The Tree of Life miRNA Blog - microRNA Research and Industry News Faster Illumina analysis pipeline via streaming Hello BioStar, After some time working with Illumina and pipelines, I've identified a bottleneck when getting early "draft" results from a run. Figuring out how the sequencing data looks like in real time, as opposed to wait for the run to finish after ~11 days. The goal would be to get an estimate of how many reads one could expect to get for each sample, thereby guiding setup for a subsequent run for topping up the data for those samples that do not reach the required amounts. It would be help a lot if we could reduce the the wall-clock time for reaching a decision on which samples need to be re-run. When it comes to implementation, I've been thinking on a file status daemon such as Guard[1], coupled with the CASAVA/OLB tools from illumina, performing basecalling and demultiplexing as soon as the files get written to disk, without having to wait for the whole run to finish. Cheers & happy new year Bio* ! [1] [3]
Regex Tutorial—From Regex 101 to Advanced Regex An efficient rRNA removal method for RNA s... [Microb Inform Exp. 2013 The Role of MicroRNA ‘Sponges’ The research and field of microRNA (miRNA) is relatively young in molecular biology. Researchers are only beginning to ascertain the essential functional impact that miRNA serve in tissue development and disease progression. For example, miRNA can act as both oncogenic ‘oncomirs’ or as tumor-suppressor genes in cancer biology. Amazingly, those same miRNA genes can also be critical to the function and cellular homeostasis of normal progenitor and mature cells. Dr. Figure 1: (from Ebert et al.) Kluiver et al. recently published a Methods paper outlining detailed protocols for the generation of stably-expressed miRNA sponges that can contain upwards of 20+ miRNA binding sites. Sources: 1. 2. Incoming search terms for this article: Tagged as: cellular mechanisms, microrna, mirna
Ten Simple Rules for Getting Help from Online Scientific Communities Citation: Dall'Olio GM, Marino J, Schubert M, Keys KL, Stefan MI, et al. (2011) Ten Simple Rules for Getting Help from Online Scientific Communities. PLoS Comput Biol 7(9): e1002202. doi:10.1371/journal.pcbi.1002202 Editor: Philip E. Bourne, University of California San Diego, United States of America Published: September 29, 2011 Copyright: © 2011 Dall'Olio et al. Funding: GMD is supported by grants SAF-2007-63171 and BFU2010-19443 (subprogram BMC) awarded by Ministerio de Educación y Ciencia (Spain), the Direcció General de Recerca, Generalitat de Catalunya (Grup de Recerca Consolidat 2009 SGR 1101) to JB. Competing interests: The authors have declared that no competing interests exist. Introduction The increasing complexity of research requires scientists to work at the intersection of multiple fields and to face problems for which their formal education has not prepared them. Nevertheless, making proper use of these resources is not easy. Rule 1. Rule 2. Rule 3. Rule 4. Rule 5. Rule 6.
