at the level of fixed plant functional types, an approach limited by its inflexibility as there is much interspecific functional variation within plant functional types. Considering a plant species as a set of functional traits greatly increases our possibilities for analysis of ecosystem functioning and carbon and nutrient fluxes associated therewith. Moreover, recently assembled large-scale databases hold comprehensive per-species data on plant functional traits, allowing a detailed functional description of many plant communities on Earth. Here, we show that plant functional traits can be used as predictors of vegetation response to climate warming, accounting in our test ecosystem (the species-rich alpine belt of Caucasus mountains, Russia) for 59% of variability in the per-species abundance relation to temperature. In this mountain belt, traits that promote conservative leaf water economy (higher leaf mass per area, thicker leaves) and large investments in belowground reserves to support next year's shoot buds (root carbon content) were the best predictors of the species increase in abundance along with temperature increase. This finding demonstrates that plant functional traits constitute a highly useful concept for forecasting changes in plant communities, and their associated ecosystem services, in response to climate change. PMID:24145400

  11. The Prediction of Broadband Shock-Associated Noise Including Propagation Effects

    NASA Technical Reports Server (NTRS)

    Miller, Steven; Morris, Philip J.

    2011-01-01

    An acoustic analogy is developed based on the Euler equations for broadband shock- associated noise (BBSAN) that directly incorporates the vector Green's function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) as the mean flow. The vector Green's function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation. An adjoint vector Green's function solver is implemented to determine the vector Green's function based on a locally parallel mean flow at streamwise locations of the SRANS solution. However, the developed acoustic analogy could easily be based on any adjoint vector Green's function solver, such as one that makes no assumptions about the mean flow. The newly developed acoustic analogy can be simplified to one that uses the Green's function associated with the Helmholtz equation, which is consistent with the formulation of Morris and Miller (AIAAJ 2010). A large number of predictions are generated using three different nozzles over a wide range of fully expanded Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise labs. In addition, two models for the so-called 'fine-scale' mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include the propagation effects, especially in the upstream direction of the jet.

  12. Reveal genes functionally associated with ACADS by a network study.

    PubMed

    Chen, Yulong; Su, Zhiguang

    2015-09-15

    Establishing a systematic network is aimed at finding essential human gene-gene/gene-disease pathway by means of network inter-connecting patterns and functional annotation analysis. In the present study, we have analyzed functional gene interactions of short-chain acyl-coenzyme A dehydrogenase gene (ACADS). ACADS plays a vital role in free fatty acid β-oxidation and regulates energy homeostasis. Modules of highly inter-connected genes in disease-specific ACADS network are derived by integrating gene function and protein interaction data. Among the 8 genes in ACADS web retrieved from both STRING and GeneMANIA, ACADS is effectively conjoined with 4 genes including HAHDA, HADHB, ECHS1 and ACAT1. The functional analysis is done via ontological briefing and candidate disease identification. We observed that the highly efficient-interlinked genes connected with ACADS are HAHDA, HADHB, ECHS1 and ACAT1. Interestingly, the ontological aspect of genes in the ACADS network reveals that ACADS, HAHDA and HADHB play equally vital roles in fatty acid metabolism. The gene ACAT1 together with ACADS indulges in ketone metabolism. Our computational gene web analysis also predicts potential candidate disease recognition, thus indicating the involvement of ACADS, HAHDA, HADHB, ECHS1 and ACAT1 not only with lipid metabolism but also with infant death syndrome, skeletal myopathy, acute hepatic encephalopathy, Reye-like syndrome, episodic ketosis, and metabolic acidosis. The current study presents a comprehensible layout of ACADS network, its functional strategies and candidate disease approach associated with ACADS network. PMID:26045367

  13. Structure and Associated Biological Functions of Viroids.

    PubMed

    Steger, Gerhard; Perreault, Jean-Pierre

    2016-01-01

    Mature viroids consist of a noncoding, covalently closed circular RNA that is able to autonomously infect respective host plants. Thus, they must utilize proteins of the host for most biological functions such as replication, processing, transport, and pathogenesis. Therefore, viroids can be regarded as minimal parasites of the host machinery. They have to present to the host machinery the appropriate signals based on either their sequence or their structure. Here, we summarize such sequence and structural features critical for the biological functions of viroids. PMID:26997592

  14. Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

    SciTech Connect

    Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

    2015-04-02

    The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO22+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K1 values are significantly overestimated. Accurate predictions of the absolute log K1 values (root mean square deviation from experiment < 1.0 for log K1 values ranging from 0 to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.

  15. Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

    DOE PAGESBeta

    Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

    2015-04-02

    The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO22+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K1 values are significantly overestimated. Accurate predictions of the absolute log K1 values (root mean square deviation from experiment < 1.0 for log K1 values ranging from 0more » to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.« less

  16. Predicting stability constants for uranyl complexes using density functional theory.

    PubMed

    Vukovic, Sinisa; Hay, Benjamin P; Bryantsev, Vyacheslav S

    2015-04-20

    The ability to predict the equilibrium constants for the formation of 1:1 uranyl/ligand complexes (log K1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We use density functional theory (B3LYP) and the integral equation formalism polarizable continuum model (IEF-PCM) to compute aqueous stability constants for UO2(2+) complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K1 values are significantly overestimated. Accurate predictions of the absolute log K1 values (root-mean-square deviation from experiment <1.0 for log K1 values ranging from 0 to 16.8) can be obtained by fitting the experimental data for two groups of mono- and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelating capability to uranyl. PMID:25835578

  17. Prediction of glass durability as a function of environmental conditions

    SciTech Connect

    Jantzen, C M

    1988-01-01

    A thermodynamic model of glass durability is applied to natural, ancient, and nuclear waste glasses. The durabilities of over 150 different natural and man-made glasses, including actual ancient Roman and Islamic glasses (Jalame ca. 350 AD, Nishapur 10-11th century AD and Gorgon 9-11th century AD), are compared. Glass durability is a function of the thermodynamic hydration free energy, ..delta..G/sub hyd/, which can be calculated from glass composition and solution pH. The durability of the most durable nuclear waste glasses examined was /approximately/10/sup 6/ years. The least durable waste glass formulations were comparable in durability to the most durable simulated medieval window glasses of /approximately/10/sup 3/ years. In this manner, the durability of nuclear waste glasses has been interpolated to be /approximately/10/sup 6/ years and no less than 10/sup 3/ years. Hydration thermodynamics have been shown to be applicable to the dissolution of glass in various natural environments. Groundwater-glass interactions relative to geologic disposal of nuclear waste, hydration rind dating of obsidians, andor other archeological studies can be modeled, e.g., the relative durabilities of six simulated medieval window glasses have been correctly predicted for both laboratory (one month) and burial (5 years) experiments. Effects of solution pH on glass dissolution has been determined experimentally for the 150 different glasses and can be predicted theoretically by hydration thermodynamics. The effects of solution redox on dissolution of glass matrix elements such as SI and B have shown to be minimal. The combined effects of solution pH and Eh have been described and unified by construction of thermodynamically calculated Pourbaix (pH-Eh) diagrams for glass dissolution. The Pourbaix diagrams have been quantified to describe glass dissolution as a function of environmental conditions by use of the data derived from hydration thermodynamics. 56 refs., 7 figs.

  18. Evolutionary-guided de novo structure prediction of self-associated transmembrane helical proteins with near-atomic accuracy

    NASA Astrophysics Data System (ADS)

    Wang, Y.; Barth, P.

    2015-05-01

    How specific protein associations regulate the function of membrane receptors remains poorly understood. Conformational flexibility currently hinders the structure determination of several classes of membrane receptors and associated oligomers. Here we develop EFDOCK-TM, a general method to predict self-associated transmembrane protein helical (TMH) structures from sequence guided by co-evolutionary information. We show that accurate intermolecular contacts can be identified using a combination of protein sequence covariation and TMH binding surfaces predicted from sequence. When applied to diverse TMH oligomers, including receptors characterized in multiple conformational and functional states, the method reaches unprecedented near-atomic accuracy for most targets. Blind predictions of structurally uncharacterized receptor tyrosine kinase TMH oligomers provide a plausible hypothesis on the molecular mechanisms of disease-associated point mutations and binding surfaces for the rational design of selective inhibitors. The method sets the stage for uncovering novel determinants of molecular recognition and signalling in single-spanning eukaryotic membrane receptors.

  19. Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism.

    PubMed

    Plitt, Mark; Barnes, Kelly Anne; Wallace, Gregory L; Kenworthy, Lauren; Martin, Alex

    2015-12-01

    Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome--adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement. PMID:26627261

  20. Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism

    PubMed Central

    Plitt, Mark; Barnes, Kelly Anne; Wallace, Gregory L.; Kenworthy, Lauren; Martin, Alex

    2015-01-01

    Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome—adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement. PMID:26627261

  1. Predicting Species-environment Relationships with Functional Traits for the Understory Flora of Wisconsin

    NASA Astrophysics Data System (ADS)

    Ash, J.; Li, D.; Johnson, S.; Rogers, D. A.; Waller, D. M.

    2015-12-01

    Understanding the processes that structure species' abundance patterns is a central problem in ecology, both for explaining current species' distributions and predicting future changes. Environmental gradients affect species' distribution patterns with these responses likely depending on species' functional traits. Thus, tracking shifts in species' traits can provide insight into the mechanisms by which species respond to dynamic environmental conditions. We examined how functional traits are associated with long-term changes in the distribution and abundance of understory plants in Wisconsin forests over the last 50+ years. We relied on detailed surveys and resurveys of the same Wisconsin forest plots, data on 12 functional traits, and site-level environmental variables including soil and climate conditions. We then related changes in the abundance of 293 species across a network of 249 sites to these environmental variables and explored whether functional traits served to predict these relationships using multilevel models. Species abundance patterns were strongly related to variation in environmental conditions among sites, but species appear to be responding to distinct sets of environmental variables. Functional traits only weakly predicted these species-environment relationships, limiting our ability to generalize these results to other systems. Nonetheless, understanding how traits interact with environmental gradients to structure species distribution patterns helps us to disentangle the drivers of ecological change across diverse landscapes.

  2. LRR Conservation Mapping to Predict Functional Sites within Protein Leucine-Rich Repeat Domains

    PubMed Central

    Helft, Laura; Reddy, Vignyan; Chen, Xiyang; Koller, Teresa; Federici, Luca; Fernández-Recio, Juan; Gupta, Rishabh; Bent, Andrew

    2011-01-01

    Computational prediction of protein functional sites can be a critical first step for analysis of large or complex proteins. Contemporary methods often require several homologous sequences and/or a known protein structure, but these resources are not available for many proteins. Leucine-rich repeats (LRRs) are ligand interaction domains found in numerous proteins across all taxonomic kingdoms, including immune system receptors in plants and animals. We devised Repeat Conservation Mapping (RCM), a computational method that predicts functional sites of LRR domains. RCM utilizes two or more homologous sequences and a generic representation of the LRR structure to identify conserved or diversified patches of amino acids on the predicted surface of the LRR. RCM was validated using solved LRR+ligand structures from multiple taxa, identifying ligand interaction sites. RCM was then used for de novo dissection of two plant microbe-associated molecular pattern (MAMP) receptors, EF-TU RECEPTOR (EFR) and FLAGELLIN-SENSING 2 (FLS2). In vivo testing of Arabidopsis thaliana EFR and FLS2 receptors mutagenized at sites identified by RCM demonstrated previously unknown functional sites. The RCM predictions for EFR, FLS2 and a third plant LRR protein, PGIP, compared favorably to predictions from ODA (optimal docking area), Consurf, and PAML (positive selection) analyses, but RCM also made valid functional site predictions not available from these other bioinformatic approaches. RCM analyses can be conducted with any LRR-containing proteins at www.plantpath.wisc.edu/RCM, and the approach should be modifiable for use with other types of repeat protein domains. PMID:21789174

  3. A continuous function model for path prediction of entities

    NASA Astrophysics Data System (ADS)

    Nanda, S.; Pray, R.

