57 research outputs found
SNPSTR: a database of compound microsatellite-SNP markers
There has been widespread and growing interest in genetic markers suitable for drawing population genetic inferences about past demographic events and to detect the effects of selection. In addition to single nucleotide polymorphisms (SNPs), microsatellites (or short tandem repeats, STRs) have received great attention in the analysis of human population history. In the SNPSTR database () we catalogue a relatively new type of compound genetic marker called SNPSTR which combines a microsatellite marker (STR) with one or more tightly linked SNPs. Here, the SNP(s) and the microsatellite are less than 250 bp apart so each SNPSTR can be considered a small haplotype with no recombination occurring between the two individual markers. Thus, SNPSTRs have the potential to become a very useful tool in the field of population genetics. The SNPSTR database contains all inferable human SNPSTRs as well as those in mouse, rat, dog and chicken, i.e. all model organisms for which extensive SNP datasets are available
Generating confidence intervals on biological networks
<p>Abstract</p> <p>Background</p> <p>In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interacting nodes. The structure of the network may introduce dependencies among the nodes and it will in general be necessary to account for these dependencies in the statistical analysis. To this end we require some form of Null model of the network: generally rewired replicates of the network are generated which preserve only the degree (number of interactions) of each node. We show that this can fail to capture important features of network structure, and may result in unrealistic significance levels, when potentially confounding additional information is available.</p> <p>Methods</p> <p>We present a new network resampling Null model which takes into account the degree sequence as well as available biological annotations. Using gene ontology information as an illustration we show how this information can be accounted for in the resampling approach, and the impact such information has on the assessment of statistical significance of correlations and motif-abundances in the <it>Saccharomyces cerevisiae </it>protein interaction network. An algorithm, GOcardShuffle, is introduced to allow for the efficient construction of an improved Null model for network data.</p> <p>Results</p> <p>We use the protein interaction network of <it>S. cerevisiae</it>; correlations between the evolutionary rates and expression levels of interacting proteins and their statistical significance were assessed for Null models which condition on different aspects of the available data. The novel GOcardShuffle approach results in a Null model for annotated network data which appears better to describe the properties of real biological networks.</p> <p>Conclusion</p> <p>An improved statistical approach for the statistical analysis of biological network data, which conditions on the available biological information, leads to qualitatively different results compared to approaches which ignore such annotations. In particular we demonstrate the effects of the biological organization of the network can be sufficient to explain the observed similarity of interacting proteins.</p
Trees on networks: resolving statistical patterns of phylogenetic similarities among interacting proteins
<p>Abstract</p> <p>Background</p> <p>Phylogenies capture the evolutionary ancestry linking extant species. Correlations and similarities among a set of species are mediated by and need to be understood in terms of the phylogenic tree. In a similar way it has been argued that biological networks also induce correlations among sets of interacting genes or their protein products.</p> <p>Results</p> <p>We develop suitable statistical resampling schemes that can incorporate these two potential sources of correlation into a single inferential framework. To illustrate our approach we apply it to protein interaction data in yeast and investigate whether the phylogenetic trees of interacting proteins in a panel of yeast species are more similar than would be expected by chance.</p> <p>Conclusions</p> <p>While we find only negligible evidence for such increased levels of similarities, our statistical approach allows us to resolve the previously reported contradictory results on the levels of co-evolution induced by protein-protein interactions. We conclude with a discussion as to how we may employ the statistical framework developed here in further functional and evolutionary analyses of biological networks and systems.</p
Individual identification via electrocardiogram analysis
Background: During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. Methods: We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. Results: 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Conclusions: Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations
Advances in research on the use of biochar in soil for remediation: a review
