Integrative Analysis of Transcriptomic Data for Identification of T-Cell
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Toolboxes for a Standardised and Systematic Study of Glycans
Campbell et al. BMC Bioinformatics 2014, 15(Suppl 1):S9 http://www.biomedcentral.com/1471-2105/15/S1/S9 RESEARCH Open Access Toolboxes for a standardised and systematic study of glycans Matthew P Campbell1, René Ranzinger2, Thomas Lütteke3, Julien Mariethoz4, Catherine A Hayes5, Jingyu Zhang1, Yukie Akune6, Kiyoko F Aoki-Kinoshita6, David Damerell7,11, Giorgio Carta8, Will S York2, Stuart M Haslam7, Hisashi Narimatsu9, Pauline M Rudd8, Niclas G Karlsson4, Nicolle H Packer1, Frédérique Lisacek4,10* From Integrated Bio-Search: 12th International Workshop on Network Tools and Applications in Biology (NETTAB 2012) Como, Italy. 14-16 November 2012 Abstract Background: Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis. However, this information is partial, scattered and often difficult to find to for non-glycobiologists. Methods: Following our diagnosis of the causes of the slow development of glycobioinformatics, we review the “objective” difficulties encountered in defining adequate formats for representing complex entities and developing efficient analysis software. Results: Various solutions already implemented and strategies defined to bridge glycobiology with different fields and integrate the heterogeneous glyco-related information are presented. Conclusions: Despite the initial stage of our integrative efforts, this paper highlights the rapid expansion of glycomics, the validity of existing resources and the bright future of glycobioinformatics. -
Life with 6000 Genes Author(S): A. Goffeau, B. G. Barrell, H. Bussey, R
Life with 6000 Genes Author(s): A. Goffeau, B. G. Barrell, H. Bussey, R. W. Davis, B. Dujon, H. Feldmann, F. Galibert, J. D. Hoheisel, C. Jacq, M. Johnston, E. J. Louis, H. W. Mewes, Y. Murakami, P. Philippsen, H. Tettelin and S. G. Oliver Source: Science, Vol. 274, No. 5287, Genome Issue (Oct. 25, 1996), pp. 546+563-567 Published by: American Association for the Advancement of Science Stable URL: https://www.jstor.org/stable/2899628 Accessed: 28-08-2019 13:31 UTC REFERENCES Linked references are available on JSTOR for this article: https://www.jstor.org/stable/2899628?seq=1&cid=pdf-reference#references_tab_contents You may need to log in to JSTOR to access the linked references. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at https://about.jstor.org/terms American Association for the Advancement of Science is collaborating with JSTOR to digitize, preserve and extend access to Science This content downloaded from 152.3.43.41 on Wed, 28 Aug 2019 13:31:29 UTC All use subject to https://about.jstor.org/terms by FISH across the whole genome. A subset of the 37. G. D. Billingsleyet al., Am. J. Hum. Genet. 52, 343 (1994); L. -
Human Receptor-Interacting Serine/Threonine-Protein Kinase 2 (RIPK2) a Target Enabling Package (TEP)
Human Receptor-Interacting Serine/Threonine-Protein Kinase 2 (RIPK2) A Target Enabling Package (TEP) Gene ID / UniProt ID / EC 8767 / O43353 / - Target Nominator SGC Internal Nomination SGC Authors Peter Canning, Daniel M. Pinkas, Joshua C. Bufton, Sarah Picaud, Jennifer A. Ward, Catherine Rogers, Benedict-Tilman Berger, Stefan Knapp, Susanne Muller-Knapp, Paul E. Brennan, Kilian V. M. Huber, Panagis Filippakopoulos, Alex N. Bullock Collaborating Authors Matous Hrdinka1, Qui Ruan2, Chalada Suebsuwong3, Lisa Schlicher1, Bing Dai2, Jenny L. Maki2, Soumya S. Ray4, Danish Saleh5, Sameer Nikhar6, Tobias Schwerd7, Holm H.Uhlig7, Gregory D. Cuny6, Alexei Degterev2, Mads Gyrd-Hansen1 Target PI Alex N. Bullock (SGC Oxford) Therapeutic Area(s) Inflammatory diseases Disease Relevance Mutations in the NOD2-RIPK2 pathway identify RIPK2 a potential therapeutic target in auto-immune and inflammatory conditions such as Crohn’s disease, Blau syndrome, early-onset osteoarthritis and multiple sclerosis. Date Approved by TEP Evaluation 13th June 2018 Group Document version Version 3 Document version date October 2020 Citation Peter Canning, Daniel M. Pinkas, Joshua C. Bufton, Sarah Picaud, Jennifer A. Ward, Catherine Rogers, … Alex N. Bullock. (2018). Human Receptor- Interacting Serine/Threonine-Protein Kinase 2 (RIPK2); A Target Enabling Package. Zenodo. http://doi.org/10.5281/zenodo.1344501 Affiliations 1. Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford 2. Department of Developmental, Molecular & Chemical Biology, Tufts University School of Medicine 3. Department of Chemistry, Science and Research Building 2, University of Houston 4. Center for Neurologic Diseases, Department of Neurology, Brigham & Women's Hospital and Harvard Medical School 5. Medical Scientist Training Program and Program in Neuroscience, Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine 6. -
Comprehensive Analysis of CRISPR/Cas9-Mediated Mutagenesis in Arabidopsis Thaliana by Genome-Wide Sequencing
International Journal of Molecular Sciences Article Comprehensive Analysis of CRISPR/Cas9-Mediated Mutagenesis in Arabidopsis thaliana by Genome-Wide Sequencing Wenjie Xu 1,2 , Wei Fu 2, Pengyu Zhu 2, Zhihong Li 1, Chenguang Wang 2, Chaonan Wang 1,2, Yongjiang Zhang 2 and Shuifang Zhu 1,2,* 1 College of Plant Protection, China Agricultural University, Beijing 100193 China 2 Institute of Plant Quarantine, Chinese Academy of Inspection and Quarantine, Beijing 100176, China * Correspondence: [email protected] Received: 9 July 2019; Accepted: 21 August 2019; Published: 23 August 2019 Abstract: The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) system has been widely applied in functional genomics research and plant breeding. In contrast to the off-target studies of mammalian cells, there is little evidence for the common occurrence of off-target sites in plants and a great need exists for accurate detection of editing sites. Here, we summarized the precision of CRISPR/Cas9-mediated mutations for 281 targets and found that there is a preference for single nucleotide deletions/insertions and longer deletions starting from 40 nt upstream or ending at 30 nt downstream of the cleavage site, which suggested the candidate sequences for editing sites detection by whole-genome sequencing (WGS). We analyzed the on-/off-target sites of 6 CRISPR/Cas9-mediated Arabidopsis plants by the optimized method. The results showed that the on-target editing frequency ranged from 38.1% to 100%, and one off target at a frequency of 9.8%–97.3% cannot be prevented by increasing the specificity or reducing the expression level of the Cas9 enzyme. -
Choudhury 22.11.2018 Suppl
The Set1 complex is dimeric and acts with Jhd2 demethylation to convey symmetrical H3K4 trimethylation Rupam Choudhury, Sukdeep Singh, Senthil Arumugam, Assen Roguev and A. Francis Stewart Supplementary Material 9 Supplementary Figures 1 Supplementary Table – an Excel file not included in this document Extended Materials and Methods Supplementary Figure 1. Sdc1 mediated dimerization of yeast Set1 complex. (A) Multiple sequence alignment of the dimerizaton region of the protein kinase A regulatory subunit II with Dpy30 homologues and other proteins (from Roguev et al, 2001). Arrows indicate the three amino acids that were changed to alanine in sdc1*. (B) Expression levels of TAP-Set1 protein in wild type and sdc1 mutant strains evaluated by Westerns using whole cell extracts and beta-actin (B-actin) as loading control. (C) Spp1 associates with the monomeric Set1 complex. Spp1 was tagged with a Myc epitope in wild type and sdc1* strains that carried TAP-Set1. TAP-Set1 was immunoprecipitated from whole cell extracts and evaluated by Western with an anti-myc antibody. Input, whole cell extract from the TAP-set1; spp1-myc strain. W303, whole cell extract from the W303 parental strain. a Focal Volume Fluorescence signal PCH Molecular brightness comparison Intensity 25 20 Time 15 10 Frequency Brightness (au) 5 0 Intensity Intensity (counts /ms) GFP1 GFP-GFP2 Time c b 1x yEGFP 2x yEGFP 3x yEGFP 1 X yEGFP ADH1 yEGFP CYC1 2 X yEGFP ADH1 yEGFP yEGFP CYC1 3 X yEGFP ADH1 yEGFP yEGFP yEGFP CYC1 d 121-165 sdc1 wt sdc1 sdc1 Swd1-yEGFP B-Actin Supplementary Figure 2. Molecular analysis of Sdc1 mediated dimerization of Set1C by Fluorescence Correlation Spectroscopy (FCS). -
