Milger Et Al. Pulmonary CCR2+CD4+ T Cells Are Immune Regulatory And
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Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Differential Physiological Role of BIN1 Isoforms in Skeletal Muscle Development, Function and Regeneration
bioRxiv preprint doi: https://doi.org/10.1101/477950; this version posted December 11, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Differential physiological role of BIN1 isoforms in skeletal muscle development, function and regeneration Ivana Prokic1,2,3,4, Belinda Cowling1,2,3,4, Candice Kutchukian5, Christine Kretz1,2,3,4, Hichem Tasfaout1,2,3,4, Josiane Hergueux1,2,3,4, Olivia Wendling1,2,3,4, Arnaud Ferry10, Anne Toussaint1,2,3,4, Christos Gavriilidis1,2,3,4, Vasugi Nattarayan1,2,3,4, Catherine Koch1,2,3,4, Jeanne Lainné6,7, Roy Combe2,3,4,8, Laurent Tiret9, Vincent Jacquemond5, Fanny Pilot-Storck9, Jocelyn Laporte1,2,3,4 1Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Illkirch, France 2Centre National de la Recherche Scientifique (CNRS), UMR7104, Illkirch, France 3Institut National de la Santé et de la Recherche Médicale (INSERM), U1258, Illkirch, France 4Université de Strasbourg, Illkirch, France 5Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR-5310, INSERM U-1217, Institut NeuroMyoGène, 8 avenue Rockefeller, 69373 Lyon, France 6Sorbonne Université, INSERM, Institute of Myology, Centre of Research in Myology, UMRS 974, F- 75013, Paris, France 7Sorbonne Université, Department of Physiology, UPMC Univ Paris 06, Pitié-Salpêtrière Hospital, F- 75013, Paris, France 8CELPHEDIA-PHENOMIN, Institut Clinique de la Souris (ICS), Illkirch, France 9U955 – IMRB, Team 10 - Biology of the neuromuscular system, Inserm, UPEC, Ecole nationale vétérinaire d’Alfort, Maisons-Alfort, 94700, France 10Sorbonne Université, INSERM, Institute of Myology, Centre of Research in Myology, UMRS 794, F- 75013, Paris, France Correspondence to: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/477950; this version posted December 11, 2018. -
Datasheet PB1029 Anti-AEBP2 Antibody
Product datasheet Anti-AEBP2 Antibody Catalog Number: PB1029 BOSTER BIOLOGICAL TECHNOLOGY Special NO.1, International Enterprise Center, 2nd Guanshan Road, Wuhan, China Web: www.boster.com.cn Phone: +86 27 67845390 Fax: +86 27 67845390 Email: [email protected] Basic Information Product Name Anti-AEBP2 Antibody Gene Name AEBP2 Source Rabbit IgG Species Reactivity human,mouse,rat Tested Application WB,IHC-P,ICC/IF,FCM Contents 500ug/ml antibody with PBS ,0.02% NaN3 , 1mg BSA and 50% glycerol. Immunogen E.coli-derived human AEBP2 recombinant protein (Position: K424-Q517). Human AEBP2 shares 98.8% amino acid (aa) sequence identity with mouse AEBP2. Purification Immunogen affinity purified. Observed MW 54KD Dilution Ratios Western blot: 1:500-2000 Immunohistochemistry(Paraffin-embedded Section): 1:50-400 Immunocytochemistry/Immunofluorescence (ICC/IF): 1:50-400 Flow cytometry (FCM): 1-3μg/1x106 cells Storage 12 months from date of receipt,-20℃ as supplied.6 months 2 to 8℃ after reconstitution. Avoid repeated freezing and thawing Background Information Adipocyte Enhancer-Binding Protein is a zinc finger protein that in humans is encoded by the evolutionarily well-conserved gene AEBP2. This gene is mapped to 12p12.3. AEBP2 is a DNA-binding transcriptional repressor. It may regulate the migration and development of the neural crest cells through the PRC2-mediated epigenetic mechanism and is most likely a targeting protein for the mammalian PRC2 complex. Reference Anti-AEBP2 Antibody被引用在0文献中。 暂无引用 FOR RESEARCH USE ONLY. NOT FOR DIAGNOSTIC AND CLINICAL USE. 1 Product datasheet Anti-AEBP2 Antibody Catalog Number: PB1029 BOSTER BIOLOGICAL TECHNOLOGY Special NO.1, International Enterprise Center, 2nd Guanshan Road, Wuhan, China Web: www.boster.com.cn Phone: +86 27 67845390 Fax: +86 27 67845390 Email: [email protected] Selected Validation Data Figure 1. -
Beta-Arrestin-Mediated Signaling in the Heart
