CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Bioinformatic
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Human OMG Blocking Peptide (CDBP2120) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use
Human OMG blocking peptide (CDBP2120) This product is for research use only and is not intended for diagnostic use. PRODUCT INFORMATION Product Overview Blocking/Immunizing peptide for anti-OMG antibody Antigen Description OMG (oligodendrocyte myelin glycoprotein) is a protein-coding gene. Diseases associated with OMG include patulous eustachian tube, and internuclear ophthalmoplegia, and among its related super-pathways are p75NTR regulates axonogenesis and Development MAG-dependent inhibition of neurite outgrowth. GO annotations related to this gene include identical protein binding. Nature Synthetic Expression System N/A Species Human Species Reactivity Human Conjugate Unconjugated Applications Apuri, BL, ELISA Procedure None Format Lyophilized powder Size 100 μg Preservative None Storage Shipped at ambient temperature, store at -20°C. ANTIGEN GENE INFORMATION Gene Name OMG oligodendrocyte myelin glycoprotein [ Homo sapiens ] Official Symbol OMG Synonyms OMG; oligodendrocyte myelin glycoprotein; oligodendrocyte-myelin glycoprotein; OMGP; Entrez Gene ID 4974 mRNA Refseq NM_002544 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 1 © Creative Diagnostics All Rights Reserved Protein Refseq NP_002535 UniProt ID P23515 Chromosome Location 17q11-q12 Pathway Axonal growth inhibition (RHOA activation), organism-specific biosystem; Signal Transduction, organism-specific biosystem; Signalling by NGF, organism-specific biosystem; p75 NTR receptor-mediated signalling, organism-specific biosystem; p75(NTR)-mediated signaling, organism-specific biosystem; p75NTR regulates axonogenesis, organism-specific biosystem; Function identical protein binding; 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 2 © Creative Diagnostics All Rights Reserved. -
Primepcr™Assay Validation Report
PrimePCR™Assay Validation Report Gene Information Gene Name Protein EVI2B Gene Symbol Evi2b Organism Mouse Gene Summary Description Not Available Gene Aliases Evi-2, Evi2 RefSeq Accession No. NC_000077.6, NT_096135.6 UniGene ID Not Available Ensembl Gene ID ENSMUSG00000093938 Entrez Gene ID 216984 Assay Information Unique Assay ID qMmuCEP0062720 Assay Type Probe - Validation information is for the primer pair using SYBR® Green detection Detected Coding Transcript(s) ENSMUST00000179322, ENSMUST00000170422 Amplicon Context Sequence ACAGTATAATCATGAGTATAGCTACCAACATAGAAATTATAATAGTACCGATTAAT ATGGCAGCAATTGCATTGTGGTTGTTTTTATGAGCAGTTCCTTTGCCACTTGGTG GTTCTGAAGTGAGTGGTGGTGGTGGTGGTGGTG Amplicon Length (bp) 114 Chromosome Location 11:79516072-79516215 Assay Design Exonic Purification Desalted Validation Results Efficiency (%) 95 R2 0.9997 cDNA Cq 22.69 cDNA Tm (Celsius) 79 gDNA Cq 24.61 Specificity (%) 49.93 Information to assist with data interpretation is provided at the end of this report. Page 1/4 PrimePCR™Assay Validation Report Evi2b, Mouse Amplification Plot Amplification of cDNA generated from 25 ng of universal reference RNA Melt Peak Melt curve analysis of above amplification Standard Curve Standard curve generated using 20 million copies of template diluted 10-fold to 20 copies Page 2/4 PrimePCR™Assay Validation Report Products used to generate validation data Real-Time PCR Instrument CFX384 Real-Time PCR Detection System Reverse Transcription Reagent iScript™ Advanced cDNA Synthesis Kit for RT-qPCR Real-Time PCR Supermix SsoAdvanced™ SYBR® Green Supermix Experimental Sample qPCR Mouse Reference Total RNA Data Interpretation Unique Assay ID This is a unique identifier that can be used to identify the assay in the literature and online. Detected Coding Transcript(s) This is a list of the Ensembl transcript ID(s) that this assay will detect. -
Discoveryspace: an Interactive Data Analysis Application