    2007-04-01

    As militaries across the world continue to evolve, the roles of humans in various theatres of operation are being increasingly targeted by military planners for substitution with automation. Forward observation and direction of supporting arms to neutralize threats from dynamic adversaries is one such example. However, contemporary tracking and targeting systems are incapable of serving autonomously for they do not embody the sophisticated algorithms necessary to predict the future positions of adversaries with the accuracy offered by the cognitive and analytical abilities of human operators. The need for these systems to incorporate methods characterizing such intelligence is therefore compelling. In this paper, we present a novel technique to achieve this goal by modeling the path of an entity as a continuous polynomial function of multiple variables expressed as a Taylor series with a finite number of terms. We demonstrate the method for evaluating the coefficient of each term to define this function unambiguously for any given entity, and illustrate its use to determine the entity's position at any point in time in the future.

  4. Local functional descriptors for surface comparison based binding prediction

    PubMed Central

    2012-01-01

    Background Molecular recognition in proteins occurs due to appropriate arrangements of physical, chemical, and geometric properties of an atomic surface. Similar surface regions should create similar binding interfaces. Effective methods for comparing surface regions can be used in identifying similar regions, and to predict interactions without regard to the underlying structural scaffold that creates the surface. Results We present a new descriptor for protein functional surfaces and algorithms for using these descriptors to compare protein surface regions to identify ligand binding interfaces. Our approach uses descriptors of local regions of the surface, and assembles collections of matches to compare larger regions. Our approach uses a variety of physical, chemical, and geometric properties, adaptively weighting these properties as appropriate for different regions of the interface. Our approach builds a classifier based on a training corpus of examples of binding sites of the target ligand. The constructed classifiers can be applied to a query protein providing a probability for each position on the protein that the position is part of a binding interface. We demonstrate the effectiveness of the approach on a number of benchmarks, demonstrating performance that is comparable to the state-of-the-art, with an approach with more generality than these prior methods. Conclusions Local functional descriptors offer a new method for protein surface comparison that is sufficiently flexible to serve in a variety of applications. PMID:23176080

  5. Efficacy of functional movement screening for predicting injuries in coast guard cadets.

    PubMed

    Knapik, Joseph J; Cosio-Lima, Ludimila M; Reynolds, Katy L; Shumway, Richard S

    2015-05-01

    Functional movement screening (FMS) examines the ability of individuals to perform highly specific movements with the aim of identifying individuals who have functional limitations or asymmetries. It is assumed that individuals who can more effectively accomplish the required movements have a lower injury risk. This study determined the ability of FMS to predict injuries in the United States Coast Guard (USCG) cadets. Seven hundred seventy male and 275 female USCG freshman cadets were administered the 7 FMS tests before the physically intense 8-week Summer Warfare Annual Basic (SWAB) training. Physical training-related injuries were recorded during SWAB training. Cumulative injury incidence was calculated at various FMS cutpoint scores. The ability of the FMS total score to predict injuries was examined by calculating sensitivity and specificity. Determination of the FMS cutpoint that maximized specificity and sensitivity was determined from the Youden's index (sensitivity + specificity - 1). For men, FMS scores ≤ 12 were associated with higher injury risk than scores >12; for women, FMS scores ≤ 15 were associated with higher injury risk than scores >15. The Youden's Index indicated that the optimal FMS cutpoint was ≤ 11 for men (22% sensitivity, 87% specificity) and ≤ 14 for women (60% sensitivity, 61% specificity). Functional movement screening demonstrated moderate prognostic accuracy for determining injury risk among female Coast Guard cadets but relatively low accuracy among male cadets. Attempting to predict injury risk based on the FMS test seems to have some limited promise based on the present and past investigations. PMID:25264669

  6. Prospective associations between bilingualism and executive function in Latino children: sustained effects while controlling for biculturalism.

    PubMed

    Riggs, Nathaniel R; Shin, Hee-Sung; Unger, Jennifer B; Spruijt-Metz, Donna; Pentz, Mary Ann

    2014-10-01

    The study purpose was to test 1-year prospective associations between English-Spanish bilingualism and executive function in 5th to 6th grade students while controlling for biculturalism. Participants included 182 US Latino students (50 % female). Self-report surveys assessed biculturalism, bilingualism, and executive function (i.e., working memory, organizational skills, inhibitory control, and emotional control, as well as a summary executive function score). General linear model regressions demonstrated that bilingualism significantly predicted the summary executive function score as well as working memory such that bilingual proficiency was positively related to executive function. Results are the first to demonstrate (a) prospective associations between bilingualism to executive function while controlling for the potential third variable of biculturalism, and (b) a principal role for working memory in this relationship. Since executive function is associated with a host of health outcomes, one implication of study findings is that bilingualism may have an indirect protective influence on youth development. PMID:23632808

  7. Handgrip Strength Predicts Functional Decline at Discharge in Hospitalized Male Elderly: A Hospital Cohort Study

    PubMed Central

    García-Peña, Carmen; García-Fabela, Luis C.; Gutiérrez-Robledo, Luis M.; García-González, Jose J.; Arango-Lopera, Victoria E.; Pérez-Zepeda, Mario U.

    2013-01-01

    Functional decline after hospitalization is a common adverse outcome in elderly. An easy to use, reproducible and accurate tool to identify those at risk would aid focusing interventions in those at higher risk. Handgrip strength has been shown to predict adverse outcomes in other settings. The aim of this study was to determine if handgrip strength measured upon admission to an acute care facility would predict functional decline (either incident or worsening of preexisting) at discharge among older Mexican, stratified by gender. In addition, cutoff points as a function of specificity would be determined. A cohort study was conducted in two hospitals in Mexico City. The primary endpoint was functional decline on discharge, defined as a 30-point reduction in the Barthel Index score from that of the baseline score. Handgrip strength along with other variables was measured at initial assessment, including: instrumental activities of daily living, cognition, depressive symptoms, delirium, hospitalization length and quality of life. All analyses were stratified by gender. Logistic regression to test independent association between handgrip strength and functional decline was performed, along with estimation of handgrip strength test values (specificity, sensitivity, area under the curve, etc.). A total of 223 patients admitted to an acute care facility between 2007 and 2009 were recruited. A total of 55 patients (24.7%) had functional decline, 23.46% in male and 25.6% in women. Multivariate analysis showed that only males with low handgrip strength had an increased risk of functional decline at discharge (OR 0.88, 95% CI 0.79–0.98, p = 0.01), with a specificity of 91.3% and a cutoff point of 20.65 kg for handgrip strength. Females had not a significant association between handgrip strength and functional decline. Measurement of handgrip strength on admission to acute care facilities may identify male elderly patients at risk of having functional decline, and

  8. Predicting strength and function for promoters of the Escherichia coli alternative sigma factor, σE

    PubMed Central

    Rhodius, Virgil A.; Mutalik, Vivek K.

    2010-01-01

    Sequenced bacterial genomes provide a wealth of information but little understanding of transcriptional regulatory circuits largely because accurate prediction of promoters is difficult. We examined two important issues for accurate promoter prediction: (1) the ability to predict promoter strength and (2) the sequence properties that distinguish between active and weak/inactive promoters. We addressed promoter prediction using natural core promoters recognized by the well-studied alternative sigma factor, Escherichia coli σE, as a representative of group 4 σs, the largest σ group. To evaluate the contribution of sequence to promoter strength and function, we used modular position weight matrix models comprised of each promoter motif and a penalty score for suboptimal motif location. We find that a combination of select modules is moderately predictive of promoter strength and that imposing minimal motif scores distinguished active from weak/inactive promoters. The combined -35/-10 score is the most important predictor of activity. Our models also identified key sequence features associated with active promoters. A conserved “AAC” motif in the -35 region is likely to be a general predictor of function for promoters recognized by group 4 σs. These results provide valuable insights into sequences that govern promoter strength, distinguish active and inactive promoters for the first time, and are applicable to both in vivo and in vitro measures of promoter strength. PMID:20133665

  9. Predicting strength and function for promoters of the Escherichia coli alternative sigma factor, sigmaE.

    PubMed

    Rhodius, Virgil A; Mutalik, Vivek K

    2010-02-16

    Sequenced bacterial genomes provide a wealth of information but little understanding of transcriptional regulatory circuits largely because accurate prediction of promoters is difficult. We examined two important issues for accurate promoter prediction: (1) the ability to predict promoter strength and (2) the sequence properties that distinguish between active and weak/inactive promoters. We addressed promoter prediction using natural core promoters recognized by the well-studied alternative sigma factor, Escherichia coli sigma(E), as a representative of group 4 sigmas, the largest sigma group. To evaluate the contribution of sequence to promoter strength and function, we used modular position weight matrix models comprised of each promoter motif and a penalty score for suboptimal motif location. We find that a combination of select modules is moderately predictive of promoter strength and that imposing minimal motif scores distinguished active from weak/inactive promoters. The combined -35/-10 score is the most important predictor of activity. Our models also identified key sequence features associated with active promoters. A conserved "AAC" motif in the -35 region is likely to be a general predictor of function for promoters recognized by group 4 sigmas. These results provide valuable insights into sequences that govern promoter strength, distinguish active and inactive promoters for the first time, and are applicable to both in vivo and in vitro measures of promoter strength. PMID:20133665

  10. In silico predicted structural and functional robustness of piscine steroidogenesis.

    PubMed

    Hala, D; Huggett, D B

    2014-03-21

    Assessments of metabolic robustness or susceptibility are inherently dependent on quantitative descriptions of network structure and associated function. In this paper a stoichiometric model of piscine steroidogenesis was constructed and constrained with productions of selected steroid hormones. Structural and flux metrics of this in silico model were quantified by calculating extreme pathways and optimal flux distributions (using linear programming). Extreme pathway analysis showed progestin and corticosteroid synthesis reactions to be highly participant in extreme pathways. Furthermore, reaction participation in extreme pathways also fitted a power law distribution (degree exponent γ=2.3), which suggested that progestin and corticosteroid reactions act as 'hubs' capable of generating other functionally relevant pathways required to maintain steady-state functionality of the network. Analysis of cofactor usage (O2 and NADPH) showed progestin synthesis reactions to exhibit high robustness, whereas estrogen productions showed highest energetic demands with low associated robustness to maintain such demands. Linear programming calculated optimal flux distributions showed high heterogeneity of flux values with a near-random power law distribution (degree exponent γ≥2.7). Subsequently, network robustness was tested by assessing maintenance of metabolite flux-sum subject to targeted deletions of rank-ordered (low to high metric) extreme pathway participant and optimal flux reactions. Network robustness was susceptible to deletions of extreme pathway participant reactions, whereas minimal impact of high flux reaction deletion was observed. This analysis shows that the steroid network is susceptible to perturbation of structurally relevant (extreme pathway) reactions rather than those carrying high flux. PMID:24333207

  11. Predicting Functional Status Following Amputation After Lower Extremity Bypass

    PubMed Central

    Suckow, Bjoern D.; Goodney, Philip P.; Cambria, Robert A.; Bertges, Daniel J.; Eldrup-Jorgensen, Jens; Indes, Jeffrey E.; Schanzer, Andres; Stone, David H.; Kraiss, Larry W.; Cronenwett, Jack L.