Systems Consequences of Amplicon Formation in Human Breast Cancer
Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Research Systems consequences of amplicon formation in human breast cancer Koichiro Inaki,1,2,9 Francesca Menghi,1,2,9 Xing Yi Woo,1,9 Joel P. Wagner,1,2,3 4,5 1 2 Pierre-Etienne Jacques, Yi Fang Lee, Phung Trang Shreckengast, Wendy WeiJia Soon,1 Ankit Malhotra,2 Audrey S.M. Teo,1 Axel M. Hillmer,1 Alexis Jiaying Khng,1 Xiaoan Ruan,6 Swee Hoe Ong,4 Denis Bertrand,4 Niranjan Nagarajan,4 R. Krishna Murthy Karuturi,4,7 Alfredo Hidalgo Miranda,8 andEdisonT.Liu1,2,7 1Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Genome, Singapore 138672, Singapore; 2The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06030, USA; 3Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; 4Computational and Systems Biology, Genome Institute of Singapore, Genome, Singapore 138672, Singapore; 5Universite de Sherbrooke, Sherbrooke, Quebec, J1K 2R1, Canada; 6Genome Technology and Biology, Genome Institute of Singapore, Genome, Singapore 138672, Singapore; 7The Jackson Laboratory, Bar Harbor, Maine 04609, USA; 8National Institute of Genomic Medicine, Periferico Sur 4124, Mexico City 01900, Mexico Chromosomal structural variations play an important role in determining the transcriptional landscape of human breast cancers. To assess the nature of these structural variations, we analyzed eight breast tumor samples with a focus on regions of gene amplification using mate-pair sequencing of long-insert genomic DNA with matched transcriptome profiling. We found that tandem duplications appear to be early events in tumor evolution, especially in the genesis of amplicons. -
Macrophage Activation JUNB Is a Key Transcriptional Modulator Of
JUNB Is a Key Transcriptional Modulator of Macrophage Activation Mary F. Fontana, Alyssa Baccarella, Nidhi Pancholi, Miles A. Pufall, De'Broski R. Herbert and Charles C. Kim This information is current as of October 2, 2021. J Immunol 2015; 194:177-186; Prepublished online 3 December 2014; doi: 10.4049/jimmunol.1401595 http://www.jimmunol.org/content/194/1/177 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2014/12/03/jimmunol.140159 Material 5.DCSupplemental References This article cites 40 articles, 7 of which you can access for free at: http://www.jimmunol.org/content/194/1/177.full#ref-list-1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on October 2, 2021 • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2014 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology JUNB Is a Key Transcriptional Modulator of Macrophage Activation Mary F. Fontana,* Alyssa Baccarella,* Nidhi Pancholi,* Miles A. -
RNA-‐Seq: Revelation of the Messengers
Supplementary Material Hands-On Tutorial RNA-Seq: revelation of the messengers Marcel C. Van Verk†,1, Richard Hickman†,1, Corné M.J. Pieterse1,2, Saskia C.M. Van Wees1 † Equal contributors Corresponding author: Van Wees, S.C.M. ([email protected]). Bioinformatics questions: Van Verk, M.C. ([email protected]) or Hickman, R. ([email protected]). 1 Plant-Microbe Interactions, Department of Biology, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands 2 Centre for BioSystems Genomics, PO Box 98, 6700 AB Wageningen, The Netherlands INDEX 1. RNA-Seq tools websites……………………………………………………………………………………………………………………………. 2 2. Installation notes……………………………………………………………………………………………………………………………………… 3 2.1. CASAVA 1.8.2………………………………………………………………………………………………………………………………….. 3 2.2. Samtools…………………………………………………………………………………………………………………………………………. 