Purpose: Soil contamination mainly from human activities remains a major environmental problem in the contemporary world. Significant work has been undertaken to position biochar as a readily-available material useful for the management of contaminants in various environmental media notably soil. Here, we review the increasing research on the use of biochar in soil for the remediation of some organic and inorganic contaminants. Materials and methods: Bibliometric analysis was carried out within the past 10 years to determine the increasing trend in research related to biochar in soil for contaminant remediation. Five exemplar contaminants were reviewed in both laboratory and field-based studies. These included two inorganic (i.e., As and Pb) and three organic classes (i.e., sulfamethoxazole, atrazine, and PAHs). The contaminants were selected based on bibliometric data and as representatives of their various contaminant classes. For example, As and Pb are potentially toxic elements (anionic and cationic, respectively), while sulfamethoxazole, atrazine, and PAHs represent antibiotics, herbicides, and hydrocarbons, respectively. Results and discussion: The interaction between biochar and contaminants in soil is largely driven by biochar precursor material and pyrolysis temperature as well as some characteristics of the contaminants such as octanol-water partition coefficient (KOW) and polarity. The structural and chemical characteristics of biochar in turn determine the major sorption mechanisms and define biochar’s suitability for contaminant sorption. Based on the reviewed literature, a soil treatment plan is suggested to guide the application of biochar in various soil types (paddy soils, brownfield, and mine soils) at different pH levels (4–5.5) and contaminant concentrations ( 50 mg kg−1). Conclusions: Research on biochar has grown over the years with significant focus on its properties, and how these affect biochar’s ability to immobilize organic and inorganic contaminants in soil. Few of these studies have been field-based. More studies with greater focus on field-based soil remediation are therefore required to fully understand the behavior of biochar under natural circumstances. Other recommendations are made aimed at stimulating future research in areas where significant knowledge gaps exist
Evidence for the additions of clustered interacting nodes during the evolution of protein interaction networks from network motifs
<p>Abstract</p> <p>Background</p> <p>High-throughput screens have revealed large-scale protein interaction networks defining most cellular functions. How the proteins were added to the protein interaction network during its growth is a basic and important issue. Network motifs represent the simplest building blocks of cellular machines and are of biological significance.</p> <p>Results</p> <p>Here we study the evolution of protein interaction networks from the perspective of network motifs. We find that in current protein interaction networks, proteins of the same age class tend to form motifs and such co-origins of motif constituents are affected by their topologies and biological functions. Further, we find that the proteins within motifs whose constituents are of the same age class tend to be densely interconnected, co-evolve and share the same biological functions, and these motifs tend to be within protein complexes.</p> <p>Conclusions</p> <p>Our findings provide novel evidence for the hypothesis of the additions of clustered interacting nodes and point out network motifs, especially the motifs with the dense topology and specific function may play important roles during this process. Our results suggest functional constraints may be the underlying driving force for such additions of clustered interacting nodes.</p
Electrocardiogram Pattern Recognition and Analysis Based on Artificial Neural Networks and Support Vector Machines: A Review
Insecticidal Effect of an Enhanced Attapulgite for the Control of Four Stored-Product Beetle Species
We examined the insecticidal effect of three different dust formulations, which were atta-pulgite (W), attapulgite mix with oregano essential oil with 52% carvacrol (D1), and attapulgite mix with oregano essential oil with 75% carvacrol (D2), in four major stored-product beetle species, Sitophilus oryzae (L.), Tribolium confusum Jacquelin du Val, Rhyzopertha dominica (F.), and Trogoderma granarium Everts. Sitophilus oryzae was the most susceptible at all three formulations, followed by T. confusum and R. dominica. In contrast, T. granarium larvae showed the lowest mortality rates even on the 14th day of observation and at the highest concentration (2000 ppm). Progeny production was particularly reduced for all species relative to the controls. Nevertheless, complete suppression of the offspring was observed only in the case of T. confusum and S. oryzae, while R. dominica was less susceptible to all three dust formulations, giving an average of up to 20 individuals per vial at 2000 ppm. To our knowledge, this study is the first that has examined the insecticidal activity of oregano compounds in combination with attapulgite for the control of stored-grain insect species. Addi-tional experimentation is required to indicate the rationale of using these natural resource-based materials under a non-chemical control strategy at the post-harvest stages of agricultural commodities. © 2022 by the authors. Licensee MDPI, Basel, Switzerland
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