    2012-01-01

    Background Some patients who undergo lower extremity bypass (LEB) for critical limb ischemia ultimately require amputation. The functional outcome achieved by these patients after amputation is not well known. Therefore, we sought to characterize the functional outcome of patients who undergo amputation after LEB, and to describe the pre- and perioperative factors associated with independent ambulation at home after lower extremity amputation. Methods Within a cohort of 3,198 patients who underwent an LEB between January, 2003 and December, 2008, we studied 436 patients who subsequently received an above-knee (AK), below-knee (BK), or minor (forefoot or toe) ipsilateral or contralateral amputation. Our main outcome measure consisted of a “good functional outcome,” defined as living at home and ambulating independently. We calculated univariate and multivariate associations among patient characteristics and our main outcome measure, as well as overall survival. Results Of the 436 patients who underwent amputation within the first year following LEB, 224 of 436 (51.4%) had a minor amputation, 105 of 436 (24.1%) had a BK amputation, and 107 of 436 (24.5%) had an AK amputation. The majority of AK (75 of 107, 72.8%) and BK amputations (72 of 105, 70.6%) occurred in the setting of bypass graft thrombosis, whereas nearly all minor amputations (200 of 224, 89.7%) occurred with a patent bypass graft. By life-table analysis at 1 year, we found that the proportion of surviving patients with a good functional outcome varied by the presence and extent of amputation (proportion surviving with good functional outcome = 88% no amputation, 81% minor amputation, 55% BK amputation, and 45% AK amputation, p = 0.001). Among those analyzed at long-term follow-up, survival was slightly lower for those who had a minor amputation when compared with those who did not receive an amputation after LEB (81 vs. 88%, p = 0.02). Survival among major amputation patients did not significantly

  12. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

    PubMed Central

    Langille, Morgan G. I.; Zaneveld, Jesse; Caporaso, J. Gregory; McDonald, Daniel; Knights, Dan; Reyes, Joshua A.; Clemente, Jose C.; Burkepile, Deron E.; Vega Thurber, Rebecca L.; Knight, Rob; Beiko, Robert G.; Huttenhower, Curtis

    2013-01-01

    Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community’s functional capabilities. Here we describe PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this ‘predictive metagenomic’ approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available. PMID:23975157

  13. The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements.

    PubMed

    Altenhoff, Adrian M; Škunca, Nives; Glover, Natasha; Train, Clément-Marie; Sueki, Anna; Piližota, Ivana; Gori, Kevin; Tomiczek, Bartlomiej; Müller, Steven; Redestig, Henning; Gonnet, Gaston H; Dessimoz, Christophe

    2015-01-01

    The Orthologous Matrix (OMA) project is a method and associated database inferring evolutionary relationships amongst currently 1706 complete proteomes (i.e. the protein sequence associated for every protein-coding gene in all genomes). In this update article, we present six major new developments in OMA: (i) a new web interface; (ii) Gene Ontology function predictions as part of the OMA pipeline; (iii) better support for plant genomes and in particular homeologs in the wheat genome; (iv) a new synteny viewer providing the genomic context of orthologs; (v) statically computed hierarchical orthologous groups subsets downloadable in OrthoXML format; and (vi) possibility to export parts of the all-against-all computations and to combine them with custom data for 'client-side' orthology prediction. OMA can be accessed through the OMA Browser and various programmatic interfaces at http://omabrowser.org. PMID:25399418

  14. Specific early number skills mediate the association between executive functioning skills and mathematics achievement.

    PubMed

    Fuhs, Mary Wagner; Hornburg, Caroline Byrd; McNeil, Nicole M

    2016-08-01

    A growing literature reports significant associations between children's executive functioning skills and their mathematics achievement. The purpose of this study was to examine if specific early number skills, such as quantity discrimination, number line estimation, number sets identification, fast counting, and number word comprehension, mediate this association. In 141 kindergarteners, cross-sectional analyses controlling for IQ revealed that number sets identification (but not the other early number skills) mediated the association between executive functioning skills and mathematics achievement. A longitudinal analysis showed that higher executive functioning skills predicted higher number sets identification in kindergarten, which in turn predicted growth in mathematics achievement from kindergarten to second grade. Results suggest that executive functioning skills may help children quickly and accurately identify number sets as wholes instead of getting distracted by the individual components of the sets, and this focus on sets, in turn, may help children learn more advanced mathematics concepts in the early elementary grades. (PsycINFO Database Record PMID:27337509

  15. Sensitivity and specificity of the functional hallux limitus test to predict foot function.

    PubMed

    Payne, Craig; Chuter, Vivienne; Miller, Kathryn

    2002-05-01

    Functional hallux limitus is an underrecognized entity that generally does not produce symptoms but can result in a variety of compensatory mechanisms that can produce symptoms. Clinically, hallux limitus can be determined by assessing the range of motion available at the first metatarsophalangeal joint while the first ray is prevented from plantarflexing. The aim of this study was to determine the sensitivity and specificity of this clinical test to predict abnormal excessive midtarsal joint function during gait. A total of 86 feet were examined for functional hallux limitus and abnormal pronation of the midtarsal joint during late midstance. The test had a sensitivity of 0.72 and a specificity of 0.66, suggesting that clinicians should consider functional hallux limitus when there is late midstance pronation of the midtarsal joint during gait. PMID:12015407

  16. Tests of executive functioning predict scores on the MacAndrew Alcoholism Scale.

    PubMed

    Deckel, A W

    1999-02-01

    1. Previous work reported that tests of executive functioning (EF) predict the risk of alcoholism in subject populations selected for a "high density" of a family history of alcoholism and/or the presence of sociopathic traits. The current experiment examined the ability of EF tests to predict the risk of alcoholism, as measured by the MacAndrew Alcoholism Scale (MAC), in outpatient subjects referred to a general neuropsychological testing service. 2. Sixty-eight male and female subjects referred for neuropsychological testing were assessed for their past drinking histories and administered the Wisconsin Card Sorting Test, the Wechsler Adult Intelligence Scale-Revised, the Trails (Part B) Test, and the MAC. Principal Components analysis (PCA) reduced the number of EF tests to two measures, including one that loaded on the WCST, and one that loaded on the Similarities, Picture Arrangement, and Trails tests. Multiple hierarchical regression first removed the variance from demographic variables, alcohol consumption, and verbal (i.e., Vocabulary) and non-verbal (i.e., Block Design) IQ, and then entered the executive functioning factors into the prediction of the MAC. 3. Seventy-six percent of the subjects were classified as either light, infrequent, or non-drinkers on the Quantity-Frequency-Variability scale. The factor derived from the WCST on PCA significantly added to the prediction of risk on the MAC (p = .0063), as did scores on Block Design (p = .033). Relatively more impaired scores on the WCST factor and Block Design were predictive of higher scores on the MAC. The other factors were not associated with MAC scores. 4. These results support the hypothesis that decrements in EF are associated with risk factors for alcoholism, even in populations where the density of alcoholic behaviors are not unusually high. When taken in conjunction with other findings, these results implicate EF test scores, and prefrontal brain functioning, in the neurobiology of the risk for

  17. Predicting performance on the Columbia Card Task: effects of personality characteristics, mood, and executive functions.

    PubMed

    Buelow, Melissa T

    2015-04-01

    Behavioral measures of risky decision making are frequently used by researchers and clinicians; however, most of these measures are strongly associated with personality characteristics and state mood. The present study sought to examine personality, mood, and executive function predictors of performance on a newer measure of decision making, the Columbia Card Task (CCT). Participants were 489 undergraduate students who completed either the hot or cold version of the CCT as well as measures of state mood, impulsive sensation seeking, behavioral inhibition and activation systems, and executive functions (Wisconsin Card Sort Task; Digit Span). Results indicated that performance on the CCT-cold was predicted by Wisconsin Card Sort Task errors, and Digit Span predicted the CCT-hot. In addition, significant correlations were found between the CCT information use variables and the predictor variables. Implications for the utility of the CCT as a clinical instrument and its relationship with other measures of decision making are discussed. PMID:24947984

  18. Neuro-oncological patients admitted in intensive-care unit: predictive factors and functional outcome.

    PubMed

    Tabouret, E; Boucard, C; Devillier, R; Barrie, M; Boussen, S; Autran, D; Chinot, O; Bruder, N

    2016-03-01

    The prognosis of oncology patients admitted to the intensive care unit (ICU) is considered poor. Our objective was to analyze the characteristics and predictive factors of death in the ICU and functional outcome following ICU treatment for neuro-oncology patients. A retrospective study was conducted on all patients with primary brain tumor admitted to our institutional ICU for medical indications. Predictive impact on the risk of death in the ICU was analyzed as well as the functional status was evaluated prior and following ICU discharge. Seventy-one patients were admitted to the ICU. ICU admission indications were refractory seizures (41 %) and septic shock (17 %). On admission, 16 % had multi-organ failure. Ventilation was necessary for 41 % and catecholamines for 13 %. Twenty-two percent of patients died in the ICU. By multivariate analysis, predictive factors associated with an increased risk of ICU death were: non-neurological cause of admission [p = 0.045; odds ratio (OR) 5.405], multiple organ failure (p = 0.021; OR 8.027), respiratory failure (p = 0.006; OR 9.615), and hemodynamic failure (p = 0.008; OR 10.111). In contrast, tumor type (p = 0.678) and disease control status (p = 0.380) were not associated with an increased risk of ICU death. Among the 35 evaluable patients, 77 % presented with a stable or improved Karnofsky performance status following ICU hospitalization compared with the ongoing status before discharge. In patients with primary brain tumor admitted to the ICU, predictive factors of death appear to be similar to those described in non-oncology patients. ICU hospitalization is generally not associated with a subsequent decrease in the functional status. PMID:26608523

  19. Striatal structure and function predict individual biases in learning to avoid pain

    PubMed Central

    Eldar, Eran; Hauser, Tobias U.; Dayan, Peter; Dolan, Raymond J.

    2016-01-01

    Pain is an elemental inducer of avoidance. Here, we demonstrate that people differ in how they learn to avoid pain, with some individuals refraining from actions that resulted in painful outcomes, whereas others favor actions that helped prevent pain. These individual biases were best explained by differences in learning from outcome prediction errors and were associated with distinct forms of striatal responses to painful outcomes. Specifically, striatal responses to pain were modulated in a manner consistent with an aversive prediction error in individuals who learned predominantly from pain, whereas in individuals who learned predominantly from success in preventing pain, modulation was consistent with an appetitive prediction error. In contrast, striatal responses to success in preventing pain were consistent with an appetitive prediction error in both groups. Furthermore, variation in striatal structure, encompassing the region where pain prediction errors were expressed, predicted participants’ predominant mode of learning, suggesting the observed learning biases may reflect stable individual traits. These results reveal functional and structural neural components underlying individual differences in avoidance learning, which may be important contributors to psychiatric disorders involving pathological harm avoidance behavior. PMID:27071092

  20. Shape invariance and laddering equations for the associated hypergeometric functions

    NASA Astrophysics Data System (ADS)

    Fakhri, H.; Chenaghlou, A.

