1,720,991 research outputs found
ProTInSeq: transposon insertion tracking by ultra-deep DNA sequencing applied to identify small and large translated ORFs
No full text<p>ProTInSeq is a novel -omics technique designed to characterize proteomes by using DNA ultra-deep sequencing. The technique is based on transposons engineered to have a positive or negative protein selection marker expressed when the transposon is inserted in-frame into a protein-coding gene. In the genome-reduced bacterium Mycoplasma pneumoniae, ProTInSeq identifies 80% of known expressed proteins, as well as 5 new open reading frames (ORFs; >100 amino acids); and 153 novel small ORF-encoded proteins (SEPs; ≤100 aa) that represent up to 18% of this bacterium’s proteome. ProTInSeq can be used to detect translational noise, for protein quantification and to provide insight into functional protein aspects such as relative half-life, stability, and membrane topology. Herein, we describe a methodology that can be easily implemented in any living system and allows the deep understanding of proteomes and more importantly the identification of small proteins by DNA ultra-sequencing.</p>
<p>We include the following files:</p>
<p>- processed_inscalling.zip: output obtain after running FASTQINS transposon calling tool over the datasets found at <a href="https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10380?key=5f54209d-ce59-490a-9bcd-7084e9c619ee">https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10380?key=5f54209d-ce59-490a-9bcd-7084e9c619ee</a>. This include every genome position in <em>M. pneumoniae</em>, the number of times an insertion has been mapped to that position and the total read count value.</p>
<p>- separated_library_metrics.zip: insertion and read count processed from processed_inscalling files associated to every ORF and intergenic region in <em>M. penumoniae. </em>Columns include frame measured (0 - whole gene, 1 - in-frame, 2 and 3 for following positions) and metric. Metrics account for number insertions in-frame (<em>I</em>), read count (<em>R</em>), linear density from non-coding regions used in the Poisson evaluation (<em>rNC</em>), probability measured (<em>sfNC</em>) and a binary for prediction (<em>pred</em>; 0 - no significant, 1 - significant).</p>
<p>- allmetrics.xlsx: merged table with the combination of results from separated_library_metrics.zip tab-delimited files.</p>
<p>- selective_metrics_allannotations.xlsx: this table includes all the available information about the 30,112 sequences that could encode for a coding sequence in <em>M. pneumoniae</em>. For each identifier (column B), we include coordinates information and nucleotide and amino acid length information (columns C-H). Column I includes the gene name when the entry is found annotated in <em>M. pneumoniae</em>. Localization and function are described in columns J and K. Column L includes the operon number in which the annotation would be expressed. We also included transcription-related information average expression (column M; as log2(gene read count/gene length) and estimated average RNA copies per cell (column N) considering 4 RNA sequencing samples covering different growth times (6, 24 and 48 hours, ArrayExpress identifier E‐MTAB‐6203). Column O accounts for the number of mass spectrometry experiments detecting that entry (to a maximum of 116) and column P accounts for the total number of unique tryptic peptides detected. This comes <a href="https://paperpile.com/c/BImj5N/eljz">[5]</a>, available for 12,426 sequences that present an amino acid length ≥19 (from 116 mass spectrometry experiments, ID PRIDE: PXD008243). Columns Q to T recapitulate protein copies per cell under different conditions (overall, extracting with urea, extracting with SDS and mean, respectively). Column U includes half-lives of the proteins. Columns V and W describe the reference density of insertion and essentiality assigned in previous studies. Column X-AA includes the predicted RanSEPs score, ribosome binding site presence, homology into seven groups: 0—no hits passed the thresholds defined; 1—conserved with an annotated function; 2—conserved as an annotated SEP in NCBI but no associated function; 3—conserved in a different species but target and homologous sequence not found in NCBI; 4—sequence is completely or partially (> 75%) repeated ≥ 3 times in the reference genome; 5—potential pseudogene; and 6—to depict those annotations that are found in the reference NCBI annotation file. , and function expected by homology, respectively. Columns AB to AD cover the output provided by Phobius, including the number of transmembrane segments, presence of signal peptide and transmembrane topology predicted by TM-HMM. Column AE includes the complex information where 1 implies that entry is functional as a monomer, 2 as dimer, and so on. Finally, columns AF-AH will be 1 if the protein is a Lon protease target, a lipoprotein, and/or a truncated gene or pseudogene, respectively, 0 otherwise. Following columns include for every sample presenting selective insertion rates in-frame using the following identifiers separated by underscores: marker (BarnB, Cm or Ery), type (control-AC or selection-BD, antibiotic concentration, sample replicate, frame measured, metric. Metrics account for number insertions in-frame (<em>I</em>), read count (<em>R</em>), linear density from non-coding regions used in the Poisson evaluation (<em>rNC</em>), probability measured (<em>sfNC</em>) and a binary for prediction (<em>pred</em>; 0 - no significant, 1 - significant). Last columns combine the number of samples each annotation has been identified. Notice for barnase library the results need to be interpreted considering it is a negative selection marker inverting the 0 and 1 meaning.</p>
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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