Theodosios Theodosiou

Gene functional annotation by statistical analysis of biomedical articles

BACKGROUND Functional annotation of genes is an important task in biology since it facilitates the characterization of genes relationships and the understanding of biochemical pathways. The various gene functions can be described by standardized and structured vocabularies, called bio-ontologies. The assignment of bio-ontology terms to genes is carried out by means of applying certain methods to datasets extracted from biomedical articles. These methods originate from data mining and machine learning and include maximum entropy or support vector machines (SVM). PURPOSE The aim of this paper is to propose an alternative to the existing methods for functionally annotating genes. The methodology involves building of classification models, validation and graphical representations of the results and reduction of the dimensions of the dataset. METHODS Classification models are constructed by Linear discriminant analysis (LDA). The validation of the models is based on statistical analysis and interpretation of the results involving techniques like hold-out samples, test datasets and metrics like confusion matrix, accuracy, recall, precision and F-measure. Graphical representations, such as boxplots, Andrews curves and scatterplots of the variables resulting from the classification models are also used for validating and interpreting the results. RESULTS The proposed methodology was applied to a dataset extracted from biomedical articles for 12 Gene Ontology terms. The validation of the LDA models and the comparison with the SVM show that LDA (mean F-measure 75.4%) outperforms the SVM (mean F-measure 68.7%) for the specific data. CONCLUSION The application of certain statistical methods can be beneficial for functional gene annotation from biomedical articles. Apart from the good performance the results can be interpreted and give insight of the bio-text data structure.

Gene socialization: gene order, GC content and gene silencing in Salmonella

BackgroundGenes of conserved order in bacterial genomes tend to evolve slower than genes whose order is not conserved. In addition, genes with a GC content lower than the GC content of the resident genome are known to be selectively silenced by the histone-like nucleoid structuring protein (H-NS) in Salmonella.ResultsIn this study, we use a comparative genomics approach to demonstrate that in Salmonella, genes whose order is not conserved (or genes without homologs) in closely related bacteria possess a significantly lower average GC content in comparison to genes that preserve their relative position in the genome. Moreover, these genes are more frequently targeted by H-NS than genes that have conserved their genomic neighborhood. We also observed that duplicated genes that do not preserve their genomic neighborhood are, on average, under less selective pressure.ConclusionsWe establish a strong association between gene order, GC content and gene silencing in a model bacterial species. This analysis suggests that genes that are not under strong selective pressure (evolve faster than others) in Salmonella tend to accumulate more AT-rich mutations and are eventually silenced by H-NS. Our findings may establish new approaches for a better understanding of bacterial genome evolution and function, using information from functional and comparative genomics.

MeSHy: Mining unanticipated PubMed information using frequencies of occurrences and concurrences of MeSH terms

MOTIVATION PubMed is the most widely used database of biomedical literature. To the detriment of the user though, the ranking of the documents retrieved for a query is not content-based, and important semantic information in the form of assigned Medical Subject Headings (MeSH) terms is not readily presented or productively utilized. The motivation behind this work was the discovery of unanticipated information through the appropriate ranking of MeSH term pairs and, indirectly, documents. Such information can be useful in guiding novel research and following promising trends. METHODS A web-based tool, called MeSHy, was developed implementing a mainly statistical algorithm. The algorithm takes into account the frequencies of occurrences, concurrences, and the semantic similarities of MeSH terms in retrieved PubMed documents to create MeSH term pairs. These are then scored and ranked, focusing on their unexpectedly frequent or infrequent occurrences. RESULTS MeSHy presents results through an online interactive interface facilitating further manipulation through filtering and sorting. The results themselves include the MeSH term pairs, along with MeSH categories, the score, and document IDs, all of which are hyperlinked for convenience. To highlight the applicability of the tool, we report the findings of an expert in the pharmacology field on querying the molecularly-targeted drug imatinib and nutrition-related flavonoids. To the best of our knowledge, MeSHy is the first publicly available tool able to directly provide such a different perspective on the complex nature of published work. IMPLEMENTATION AND AVAILABILITY Implemented in Perl and served by Apache2 at http://bat.ina.certh.gr/tools/meshy/ with all major browsers supported.