3 2.3. MiSO……………………………………………………………………………………………………………………………………………….. 4 3. Quality Control: FastQC……………………………………………………………………………………………………………………………. 5 4. Creating indeXes………………………………………………………………………………………………………………………………………. 5 4.1. Genome IndeX for Bowtie / TopHat alignment……………………………………………………………………………….. 5 4.2. Transcriptome IndeX for Bowtie alignment……………………………………………………………………………………… 6 4.3. Genome IndeX for BWA alignment………………………………………………………………………………………………….. 7 4.4. Transcriptome IndeX for BWA alignment………………………………………………………………………………………….7 5. Read Alignment………………………………………………………………………………………………………………………………………… 8 5.1. Preliminaries…………………………………………………………………………………………………………………………………… 8 5.2. Genome read alignment with Bowtie……………………………………………………………………………………………… -
Introduction to Bioinformatics (Elective) – SBB1609
SCHOOL OF BIO AND CHEMICAL ENGINEERING DEPARTMENT OF BIOTECHNOLOGY Unit 1 – Introduction to Bioinformatics (Elective) – SBB1609 1 I HISTORY OF BIOINFORMATICS Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biologicaldata. As an interdisciplinary field of science, bioinformatics combines computer science, statistics, mathematics, and engineering to analyze and interpret biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques. Bioinformatics derives knowledge from computer analysis of biological data. These can consist of the information stored in the genetic code, but also experimental results from various sources, patient statistics, and scientific literature. Research in bioinformatics includes method development for storage, retrieval, and analysis of the data. Bioinformatics is a rapidly developing branch of biology and is highly interdisciplinary, using techniques and concepts from informatics, statistics, mathematics, chemistry, biochemistry, physics, and linguistics. It has many practical applications in different areas of biology and medicine. Bioinformatics: Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data. Computational Biology: The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. "Classical" bioinformatics: "The mathematical, statistical and computing methods that aim to solve biological problems using DNA and amino acid sequences and related information.” The National Center for Biotechnology Information (NCBI 2001) defines bioinformatics as: "Bioinformatics is the field of science in which biology, computer science, and information technology merge into a single discipline. -
Supplementary Materials
Supplementary Materials Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR/Cas9 screening 1,† 1,† 2,3 1,3 Gabriele Picco , Elisabeth D Chen , Luz Garcia Alonso , Fiona M Behan , Emanuel 1 1 1 1 1 Gonçalves , Graham Bignell , Angela Matchan , Beiyuan Fu , Ruby Banerjee , Elizabeth 1 1 4 1,7 5,3 Anderson , Adam Butler , Cyril H Benes , Ultan McDermott , David Dow , Francesco 2,3 5,3 1 1 6,2,3 Iorio E uan Stronach , Fengtang Yang , Kosuke Yusa , Julio Saez-Rodriguez , Mathew 1,3,* J Garnett 1 Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK. 2 European Molecular Biology Laboratory – European Bioinformatics Institute, Wellcome Genome Campus, Cambridge CB10 1SD, UK. 3 Open Targets, Wellcome Genome Campus, Cambridge CB10 1SA, UK. 4 Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA. 5 GSK, Target Sciences, Gunnels Wood Road, Stevenage, SG1 2NY, UK and Collegeville, 25 Pennsylvania, 19426-0989, USA. 6 Heidelberg University, Faculty of Medicine, Institute for Computational Biomedicine, Bioquant, Heidelberg 69120, Germany. 7 AstraZeneca, CRUK Cambridge Institute, Cambridge CB2 0RE * Correspondence to: [email protected] † Equally contributing authors Supplementary Tables Supplementary Table 1: Annotation of 1,034 human cancer cell lines used in our study and the source of RNA-seq data. All cell lines are part of the GDSC cancer cell line project (see COSMIC IDs). Supplementary Table 2: List and annotation of 10,514 fusion transcripts found in 1,011 cell lines. Supplementary Table 3: Significant results from differential gene expression for recurrent fusions. Supplementary Table 4: Annotation of gene fusions for aberrant expression of the 3 prime end gene. -