    2004-03-01

    Introducing the associated hypergeometric functions in terms of two non-negative integers, we factorize their corresponding differential equation into a product of first-order differential operators by four different ways as shape invariance equations. These shape invariances are realized by four different types of raising and lowering operators. This procedure gives four different pairs of recursion relations on the associated hypergeometric functions.

  1. Systemic vascular function is associated with muscular power in adults

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Age-associated loss of muscular strength and muscular power are critical determinants of loss of physical function and progression to disability in older adults. In this study, we examined the association of systemic vascular function and measures of muscle strength and power in older adults. Measu...

  2. Prediction Error Associated with the Perceptual Segmentation of Naturalistic Events

    ERIC Educational Resources Information Center

    Zacks, Jeffrey M.; Kurby, Christopher A.; Eisenberg, Michelle L.; Haroutunian, Nayiri

    2011-01-01

    Predicting the near future is important for survival and plays a central role in theories of perception, language processing, and learning. Prediction failures may be particularly important for initiating the updating of perceptual and memory systems and, thus, for the subjective experience of events. Here, we asked observers to make predictions…

  3. Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

    PubMed

    Xu, Yonghui; Min, Huaqing; Song, Hengjie; Wu, Qingyao

    2016-08-01

    Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an appropriate MIML learning method for genome-wide protein function prediction, many studies in the literature attempted to optimize objective functions in which dissimilarity between instances is measured using the Euclidean distance. But in many real applications, Euclidean distance may be unable to capture the intrinsic similarity/dissimilarity in feature space and label space. Unlike other previous approaches, in this paper, we propose to learn a multi-instance multi-label distance metric learning framework (MIMLDML) for genome-wide protein function prediction. Specifically, we learn a Mahalanobis distance to preserve and utilize the intrinsic geometric information of both feature space and label space for MIML learning. In addition, we try to deal with the sparsely labeled data by giving weight to the labeled data. Extensive experiments on seven real-world organisms covering the biological three-domain system (i.e., archaea, bacteria, and eukaryote; Woese et al., 1990) show that the MIMLDML algorithm is superior to most state-of-the-art MIML learning algorithms. PMID:26923212

  4. Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

    PubMed Central

    van Zanten, Martijn

    2015-01-01

    Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation. PMID:26496492

  5. Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits.

    PubMed

    van Heerwaarden, Joost; van Zanten, Martijn; Kruijer, Willem

    2015-10-01

    Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation. PMID:26496492

  6. Radiomic Texture Analysis Mapping Predicts Areas of True Functional MRI Activity

    PubMed Central

    Hassan, Islam; Kotrotsou, Aikaterini; Bakhtiari, Ali Shojaee; Thomas, Ginu A.; Weinberg, Jeffrey S.; Kumar, Ashok J.; Sawaya, Raymond; Luedi, Markus M.; Zinn, Pascal O.; Colen, Rivka R.

    2016-01-01

    Individual analysis of functional Magnetic Resonance Imaging (fMRI) scans requires user-adjustment of the statistical threshold in order to maximize true functional activity and eliminate false positives. In this study, we propose a novel technique that uses radiomic texture analysis (TA) features associated with heterogeneity to predict areas of true functional activity. Scans of 15 right-handed healthy volunteers were analyzed using SPM8. The resulting functional maps were thresholded to optimize visualization of language areas, resulting in 116 regions of interests (ROIs). A board-certified neuroradiologist classified different ROIs into Expected (E) and Non-Expected (NE) based on their anatomical locations. TA was performed using the mean Echo-Planner Imaging (EPI) volume, and 20 rotation-invariant texture features were obtained for each ROI. Using forward stepwise logistic regression, we built a predictive model that discriminated between E and NE areas of functional activity, with a cross-validation AUC and success rate of 79.84% and 80.19% respectively (specificity/sensitivity of 78.34%/82.61%). This study found that radiomic TA of fMRI scans may allow for determination of areas of true functional activity, and thus eliminate clinician bias. PMID:27151623

  7. Motor function predicts parent-reported musculoskeletal pain in children with cerebral palsy

    PubMed Central

    Barney, Chantel C; Krach, Linda E; Rivard, Patrick F; Belew, John L; Symons, Frank J

    2013-01-01

    BACKGROUND: The relationship between pain and motor function is not well understood, especially for children and adolescents with communication and motor impairments associated with cerebral palsy (CP). OBJECTIVES: To determine whether a predictive relationship between motor function and musculoskeletal pain exists in children with CP. METHODS: Following informed consent, caregivers of 34 pediatric patients with CP (mean [± SD] age 9.37±4.49 years; 80.0% male) completed pain- and function-related measures. Parents completed the Dalhousie Pain Interview and the Brief Pain Inventory based on a one-week recall to determine whether pain had been experienced in the past week, its general description, possible cause, duration, frequency, intensity and interference with daily function. The Gross Motor Function Classification System (GMFCS) was used to classify the motor involvement of the child based on their functional ability and their need for assistive devices for mobility. RESULTS: GMFCS level significantly predicted parent-reported musculoskeletal pain frequency (P<0.02), duration (P=0.05) and intensity (P<0.01). Duration of pain was significantly related to interference with activities of daily living (P<0.05). CONCLUSIONS: Children with CP with greater motor involvement, as indexed by GMFCS level, may be at risk for increased pain (intensity, frequency and duration) that interfers with activities of daily living. The clinical index of suspicion should be raised accordingly when evaluating children with developmental disability who cannot self-report reliably. PMID:24308022

  8. Resting-state functional connectivity predicts impulsivity in economic decision-making.

    PubMed

    Li, Nan; Ma, Ning; Liu, Ying; He, Xiao-Song; Sun, De-Lin; Fu, Xian-Ming; Zhang, Xiaochu; Han, Shihui; Zhang, Da-Ren

    2013-03-13

    Increasing neuroimaging evidence suggests an association between impulsive decision-making behavior and task-related brain activity. However, the relationship between impulsivity in decision-making and resting-state brain activity remains unknown. To address this issue, we used functional MRI to record brain activity from human adults during a resting state and during a delay discounting task (DDT) that requires choosing between an immediate smaller reward and a larger delayed reward. In experiment I, we identified four DDT-related brain networks. The money network (the striatum, posterior cingulate cortex, etc.) and the time network (the medial and dorsolateral prefrontal cortices, etc.) were associated with the valuation process; the frontoparietal network and the dorsal anterior cingulate cortex-anterior insular cortex network were related to the choice process. Moreover, we found that the resting-state functional connectivity of the brain regions in these networks was significantly correlated with participants' discounting rate, a behavioral index of impulsivity during the DDT. In experiment II, we tested an independent group of subjects and demonstrated that this resting-state functional connectivity was able to predict individuals' discounting rates. Together, these findings suggest that resting-state functional organization of the human brain may be a biomarker of impulsivity and can predict economic decision-making behavior. PMID:23486959

  9. Functional identity and diversity of animals predict ecosystem functioning better than species-based indices

    PubMed Central

    Gagic, Vesna; Bartomeus, Ignasi; Jonsson, Tomas; Taylor, Astrid; Winqvist, Camilla; Fischer, Christina; Slade, Eleanor M.; Steffan-Dewenter, Ingolf; Emmerson, Mark; Potts, Simon G.; Tscharntke, Teja; Weisser, Wolfgang; Bommarco, Riccardo

    2015-01-01

    Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se. PMID:25567651

  10. A density functional theory for colloids with two multiple bonding associating sites

    NASA Astrophysics Data System (ADS)

    Haghmoradi, Amin; Wang, Le; Chapman, Walter G.

    2016-06-01

    Wertheim’s multi-density formalism is extended for patchy colloidal fluids with two multiple bonding patches. The theory is developed as a density functional theory to predict the properties of an associating inhomogeneous fluid. The equation of state developed for this fluid depends on the size of the patch, and includes formation of cyclic, branched and linear clusters of associated species. The theory predicts the density profile and the fractions of colloids in different bonding states versus the distance from one wall as a function of bulk density and temperature. The predictions from our theory are compared with previous results for a confined fluid with four single bonding association sites. Also, comparison between the present theory and Monte Carlo simulation indicates a good agreement.

  11. A density functional theory for colloids with two multiple bonding associating sites.

    PubMed

    Haghmoradi, Amin; Wang, Le; Chapman, Walter G

    2016-06-22

    Wertheim's multi-density formalism is extended for patchy colloidal fluids with two multiple bonding patches. The theory is developed as a density functional theory to predict the properties of an associating inhomogeneous fluid. The equation of state developed for this fluid depends on the size of the patch, and includes formation of cyclic, branched and linear clusters of associated species. The theory predicts the density profile and the fractions of colloids in different bonding states versus the distance from one wall as a function of bulk density and temperature. The predictions from our theory are compared with previous results for a confined fluid with four single bonding association sites. Also, comparison between the present theory and Monte Carlo simulation indicates a good agreement. PMID:27115237

  12. NTSMDA: prediction of miRNA-disease associations by integrating network topological similarity.

    PubMed

    Sun, Dongdong; Li, Ao; Feng, Huanqing; Wang, Minghui

    2016-06-21

    Recently, accumulating studies have indicated that microRNAs (miRNAs) play an important role in exploring the pathogenesis of various human diseases at the molecular level and may result in the design of specific tools for diagnosis, treatment evaluation and prevention. Experimental identification of disease-related miRNAs is time-consuming and labour-intensive. Hence, there is a stressing need to propose efficient computational methods to detect more potential miRNA-disease associations. Currently, several computational approaches for identifying disease-related miRNAs on the miRNA-disease network have gained much attention by means of integrating miRNA functional similarities and disease semantic similarities. However, these methods rarely consider the network topological similarity of the miRNA-disease association network. Here, in this paper we develop an improved computational method named NTSMDA that is based on known miRNA-disease network topological similarity to exploit more potential disease-related miRNAs. We achieve an AUC of 89.4% by using the leave-one-out cross-validation experiment, demonstrating the excellent predictive performance of NTSMDA. Furthermore, predicted highly ranked miRNA-disease associations of breast neoplasms, lung neoplasms and prostatic neoplasms are manually confirmed by different related databases and literature, providing evidence for the good performance and potential value of the NTSMDA method in inferring miRNA-disease associations. The R code and readme file of NTSMDA can be downloaded from . PMID:27153230

  13. Prediction of Membership in Rehabilitation Counseling Professional Associations

    ERIC Educational Resources Information Center

    Phillips, Brian N.; Leahy, Michael J.