Open Access Software2007RobertsonetVolume al. 8, Issue 1, Article R6 DiscoverySpace: an interactive data analysis application comment Neil Robertson, Mehrdad Oveisi-Fordorei, Scott D Zuyderduyn, Richard J Varhol, Christopher Fjell, Marco Marra, Steven Jones and Asim Siddiqui Address: Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Research Centre (BCCRC), British Columbia Cancer Agency (BCCA), Vancouver, BC, Canada. reviews Correspondence: Neil Robertson. Email: [email protected]. Mehrdad Oveisi-Fordorei. Email: [email protected]. Asim Siddiqui. Email: [email protected] Published: 08 January 2007 Received: 24 March 2006 Revised: 4 July 2006 Genome Biology 2007, 8:R6 (doi:10.1186/gb-2007-8-1-r6) Accepted: 8 January 2007 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2007/8/1/R6 reports © 2007 Robertson et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Interactive<p>DiscoverySpace, data analysis a graphical application for bioinformatics data analysis, in particular analysis of SAGE data, is described</p> deposited research Abstract DiscoverySpace is a graphical application for bioinformatics data analysis. Users can seamlessly traverse references between biological databases and draw together annotations in an intuitive tabular interface. Datasets can be compared using a suite of novel tools to aid in the identification of significant patterns. DiscoverySpace is of broad utility and its particular strength is in the analysis of serial analysis of gene expression (SAGE) data. -
In This Table Protein Name, Uniprot Code, Gene Name P-Value
Supplementary Table S1: In this table protein name, uniprot code, gene name p-value and Fold change (FC) for each comparison are shown, for 299 of the 301 significantly regulated proteins found in both comparisons (p-value<0.01, fold change (FC) >+/-0.37) ALS versus control and FTLD-U versus control. Two uncharacterized proteins have been excluded from this list Protein name Uniprot Gene name p value FC FTLD-U p value FC ALS FTLD-U ALS Cytochrome b-c1 complex P14927 UQCRB 1.534E-03 -1.591E+00 6.005E-04 -1.639E+00 subunit 7 NADH dehydrogenase O95182 NDUFA7 4.127E-04 -9.471E-01 3.467E-05 -1.643E+00 [ubiquinone] 1 alpha subcomplex subunit 7 NADH dehydrogenase O43678 NDUFA2 3.230E-04 -9.145E-01 2.113E-04 -1.450E+00 [ubiquinone] 1 alpha subcomplex subunit 2 NADH dehydrogenase O43920 NDUFS5 1.769E-04 -8.829E-01 3.235E-05 -1.007E+00 [ubiquinone] iron-sulfur protein 5 ARF GTPase-activating A0A0C4DGN6 GIT1 1.306E-03 -8.810E-01 1.115E-03 -7.228E-01 protein GIT1 Methylglutaconyl-CoA Q13825 AUH 6.097E-04 -7.666E-01 5.619E-06 -1.178E+00 hydratase, mitochondrial ADP/ATP translocase 1 P12235 SLC25A4 6.068E-03 -6.095E-01 3.595E-04 -1.011E+00 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 Protein kinase C and casein Q9BY11 PACSIN1 3.837E-03 -5.863E-01 3.680E-06 -1.824E+00 kinase substrate in neurons protein 1 Tubulin polymerization- O94811 TPPP 6.466E-03 -5.755E-01 6.943E-06 -1.169E+00 promoting protein MIC C9JRZ6 CHCHD3 2.912E-02 -6.187E-01 2.195E-03 -9.781E-01 Mitochondrial 2- -
Associated Fibroblasts in Non-Small Cell Lung Cancer
Prognostic gene-expression signature of carcinoma- associated fibroblasts in non-small cell lung cancer Roya Navaba,1, Dan Strumpfa,1, Bizhan Bandarchia,1, Chang-Qi Zhua,1, Melania Pintiliea, Varune Rohan Ramnarinea, Emin Ibrahimova, Nikolina Radulovicha, Lisa Leunga, Malgorzata Barczyka,b, Devang Panchala, Christine Toa, James J. Yuna, Sandy Dera, Frances A. Shepherda,c, Igor Jurisicaa,d,e, and Ming-Sound Tsaoa,e,f,2 aThe Campbell Family Institute for Cancer Research, Ontario Cancer Institute at Princess Margaret Hospital, University Health Network, Toronto, ON, Canada M5G 2M9; bDepartment of Biomedicine, Jonas Lies vei, N-5009 Bergen, Norway; Departments of cMedicine, dComputer Science, and eMedical Biophysics, and fLaboratory of Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada M5A 2N4 Edited* by Tak Wah Mak, The Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute at Princess Margaret Hospital, University Health Network, Toronto, ON, Canada, and approved March 10, 2011 (received for review September 28, 2010) The tumor microenvironment strongly influences cancer develop- Results ment, progression, and metastasis. The role of carcinoma-associated Cultured CAFs Display Features of Myofibroblasts. By using a study fibroblasts (CAFs) in these processes and their clinical impact has protocol approved by the Institutional Research Ethics Board, not been studied systematically in non-small cell lung carcinoma CAFs and NFs were cultured from 15 surgically resected primary (NSCLC). We established primary cultures of CAFs and matched nor- NSCLCs, and the histologically confirmed normal lung tissue was mal fibroblasts (NFs) from 15 resected NSCLC. We demonstrate that obtained from the same lobe (Table S1A). Both the primary CAFs have greater ability than NFs to enhance the tumorigenicity of cultured CAFs and tumor stromal fibroblasts expressed α-smooth lung cancer cell lines. -
Review Article J Med Genet: First Published As 10.1136/Jmg.33.1.2 on 1 January 1996
2 J7 Med Genet 1996;33:2-17 Review article J Med Genet: first published as 10.1136/jmg.33.1.2 on 1 January 1996. Downloaded from Molecular genetics of neurofibromatosis type 1 (NFl) Ming Hong Shen, Peter S Harper, Meena Upadhyaya Abstract several discrete entities.'` At least two dis- Neurofibromatosis type 1 (NF1), also tinctive forms, neurofibromatosis type 1 (NF1) called von Recklinghausen disease or peri- and neurofibromatosis type 2 (NF2), were re- pheral neurofibromatosis, is a common cognised and later confirmed by the cloning of autosomal dominant disorder char- two separate genes, the NF1 gene on chro- acterised by multiple neurofibromas, cafe mosome 1746 and the NF2 gene on chro- au lait spots, and Lisch nodules ofthe iris, mosome 22.78 Other NF related syndromes with a variable clinical expression. The were also reported, such as segmental NF,9 gene responsible for this condition, NF1, Watson syndrome,'0 Noonan syndrome," has been isolated by positional cloning. spinal NF,'2 familial cafe au lait spots It spans over 350kb of genomic DNA in (CLS)," and Schwannomatosis.'4 It remains chromosomal region 17qll.2 and encodes to be determined whether such disorders are an mRNA of 11-13 kb containing at least genetically discrete. 59 exons. NFI is widely expressed in a NFl, also called von Recklinghausen disease variety of human and rat tissues. Four or peripheral neurofibromatosis, is a common alternatively spliced NFI transcripts have autosomal dominant disorder affecting about been identified. Three of these transcript 1 in 3000 to 5000 people. It exhibits full pene- isoforms (each with an extra exon: 9br, trance and a high mutation rate with 30 to 23a, and 48a, respectively) show differ- 50% ofNFl patients representing a new muta- ential expression to some extent in various tion. -
ID AKI Vs Control Fold Change P Value Symbol Entrez Gene Name *In
ID AKI vs control P value Symbol Entrez Gene Name *In case of multiple probesets per gene, one with the highest fold change was selected. Fold Change 208083_s_at 7.88 0.000932 ITGB6 integrin, beta 6 202376_at 6.12 0.000518 SERPINA3 serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 3 1553575_at 5.62 0.0033 MT-ND6 NADH dehydrogenase, subunit 6 (complex I) 212768_s_at 5.50 0.000896 OLFM4 olfactomedin 4 206157_at 5.26 0.00177 PTX3 pentraxin 3, long 212531_at 4.26 0.00405 LCN2 lipocalin 2 215646_s_at 4.13 0.00408 VCAN versican 202018_s_at 4.12 0.0318 LTF lactotransferrin 203021_at 4.05 0.0129 SLPI secretory leukocyte peptidase inhibitor 222486_s_at 4.03 0.000329 ADAMTS1 ADAM metallopeptidase with thrombospondin type 1 motif, 1 1552439_s_at 3.82 0.000714 MEGF11 multiple EGF-like-domains 11 210602_s_at 