Chromatin integrity of ram spermatozoa. Relationships to annual fluctuations of scrotal surface temperature and temperature-humidity index

The objective of the present study was to explore the potential relationships of ovine sperm chromatin integrity, quantified using the sperm chromatin structure assay (SCSA), to the heat load of the scrotum and the discomfort felt by the animals because of fluctuations of microclimatic factors at different time periods before ejaculation. Ejaculates were collected once per week from five Chios rams and four East Friesian rams for 12 months and stored in liquid nitrogen. Frozen-thawed semen samples were analyzed using the SCSA, to determine the DNA fragmentation index (DFI) and the percentage of cells outside the main sperm population (%DFI) in each one of the samples. Scrotal surface temperature (SST) of each ram was measured using an infrared thermometer on a daily basis. Ambient air temperature and relative humidity were recorded at hourly intervals throughout the experimental period and temperature-humidity index (THI) was used to assess the discomfort felt by the rams. Mean values of SST (SST mean) and THI (THI mean) were computed for eight different time periods (up to 61 days) preceding each ejaculation day (Day 0). A linear mixed-effect model analysis was performed to describe the relation of SCSA parameters to collection month, SST mean, and THI mean of different time periods before ejaculation. The results of the statistical analysis revealed a relation of %DFI to the SST mean of the last 12 days preceding ejaculation, namely the period that resembled the phase of epididymal maturation. On the contrary, the variation of DFI was most adequately described by the linear mixed-effect model applied for Days 54 to 48 before ejaculation, which resembled the phase of spermatogonial mitoses. The effect of collection month was significant for DFI and %DFI, with semen samples collected in September and February exhibiting the lowest DFI values; a less profound seasonal pattern was detected for %DFI. The effect of THI mean on DFI and %DFI was proven nonsignificant in regard to all time periods. In conclusion, a relation of SCSA parameters to SST mean of different periods before ejaculation was shown in the present study, implying an effect of scrotal microenvironment on intratesticular and epididymal sperm population. In contrast, we failed to detect any effect of microclimate-induced discomfort felt by the animals on the chromatin integrity of frozen-thawed ram spermatozoa.

Non-linear correlation of content and metadata information extracted from biomedical article datasets

Biomedical literature databases constitute valuable repositories of up to date scientific knowledge. The development of efficient machine learning methods in order to facilitate the organization of these databases and the extraction of novel biomedical knowledge is becoming increasingly important. Several of these methods require the representation of the documents as vectors of variables forming large multivariate datasets. Since the amount of information contained in different datasets is voluminous, an open issue is to combine information gained from various sources to a concise new dataset, which will efficiently represent the corpus of documents. This paper investigates the use of the multivariate statistical approach, called Non-Linear Canonical Correlation Analysis (NLCCA), for exploiting the correlation among the variables of different document representations and describing the documents with only one new dataset. Experiments with document datasets represented by text words, Medical Subject Headings (MeSH) and Gene Ontology (GO) terms showed the effectiveness of NLCCA.

Lag effect of microclimatic conditions on DNA integrity of frozen–thawed bovine sperm

The objective of this study was to investigate the effect of microclimatic conditions on DNA integrity of bovine sperm. DNA fragmentation of frozen-thawed sperm was analyzed in monthly semen samples of nine AI bulls ejaculating in weekly routine for one year. The extent of DNA fragmentation was determined using the Sperm Chromatin Structure Assay (SCSA™) and quantified by the DNA fragmentation index (DFI) and the percentage of sperm showing high DFI values (%DFI) immediately (0h) and 3h (3h) after thawing. Microclimatic factors (ambient air temperature, relative humidity, dew point) were recorded in hourly intervals throughout the year. Their mean values were calculated for seven different time periods (up to day 56) preceding ejaculation (day 0). DFI (P<0.01) and its relative change between 0h and 3h (P<0.05) were related to the set of microclimatic parameters recorded the last 11 days and from day 49 to 43 prior to ejaculation, respectively. A significant relationship was detected between %DFI and microclimatic parameters of days 35-29 preceding ejaculation (P<0.05), while the degree of change of %DFI from 0h to 3h was related to microclimatic parameters recorded from day 28 to 22 before ejaculation (P<0.05). Dew point and relative humidity appeared to be the strongest and weakest predictors of DNA integrity, respectively. In conclusion, the results of the present study showed a lag effect of microclimate on DNA integrity of frozen-thawed bovine sperm. However, microclimatic parameters of a single time period before ejaculation could not be identified as the source of variation of different SCSA parameters.