SPECIAL ARTICLE Circ J 2008; 72: 1725–1729 Beta-Arrestin-Mediated Signaling in the Heart Priyesh A. Patel, BS; Douglas G. Tilley, PhD*; Howard A. Rockman, MD*,** Beta-arrestin is a multifunctional adapter protein well known for its role in G-protein-coupled receptor (GPCR) desensitization. Exciting new evidence indicates thatβ-arrestin is also a signaling molecule capable of initiating its own G-protein-independent signaling at GPCRs. One of the best-studiedβ-arrestin signaling pathways is the one involvingβ-arrestin-dependent activation of a mitogen-activated protein kinase cascade, the extracellular regulated kinase (ERK). ERK signaling, which is classically activated by agonist stimulation of the epidermal growth factor receptor (EGFR), can be activated by a number of GPCRs in aβ-arrestin-dependent manner. Recent work in animal models of heart failure suggests thatβ-arrestin-dependent activation of EGFR/ERK signaling by theβ-1-adrenergic receptor, and possibly the angiotensin II Type 1A receptor, are cardioprotective. Hence, a new model of signaling at cardiac GPCRs has emerged and implicates classical G-protein-mediated signaling with promoting harmful remodeling in heart failure, while concurrently linkingβ-arrestin-dependent, G-protein-inde- pendent signaling with cardioprotective effects. Based on this paradigm, a new class of drugs could be identified, termed “biased ligands”, which simultaneously block harmful G-protein signaling, while also promoting cardio- protectiveβ-arrestin-dependent signaling, leading to a potential breakthrough -
BMC Evolutionary Biology Biomed Central
BMC Evolutionary Biology BioMed Central Research article Open Access On the origins of arrestin and rhodopsin Carlos E Alvarez1,2,3 Address: 1Center for Molecular and Human Genetics, The Research Institute at Nationwide Children's Hospital, Columbus, OH, 43205, USA, 2Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, 43210, USA and 3Novartis Institutes of BioMedical Research, CH-4002 Basel, Switzerland Email: Carlos E Alvarez - [email protected] Published: 29 July 2008 Received: 11 January 2008 Accepted: 29 July 2008 BMC Evolutionary Biology 2008, 8:222 doi:10.1186/1471-2148-8-222 This article is available from: http://www.biomedcentral.com/1471-2148/8/222 © 2008 Alvarez; 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. Abstract Background: G protein coupled receptors (GPCRs) are the most numerous proteins in mammalian genomes, and the most common targets of clinical drugs. However, their evolution remains enigmatic. GPCRs are intimately associated with trimeric G proteins, G protein receptor kinases, and arrestins. We conducted phylogenetic studies to reconstruct the history of arrestins. Those findings, in turn, led us to investigate the origin of the photosensory GPCR rhodopsin. Results: We found that the arrestin clan is comprised of the Spo0M protein family in archaea and bacteria, and the arrestin and Vps26 families in eukaryotes. The previously known animal arrestins are members of the visual/beta subfamily, which branched from the founding "alpha" arrestins relatively recently. -
The Role and Mechanisms of Action of Micrornas in Cancer Drug Resistance Wengong Si1,2,3, Jiaying Shen4, Huilin Zheng1,5 and Weimin Fan1,6*
Si et al. Clinical Epigenetics (2019) 11:25 https://doi.org/10.1186/s13148-018-0587-8 REVIEW Open Access The role and mechanisms of action of microRNAs in cancer drug resistance Wengong Si1,2,3, Jiaying Shen4, Huilin Zheng1,5 and Weimin Fan1,6* Abstract MicroRNAs (miRNAs) are small non-coding RNAs with a length of about 19–25 nt, which can regulate various target genes and are thus involved in the regulation of a variety of biological and pathological processes, including the formation and development of cancer. Drug resistance in cancer chemotherapy is one of the main obstacles to curing this malignant disease. Statistical data indicate that over 90% of the mortality of patients with cancer is related to drug resistance. Drug resistance of cancer chemotherapy can be caused by many mechanisms, such as decreased antitumor drug uptake, modified drug targets, altered cell cycle checkpoints, or increased DNA damage repair, among others. In recent years, many studies have shown that miRNAs are involved in the drug resistance of tumor cells by targeting drug-resistance-related genes or influencing genes related to cell proliferation, cell cycle, and apoptosis. A single miRNA often targets a number of genes, and its regulatory effect is tissue-specific. In this review, we emphasize the miRNAs that are involved in the regulation of drug resistance among different cancers and probe the mechanisms of the deregulated expression of miRNAs. The molecular targets of miRNAs and their underlying signaling pathways are also explored comprehensively. A holistic understanding of the functions of miRNAs in drug resistance will help us develop better strategies to regulate them efficiently and will finally pave the way toward better translation of miRNAs into clinics, developing them into a promising approach in cancer therapy. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
