Abstract: Annotation of a protein sequence is pivotal for the understanding of its function. Accuracy of manual annotation provided by curators is still questionable by having lesser evidence strength and yet a hard task and time consuming. A number of computational methods including tools have been developed to tackle this challenging task. However, they require high-cost hardware, are difficult to be setup by the bioscientists, or depend on time intensive and blind sequence similarity search like Basic Local Alignment Search Tool. This paper introduces a new method of assigning highly correlated Gene Ontology terms of annotated protein sequences to partially annotated or newly discovered protein sequences. This method is fully based on Gene Ontology data and annotations. Two problems had been identified to achieve this method. The first problem relates to splitting the single monolithic Gene Ontology RDF/XML file into a set of smaller files that can be easy to assess and process. Thus, these files can be enriched with protein sequences and Inferred from Electronic Annotation evidence associations. The second problem involves searching for a set of semantically similar Gene Ontology terms to a given query. The details of macro and micro problems involved and their solutions including objective of this study are described. This paper also describes the protein sequence annotation and the Gene Ontology. The methodology of this study and Gene Ontology based protein sequence annotation tool namely extended UTMGO is presented. Furthermore, its basic version which is a Gene Ontology browser that is based on semantic similarity search is also introduced.
Abstract: Dilated cardiomyopathy (DCM) is a severe
cardiovascular disorder characterized by progressive systolic
dysfunction due to cardiac chamber dilatation and inefficient
myocardial contractility often leading to chronic heart failure.
Recently, a genome-wide association studies (GWASs) on DCM
indicate that the ZBTB17 gene rs10927875 single nucleotide
polymorphism is associated with DCM. The aim of the study was to
identify the distribution of ZBTB17 gene rs10927875 polymorphism
in 50 Slovak patients with DCM and 80 healthy control subjects
using the Custom Taqman®SNP Genotyping assays. Risk factors
detected at baseline in each group included age, sex, body mass
index, smoking status, diabetes and blood pressure. The mean age of
patients with DCM was 52.9±6.3 years; the mean age of individuals
in control group was 50.3±8.9 years. The distribution of investigated
genotypes of rs10927875 polymorphism within ZBTB17 gene in the
cohort of Slovak patients with DCM was as follows: CC (38.8%), CT
(55.1%), TT (6.1%), in controls: CC (43.8%), CT (51.2%), TT
(5.0%). The risk allele T was more common among the patients with
dilated cardiomyopathy than in normal controls (33.7% versus
30.6%). The differences in genotype or allele frequencies of ZBTB17
gene rs10927875 polymorphism were not statistically significant
(p=0.6908; p=0.6098). The results of this study suggest that ZBTB17
gene rs10927875 polymorphism may be a risk factor for
susceptibility to DCM in Slovak patients with DCM. Studies of
numerous files and additional functional investigations are needed to
fully understand the roles of genetic associations.
Abstract: This paper investigates the relationship between state and business in the context of structural and institutional transformations in Indonesia following the collapse of the New Order regime in 1998. Since 1998, Indonesia has embarked on a shift from an authoritarian to democratic polity and from a centralised to a decentralised system of governance, transforming the country into the third largest democracy and one of the most decentralised states in the world. This paper examines whether the transformation of the Indonesian state has altered the pattern of state and business relations with focus on clientism and corruption as the key dependent variable, and probes how/to what extent this has changed as a result of the transformation and the ensuring shifts in business and state relations. Based on interviews with key government and business actors as well as prominent scholars in Indonesia, it is found that since the demise of the New Order, business associations in Indonesia have become more independent of state control and more influential in public decision-making whereas the government has become more responsive of business concerns and more committed to combat corruption and clientism. However, these changes have not necessarily rendered business people completely leave individualclientelistic relationship with the government, and simply pursue wider sectoral and business-wide collectivism as an alternative way of channelling their aspirations, which is expected to help reduce corruption and clientism in Indonesia. This paper concludes that democratisation and a more open politics may have helped reduce corruption and clientism in Indonesia through changes in government. However, it is still difficult to imply that such political transformation has fostered business collective action and a broader, more encompassing pattern of business lobbying and activism, which is expected to help reduce corruption and clientism.