    2012-01-01

    Declining membership is a concerning yet poorly understood issue affecting professional associations across disciplines (Bauman, 2008). Rehabilitation counseling association membership is in decline even while number of certified rehabilitation counselors continues to increase (Leahy, 2009). Factors influencing rehabilitation counseling…

  14. An integrative approach to predicting the functional effects of non-coding and coding sequence variation

    PubMed Central

    Shihab, Hashem A.; Rogers, Mark F.; Gough, Julian; Mort, Matthew; Cooper, David N.; Day, Ian N. M.; Gaunt, Tom R.; Campbell, Colin

    2015-01-01

    Motivation: Technological advances have enabled the identification of an increasingly large spectrum of single nucleotide variants within the human genome, many of which may be associated with monogenic disease or complex traits. Here, we propose an integrative approach, named FATHMM-MKL, to predict the functional consequences of both coding and non-coding sequence variants. Our method utilizes various genomic annotations, which have recently become available, and learns to weight the significance of each component annotation source. Results: We show that our method outperforms current state-of-the-art algorithms, CADD and GWAVA, when predicting the functional consequences of non-coding variants. In addition, FATHMM-MKL is comparable to the best of these algorithms when predicting the impact of coding variants. The method includes a confidence measure to rank order predictions. Availability and implementation: The FATHMM-MKL webserver is available at: http://fathmm.biocompute.org.uk Contact: H.Shihab@bristol.ac.uk or Mark.Rogers@bristol.ac.uk or C.Campbell@bristol.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25583119

  15. Exercise Ventilatory Inefficiency Adds to Lung Function in Predicting Mortality in COPD.

    PubMed

    Neder, J Alberto; Alharbi, Abdullah; Berton, Danilo C; Alencar, Maria Clara N; Arbex, Flavio F; Hirai, Daniel M; Webb, Katherine A; O'Donnell, Denis E

    2016-08-01

    Severity of resting functional impairment only partially predicts the increased risk of death in chronic obstructive pulmonary disease (COPD). Increased ventilation during exercise is associated with markers of disease progression and poor prognosis, including emphysema extension and pulmonary vascular impairment. Whether excess exercise ventilation would add to resting lung function in predicting mortality in COPD, however, is currently unknown. After an incremental cardiopulmonary exercise test, 288 patients (forced expiratory volume in one second ranging from 18% to 148% predicted) were followed for a median (interquartile range) of 57 (47) months. Increases in the lowest (nadir) ventilation to CO2 output (VCO2) ratio determined excess exercise ventilation. Seventy-seven patients (26.7%) died during follow-up: 30/77 (38.9%) deaths were due to respiratory causes. Deceased patients were older, leaner, had a greater co-morbidity burden (Charlson Index) and reported more daily life dyspnea. Moreover, they had poorer lung function and exercise tolerance (p < 0.05). A logistic regression analysis revealed that ventilation/VCO2 nadir was the only exercise variable that added to age, body mass index, Charlson Index and resting inspiratory capacity (IC)/total lung capacity (TLC) ratio to predict all-cause and respiratory mortality (p < 0.001). Kaplan-Meier analyses showed that survival time was particularly reduced when ventilation/VCO2 nadir > 34 was associated with IC/TLC ≤ 0.34 or IC/TLC ≤ 0.31 for all-cause and respiratory mortality, respectively (p < 0.001). Excess exercise ventilation is an independent prognostic marker across the spectrum of COPD severity. Physiological abnormalities beyond traditional airway dysfunction and lung mechanics are relevant in determining the course of the disease. PMID:27077955

  16. Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

    PubMed

    Choi, Ickwon; Chung, Amy W; Suscovich, Todd J; Rerks-Ngarm, Supachai; Pitisuttithum, Punnee; Nitayaphan, Sorachai; Kaewkungwal, Jaranit; O'Connell, Robert J; Francis, Donald; Robb, Merlin L; Michael, Nelson L; Kim, Jerome H; Alter, Galit; Ackerman, Margaret E; Bailey-Kellogg, Chris

    2015-04-01

    The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates. PMID:25874406

  17. CARDIO-PRED: an in silico tool for predicting cardiovascular-disorder associated proteins.

    PubMed

    Jain, Prerna; Thukral, Nitin; Gahlot, Lokesh Kumar; Hasija, Yasha

    2015-06-01

    Interactions between proteins largely govern cellular processes and this has led to numerous efforts culminating in enormous information related to the proteins, their interactions and the function which is determined by their interactions. The main concern of the present study is to present interface analysis of cardiovascular-disorder (CVD) related proteins to shed lights on details of interactions and to emphasize the importance of using structures in network studies. This study combines the network-centred approach with three dimensional studies to comprehend the fundamentals of biology. Interface properties were used as descriptors to classify the CVD associated proteins and non-CVD associated proteins. Machine learning algorithm was used to generate a classifier based on the training set which was then used to predict potential CVD related proteins from a set of polymorphic proteins which are not known to be involved in any disease. Among several classifying algorithms applied to generate models, best performance was achieved using Random Forest with an accuracy of 69.5 %. The tool named CARDIO-PRED, based on the prediction model is present at http://www.genomeinformatics.dce.edu/CARDIO-PRED/. The predicted CVD related proteins may not be the causing factor of particular disease but can be involved in pathways and reactions yet unknown to us thus permitting a more rational analysis of disease mechanism. Study of their interactions with other proteins can significantly improve our understanding of the molecular mechanism of diseases. PMID:25972989

  18. Predicting invasive species impacts: a community module functional response approach reveals context dependencies.

    PubMed

    Paterson, Rachel A; Dick, Jaimie T A; Pritchard, Daniel W; Ennis, Marilyn; Hatcher, Melanie J; Dunn, Alison M

    2015-03-01

    Predatory functional responses play integral roles in predator-prey dynamics, and their assessment promises greater understanding and prediction of the predatory impacts of invasive species. Other interspecific interactions, however, such as parasitism and higher-order predation, have the potential to modify predator-prey interactions and thus the predictive capability of the comparative functional response approach. We used a four-species community module (higher-order predator; focal native or invasive predators; parasites of focal predators; native prey) to compare the predatory functional responses of native Gammarus duebeni celticus and invasive Gammarus pulex amphipods towards three invertebrate prey species (Asellus aquaticus, Simulium spp., Baetis rhodani), thus, quantifying the context dependencies of parasitism and a higher-order fish predator on these functional responses. Our functional response experiments demonstrated that the invasive amphipod had a higher predatory impact (lower handling time) on two of three prey species, which reflects patterns of impact observed in the field. The community module also revealed that parasitism had context-dependent influences, for one prey species, with the potential to further reduce the predatory impact of the invasive amphipod or increase the predatory impact of the native amphipod in the presence of a higher-order fish predator. Partial consumption of prey was similar for both predators and occurred increasingly in the order A. aquaticus, Simulium spp. and B. rhodani. This was associated with increasing prey densities, but showed no context dependencies with parasitism or higher-order fish predator. This study supports the applicability of comparative functional responses as a tool to predict and assess invasive species impacts incorporating multiple context dependencies. PMID:25265905

  19. Predicting invasive species impacts: a community module functional response approach reveals context dependencies

    PubMed Central

    Paterson, Rachel A; Dick, Jaimie T A; Pritchard, Daniel W; Ennis, Marilyn; Hatcher, Melanie J; Dunn, Alison M

    2015-01-01

    Summary Predatory functional responses play integral roles in predator–prey dynamics, and their assessment promises greater understanding and prediction of the predatory impacts of invasive species. Other interspecific interactions, however, such as parasitism and higher-order predation, have the potential to modify predator–prey interactions and thus the predictive capability of the comparative functional response approach. We used a four-species community module (higher-order predator; focal native or invasive predators; parasites of focal predators; native prey) to compare the predatory functional responses of native Gammarus duebeni celticus and invasive Gammarus pulex amphipods towards three invertebrate prey species (Asellus aquaticus, Simulium spp., Baetis rhodani), thus, quantifying the context dependencies of parasitism and a higher-order fish predator on these functional responses. Our functional response experiments demonstrated that the invasive amphipod had a higher predatory impact (lower handling time) on two of three prey species, which reflects patterns of impact observed in the field. The community module also revealed that parasitism had context-dependent influences, for one prey species, with the potential to further reduce the predatory impact of the invasive amphipod or increase the predatory impact of the native amphipod in the presence of a higher-order fish predator. Partial consumption of prey was similar for both predators and occurred increasingly in the order A. aquaticus, Simulium spp. and B. rhodani. This was associated with increasing prey densities, but showed no context dependencies with parasitism or higher-order fish predator. This study supports the applicability of comparative functional responses as a tool to predict and assess invasive species impacts incorporating multiple context dependencies. PMID:25265905

  20. Reduced Cognitive Function Predicts Functional Decline in Patients with Heart Failure over 12 months

    PubMed Central

    Alosco, Michael L.; Spitznagel, Mary Beth; Cohen, Ronald; Sweet, Lawrence H.; Colbert, Lisa H.; Josephson, Richard; Hughes, Joel; Rosneck, Jim; Gunstad, John

    2016-01-01

    Background Impaired activities of daily living (ADL) are common in heart failure (HF) patients and contribute to the elevated mortality and hospitalization rates in this population. Cognitive impairment is also prevalent in HF, though its ability to predict functional decline over time is unknown. Aims This study examined the longitudinal pattern of activities of daily living in HF persons and whether reduced baseline cognitive status predicts functional decline in this population. Methods 110 persons with HF completed the Lawton-Brody Activities of Daily Living Scale and were administered the Modified Mini-Mental Status Examination (3MS) at baseline and a 12-month follow-up. Three composite scores were derived from the Lawton-Brody, including total, instrumental, and basic ADLs. Results HF patients reported high rates of baseline impairments in instrumental ADLs, including shopping, food preparation, housekeeping duties, laundry, among others. Repeated measures analyses showed significant declines in total and instrumental ADLs from baseline to the 12-month follow-up in HF (p < .05). Hierarchical regression analyses showed that poorer baseline performance on the 3MS predicted worse total ADL performance at 12-months (β = .15, p = .049), including greater dependence in shopping, driving, feeding, and physical ambulation (p < .05 for all). Conclusion The current results show that HF patients report significant functional decline over a 12-month period and brief cognitive tests can identify those patients at highest risk for decline. If replicated, such findings encourage the use of cognitive screening measures to identify HF patients most likely to require assistance with ADL tasks. PMID:23754840

  1. Gene Co-Expression Analysis Predicts Genetic Variants Associated with Drug Responsiveness in Lung Cancer

    PubMed Central

    Shroff, Sanaya; Zhang, Jie; Huang, Kun

    2016-01-01

    Responsiveness to drugs is an important concern in designing personalized treatment for cancer patients. Currently genetic markers are often used to guide targeted therapy. However, deeper understanding of the molecular basis for drug responses and discovery of new predictive biomarkers for drug sensitivity are much needed. In this paper, we present a workflow for identifying condition-specific gene co-expression networks associated with responses to the tyrosine kinase inhibitor, Erlotinib, in lung adenocarcinoma cell lines using data from the Cancer Cell Line Encyclopedia by combining network mining and statistical analysis. Particularly, we have identified multiple gene modules specifically co-expressed in the drug responsive cell lines but not in the unresponsive group. Interestingly, most of these modules are enriched on specific cytobands, suggesting potential copy number variation events on these loci. Our results therefore imply that there are multiple genetic loci with copy number variations associated with the Erlotinib responses. The existence of CNVs in these loci is also confirmed in lung cancer tissue samples using the TCGA data. Since these structural variations are inferred from functional genomics data, these CNVs are functional variations. These results suggest the condition specific gene co- expression network mining approach is an effective approach in predicting candidate biomarkers for drug responses. PMID:27570645