3.74 0.000408 CDH6 cadherin 6, type 2, K-cadherin (fetal kidney) 229947_at 3.62 0.00843 PI15 peptidase inhibitor 15 204006_s_at 3.39 0.00241 FCGR3A Fc fragment of IgG, low affinity IIIa, receptor (CD16a) 202238_s_at 3.29 0.00492 NNMT nicotinamide N-methyltransferase 202917_s_at 3.20 0.00369 S100A8 S100 calcium binding protein A8 215223_s_at 3.17 0.000516 SOD2 superoxide dismutase 2, mitochondrial 204627_s_at 3.04 0.00619 ITGB3 integrin, beta 3 (platelet glycoprotein IIIa, antigen CD61) 223217_s_at 2.99 0.00397 NFKBIZ nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, zeta 231067_s_at 2.97 0.00681 AKAP12 A kinase (PRKA) anchor protein 12 224917_at 2.94 0.00256 VMP1/ mir-21likely ortholog -
Genomics and Risk Assessment | Mini-Monograph
Genomics and Risk Assessment | Mini-Monograph Database Development in Toxicogenomics: Issues and Efforts William B. Mattes,1 Syril D. Pettit,2 Susanna-Assunta Sansone,3 Pierre R. Bushel,4 and Michael D. Waters4 1Pfizer Inc, Groton, Connecticut, USA; 2ILSI Health and Environmental Sciences Institute, Washington, DC, USA; 3European Molecular Biology Laboratory–European Bioinformatics Institute, Hinxton, United Kingdom; 4National Center for Toxicogenomics, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA thousands of defined probes, each of which The marriage of toxicology and genomics has created not only opportunities but also novel infor- is intended to detect a single mRNA mole- matics challenges. As with the larger field of gene expression analysis, toxicogenomics faces the cule. The mRNA sample is labeled and problems of probe annotation and data comparison across different array platforms. hybridized to the microarray such that the Toxicogenomics studies are generally built on standard toxicology studies generating biological end signal at a given probe is related to the point data, and as such, one goal of toxicogenomics is to detect relationships between changes in amount of that particular mRNA in the sam- gene expression and in those biological parameters. These challenges are best addressed through ple. This readout characteristic makes data collection into a well-designed toxicogenomics database. A successful publicly accessible toxi- microarray-based transcript profiling particu- cogenomics database will serve as a repository for data sharing and as a resource for analysis, data larly appealing because the identities of the mining, and discussion. -
Gene Expression Specification
Gene Expression Specification October 2003 Version 1.1 formal/03-10-01 An Adopted Specification of the Object Management Group, Inc. Copyright © 2002, EMBL-EBI (European Bioinformatics Institute) Copyright © 2003 Object Management Group Copyright © 2002, Rosetta Inpharmatics USE OF SPECIFICATION - TERMS, CONDITIONS & NOTICES The material in this document details an Object Management Group specification in accordance with the terms, conditions and notices set forth below. This document does not represent a commitment to implement any portion of this specification in any company's products. The information contained in this document is subject to change without notice. LICENSES The companies listed above have granted to the Object Management Group, Inc. (OMG) a nonexclusive, royalty-free, paid up, worldwide license to copy and distribute this document and to modify this document and distribute copies of the modified version. Each of the copyright holders listed above has agreed that no person shall be deemed to have infringed the copyright in the included material of any such copyright holder by reason of having used the specification set forth herein or having conformed any computer software to the specification. Subject to all of the terms and conditions below, the owners of the copyright in this specification hereby grant you a fully-paid up, non-exclusive, nontransferable, perpetual, worldwide license (without the right