Abstract: To develop a process of extracting pixel values over the using of satellite remote sensing image data in Thailand. It is a very important and effective method of forecasting rainfall. This paper presents an approach for forecasting a possible rainfall area based on pixel values from remote sensing satellite images. First, a method uses an automatic extraction process of the pixel value data from the satellite image sequence. Then, a data process is designed to enable the inference of correlations between pixel value and possible rainfall occurrences. The result, when we have a high averaged pixel value of daily water vapor data, we will also have a high amount of daily rainfall. This suggests that the amount of averaged pixel values can be used as an indicator of raining events. There are some positive associations between pixel values of daily water vapor images and the amount of daily rainfall at each rain-gauge station throughout Thailand. The proposed approach was proven to be a helpful manual for rainfall forecasting from meteorologists by which using automated analyzing and interpreting process of meteorological remote sensing data.
Abstract: Microarray data profiles gene expression on a whole
genome scale, therefore, it provides a good way to study associations
between gene expression and occurrence or progression of cancer.
More and more researchers realized that microarray data is helpful
to predict cancer sample. However, the high dimension of gene
expressions is much larger than the sample size, which makes this
task very difficult. Therefore, how to identify the significant genes
causing cancer becomes emergency and also a hot and hard research
topic. Many feature selection algorithms have been proposed in
the past focusing on improving cancer predictive accuracy at the
expense of ignoring the correlations between the features. In this
work, a novel framework (named by SGS) is presented for stable gene
selection and efficient cancer prediction . The proposed framework
first performs clustering algorithm to find the gene groups where
genes in each group have higher correlation coefficient, and then
selects the significant genes in each group with Bayesian Lasso and
important gene groups with group Lasso, and finally builds prediction
model based on the shrinkage gene space with efficient classification
algorithm (such as, SVM, 1NN, Regression and etc.). Experiment
results on real world data show that the proposed framework often
outperforms the existing feature selection and prediction methods,
say SAM, IG and Lasso-type prediction model.
Abstract: The association between emotional inhibition strategies linked to depression has been showed inconsistent among studies. Mild emotional inhibition maybe benefit for social interaction, especially for female among East Asian cultures. The present study aimed to examine whether the inhibition–depression relationship is dependent on level of emotion inhibition and gender context, given differing value of suppressing emotional displays. We hypothesized that the negative associations between inhibition and adolescent depression would not directly, in which affected by interaction between emotion inhibition and gender. To test this hypothesis, we asked 309 junior high school students which age range from 12 to14 years old to report on their use of emotion inhibition and depression syndrome. A multiple regressions analysis revealed that significant interaction that gender as a moderator to the relationships between emotion inhibition and adolescent depression. The group with the highest level of depression was girls with high levels of emotion inhibition, whose depression score was higher than that of boys with high levels of emotion inhibition. The result highlights that the importance of context in understanding the inhibition-depression relationship.
Abstract: Network warfare is an emerging concept that focuses on the network and computer based forms through which information is attacked and defended. Various computer and network security concepts thus play a role in network warfare. Due the intricacy of the various interacting components, a model to better understand the complexity in a network warfare environment would be beneficial. Non-quantitative modeling is a useful method to better characterize the field due to the rich ideas that can be generated based on the use of secular associations, chronological origins, linked concepts, categorizations and context specifications. This paper proposes the use of non-quantitative methods through a morphological analysis to better explore and define the influential conditions in a network warfare environment.
Abstract: In this work, I present a review on Sparse Distributed
Memory for Small Cues (SDMSCue), a variant of Sparse Distributed
Memory (SDM) that is capable of handling small cues. I then conduct
and show some cognitive experiments on SDMSCue to test its
cognitive soundness compared to SDM. Small cues refer to input
cues that are presented to memory for reading associations; but have
many missing parts or fields from them. The original SDM failed to
handle such a problem. SDMSCue handles and overcomes this
pitfall. The main idea in SDMSCue; is the repeated projection of the
semantic space on smaller subspaces; that are selected based on the
input cue length and pattern. This process allows for Read/Write
operations using an input cue that is missing a large portion.
SDMSCue is augmented with the use of genetic algorithms for
memory allocation and initialization. I claim that SDM functionality
is a subset of SDMSCue functionality.
