1,721,040 research outputs found
A Support Vector Machine for the Discrimination of MicroRNA Precursors from Other Genomic Hairpin Structures
Full text linkMotivation: MicroRNAs (miRNAs) are endogenous, small (~ 20 nt), single-stranded, non-coding RNAs (ncRNAs) that result from the nuclear and cytoplasmic processing of transcribed precursor hairpin structures. They are increasingly recognized as playing crucial roles as post-transcriptional antisense regulators of gene expression through regulation of mRNA stability or translational efficiency. miRNAs, first reported in Caenorhabditis elegans, have been identified in the genomes of most higher organisms, including worms, flies, plants, mammals and recently in viruses.
Functional studies have shown that miRNAs play important roles in processes such as, cell proliferation, fat metabolism, apoptosis, neuronal cell fate, insulin secretion, haematopoietic differentiation and developmental regulation.
The detection of homologs of known miRNAs through comparative genomic approaches has proved relatively tractable. However, the ab-initio prediction of miRNA precursors through computational methods poses several additional difficulties, not least the fact that not all thermodynamically plausible transcribed hairpins are processed to yield mature miRNAs. It has not until now been possible to identify conserved sequence or structural elements that define consensus recognition elements for the enzymes that process miRNA precursors.
In the light of these observations we wished to develop and improve methods for the discrimination of true miRNA precursor hairpins from spurious hairpins
Methods: We have developed a SVM (Support Vector Machine) that considers up to 74 features associated with the primary and secondary structures and thermodynamic characteristics of candidate hairpin structures. We use a standard heuristic approach to optimize combinations of features used and train the SVM with sets of characterized hairpin miRNA precursors and known non-miRNA hairpins.
Results: Our SVM shows highly promising results in the discrimination of true miRNA precursors from “spurious” hairpins (typically around 95% sensitivity) in various species. In particular, our levels of false positive predictions appear to be low relative to comparable methods
MICRORNA DISCOVERY AND CHARACTERIZATION IN VITIS VINIFERA USING SMALLRNA DEEP SEQUENCING AND SUPPORT VECTOR MACHINE
Full text linkMiRNAs are small non coding RNAs that play an important role in the regulation of multiple cell events. They inhibit gene expression at post transcriptional level by binding mRNA targets that are degraded or squestred from translation.
Vitis vinifera is the first whole genome sequenced for a commercially important fruit species. Here we present the development and implementation of diverse strategies for the identification and validation of miRNAs of the grapevine. Many putative conserved microRNA precursors were identified by comparative methods and subsequently validated through high throughput smallRNA sequencing and oligonucleotide array technology. Additional bioinformatics tools were implemented for the ab-initio prediction of miRNAs and for the identification of lineage-specific miRNAs from smallRNA deep sequence data.
Materials and methods
Software to assist in the design of oligonucleotide arrays for the validation of miRNA expression in grape was developed and oligonucleotide array and deep sequencing experiments were used to confirm the expression of conserved mature miRNAs from most of these loci in at least one tissue or developmental stage.
Support Vector Machine - based software to predict novel miRNAs and to study their evolution was developed and shown to outperform similar published methods. This classifier was also incorporated into a novel approach to the analysis of smallRNA deep sequence utilizing patterns of mapping of reads on the genome. Our method performs well in the identification novel miRNAs and non-canonical miRNA-like loci.
Results
Many conserved miRNAs were identified and show strong patterns of tissue specific expression. We have shown that for many, but by no means all known miRNA precursors, evidence for primary transcript expression can be obtained from high throughput transc-riptome analysis, classically performed to follow expression levels of protein coding genes. We estimated patterns of splicing and alternative splicing of known pri-miRNA transcripts
The method developed for the identification of plant miRNA precursors from smallRNA NGS data recovers many novel, canonical miRNAs from Vitis and is capable of identifying loci producing miRNA-like smallRNAs with characteristics that are atypical of most conserved miRNAs.
The patterns of smallRNA generated from putatively lineage specific loci have been considered in the context of a current model of miRNA gene evolution
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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