Analysis Of Interaction Patterns Research Articles (Page 5)

Pull-downs based on tag fusion proteins as well as immunoprecipitations (IP) are widely used methods to analyze protein interactions. Selectivity and specificity of both methods are compromised by nonspecific binding to the capture agent or carrier beads thereby generating false positives. Here, we provide a method combining stable isotope labeling of amino acids in cell culture (SILAC) with affinity purification, coupled to quantitative tandem mass spectrometry. It permits the analysis of protein interactions with high sensitivity, while being able to discriminate contaminants and nonspecific binders. Besides pruning out contaminants, high-resolution MS data combined with quantitative proteomics software allow the comparative analysis of protein interaction patterns of different protein variants, for example mutated versus normal protein variant or of regulatory changes in a given protein complex due to different states of activity.

The lmdme package decomposes analysis of variance (ANOVA) through linear models on designed multivariate experiments, allowing ANOVA-principal component analysis (APCA) and ANOVA-simultaneous component analysis (ASCA) in R. It also extends both methods with the application of partial least squares (PLS) through the specification of a desired output matrix. The package is freely available from Bioconductor and licensed under the GNU General Public License. ANOVA decomposition methods for designed multivariate experiments are becoming popular in “omics” experiments (transcriptomics, metabolomics, etc.), where measurements are performed according to a predefined experimental design, with several experimental factors or including subject-specific clinical covariates, such as those present in current clinical genomic studies. ANOVA-PCA and ASCA are well-suited methods for studying interaction patterns on multidimensional datasets. However, currently an R implementation of APCA is only available for Spectra data in the ChemoSpec package, whereas ASCA is based on average calculations on the indices of up to three design matrices. Thus, no statistical inference on estimated effects is provided. Moreover, ASCA is not available in an R package. Here, we present an R implementation for ANOVA decomposition with PCA/PLS analysis that allows the user to specify (through a flexible formula interface), almost any linear model with the associated inference on the estimated effects, as well as to display functions to explore results both of PCA and PLS. We describe the model, its implementation and two high-throughput microarray examples: one applied to interaction pattern analysis and the other to quality assessment.

In this study the aim was to investigate the development of Pedagogical Content Knowledge (PCK) of early career chemistry teachers. Two pre-service chemistry teachers were followed during a one-semester course and after a three-year period as formal high school teachers. The data involved teachers´ writings, recordings of lessons and reflections during the course. After three years, the same content lessons in an actual school environment were videotaped. The teachers were then interviewed using the videotapes for stimulated recall. The instruments Content Representation (CoRe) and Pedagogical and Professional-experience Repertoires (PaP-eR´s) were used to document and to describe teachers’ PCK. Analysis of discursive interaction patterns was performed during lessons. Data analysis was based on the components of teacher knowledge as described in the Morine-Dershimer Model. The development of PCK was enhanced during the pre-service teacher education through the experiences of planning and conducting interventions in the classroom and particularly during the reflection-on-action activities. Results after three years of professional experience revealed an improvement in these teachers’ PCK and highlighted the central role of the reflection process and practical experience. From the analysis carried out, it emphasized the need to act in these early years of professional experience through collaborative groups, supporting the reflection process and aiming to contribute more directly to the development of teachers' PCK. Key words: pedagogical content knowledge, teacher's knowledge, teacher’s professional development.

This paper presents an integrated view on a series of experiments conducted with an affective dialog system, applied as a tool in studies of emotions and social processes in online communication. The different realizations of the system are evaluated in three experimental setups to verify effects of affective profiles, as well as of fine-grained communication scenarios on users' expressions of affective states, experienced emotional changes, and interaction patterns. Results demonstrate that the system applied in virtual reality settings matches a Wizard-of-Oz in terms of chatting enjoyment, dialog coherence, and realism. Variants of the system's affective profile significantly influence the rating of chatting enjoyment and an emotional connection. Self-reported emotional changes experienced by participants during an interaction with the system are in line with the type of applied profile. Analysis of interaction patterns, i.e., usage of particular dialog act classes, word categories, and textual expressions of affective states for different scenarios, demonstrates that a communication scenario for social sharing of emotions was successfully established. The experimental evidence provides valuable input for applications of affective dialog systems and strengthens them as valid tools for studying affect and social aspects in online communication.

Interaction of Carthamus tinctorius lignan arctigenin with the binding site of tryptophan-degrading enzyme indoleamine 2,3-dioxygenase

