1,721,020 research outputs found
GMIEC: A shiny application for the identification of gene-targeted drugs for precision medicine
Full text linkBackground: Precision medicine is a medical approach that takes into account individual genetic variability and often requires Next Generation Sequencing data in order to predict new treatments. Here we present GMIEC, Genomic Modules Identification et Characterization for genomics medicine, an application that is able to identify specific drugs at the level of single patient integrating multi-omics data such as RNA-sequencing, copy-number variation, methylation, Chromatin Immuno-Precipitation and Exome/Whole Genome sequencing. It is also possible to include clinical data related to each patient. GMIEC has been developed as a web-based R-Shiny platform and gives as output a table easy to use and explore. Results: We present GMIEC, a Shiny application for genomics medicine. The tool allows the users the integration of two or more multiple omics datasets (e.g. gene-expression, copy-number), at sample level, to identify groups of genes that share common genomic and corresponding drugs. We demonstrate the characteristics of our application by using it to analyze a prostate cancer data set. Conclusions: GMIEC provides a simple interface for genomics medicine. GMIEC was develop with Shiny to provide an application that does not require advanced programming skills. GMIEC consists of three sub-application for the analysis (GMIEC-AN), the visualization (GMIEC-VIS) and the exploration of results (GMIEC-RES). GMIEC is an open source software and is available at https://github.com/guidmt/GMIEC-shin
Comparison of machine learning methods to predict udder health status based on somatic cell counts in dairy cows
Full text linkBovine mastitis is one of the most important economic and health issues in dairy farms. Data collection during routine recording procedures and access to large datasets have shed the light on the possibility to use trained machine learning algorithms to predict the udder health status of cows. In this study, we compared eight different machine learning methods (Linear Discriminant Analysis, Generalized Linear Model with logit link function, Naïve Bayes, Classification and Regression Trees, k-Nearest Neighbors, Support Vector Machines, Random Forest and Neural Network) to predict udder health status of cows based on somatic cell counts. Prediction accuracies of all methods were above 75%. According to different metrics, Neural Network, Random Forest and linear methods had the best performance in predicting udder health classes at a given test-day (healthy or mastitic according to somatic cell count below or above a predefined threshold of 200,000 cells/mL) based on the cow’s milk traits recorded at previous test-day. Our findings suggest machine learning algorithms as a promising tool to improve decision making for farmers. Machine learning analysis would improve the surveillance methods and help farmers to identify in advance those cows that would possibly have high somatic cell count in the subsequent test-day
Comparative analysis of bats and rodents’ genomes suggests a relation between non-LTR retrotransposons, cancer incidence, and ageing
Full text linkThe presence in nature of species showing drastic differences in lifespan and cancer incidence has recently increased the interest of the scientific community. In particular, the adaptations and the genomic features underlying the evolution of cancer-resistant and long-lived organisms have recently focused on transposable elements (TEs). In this study, we compared the content and dynamics of TE activity in the genomes of four rodent and six bat species exhibiting different lifespans and cancer susceptibility. Mouse, rat, and guinea pig genomes (short-lived and cancer-prone organisms) were compared with that of naked mole rat (Heterocephalus glaber) which is a cancer-resistant organism and the rodent with the longest lifespan. The long-lived bats of the genera Myotis, Rhinolophus, Pteropus and Rousettus were instead compared with Molossus molossus, which is one of the organisms with the shortest lifespan among the order Chiroptera. Despite previous hypotheses stating a substantial tolerance of TEs in bats, we found that long-lived bats and the naked mole rat share a marked decrease of non-LTR retrotransposons (LINEs and SINEs) accumulation in recent evolutionary times
InstaCircos: A Web Application for Fast and Interactive Circular Visualization of Large Genomic Data (Work in Progress)
No full textOne of the most effective visualizations for genomics data is the circular one, supported by popular packages and visualization suites. Many tools are available, however most of them share a number of negative points including limited ease of installation/usage, slow performance and memory limitations (making them unfeasible for very large genomes such as the human one) and non interactivity. In this paper we present the ongoing work on InstaCircos, a web application born from the scientific collaboration between Big Data Analytics and Bioinformatics researchers and aiming at overcoming the available tools' limitations. It provides advanced visualization features through an easy to use web interface and offers interactive functionalities and near real-Time performances thanks to an integrated big data management back-end based on MongoDB
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
Mutations and Drugs Portal (MDP): A database linking drug response data and genomic information
No full textThe integration of large-scale genomic and pharmacological data from cancer cell lines promises to be effective in the discovery of new genetic markers of drug sensitivity and of clinically relevant anticancer compounds. The Mutations and Drugs Portal (MDP, http://mdp.unimore.it) is a web accessible database that combines the cell-based NCI60 pharmacological screening with genomic data extracted from the Cancer Cell Line Encyclopedia and the NCI60 DTP projects. MDP currently contains drug sensitivity data for more than 50,800 compounds, describing response to drugs across 115 cancer cell lines. To identify genomic features associated to drug response, cell line drug sensitivity data are integrated with large genomic datasets, including information on somatic mutations and transcriptional data. MDP can be queried for drugs active in cancer cell lines carrying mutations or transcriptional alterations in specific cancer genes and signaling pathways or for genetic and transcriptional profiles associated to sensitivity or resistance to a given compound. Results are presented through graphical representations with links to related data and are fully downloadable. MDP provides a user-friendly web resource to perform in-silico high-throughput screenings of thousand of compounds and facilitate the discovery of associations between genomic portraits and drug responses
VarCopy: A Visual Exploratory Data Analysis Platform for Copy Number Variation Studies
No full textThe study of such a complex phenomenon as cancer, which depends on several but unexplored and unclear factors, needs new ways to visualize, analyze and combine different data both on species characteristics and genes function. To this respect, we propose a novel platform, named VarCopy, supporting visual Exploratory Data Analysis (EDA) in the context of Copy Number Variation (CNV) data. The platform will be publicly available as a web application soon, and is, to our best knowledge, the first tool allowing visual, interactive exploration and analysis of the CNV landscape of multiple species, allowing the identification of new target genes that might be useful for biomedical research
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