  2. Gene Co-Expression Analysis Predicts Genetic Variants Associated with Drug Responsiveness in Lung Cancer.

    PubMed

    Shroff, Sanaya; Zhang, Jie; Huang, Kun

    2016-01-01

    Responsiveness to drugs is an important concern in designing personalized treatment for cancer patients. Currently genetic markers are often used to guide targeted therapy. However, deeper understanding of the molecular basis for drug responses and discovery of new predictive biomarkers for drug sensitivity are much needed. In this paper, we present a workflow for identifying condition-specific gene co-expression networks associated with responses to the tyrosine kinase inhibitor, Erlotinib, in lung adenocarcinoma cell lines using data from the Cancer Cell Line Encyclopedia by combining network mining and statistical analysis. Particularly, we have identified multiple gene modules specifically co-expressed in the drug responsive cell lines but not in the unresponsive group. Interestingly, most of these modules are enriched on specific cytobands, suggesting potential copy number variation events on these loci. Our results therefore imply that there are multiple genetic loci with copy number variations associated with the Erlotinib responses. The existence of CNVs in these loci is also confirmed in lung cancer tissue samples using the TCGA data. Since these structural variations are inferred from functional genomics data, these CNVs are functional variations. These results suggest the condition specific gene co- expression network mining approach is an effective approach in predicting candidate biomarkers for drug responses. PMID:27570645

  3. Genome wide prediction of protein function via a generic knowledge discovery approach based on evidence integration

    PubMed Central

    Xiong, Jianghui; Rayner, Simon; Luo, Kunyi; Li, Yinghui; Chen, Shanguang

    2006-01-01

    Background The automation of many common molecular biology techniques has resulted in the accumulation of vast quantities of experimental data. One of the major challenges now facing researchers is how to process this data to yield useful information about a biological system (e.g. knowledge of genes and their products, and the biological roles of proteins, their molecular functions, localizations and interaction networks). We present a technique called Global Mapping of Unknown Proteins (GMUP) which uses the Gene Ontology Index to relate diverse sources of experimental data by creation of an abstraction layer of evidence data. This abstraction layer is used as input to a neural network which, once trained, can be used to predict function from the evidence data of unannotated proteins. The method allows us to include almost any experimental data set related to protein function, which incorporates the Gene Ontology, to our evidence data in order to seek relationships between the different sets. Results We have demonstrated the capabilities of this method in two ways. We first collected various experimental datasets associated with yeast (Saccharomyces cerevisiae) and applied the technique to a set of previously annotated open reading frames (ORFs). These ORFs were divided into training and test sets and were used to examine the accuracy of the predictions made by our method. Then we applied GMUP to previously un-annotated ORFs and made 1980, 836 and 1969 predictions corresponding to the GO Biological Process, Molecular Function and Cellular Component sub-categories respectively. We found that GMUP was particularly successful at predicting ORFs with functions associated with the ribonucleoprotein complex, protein metabolism and transportation. Conclusion This study presents a global and generic gene knowledge discovery approach based on evidence integration of various genome-scale data. It can be used to provide insight as to how certain biological processes are

  4. Individual differences in common factors of emotional traits and executive functions predict functional connectivity of the amygdala.

    PubMed

    Rohr, C S; Dreyer, F R; Aderka, I M; Margulies, D S; Frisch, S; Villringer, A; Okon-Singer, H

    2015-10-15

    Evidence suggests that individual differences in emotion control are associated with frontoparietal-limbic networks and linked to emotional traits and executive functions. In a first attempt to directly target the link between emotional traits and executive functions using resting-state fMRI analysis, 43 healthy adults completed a test battery including executive tasks and emotional trait self-assessments that were subjected to a principal component analysis. Of the three factors detected, two explained 40.4% of the variance and were further investigated. Both factors suggest a relation between emotional traits and executive functions. Specifically, the first factor consisted of measures related to inhibitory control and negative affect, and the second factor was related to reward and positive affect. To investigate whether this interplay between emotional traits and executive functions is reflected in neural connectivity, we used resting-state fMRI to explore the functional connectivity of the amygdala as a starting point, and progressed to other seed-based analyses based on the initial findings. We found that the first factor predicted the strength of connectivity between brain regions known to be involved in the cognitive control of emotion, including the amygdala and the dorsolateral prefrontal cortex, whereas the second factor predicted the strength of connectivity between brain regions known to be involved in reward and attention, including the amygdala, the caudate and the thalamus. These findings suggest that individual differences in the ability to inhibit negative affect are mediated by prefrontal-limbic pathways, while the ability to be positive and use rewarding information is mediated by a network that includes the amygdala and thalamostriatal regions. PMID:26108101

  5. Prediction of functional sites in proteins using conserved functional group analysis.

    PubMed

    Innis, C Axel; Anand, A Prem; Sowdhamini, R

    2004-04-01

    A detailed knowledge of a protein's functional site is an absolute prerequisite for understanding its mode of action at the molecular level. However, the rapid pace at which sequence and structural information is being accumulated for proteins greatly exceeds our ability to determine their biochemical roles experimentally. As a result, computational methods are required which allow for the efficient processing of the evolutionary information contained in this wealth of data, in particular that related to the nature and location of functionally important sites and residues. The method presented here, referred to as conserved functional group (CFG) analysis, relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. We show that CFG analysis can fully or partially predict the location of functional sites in approximately 96% of the 470 cases tested and that, unlike other methods available, it is able to tolerate wide variations in sequence identity. In addition, we discuss its potential in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function. This is exemplified by our analysis of the hypothetical protein Ydde_Ecoli, whose structure was recently solved by members of the North East Structural Genomics consortium. Although the proposed active site for this protein needs to be validated experimentally, this example illustrates the scope of CFG analysis as a general tool for the identification of residues likely to play an important role in a protein's biochemical function. Thus, our method offers a convenient solution to rapidly and automatically process the vast amounts of data that are beginning to emerge from structural genomics projects. PMID:15033369

  6. Physical activity and obesity mediate the association between childhood motor function and adolescents' academic achievement.

    PubMed

    Kantomaa, Marko T; Stamatakis, Emmanuel; Kankaanpää, Anna; Kaakinen, Marika; Rodriguez, Alina; Taanila, Anja; Ahonen, Timo; Järvelin, Marjo-Riitta; Tammelin, Tuija

    2013-01-29

    The global epidemic of obesity and physical inactivity may have detrimental implications for young people's cognitive function and academic achievement. This prospective study investigated whether childhood motor function predicts later academic achievement via physical activity, fitness, and obesity. The study sample included 8,061 children from the Northern Finland Birth Cohort 1986, which contains data about parent-reported motor function at age 8 y and self-reported physical activity, predicted cardiorespiratory fitness (cycle ergometer test), obesity (body weight and height), and academic achievement (grades) at age 16 y. Structural equation models with unstandardized (B) and standardized (β) coefficients were used to test whether, and to what extent, physical activity, cardiorespiratory fitness, and obesity at age 16 mediated the association between childhood motor function and adolescents' academic achievement. Physical activity was associated with a higher grade-point average, and obesity was associated with a lower grade-point average in adolescence. Furthermore, compromised motor function in childhood had a negative indirect effect on adolescents' academic achievement via physical inactivity (B = -0.023, 95% confidence interval = -0.031, -0.015) and obesity (B = -0.025, 95% confidence interval = -0.039, -0.011), but not via cardiorespiratory fitness. These results suggest that physical activity and obesity may mediate the association between childhood motor function and adolescents' academic achievement. Compromised motor function in childhood may represent an important factor driving the effects of obesity and physical inactivity on academic underachievement. PMID:23277558

  7. Predicted energies and structures associated with the mixed calcium strontium fluorapatites

    SciTech Connect

    Michie, Emily M.; Grimes, Robin W. Fong, Shirley K.; Metcalfe, Brian L.

    2008-12-15

    Atomic scale local density functional simulations and configurational averaging are used to predict the energies and lattice parameters associated with mixed calcium/strontium fluorapatites, Ca{sub x}Sr{sub 10-x}(PO{sub 4}){sub 6}F{sub 2}. In particular, the partition of Sr{sup 2+} and Ca{sup 2+} ions between the 6h and 4f cation sites is established across the entire compositional range. Lattice parameters and lattice volume are also analyzed as a function of Ca{sup 2+} to Sr{sup 2+} concentration and their cation site distribution. The predicted internal energy of mixing between the end members is used to discuss the available experimental data. - Graphical abstract: Quantum mechanical simulations rationalize the distribution of strontium and calcium over 6h and 4f cation sites in fluorapatite across the entire Ca{sub x}Sr{sub 10-x}(PO{sub 4}){sub 6}F{sub 2} solid solution. Lattice parameters and lattice volume are also analyzed as a function of Ca{sup 2+} and Sr{sup 2+} cation site distribution and concentration.

  8. 21 CFR 868.1890 - Predictive pulmonary-function value calculator.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Predictive pulmonary-function value calculator. 868.1890 Section 868.1890 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN... pulmonary-function value calculator. (a) Identification. A predictive pulmonary-function value calculator...

  9. firestar--advances in the prediction of functionally important residues.

    PubMed

    Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L

    2011-07-01

    firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php. PMID:21672959

  10. Improved association in a classical density functional theory for water.

    PubMed

    Krebs, Eric J; Schulte, Jeff B; Roundy, David

    2014-03-28

    We present a modification to our recently published statistical associating fluid theory-based classical density functional theory for water. We have recently developed and tested a functional for the averaged radial distribution function at contact of the hard-sphere fluid that is dramatically more accurate at interfaces than earlier approximations. We now incorporate this improved functional into the association term of our free energy functional for water, improving its description of hydrogen bonding. We examine the effect of this improvement by studying two hard solutes (a hard hydrophobic rod and a hard sphere) and a Lennard-Jones approximation of a krypton atom solute. The improved functional leads to a moderate change in the density profile and a large decrease in the number of hydrogen bonds broken in the vicinity of the hard solutes. We find an improvement of the partial radial distribution for a krypton atom in water when compared with experiment. PMID:24697459

  11. Improved association in a classical density functional theory for water

    SciTech Connect

    Krebs, Eric J.; Schulte, Jeff B.; Roundy, David

    2014-03-28

    We present a modification to our recently published statistical associating fluid theory-based classical density functional theory for water. We have recently developed and tested a functional for the averaged radial distribution function at contact of the hard-sphere fluid that is dramatically more accurate at interfaces than earlier approximations. We now incorporate this improved functional into the association term of our free energy functional for water, improving its description of hydrogen bonding. We examine the effect of this improvement by studying two hard solutes (a hard hydrophobic rod and a hard sphere) and a Lennard-Jones approximation of a krypton atom solute. The improved functional leads to a moderate change in the density profile and a large decrease in the number of hydrogen bonds broken in the vicinity of the hard solutes. We find an improvement of the partial radial distribution for a krypton atom in water when compared with experiment.

  12. Pretransplant thymic function predicts acute rejection in antithymocyte globulin-treated renal transplant recipients.