Recent genome-wide association studies (GWAS) have reported multiple risk loci associated with risk of colorectal cancer (CRC), some of which are involved in the transforming growth factor beta (TGFβ) signaling pathway. We systematically examined associations of common genetic variations in the TGFβ signaling pathway and environmental factors with CRC risk using a two-staged case-control study in a Chinese population. A set of 77 single-nucleotide polymorphisms (SNPs) in 10 candidate genes involved in the TGFβ signaling pathway and several environmental factors including sex, age, smoking and drinking were examined by random forest (RF) to capture the potential gene-gene and gene-environment interactions in stage 1 of the study with 443 CRC patients and 480 controls. Three promising SNPs (SMAD7 rs11874392, TGFBR1 rs10988706 and rs6478972) selected by the RF method were genotyped in stage 2 comprising 351 cases and 360 controls for validation. SMAD7 rs11874392 presented consistently significant associations with a risk of CRC at both stages, with odds ratio = 1.41 (95% confidence interval = 1.21-1.63) using additive modes in combined analyses. Moreover, the potential interactions between SMAD7 rs11874392, TGFBR1 rs10988706 and rs6478972 were indicated consistently in both stages of the study by using pair-wise interaction and multilocus genotype pattern analysis. Additionally, gene-smoking interactions for rs11874392, rs10988706 and rs6478972 were also found to enhance the risk of CRC at both stages, with P for multiplicative interaction equal to 1.162×10(-6), 8.574×10(-8) and 9.410×10(-8) in combined analyses, respectively. This study emphasized the substantial role of the TGFβ signaling pathway in CRC, especially in interaction with smoking.

Interaction Pattern Analysis Focused on Embodied Synchrony

The rheological properties of mucin–alginate blends can be modulated by addition of oligoguluronates. In the present study, we report on destabilisation of mucin–alginate interactions by oligoguluronates as determined by forced unbinding of these macromolecular components. The forces needed to rupture the bonds formed between purified pig gastric mucin (PGM) and high molecular weight alginate, covalently linked to mica and the AFM tip, respectively were determined under physiologically relevant conditions. The experiments were conducted in the presence and absence of oligoguluronate with DPn = 12 in concentrations ranging from 0.001 to 2 mg ml−1 in buffer solution. The PGM–alginate forced unbinding profiles revealed unbinding events with magnitudes up to 4 nN occurring at separation distances up to 3 μm. The observed unbinding profiles were consistent with a multivalent nature of the macromolecular compounds. The oligoguluronate concentration-dependent suppression of mucin–alginate interactions modelled as a one-site competitive model yielded an estimate of 1.4 μg ml−1 oligoguluronate for 50% reduction of the mucin–alginate deadhesion work. Analysis of interaction patterns between alginate and mucin immobilized on the AFM tip probed independently against immobilised oligoguluronate suggests that oligoguluronate interaction with mucin is the mechanism underlying the observed suppression of the alginate–mucin interactions. The oligoguluronate concentration-dependent suppression of mucin–alginate interactions increases the molecular understanding of oligoguluronates' action as an apparent mucolytic agent of potential relevance for application to improve lung function in patients suffering from cystic fibrosis.

Obstacles and opportunities for developing thinking through interaction in language classrooms

BackgroundA fundamental assumption in animal socio-ecology is that animals compete over limited resources. This view has been challenged by the finding that individuals might cooperatively partition resources by "taking turns". Turn-taking occurs when two individuals coordinate their agonistic behaviour in a way that leads to an alternating pattern in who obtains a resource without engaging in costly fights. Cooperative turn-taking has been largely ignored in models of animal conflict and socio-ecological models that explain the evolution of social behaviours based only on contest and scramble competition. Currently it is unclear whether turn-taking should be included in socio-ecological models because the evolution of turn-taking is not well understood. In particular, it is unknown whether turn-taking can evolve when fighting costs and assessment of fighting abilities are not fixed but emerge from evolved within-fight behaviour. We address this problem with an evolutionary agent-based model.ResultsWe found that turn-taking evolves for small resource values, alongside a contest strategy that leads to stable dominance relationships. Turn-taking leads to egalitarian societies with unclear dominance relationships and non-linear dominance hierarchies. Evolutionary stability of turn-taking emerged despite strength differences among individuals and the possibility to evolve within-fight behaviour that allows good assessment of fighting abilities. Evolutionary stability emerged from frequency-dependent effects on fitness, which are modulated by feedbacks between the evolution of within-fight behaviour and the evolution of higher-level conflict strategies.ConclusionsOur results reveal the impact of feedbacks between the evolution of within-fight behaviour and the evolution of higher-level conflict strategies, such as turn-taking. Similar feedbacks might be important for the evolution of other conflict strategies such as winner-loser effects or coalitions. However, we are not aware of any study that investigated such feedbacks. Furthermore, our model suggests that turn-taking could be used by animals to partition low value resources, but to our knowledge this has never been tested. The existence of turn-taking might have been overlooked because it leads to societies with similar characteristics that have been expected to emerge from scramble competition. Analyses of temporal interaction patterns could be used to test whether turn-taking occurs in animals.

We provide a corpus-based computational approach to analyzing acquisition data on Turkish, a richly inflected language. We describe the process by which transcripts from the CHILDES database for 16 children aged 2;0 to 3;0 were morphologically tagged and parsed. We computed a number of imitation, overlap, and repetition measures on the transcripts using CLAN and CHIP programs. These measures tended to decrease as a function of mean length of utterance, which was broadly consistent with previously published work on English-speaking children. The data also revealed additional usage patterns, where the adult utterances provided children with rich morphosyntax in the input, while at the same time helping them to maintain discourse. Children on the other hand, tended to omit optional constituents and repeat morphemes from the previous utterance. The Turkish data and previously published English data showed cross-linguistic differences in repetition patterns that were congruent with the typological differences between the two languages. More generally, the data were consistent with a usage-based model for the acquisition of Turkish as a first language. The corpora and methods provided here can be extended to future applications.