Abstract: The paper describes the carbonate microfacies identified in the Sinjar Formation (Late Paleocene–Early Eocene) cropping out in Qara Dagh Mountain, near Sulekan Village approximately 20km south–west of Sulaimani (Iraq). One section (62m thick) has been measured in the field and closely sampled to undertake detailed microfaciesal and micropalaeontological studies to determine the formation-s age and environment of deposition. A samples were collected illustrating all the lithological changes along the section. The limestone in the studied area is hard and extremely rich in large foraminifers (soritids, rotaliids, nummulites, miliolids) and green algae (dasycladales). The investigation of the thin sections allowed us to identify the carbonate microfacies (18 types and subtypes) and the micropaleontological association (foraminifers and green algae), to determine the age of formation and to reconstruct the paleoenvironment of deposition (fore-reef, reef, back-reef). Based on the field observations and the studied thin sections, we determined three Units of a carbonate platform (I, II and III) from the base to the top of the section: Unit I with coralgal associations, Unit II is dominated by larger foraminifers and haracterized by the absence of coralgal associations, while Unit III is dominated by small foraminifers (mostly miliolids), peloids and green algae. It is partially dolomitized.
Abstract: Based on assumptions of neo-classical economics and
rational choice / public choice theory, this paper investigates the
regulation of industrial land use in Taiwan by homeowners
associations (HOAs) as opposed to traditional government
administration. The comparison, which applies the transaction cost
theory and a polynomial regression analysis, manifested that HOAs
are superior to conventional government administration in terms of
transaction costs and overall efficiency. A case study that compares
Taiwan-s commonhold industrial park, NangKang Software Park, to
traditional government counterparts using limited data on the costs
and returns was analyzed. This empirical study on the relative
efficiency of governmental and private institutions justified the
important theoretical proposition. Numerical results prove the
efficiency of the established model.
Abstract: In networks, mainly small and medium-sized businesses benefit from the knowledge, experiences and solutions offered by experts from industry and science or from the exchange with practitioners. Associations which focus, among other things, on networking, information and knowledge transfer and which are interested in supporting such cooperations are especially well suited to provide such networks and the appropriate web platforms. Using METORA as an example – a project developed and run by the Federal Association for Information Economy, Telecommunications and New Media e.V. (BITKOM) for the Federal Ministry of Economics and Technology (BMWi) – This paper will discuss how associations and other network organizations can achieve this task and what conditions they have to consider.
Abstract: Concept maps can be generated manually or
automatically. It is important to recognize differences of the two
types of concept maps. The automatically generated concept maps
are dynamic, interactive, and full of associations between the terms
on the maps and the underlying documents. Through a specific
concept mapping system, Visual Concept Explorer (VCE), this paper
discusses how automatically generated concept maps are different
from manually generated concept maps and how different
applications and learning opportunities might be created with the
automatically generated concept maps. The paper presents several
examples of learning strategies that take advantages of the
automatically generated concept maps for concept learning and
exploration.
Abstract: This study compares family communication patterns in association with family socio-cultural status, especially marriage and family pattern, and couples- socio-economic status between Muslim and Santal communities in rural Bangladesh. A total of 288 couples, 145 couples from the Muslim and 143 couples from the Santal were randomly selected through cluster sampling procedure from Kalna village situated in Tanore Upazila of Rajshahi district of Bangladesh, where both the communities dwell as neighbors. In order to collect data from the selected samples, interview method with semistructural questionnaire schedule was applied. The responses given by the respondents were analyzed by Pearson-s chi-squire test and bivariate correlation techniques. The results of Pearson-s chi-squire test revealed that family communication patterns (X2= 25. 90, df= 2, p0.05) were significantly different between the Muslim and Santal communities. In addition, Spearman-s bivariate correlation coefficients suggested that among the exogenous factors, family type (rs=.135, p
Abstract: The request for a sustainable development challenges
both managers and consumers to rethink habitual practices and
activities. While consumers are challenged to develop sustainable
consumption patterns, companies are asked to establish managerial
systems and structures considering economical, ecological, and social
issues. As this is in particular true for housing associations, this paper
aims first, at providing an understanding of sustainability strategy in
residential trade and industry (RTI) by identifying relevant facets of
this construct and second, at conceptually analyzing the impact of
sustainability strategy in RTI on operational efficiency and
performance of municipal housing companies. The author develops a
model of sustainability strategy in RTI and its effects and further,
sheds light in priorities for future research.
Abstract: Most of the existing text mining approaches are
proposed, keeping in mind, transaction databases model. Thus, the
mined dataset is structured using just one concept: the “transaction",
whereas the whole dataset is modeled using the “set" abstract type. In
such cases, the structure of the whole dataset and the relationships
among the transactions themselves are not modeled and
consequently, not considered in the mining process.
We believe that taking into account structure properties of
hierarchically structured information (e.g. textual document, etc ...)
in the mining process, can leads to best results. For this purpose, an
hierarchical associations rule mining approach for textual documents
is proposed in this paper and the classical set-oriented mining
approach is reconsidered profits to a Direct Acyclic Graph (DAG)
oriented approach. Natural languages processing techniques are used
in order to obtain the DAG structure. Based on this graph model, an
hierarchical bottom up algorithm is proposed. The main idea is that
each node is mined with its parent node.
Abstract: Frequent patterns are patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a dataset. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages such as C, Cµ, Java. The imperative paradigm is significantly inefficient when itemset is large and the frequent pattern is long. We suggest a high-level declarative style of programming using a functional language. Our supposition is that the problem of frequent pattern discovery can be efficiently and concisely implemented via a functional paradigm since pattern matching is a fundamental feature supported by most functional languages. Our frequent pattern mining implementation using the Haskell language confirms our hypothesis about conciseness of the program. The performance studies on speed and memory usage support our intuition on efficiency of functional language.
Abstract: The aim of this study is to describe the associations
between the temperamental traits and the narrative emotional
expression. The Temperament Questionnaire was used: The FCB-TI
of Zawadzki & Strelau. A sample of 85 persons described three
emotional situations: love. hate, and anxiety. This study analyzes the
verbal form of expression by means of a written account of
emotions. The relationship between the narratives of love, hate and
anxiety and temperament characteristics were studied. Results
indicate that vigorousness (VI), perseverance (PE), sensory
sensitivity (SS), emotional reactivity (ER), endurance (EN) and
activeness (AC) have a significant impact on the emotional
expression in narratives. The temperamental traits are linked to the
form of emotional language. It means that temperament has an
impact on cognitive representations of emotions.
Abstract: This paper reports optimization of characteristics of bioballistic transformation of spring soft wheat (Triticum aestivum L. cultivar Raduga) and getting of transgenic plants, carrying pea lectin gene. This gene will let to create new associative wheat symbiosis with nodule bacteria of field pea, which has growth encouraging, fungistatic and other useful characteristics.
Abstract: Recent developments in storage technology and
networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate
decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is
logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among
concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data
streams.
Abstract: Sense-antisense gene pair (SAGP) is a pair of two oppositely transcribed genes sharing a common region on a chromosome. In the mammalian genomes, SAGPs can be organized in more complex sense-antisense gene architectures (CSAGA) in which at least one gene could share loci with two or more antisense partners. Many dozens of CSAGAs can be found in the human genome. However, CSAGAs have not been systematically identified and characterized in context of their role in human diseases including cancers. In this work we characterize the structural-functional properties of a cluster of 5 genes –TMEM97, IFT20, TNFAIP1, POLDIP2 and TMEM199, termed TNFAIP1 / POLDIP2 module. This cluster is organized as CSAGA in cytoband 17q11.2. Affymetrix U133A&B expression data of two large cohorts (410 atients, in total) of breast cancer patients and patient survival data were used. For the both studied cohorts, we demonstrate (i) strong and reproducible transcriptional co-regulatory patterns of genes of TNFAIP1/POLDIP2 module in breast cancer cell subtypes and (ii) significant associations of TNFAIP1/POLDIP2 CSAGA with amplification of the CSAGA region in breast cancer, (ii) cancer aggressiveness (e.g. genetic grades) and (iv) disease free patient-s survival. Moreover, gene pairs of this module demonstrate strong synergetic effect in the prognosis of time of breast cancer relapse. We suggest that TNFAIP1/ POLDIP2 cluster can be considered as a novel type of structural-functional gene modules in the human genome.