    PubMed

    Bamoulid, Jamal; Courivaud, Cécile; Crepin, Thomas; Carron, Clémence; Gaiffe, Emilie; Roubiou, Caroline; Laheurte, Caroline; Moulin, Bruno; Frimat, Luc; Rieu, Philippe; Mousson, Christiane; Durrbach, Antoine; Heng, Anne-Elisabeth; Rebibou, Jean-Michel; Saas, Philippe; Ducloux, Didier

    2016-05-01

    Lack of clear identification of patients at high risk of acute rejection hampers the ability to individualize immunosuppressive therapy. Here we studied whether thymic function may predict acute rejection in antithymocyte globulin (ATG)-treated renal transplant recipients in 482 patients prospectively studied during the first year post-transplant of which 86 patients experienced acute rejection. Only CD45RA(+)CD31(+)CD4(+) T cell (recent thymic emigrant [RTE]) frequency (RTE%) was marginally associated with acute rejection in the whole population. This T-cell subset accounts for 26% of CD4(+) T cells. Pretransplant RTE% was significantly associated with acute rejection in ATG-treated patients (hazard ratio, 1.04; 95% confidence interval, 1.01-1.08) for each increased percent in RTE/CD4(+) T cells), but not in anti-CD25 monoclonal (αCD25 mAb)-treated patients. Acute rejection was significantly more frequent in ATG-treated patients with high pretransplant RTE% (31.2% vs. 16.4%) or absolute number of RTE/mm(3) (31.7 vs. 16.1). This difference was not found in αCD25 monclonal antibody-treated patients. Highest values of both RTE% (>31%, hazard ratio, 2.50; 95% confidence interval, 1.09-5.74) and RTE/mm(3) (>200/mm(3), hazard ratio, 3.71; 95% confidence interval, 1.59-8.70) were predictive of acute rejection in ATG-treated patients but not in patients having received αCD25 monoclonal antibody). Results were confirmed in a retrospective cohort using T-cell receptor excision circle levels as a marker of thymic function. Thus, pretransplant thymic function predicts acute rejection in ATG-treated patients. PMID:27083287

  13. Survival in rectal cancer is predicted by T cell infiltration of tumour-associated lymphoid nodules

    PubMed Central

    McMullen, T P W; Lai, R; Dabbagh, L; Wallace, T M; de Gara, C J

    2010-01-01

    Lymphoid nodules are a normal component of the mucosa of the rectum, but little is known about their function and whether they contribute to the host immune response in malignancy. In rectal cancer specimens from patients with local (n = 18), regional (n = 12) and distant (n = 10) disease, we quantified T cell (CD3, CD25) and dendritic cell (CD1a, CD83) levels at the tumour margin as well as within tumour-associated lymphoid nodules. In normal tissue CD3+, but not CD25+, T cells are concentrated at high levels within lymphoid nodules, with significantly fewer cells found in surrounding normal mucosa (P = 0·001). Mature (CD83), but not immature (CD1a), dendritic cells in normal tissue are also found clustered almost exclusively within lymphoid nodules (P = < 0·0001). In rectal tumours, both CD3+ T cells (P = 0·004) and CD83+ dendritic cells (P = 0·0001) are also localized preferentially within tumour-associated lymphoid nodules. However, when comparing tumour specimens to normal rectal tissue, the average density of CD3+ T cells (P = 0·0005) and CD83+ dendritic cells (P = 0·0006) in tumour-associated lymphoid nodules was significantly less than that seen in lymphoid nodules in normal mucosa. Interestingly, regardless of where quantified, T cell and dendritic cell levels did not depend upon the stage of disease. Increased CD3+ T cell infiltration of tumour-associated lymphoid nodules predicted improved survival, independent of stage (P = 0·05). Other T cell (CD25) markers and different levels of CD1a+ or CD83+ dendritic cells did not predict survival. Tumour-associated lymphoid nodules, enriched in dendritic cells and T cells, may be an important site for antigen presentation and increased T cell infiltration may be a marker for improved survival. PMID:20408858

  14. Intrapersonal and interpersonal functions of non suicidal self-injury: associations with emotional and social functioning.

    PubMed

    Turner, Brianna J; Chapman, Alexander L; Layden, Brianne K

    2012-02-01

    Understanding the functions of nonsuicidal self-injury (NSSI) has important implications for the development and refinement of theoretical models and treatments of NSSI. Emotional and social vulnerabilities associated with five common functions of NSSI-emotion relief (ER), feeling generation (FG), self-punishment (SP), interpersonal influence (II), and interpersonal communication (IC)-were investigated to clarify why individuals use this behavior in the service of different purposes. Female participants (n = 162) with a history of NSSI completed online measures of self-injury, emotion regulation strategies and abilities, trait affectivity, social problem-solving styles, and interpersonal problems. ER functions were associated with more intense affectivity, expressive suppression, and limited access to emotion regulation strategies. FG functions were associated with a lack of emotional clarity. Similar to ER functions, SP functions were associated with greater affective intensity and expressive suppression. II functions were negatively associated with expressive suppression and positively associated with domineering/controlling and intrusive/needy interpersonal styles. IC functions were negatively associated with expressive suppression and positively associated with a vindictive or self-centered interpersonal style. These findings highlight the specific affective traits, emotional and social skill deficits, and interpersonal styles that may render a person more likely to engage in NSSI to achieve specific goals. PMID:22276747

  15. The inhomogeneous distribution of liver function: possible impact on the prediction of post-operative remnant liver function

    PubMed Central

    Nilsson, Henrik; Karlgren, Silja; Blomqvist, Lennart; Jonas, Eduard

    2015-01-01

    Background Previous studies have shown that liver function is inhomogeneously distributed in diseased livers, and this uneven distribution cannot be compensated for if a global liver function test is used for the prediction of post-operative remnant liver function. Dynamic Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) can assess segmental liver function, thus offering the possibility to overcome this problem. Methods In 10 patients with liver cirrhosis and 10 normal volunteers, the contribution of individual liver segments to total liver function and volume was calculated using dynamic Gd-EOB-DTPA-enhanced MRI. Remnant liver function predictions using a segmental method and global assessment were compared for a simulated left hemihepatectomy. For the prediction based on segmental functional MRI assessment, the estimated function of the remnant liver segments was added. Results Global liver function assessment overestimated the remnant liver function in 9 out of 10 patients by as much as 9.3% [median −3.5% (−9.3–3.5%)]. In the normal volunteers there was a slight underestimation of remnant function in 9 out of 10 cases [median 1.07% (−0.7–2.5%)]. Discussion The present study underlines the necessity of a segmental liver function test able to compensate for the non-homogeneous nature of liver function, if the prediction of post-operative remnant liver function is to be improved. PMID:25297934

  16. Predicting brain states associated with object categories from fMRI data.

    PubMed

    Behroozi, Mehdi; Daliri, Mohammad Reza

    2014-12-01

    Recently, the multivariate analysis methods have been widely used for predicting the human cognitive states from fMRI data. Here, we explore the possibility of predicting the human cognitive states using a pattern of brain activities associated with thinking about concrete objects. The fMRI signals in conjunction with pattern recognition methods were used for the analysis of cognitive functions associated with viewing of 60 object pictures named by the words in 12 categories. The important step in Multi Voxel Pattern Analysis (MVPA) is feature extraction and feature selection parts. In this study, the new feature selection method (accuracy method) was developed for multi-class fMRI dataset to select the informative voxels corresponding to the objects category from the whole brain voxels. Here the result of three multivariate classifiers namely, Naïve Bayes, K-nearest neighbor and support vector machine, were compared for predicting the category of presented objects from activation BOLD patterns in human whole brain. We investigated whether the multivariate classifiers are capable to find the associated regions of the brain with the visual presentation of categories of various objects. Overall Naïve Bayes classifier perfumed best and it was the best method for extracting features from the whole brain data. In addition, the results of this study indicate that thinking about different semantic categories of objects have an effect on different spatial patterns of neural activation, and so it is possible to identify the category of the objects based on the patterns of neural activation recorded during representation of object line drawing from participants with high accuracy. Finally we demonstrated that the selected brain regions that were informative for object categorization were similar across subjects and this distribution of selected voxels on the cortex may neutrally represent the various object's category properties. PMID:25352153

  17. Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

    PubMed Central

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome. PMID:23971032

  18. Cloud prediction of protein structure and function with PredictProtein for Debian.

    PubMed

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome. PMID:23971032

  19. Prediction of gene–phenotype associations in humans, mice, and plants using phenologs

    PubMed Central

    2013-01-01

    Background Phenotypes and diseases may be related to seemingly dissimilar phenotypes in other species by means of the orthology of underlying genes. Such “orthologous phenotypes,” or “phenologs,” are examples of deep homology, and may be used to predict additional candidate disease genes. Results In this work, we develop an unsupervised algorithm for ranking phenolog-based candidate disease genes through the integration of predictions from the k nearest neighbor phenologs, comparing classifiers and weighting functions by cross-validation. We also improve upon the original method by extending the theory to paralogous phenotypes. Our algorithm makes use of additional phenotype data — from chicken, zebrafish, and E. coli, as well as new datasets for C. elegans — establishing that several types of annotations may be treated as phenotypes. We demonstrate the use of our algorithm to predict novel candidate genes for human atrial fibrillation (such as HRH2, ATP4A, ATP4B, and HOPX) and epilepsy (e.g., PAX6 and NKX2-1). We suggest gene candidates for pharmacologically-induced seizures in mouse, solely based on orthologous phenotypes from E. coli. We also explore the prediction of plant gene–phenotype associations, as for the Arabidopsis response to vernalization phenotype. Conclusions We are able to rank gene predictions for a significant portion of the diseases in the Online Mendelian Inheritance in Man database. Additionally, our method suggests candidate genes for mammalian seizures based only on bacterial phenotypes and gene orthology. We demonstrate that phenotype information may come from diverse sources, including drug sensitivities, gene ontology biological processes, and in situ hybridization annotations. Finally, we offer testable candidates for a variety of human diseases, plant traits, and other classes of phenotypes across a wide array of species. PMID:23800157

  20. Genome-environment associations in sorghum landraces predict adaptive traits

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these ...

  1. PINALOG: a novel approach to align protein interaction networks—implications for complex detection and function prediction

    PubMed Central

    Phan, Hang T. T.; Sternberg, Michael J. E.

    2012-01-01

    Motivation: Analysis of protein–protein interaction networks (PPINs) at the system level has become increasingly important in understanding biological processes. Comparison of the interactomes of different species not only provides a better understanding of species evolution but also helps with detecting conserved functional components and in function prediction. Method and Results: Here we report a PPIN alignment method, called PINALOG, which combines information from protein sequence, function and network topology. Alignment of human and yeast PPINs reveals several conserved subnetworks between them that participate in similar biological processes, notably the proteasome and transcription related processes. PINALOG has been tested for its power in protein complex prediction as well as function prediction. Comparison with PSI-BLAST in predicting protein function in the twilight zone also shows that PINALOG is valuable in predicting protein function. Availability and implementation: The PINALOG web-server is freely available from http://www.sbg.bio.ic.ac.uk/~pinalog. The PINALOG program and associated data are available from the Download section of the web-server. Contact: m.sternberg@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22419782

  2. Prediction of Functional Outcome in Individuals at Clinical High Risk for Psychosis

    PubMed Central

    Carrión, Ricardo E.; McLaughlin, Danielle; Goldberg, Terry E.; Auther, Andrea M.; Olsen, Ruth H.; Olvet, Doreen M.; Correll, Christoph U.; Cornblatt, Barbara A.