Competence assessment as an expert system for human resource management: A mathematical approach

Abstract Efficient human resource management needs accurate assessment and representation of available competences as well as effective mapping of required competences for specific jobs and positions. In this regard, appropriate definition and identification of competence gaps express differences between acquired and required competences. Using a detailed quantification scheme together with a mathematical approach is a way to support accurate competence analytics, which can be applied in a wide variety of sectors and fields. This article describes the combined use of software technologies and mathematical and statistical methods for assessing and analyzing competences in human resource information systems. Based on a standard competence model, which is called a Professional, Innovative and Social competence tree, the proposed framework offers flexible tools to experts in real enterprise environments, either for evaluation of employees towards an optimal job assignment and vocational training or for recruitment processes. The system has been tested with real human resource data sets in the frame of the European project called ComProFITS.

Factors Affecting Consumers in Greece to Buy During the Economic Crisis Period Food Produced Domestically in Greece

Abstract This paper aims to identify the factors that affect consumers’ purchasing behaviour towards food produced domestically in Greece (Hellenic Food) during the economic crisis in Greece. Intercept survey conducted in a random selected sample consisted of 197 consumers in summer of 2012 in Greece. Multivariate statistical analysis performed to identify consumers’ behaviour towards those food. In particular, principal components analysis (PCA) was conducted in order to identify the factors that affect people in purchasing food produced domestically in Greece. The factors that influence people in Greece to buy Hellenic food are: (a) products features (b) psychological issues, (c) economic issues. Furthermore, cluster analysis was employed to classify consumers with similar buying behaviour towards Hellenic food, and identified three groups of consumers: (a) those that support the National Economy, (b) those who are influenced by psychological issues and (c) opportunists. Discriminant analysis was performed to assess how the identified factors derived from PCA could predict cluster membership. Non parametric tests employed to profile each group of consumers with a particular buying behaviour towards food produced domestically in Greece, regarding their opinion about those products, their WTP for them and their demographic characteristics.

Measuring, archetyping and mining Olea europaea production data

Purpose – A huge amount of data are produced in the agriculture sector. Due to the huge number of these datasets it is necessary to use data analysis techniques in order to comprehend the data and extract useful information. The purpose of this paper is to measure, archetype and mine olea europaea production data.Design/methodology/approach – This work applies three different data mining techniques to data about Olea europaea var. media oblonga from the island of Thassos, at the northern part of Greece. The data were from 1,063 farmers from three different municipalities of Thassos, namely Kallirachi, Limenaria and Prinos and concerned the year 2010. They were analysed using the classification algorithm OneR, the clustering algorithm k‐means and the association rule mining algorithm, Apriori from the WEKA data mining package. Also, new measures which quantify the performance of the productions of olives and oil are applied. Finally, archetypal analysis is applied in order to distinguish the most typical/s...

Protein sequences of linked genes are highly conserved in two bacterial species

It has been shown that proteins encoded by linked genes have similar rates of evolution and that clusters of essential genes are found in regions with low recombination rates. We show here that proteins encoded by linked genes in two closely related bacterial species, namely Escherichia coli K12 and Salmonella typhimurium LT2, evolve more slowly when compared with proteins encoded by genes that are not linked as assessed by protein sequence similarity. The proteins encoded by the identified linked genes share an average sequence identity of 82.5% compared with a 46.5% identity of proteins encoded by genes that are not linked.