bedtools: a powerful toolset for genome arithmetic — bedtools 2.30.0 documentation Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. For example, bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. bedtools is developed in the Quinlan laboratory at the University of Utah and benefits from fantastic contributions made by scientists worldwide. We have developed a fairly comprehensive tutorial that demonstrates both the basics, as well as some more advanced examples of how bedtools can help you in your research. As of version 2.28.0, bedtools now supports the CRAM format via the use of htslib. As of version 2.18, bedtools is substantially more scalable thanks to improvements we have made in the algorithm used to process datasets that are pre-sorted by chromosome and start position. Commands used:
The rRNA methyltransferase Bud23 shows functional interaction with components of the SSU processome and RNase MRP + Author Affiliations Abstract Bud23 is responsible for the conserved methylation of G1575 of 18S rRNA, in the P-site of the small subunit of the ribosome. bud23Δ mutants have severely reduced small subunit levels and show a general failure in cleavage at site A2 during rRNA processing. Site A2 is the primary cleavage site for separating the precursors of 18S and 25S rRNAs. Footnotes Abbreviations: SSU processome, small subunit processome; IP, immunoprecipitation; TEV protease, tobacco etch virus protease; YFEG, You Favorite Essential Gene; snoRNA, small nucleolar RNA; rRNA, ribosomal RNA; GFP, green fluorescent protein; TAP, tandem affinity purification; ETS, external transcribed spacer; ITS, internal transcribed spacer; PMSF, phenylmethylsulfonyl fluoride; TCA, trichloroacetic acid; IgG, immunoglobulin G; ts, temperature sensitive
Lack of miRNA Misregulation at Early Pathological Stages in Drosophila Neurodegenerative Disease Models Anita Reinhardt1, Sébastien Feuillette2,3, Marlène Cassar4, Céline Callens4, Hélène Thomassin5, Serge Birman4, Magalie Lecourtois2,3, Christophe Antoniewski5 and Hervé Tricoire1* 1Laboratoire de Génétique du Stress et du Vieillissement, Unité de Biologie Fonctionnelle et Adaptative, CNRS EAC 4413, Université Paris Diderot, Sorbonne Paris Cité, Paris, France 2INSERM, U1079, Rouen, France 3Institute for Research and Innovation in Biomedicine, University of Rouen, Rouen, France 4Genetics and Physiopathology of Neurotransmission, Neurobiology Unit, CNRS, ESPCI ParisTech, Paris, France 5Génétique et Epigénétique de la Drosophile, UMR 7622 Biologie du Développement, UPMC-CNRS 9, Paris, France Late onset neurodegenerative diseases represent a major public health concern as the population in many countries ages. Keywords: miRNA, neurodegenerative diseases, ataxia, frontotemporal lobar degeneration, Parkinson disease, polyQ diseases, deep sequencing Edited by:
Matlab Code by Mark Schmidt (optimization, graphical models, machine learning) Summary This package contains the most recent version of various Matlab codes I released during my PhD work. I would recommend downloading and using this package if you plan on using more than one of my Matlab codes. This is because this package includes all the more recent bug-fixes and efficiency-improvements, while in making this package I have updated my old code to make it compatible with the new code and newer versions of Matlab. Further, I typically do not update the individual packages unless I am making a major change (such as the updates of minFunc and UGM). The particular packages included (from oldest to newest) are: minFunc - Function for unconstrained optimization of differentiable real-valued multivariate functions. Examples Each of the packages includes one or more demos that show how to use the code. minFunc Updates
18.04.6 LTS (Bionic Beaver) Ubuntu is distributed on three types of images described below. Desktop image The desktop image allows you to try Ubuntu without changing your computer at all, and at your option to install it permanently later. This type of image is what most people will want to use. You will need at least 1024MiB of RAM to install from this image. 64-bit PC (AMD64) desktop image Choose this if you have a computer based on the AMD64 or EM64T architecture (e.g., Athlon64, Opteron, EM64T Xeon, Core 2). Server install image The server install image allows you to install Ubuntu permanently on a computer for use as a server. 64-bit PC (AMD64) server install image A full list of available files, including BitTorrent files, can be found below. If you need help burning these images to disk, see the Image Burning Guide.
Microbial Informatics and Experimentation | Abstract | An efficient rRNA removal method for RNA sequencing in GC-rich bacteria Research Clelia Peano1*†, Alessandro Pietrelli1†, Clarissa Consolandi1, Elio Rossi2, Luca Petiti3, Letizia Tagliabue2, Gianluca De Bellis1 and Paolo Landini2 * Corresponding author: Clelia Peano clelia.peano@itb.cnr.it † Equal contributors Author Affiliations 1 Institute of Biomedical Technologies, National Research Council, Segrate, Milan, Italy 2 Department of Biosciences, University of Milan, Milan, Italy 3 Department of Medical Biotechnologies and Translational Medicine, University of Milan, Milan, Italy For all author emails, please log on. Microbial Informatics and Experimentation 2013, 3:1 doi:10.1186/2042-5783-3-1 Published: 7 January 2013 Abstract Background Next generation sequencing (NGS) technologies have revolutionized gene expression studies and functional genomics analysis. Results In this work, we tested two commercial kits for rRNA removal, either alone or in combination, on Burkholderia thailandensis. Conclusions Keywords: close