to sublicense), to use this specification to create and distribute software and special purpose specifications that are based upon this specification, and to use, copy, and distribute this specification as provided under the Copyright Act; provided that: (1) both the copyright notice identified above and this permission notice appear on any copies of this specification; (2) the use of the specifications is for informational purposes and will not be copied or posted on any network computer or broadcast in any media and will not be otherwise resold or transferred for commercial purposes; and (3) no modifications are made to this specification. -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
UC Irvine UC Irvine Electronic Theses and Dissertations
UC Irvine UC Irvine Electronic Theses and Dissertations Title Generation and application of a chimeric model to examine human microglia responses to amyloid pathology Permalink https://escholarship.org/uc/item/38g5s0sj Author Hasselmann, Jonathan Publication Date 2021 Supplemental Material https://escholarship.org/uc/item/38g5s0sj#supplemental Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, IRVINE Generation and application of a chimeric model to examine human microglia responses to amyloid pathology DISSERTATION Submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY In Biological Sciences By Jonathan Hasselmann Dissertation Committee: Associate Professor Mathew Blurton-Jones, Chair Associate Professor Kim Green Professor Brian Cummings 2021 Portions of the Introduction and Chapter 2 © 2020 Wiley Periodicals, Inc. Chapter 1 and a portion of Chapter 2 © 2019 Elsevier Inc. All other materials © 2021 Jonathan Hasselmann DEDICATION To Nikki and Isla: During this journey, I have been fortunate enough to have the love and support of two of the strongest ladies I have ever met. I can say without a doubt that I would not have made it here without the two of you standing behind me. I love you both with all my heart and this achievement belongs to the two of you just as much as it belongs to me. Thank you for always having my back. ii TABLE OF CONTENTS LIST OF FIGURES .......................................................................................................................v -
Microarray Bioinformatics and Its Applications to Clinical Research
Microarray Bioinformatics and Its Applications to Clinical Research A dissertation presented to the School of Electrical and Information Engineering of the University of Sydney in fulfillment of the requirements for the degree of Doctor of Philosophy i JLI ··_L - -> ...·. ...,. by Ilene Y. Chen Acknowledgment This thesis owes its existence to the mercy, support and inspiration of many people. In the first place, having suffering from adult-onset asthma, interstitial cystitis and cold agglutinin disease, I would like to express my deepest sense of appreciation and gratitude to Professors Hong Yan and David Levy for harbouring me these last three years and providing me a place at the University of Sydney to pursue a very meaningful course of research. I am also indebted to Dr. Craig Jin, who has been a source of enthusiasm and encouragement on my research over many years. In the second place, for contexts concerning biological and medical aspects covered in this thesis, I am very indebted to Dr. Ling-Hong Tseng, Dr. Shian-Sehn Shie, Dr. Wen-Hung Chung and Professor Chyi-Long Lee at Change Gung Memorial Hospital and University of Chang Gung School of Medicine (Taoyuan, Taiwan) as well as Professor Keith Lloyd at University of Alabama School of Medicine (AL, USA). All of them have contributed substantially to this work. In the third place, I would like to thank Mrs. Inge Rogers and Mr. William Ballinger for their helpful comments and suggestions for the writing of my papers and thesis. In the fourth place, I would like to thank my swim coach, Hirota Homma.