    2014-01-01

    Importance A major public health concern associated with schizophrenia and psychotic disorders is the long-term disability that involves impaired cognition, lack of social support, and an inability to function independently in the community. A critical goal of early detection and intervention studies in psychosis is therefore to understand the factors leading to this often profound impairment. Objective To develop a predictive model of functional (social and role) outcome in a clinical high-risk sample for psychosis. Design Prospective, naturalistic, longitudinal 3- to 5-year follow-up study. Setting The Recognition and Prevention Program in New York, a research clinic located in the Zucker Hillside Hospital in New York. Participants One hundred one treatment-seeking patients at clinical high risk for psychosis. Ninety-two (91%) were followed up prospectively for a mean (SD) of 3 (1.6) years. Intervention Neurocognitive and clinical assessment. Main Outcomes and Measures The primary outcome variables were social and role functioning at the last follow-up visit. Results Poor social outcome was predicted by reduced processing speed (odds ratio [OR], 1.38; 95% CI, 1.050-1.823; P = .02), impaired social functioning at baseline (OR, 1.85; 95% CI, 1.258-2.732; P = .002), and total disorganized symptoms (OR, 5.06; 95% CI, 1.548-16.527; P = .007). Reduced performance on tests for verbal memory (OR, 1.74; 95% CI, 1.169-2.594; P = .006), role functioning at baseline (OR, 1.34; 95% CI, 1.053-1.711; P = .02), and motor disturbances (OR, 1.77; 95% CI, 1.060-2.969; P = .03) predicted role outcome. The areas under the curve for the social and role prediction models were 0.824 (95% CI, 0.736-0.913; P < .001) and 0.77 (95% CI, 0.68-0.87; P < .001), respectively, demonstrating a high discriminative ability. In addition, poor functional outcomes were not entirely dependent on the development of psychosis, because 40.3% and 45.5% of nonconverters at clinical high risk had poor social

  3. Improved detection of disease-associated variation by sex-specific characterization and prediction of genes required for fertility

    PubMed Central

    Ho, Nicholas Rui Yuan; Huang, Ni; Conrad, Donald F.

    2016-01-01

    Despite its great potential, high-throughput functional genomic data is rarely integrated and applied to characterizing the genomic basis of fertility. We obtained and reprocessed over 30 functional genomics datasets from human and mouse germ cells to perform genomewide prediction of genes underlying various reproductive phenotypes in both species. Genes involved in male fertility are easier to predict than their female analogs. Of the multiple genomic data types examined, protein-protein interactions are by far the most informative for gene prediction, followed by gene expression, and then epigenetic marks. As an application of our predictions, we show that CNVs disrupting predicted fertility genes are more strongly associated with gonadal dysfunction in male and female case-control cohorts when compared to all gene-disrupting CNVs (OR=1.64, p< 1.64 × 10−8 versus OR=1.25, p < 4 × 10−6). Using gender-specific fertility gene annotations further increased the observed associations (OR = 2.31, p< 2.2 × 10−16). We provide our gene predictions as a resource with this paper. PMID:26473511

  4. Executive Function Predicts Artificial Language Learning in Children and Adults

    ERIC Educational Resources Information Center

    Kapa, Leah Lynn

    2013-01-01

    Prior research has established an executive function advantage among bilinguals as compared to monolingual peers. These non-linguistic cognitive advantages are largely assumed to result from the experience of managing two linguistic systems. However, the possibility remains that the relationship between bilingualism and executive function is…

  5. Longitudinal Associations Between Depression and Functioning In Midlife Women

    PubMed Central

    Bromberger, Joyce T.; di Scalea, Teresa Lanza

    2009-01-01

    Associations between depression and impaired functioning are well known and have been documented in numerous clinical, primary care and epidemiological studies. Reviews of this research have focused on the elderly. Recent studies suggest that women become increasingly vulnerable during the menopausal transition to declines in physical and role function and increases in depressive symptoms. The purpose of the current research is to review the literature since 1966 for studies examining the association between depression and physical and psychosocial impairment in midlife women. We selected only longitudinal studies that had the potential to elucidate the nature of the complex relationship between depression and functioning. Results of the review indicate evidence for bi-directional associations between depression and functioning in middle-aged women. However, the studies are only broadly informative. Most adjusted for only a limited group of factors that could be associated with both depression and functioning. None of them directly examined potential moderators or mediators of the relationship between depression and impaired functioning. PMID:19854010

  6. Longitudinal associations between depression and functioning in midlife women.

    PubMed

    Bromberger, Joyce T; di Scalea, T Lanza

    2009-11-20

    Associations between depression and impaired functioning are well known and have been documented in numerous clinical, primary care and epidemiological studies. Reviews of this research have focused on the elderly. Recent studies suggest that women become increasingly vulnerable during the menopausal transition to declines in physical and role function and increases in depressive symptoms. The purpose of the current research is to review the literature since 1966 for studies examining the association between depression and physical and psychosocial impairment in midlife women. We selected only longitudinal studies that had the potential to elucidate the nature of the complex relationship between depression and functioning. Results of the review indicate evidence for bi-directional associations between depression and functioning in middle-aged women. However, the studies are only broadly informative. Most adjusted for only a limited group of factors that could be associated with both depression and functioning. None of them directly examined potential moderators or mediators of the relationship between depression and impaired functioning. PMID:19854010

  7. Influencing factors on color and product-function association.

    PubMed

    Ko, Ya-Hsien

    2011-06-01

    The associations of age, sex, and matching types with color and product-function were examined in a real-world product scenario (shampoo) among 128 volunteers (M age = 29.3 yr.; SD = 15.6). A pilot study identified eight popular colors and eight product-functions. The association between color and product-function was explored in the main sample. Responses suggested seven pairings of color/product-functions: Red/Hot oil treatment, Yellow/Bright and shiny hair, Green/Herbal extracts, Blue/Deep cleaning, Purple/Soothing, Black/Antiseptic, and White/Anti-dandruff. Analyses indicated that adult participants required more repetitions for retention, as did memorization with random pairing compared to participant-selected pairings. There were statistically significant correlations of responses to colors and product functions. With known color/product-function associations, manufacturers might promote their products more effectively. It is suggested that the associations might be sex- or culture-specific. PMID:21879633

  8. Baseline burnout symptoms predict visuospatial executive function during survival school training in special operations military personnel.

    PubMed

    Morgan, Charles A; Russell, Bartlett; McNeil, Jeff; Maxwell, Jeff; Snyder, Peter J; Southwick, Steven M; Pietrzak, Robert H

    2011-05-01

    Burnout symptoms, which are characterized by exhaustion, cynicism, and a reduced sense of professional efficacy, may deleteriously affect cognitive function in military personnel. A total of 32 U.S. Military Special Operations personnel enrolled in Survival School completed measures of trauma history, dissociation, and burnout before training. They then completed the Groton Maze Learning Test (GMLT), a neuropsychological measure of integrative visuospatial executive function during three field-based phases of Survival School-enemy evasion, captivity/interrogation, and escape/release from captivity. Lower pre-training perceptions of professional efficacy were associated with reduced executive function during all of the field-based phases of Survival School, even after adjustment for years of education, cynicism, and baseline GMLT scores. Magnitudes of decrements in executive function in Marines with low efficacy relative to those with high efficacy increased as training progressed and ranged from .58 during enemy evasion to .99 during escape/release from captivity. Pre-training perceptions of burnout may predict visuospatial executive function during naturalistic training-related stress in military personnel. Assessment of burnout symptoms, particularly perceptions of professional efficacy, may help identify military personnel at risk for stress-related executive dysfunction. PMID:21466738

  9. Genome-Wide Association Study of Lung Function Phenotypes in a Founder Population

    PubMed Central

    Yao, Tsung-Chieh; Du, Gaixin; Han, Lide; Sun, Ying; Hu, Donglei; Yang, James J.; Mathias, Rasika; Roth, Lindsey A.; Rafaels, Nicholas; Thompson, Emma E.; Loisel, Dagan A.; Anderson, Rebecca; Eng, Celeste; Orbegozo, Maitane Arruabarrena; Young, Melody; Klocksieben, James M.; Anderson, Elizabeth; Shanovich, Kathleen; Lester, Lucille A.; Williams, L. Keoki; Barnes, Kathleen C.; Burchard, Esteban G.; Nicolae, Dan L.; Abney, Mark; Ober, Carole

    2014-01-01

    Background Lung function is a long-term predictor of mortality and morbidity. Objective We sought to identify single nucleotide polymorphisms (SNPs) associated with lung function. Methods We performed a genome-wide association study (GWAS) of forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and FEV1/FVC in 1,144 Hutterites aged 6–89 years, who are members of a founder population of European descent. We performed least absolute shrinkage and selection operation (LASSO) regression to select the minimum set of SNPs that best predict FEV1/FVC in the Hutterites and used the GRAIL algorithm to mine the Gene Ontology database for evidence of functional connections between genes near the predictive SNPs. Results Our GWAS identified significant associations between FEV1/FVC and SNPs at the THSD4-UACA-TLE3 locus on chromosome 15q23 (P = 5.7x10−8 ~ 3.4x10−9). Nine SNPs at or near four additional loci had P-values < 10−5 with FEV1/FVC. There were only two SNPs with P-values < 10−5 for FEV1 or FVC. We found nominal levels of significance with SNPs at 9 of the 27 previously reported loci associated with lung function measures. Among a predictive set of 80 SNPs, six loci were identified that had a significant degree of functional connectivity (GRAIL P < 0.05), including three clusters of β-defensin genes, two chemokine genes (CCL18 and CXCL12), and TNFRSF13B. Conclusion This study identifies genome-wide significant associations and replicates results of previous GWAS. Multimarker modeling implicated for the first time common variation in genes involved in anti-microbial immunity in airway mucosa influences lung function. PMID:23932459

  10. DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELING FOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS

    SciTech Connect

    McDermott, Jason E.; Costa, Michelle N.; Stevens, S.L.; Stenzel-Poore, Mary; Sanfilippo, Antonio P.

    2011-01-20

    A difficult problem that is currently growing rapidly due to the sharp increase in the amount of high-throughput data available for many systems is that of determining useful and informative causative influence networks. These networks can be used to predict behavior given observation of a small number of components, predict behavior at a future time point, or identify components that are critical to the functioning of the system under particular conditions. In these endeavors incorporating observations of systems from a wide variety of viewpoints can be particularly beneficial, but has often been undertaken with the objective of inferring networks that are generally applicable. The focus of the current work is to integrate both general observations and measurements taken for a particular pathology, that of ischemic stroke, to provide improved ability to produce useful predictions of systems behavior. A number of hybrid approaches have recently been proposed for network generation in which the Gene Ontology is used to filter or enrich network links inferred from gene expression data through reverse engineering methods. These approaches have been shown to improve the biological plausibility of the inferred relationships determined, but still treat knowledge-based and machine-learning inferences as incommensurable inputs. In this paper, we explore how further improvements may be achieved through a full integration of network inference insights achieved through application of the Gene Ontology and reverse engineering methods with specific reference to the construction of dynamic models of transcriptional regulatory networks. We show that integrating two approaches to network construction, one based on reverse-engineering from conditional transcriptional data, one based on reverse-engineering from in situ hybridization data, and another based on functional associations derived from Gene Ontology, using probabilities can improve results of clustering as evaluated by a