The present study shows that power relations in classrooms between Dutch and immigrant students radically shift when students move from academic talk to more open, free talk. Whereas in their interactions with immigrant students, Dutch students are able to represent the more powerful role in the official, academic discourse, they lose this position in the unofficial, nonacademic discourse. These shifts show that ethnic relationships are played out differently in different discursive domains. They also show that academic identities do not exist as such but are specific to certain minority-majority relationships. This study builds upon a tradition of studies that have argued that ethnic minorities construct academic identities depending on the social setting. However, this study shows the instability of these constructions while demonstrating their dependency on specific ethnic interactions and discursive modes. The study is based on the analysis of interaction patterns in multiethnic classrooms in the Netherlands focussing on (a)symmetries in knowledge sharing. An ethnographic approach is combined with quantitative analyses to test group differences. The results are interpreted and discussed in the light of a poststructuralist view on how ethnic minority groups construct academic identities and how these are related to minority-majority relationships.

A programmable system, the Textur Analyse System (T.A.S.) of E. Leitz, is described for use in interactive work on pattern recognition of white blood cells. The system appears well suited for the task of finding new parameters for the characterization of normal and abnormal blood cells. Hardware advantages such as speed of operation are coupled with software flexibility. The first application of the machine has been the extraction of some of the ordinary parameters for characterization of leucocytes. The value of each parameter has been analysed with the interactive statistical pattern analysis program (ISPAHAN). A separation in the five normal classes of peripheral white blood cells can be achieved, in which the nuclear/cell area ratio and nuclear area together with the density histograms proved to be the most important parameters. The interesting feature of the system is, however, the possibility of finding new data for the recognition of normal and abnormal blood cells.

An analysis of peer interaction patterns as discoursed by on-line small group problem-solving activity

Gene Expression Pattern Scanner (GEPS) is a web-based server to provide interactive pattern analysis of user-submitted microarray data for facilitating their further interpretation. Putative gene expression patterns such as correlated expression, similar expression and specific expression are determined globally and systematically using geometric comparison and correlation analysis methods. These patterns can be visualized via linear plot with quantitative measures. User-defined threshold value is allowed to customize the format of the pattern search results. For better understanding of gene expression, patterns derived from 329 205 non-redundant gene expression records from the GNF SymAltas and the Gene Expression Omnibus are also provided. These profiles cover 24 277 human genes in 79 tissues, 32 905 mouse genes in 61 tissues and 4201 rat genes in 44 tissues. GEPS is available at .

An agent based model for real-time signaling induced in osteocytic networks by mechanical stimuli

ABSTRACT Taiwan, once called Formosa (meaning “beautiful island” in Portuguese), is a country with a diverse ethno-linguistic heritage, and therefore it is a multiracial, multicultural, and multilingual country. The society consists of more than 10 different aboriginal communities in addition to the 3H: three different groups of Hun peoples (Hoklo or Minnan group speakers, Hakka speakers, and Holam in Amis language—the latest immigrants). This paper explores how the different cultural backgrounds of senior high-school students in Taiwan in a multilingual classroom that promoted multilingualism allow them to come to value other languages spoken in their classes or in their communities. Evidence supporting students' attitudes and motivation in learning community languages and English came from close analysis of interactional patterns with peers and teachers in classes and informal settings, from students' explanations of their school experiences in group work, and from interviews with students, parents, community figures, and educational leaders over a four-month period during the process of the course. Sensitizing students to cultural-linguistic diversity through English language classes in a multicultural Taiwan has the potential to promote multilingualism and pluralism in minority and majority group students who study several languages at a time in a multilingual classroom.

Relevance feedback is a mechanism to interactively learn a user's query concept online. It has been extensively used to improve the performance of multimedia information retrieval. In this paper, we present a novel interactive pattern analysis method that reduces relevance feedback to a two-class classification problem and classifies multimedia objects as relevant or irrelevant. To perform interactive pattern analysis, we propose two online pattern classification methods, called interactive random forests (IRF) and adaptive random forests (ARF), that adapt a composite classifier known as random forests for relevance feedback. IRF improves the efficiency of regular random forests (RRF) with a novel two-level resampling technique called biased random sample reduction, while ARF boosts the performance of RRF with two adaptive learning techniques called dynamic feature extraction and adaptive sample selection. During interactive multimedia retrieval, both ARF and IRF run two to three times faster than RRF while achieving comparable precision and recall against the latter. Extensive experiments on a COREL image set (with 31,438 images) demonstrate that our methods (i.e., IRF and RRF) achieve at least a $20\%$ improvement on average precision and recall over the state-of-the-art approaches.

면대면 학습 환경과 온라인 실시간/비실시간 학습 환경에서의 상호작용 패턴 분석

The Sequence Dependence of Fiber Organization. A Comparative Molecular Dynamics Study of the Islet Amyloid Polypeptide Segments 22–27 and 22–29