Embnet Conference 2020 Programme
EMBnet Conference 2020 Bioinformatics Approaches to Precision Research 23-24 September 2020 Zoom Platform - Time 3 pm to 8 pm (CEST) Registration: https://us02web.zoom.us/meeting/register/tZEvd-mupjwiE911qtAnYln4TrNwQlxDMYm4 Programme 1st Day: 23 September 9, 2020 15:00-15:10 Welcome & Programme Presentation Domenica D’Elia & Erik Bongcam-Rudloff 15:10-15:30 Exosomes in breast milk; a beneficial genetic trojan horse from mother to child Dimitrios Vlachakis, Aspasia Efthimiadou, Flora Bacopoulou, Elias Eliopoulos, George P. Chrousos 15:30-15:50 Precision dairy farming – A Phenomenal opportunity Tomas Klingström 15:50-16:10 Genome regulation by long non-coding RNAs Katerina Pierouli, George N. Goulielmos, Elias Eliopoulos, Dimitrios Vlachakis European Molecular Biology Network (EMBnet) and Global Bioinformatics Network since 1988 16:10-16:30 Precision Epidemiology of Multi-drug resistance bacteria: bioinformatics tools J.Donato, L. Lugo, H. Perez, H. Ballen, D. Talero, S. Prada, F.Brion, V. Rincon, L. Falquet, M.T. Reguero, E. Barreto-Hernandez 16:30-16:50 Mechanisms of epigenetic inheritance in children following exposure to abuse E. Damaskopoulou, G.P. Chrousos, E. Eliopoulos, D. Vlachakis 16:50-17:00 Break 17:00-17:20 Genome-wide association studies (GWAS) in an effort to provide insights into the complex interplay of nuclear receptor transcriptional networks and their contribution to the maintenance of homeostasis Thanassis Mitsis, G.P. Chrousos, E. Eliopoulos, D.Vlachakis 17:20-17:40 Computer aided drug design and pharmacophore modelling towards the discovery of novel anti-ebola agents Kalliopi Io Diakou, G.P. Chrousos, E. Eliopoulos, D. Vlachakis 17:40-18:00 3′-Tag RNA-sequencing Andreas Gisel 18:00-18:20 Expression profiling of non-coding RNA in coronaviruses provides clues for virus RNA interference with immune system response Arianna Consiglio, V.F. -
Targeting RIP Kinases in Chronic Inflammatory Disease
biomolecules Review Targeting RIP Kinases in Chronic Inflammatory Disease Mary Speir 1,2, Tirta M. Djajawi 1,2 , Stephanie A. Conos 1,2, Hazel Tye 1 and Kate E. Lawlor 1,2,* 1 Centre for Innate Immunity and Infectious Diseases, Hudson Institute of Medical Research, Clayton, VIC 3168, Australia; [email protected] (M.S.); [email protected] (T.M.D.); [email protected] (S.A.C.); [email protected] (H.T.) 2 Department of Molecular and Translational Science, Monash University, Clayton, VIC 3168, Australia * Correspondence: [email protected]; Tel.: +61-85722700 Abstract: Chronic inflammatory disorders are characterised by aberrant and exaggerated inflam- matory immune cell responses. Modes of extrinsic cell death, apoptosis and necroptosis, have now been shown to be potent drivers of deleterious inflammation, and mutations in core repressors of these pathways underlie many autoinflammatory disorders. The receptor-interacting protein (RIP) kinases, RIPK1 and RIPK3, are integral players in extrinsic cell death signalling by regulating the production of pro-inflammatory cytokines, such as tumour necrosis factor (TNF), and coordinating the activation of the NOD-like receptor protein 3 (NLRP3) inflammasome, which underpin patholog- ical inflammation in numerous chronic inflammatory disorders. In this review, we firstly give an overview of the inflammatory cell death pathways regulated by RIPK1 and RIPK3. We then discuss how dysregulated signalling along these pathways can contribute to chronic inflammatory disorders of the joints, skin, and gastrointestinal tract, and discuss the emerging evidence for targeting these RIP kinases in the clinic. Keywords: apoptosis; necroptosis; RIP kinases; chronic inflammatory disease; tumour necrosis factor; Citation: Speir, M.; Djajawi, T.M.; interleukin-1 Conos, S.A.; Tye, H.; Lawlor, K.E.