) (51) International Patent Classification: Columbia V5G 1G3
) ( (51) International Patent Classification: Columbia V5G 1G3 (CA). PANDEY, Nihar R.; 10209 A 61K 31/4525 (2006.01) C07C 39/23 (2006.01) 128A St, Surrey, British Columbia V3T 3E7 (CA). A61K 31/05 (2006.01) C07D 405/06 (2006.01) (74) Agent: ZIESCHE, Sonia et al.; Gowling WLG (Canada) A61P25/22 (2006.01) LLP, 2300 - 550 Burrard Street, Vancouver, British Colum¬ (21) International Application Number: bia V6C 2B5 (CA). PCT/CA2020/050165 (81) Designated States (unless otherwise indicated, for every (22) International Filing Date: kind of national protection av ailable) . AE, AG, AL, AM, 07 February 2020 (07.02.2020) AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, (25) Filing Language: English DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, (26) Publication Language: English HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (30) Priority Data: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, 16/270,389 07 February 2019 (07.02.2019) US OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (63) Related by continuation (CON) or continuation-in-part SC, SD, SE, SG, SK, SL, ST, SV, SY, TH, TJ, TM, TN, TR, (CIP) to earlier application: TT, TZ, UA, UG, US, UZ, VC, VN, WS, ZA, ZM, ZW. US 16/270,389 (CON) (84) Designated States (unless otherwise indicated, for every Filed on 07 Februaiy 2019 (07.02.2019) kind of regional protection available) . -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Murine Megakaryopoiesis Is Critical for P21 SCL-Mediated Regulation Of
From bloodjournal.hematologylibrary.org at UNIVERSITY OF BIRMINGHAM on March 1, 2012. For personal use only. 2011 118: 723-735 Prepublished online May 19, 2011; doi:10.1182/blood-2011-01-328765 SCL-mediated regulation of the cell-cycle regulator p21 is critical for murine megakaryopoiesis Hedia Chagraoui, Mira Kassouf, Sreemoti Banerjee, Nicolas Goardon, Kevin Clark, Ann Atzberger, Andrew C. Pearce, Radek C. Skoda, David J. P. Ferguson, Steve P. Watson, Paresh Vyas and Catherine Porcher Updated information and services can be found at: http://bloodjournal.hematologylibrary.org/content/118/3/723.full.html Articles on similar topics can be found in the following Blood collections Platelets and Thrombopoiesis (260 articles) Information about reproducing this article in parts or in its entirety may be found online at: http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#repub_requests Information about ordering reprints may be found online at: http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#reprints Information about subscriptions and ASH membership may be found online at: http://bloodjournal.hematologylibrary.org/site/subscriptions/index.xhtml Blood (print ISSN 0006-4971, online ISSN 1528-0020), is published weekly by the American Society of Hematology, 2021 L St, NW, Suite 900, Washington DC 20036. Copyright 2011 by The American Society of Hematology; all rights reserved. From bloodjournal.hematologylibrary.org at UNIVERSITY OF BIRMINGHAM on March 1, 2012. For personal use only. PLATELETS AND THROMBOPOIESIS SCL-mediated regulation of the cell-cycle regulator p21 is critical for murine megakaryopoiesis Hedia Chagraoui,1 *Mira Kassouf,1 *Sreemoti Banerjee,1 Nicolas Goardon,1 Kevin Clark,1 Ann Atzberger,1 Andrew C. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
TITLE PAGE Oxidative Stress and Response to Thymidylate Synthase
Downloaded from molpharm.aspetjournals.org at ASPET Journals on October 2, 2021 -Targeted -Targeted 1 , University of of , University SC K.W.B., South Columbia, (U.O., Carolina, This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted.