DOCSLIB.ORG

PDF Output of CLIC (Clustering by Inferred Co-Expression)

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
PDF Output of CLIC (Clustering by Inferred Co-Expression) PDF Output of CLIC (clustering by inferred co-expression) Dataset: Num of genes in input gene set: 93 Total number of genes: 16493 CLIC PDF output has three sections: 1) Overview of Co-Expression Modules (CEMs) Heatmap shows pairwise correlations between all genes in the input query gene set. Red lines shows the partition of input genes into CEMs, ordered by CEM strength. Each row shows one gene, and the brightness of squares indicates its correlations with other genes. Gene symbols are shown at left side and on the top of the heatmap. 2) Details of each CEM and its expansion CEM+ Top panel shows the posterior selection probability (dataset weights) for top GEO series datasets. Bottom panel shows the CEM genes (blue rows) as well as expanded CEM+ genes (green rows). Each column is one GEO series dataset, sorted by their posterior probability of being selected. The brightness of squares indicates the gene's correlations with CEM genes in the corresponding dataset. CEM+ includes genes that co-express with CEM genes in high-weight datasets, measured by LLR score. 3) Details of each GEO series dataset and its expression profile: Top panel shows the detailed information (e.g. title, summary) for the GEO series dataset. Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Overview of Co-Expression Modules (CEMs) with Dataset Weighting Scale of average Pearson correlations Num of Genes in Query Geneset: 93. Num of CEMs: 0. 0.0 0.2 0.4 0.6 0.8 1.0 Arfgef1 Gbf1 Rab31 Inpp5k Scoc Ap4b1 Snap25 Pcsk1n Cln3 Slc11a2 Sod3 Cpd Fbxo8 Furin Psd3 Cyth3 Crhr1 Aqp2 Birc6 Pcsk1 Atp7b Bace1 Golph3 Rab10 Prkd1 Chst2 Vamp4 Syt17 Snx9 Dpy30 5430435G22Rik Arfrp1 Atp9a D230025D16Rik Flna 5330417C22Rik Iqsec1 March9 Gsap Bicd1 Gga2 Psd2 Mon2 Gcc2 Smpd4 Optn Clasp2 Becn1 Clip3 Mlana Atp2c1 Lrrk2 Clvs1 Golga1 Rab11a D10Bwg1379e Psd Plekha8 Nmnat2 AI314180 Arfgef2 Iqsec2 Cnst Atp7a Clvs2 Iqsec3 Gga3 Fam109b Rbfox1 Tgfb2 Wipi1 Atp9b March4 Atxn2 Arl1 Cyth1 Cdh1 Rab6a Golga4 Car4 Vamp5 Cyth2 Cby1 Chac1 Stx4a Nbea Scamp1 Cltb Pifo Chst4 Fam109a Psd4 Cyth4 Arfgef1 Gbf1 Rab31 Inpp5k Scoc Ap4b1 Snap25 Pcsk1n Cln3 Slc11a2 Sod3 Cpd Fbxo8 Furin Psd3 Cyth3 Crhr1 Aqp2 Birc6 Pcsk1 Atp7b Bace1 Golph3 Rab10 Prkd1 Chst2 Vamp4 Syt17 Snx9 Dpy30 5430435G22Rik Arfrp1 Atp9a D230025D16Rik Flna 5330417C22Rik Iqsec1 March9 Gsap Bicd1 Gga2 Psd2 Mon2 Gcc2 Smpd4 Optn Clasp2 Singletons Becn1 Clip3 Mlana Atp2c1 Lrrk2 Clvs1 Golga1 Rab11a D10Bwg1379e Psd Plekha8 Nmnat2 AI314180 Arfgef2 Iqsec2 Cnst Atp7a Clvs2 Iqsec3 Gga3 Fam109b Rbfox1 Tgfb2 Wipi1 Atp9b March4 Atxn2 Arl1 Cyth1 Cdh1 Rab6a Golga4 Car4 Vamp5 Cyth2 Cby1 Chac1 Stx4a Nbea Scamp1 Cltb Pifo Chst4 Fam109a Psd4 Cyth4.
Load more

Recommended publications
  • Anti-ARL4A Antibody (ARG41291)
    Product datasheet [email protected] ARG41291 Package: 100 μl anti-ARL4A antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes ARL4A Tested Reactivity Hu, Ms, Rat Tested Application ICC/IF, IHC-P Host Rabbit Clonality Polyclonal Isotype IgG Target Name ARL4A Antigen Species Human Immunogen Recombinant fusion protein corresponding to aa. 121-200 of Human ARL4A (NP_001032241.1). Conjugation Un-conjugated Alternate Names ARL4; ADP-ribosylation factor-like protein 4A Application Instructions Application table Application Dilution ICC/IF 1:50 - 1:200 IHC-P 1:50 - 1:200 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 23 kDa Properties Form Liquid Purification Affinity purified. Buffer PBS (pH 7.3), 0.02% Sodium azide and 50% Glycerol. Preservative 0.02% Sodium azide Stabilizer 50% Glycerol Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. Note For laboratory research only, not for drug, diagnostic or other use. www.arigobio.com 1/2 Bioinformation Gene Symbol ARL4A Gene Full Name ADP-ribosylation factor-like 4A Background ADP-ribosylation factor-like 4A is a member of the ADP-ribosylation factor family of GTP-binding proteins. ARL4A is similar to ARL4C and ARL4D and each has a nuclear localization signal and an unusually high guaninine nucleotide exchange rate.
    [Show full text]
  • 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.
    [Show full text]
  • Targeting PH Domain Proteins for Cancer Therapy
    The Texas Medical Center Library DigitalCommons@TMC The University of Texas MD Anderson Cancer Center UTHealth Graduate School of The University of Texas MD Anderson Cancer Biomedical Sciences Dissertations and Theses Center UTHealth Graduate School of (Open Access) Biomedical Sciences 12-2018 Targeting PH domain proteins for cancer therapy Zhi Tan Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Bioinformatics Commons, Medicinal Chemistry and Pharmaceutics Commons, Neoplasms Commons, and the Pharmacology Commons Recommended Citation Tan, Zhi, "Targeting PH domain proteins for cancer therapy" (2018). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 910. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/910 This Dissertation (PhD) is brought to you for free and open access by the The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences at DigitalCommons@TMC. It has been accepted for inclusion in The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access) by an authorized administrator of DigitalCommons@TMC. For more information, please contact [email protected]. TARGETING PH DOMAIN PROTEINS FOR CANCER THERAPY by Zhi Tan Approval page APPROVED: _____________________________________________ Advisory Professor, Shuxing Zhang, Ph.D. _____________________________________________
    [Show full text]
  • SUPPLEMENTARY APPENDIX Inflammation Regulates Long Non-Coding RNA-PTTG1-1:1 in Myeloid Leukemia
    SUPPLEMENTARY APPENDIX Inflammation regulates long non-coding RNA-PTTG1-1:1 in myeloid leukemia Sébastien Chateauvieux, 1,2 Anthoula Gaigneaux, 1° Déborah Gérard, 1 Marion Orsini, 1 Franck Morceau, 1 Barbora Orlikova-Boyer, 1,2 Thomas Farge, 3,4 Christian Récher, 3,4,5 Jean-Emmanuel Sarry, 3,4 Mario Dicato 1 and Marc Diederich 2 °Current address: University of Luxembourg, Faculty of Science, Technology and Communication, Life Science Research Unit, Belvaux, Luxemburg. 1Laboratoire de Biologie Moléculaire et Cellulaire du Cancer, Hôpital Kirchberg, Luxembourg, Luxembourg; 2College of Pharmacy, Seoul National University, Gwanak-gu, Seoul, Korea; 3Cancer Research Center of Toulouse, UMR 1037 INSERM/ Université Toulouse III-Paul Sabatier, Toulouse, France; 4Université Toulouse III Paul Sabatier, Toulouse, France and 5Service d’Hématologie, Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopôle, Toulouse, France Correspondence: MARC DIEDERICH - [email protected] doi:10.3324/haematol.2019.217281 Supplementary data Inflammation regulates long non-coding RNA-PTTG1-1:1 in myeloid leukemia Sébastien Chateauvieux1,2, Anthoula Gaigneaux1*, Déborah Gérard1, Marion Orsini1, Franck Morceau1, Barbora Orlikova-Boyer1,2, Thomas Farge3,4, Christian Récher3,4,5, Jean-Emmanuel Sarry3,4, Mario Dicato1 and Marc Diederich2 1 Laboratoire de Biologie Moléculaire et Cellulaire du Cancer, Hôpital Kirchberg, 9, rue Edward Steichen, 2540 Luxembourg, Luxemburg; 2 College of Pharmacy, Seoul National University, 1 Gwanak-ro,
    [Show full text]
  • Gene Ontology Functional Annotations and Pleiotropy
    Network based analysis of genetic disease associations Sarah Gilman Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2013 Sarah Gilman All Rights Reserved ABSTRACT Network based analysis of genetic disease associations Sarah Gilman Despite extensive efforts and many promising early findings, genome-wide association studies have explained only a small fraction of the genetic factors contributing to common human diseases. There are many theories about where this “missing heritability” might lie, but increasingly the prevailing view is that common variants, the target of GWAS, are not solely responsible for susceptibility to common diseases and a substantial portion of human disease risk will be found among rare variants. Relatively new, such variants have not been subject to purifying selection, and therefore may be particularly pertinent for neuropsychiatric disorders and other diseases with greatly reduced fecundity. Recently, several researchers have made great progress towards uncovering the genetics behind autism and schizophrenia. By sequencing families, they have found hundreds of de novo variants occurring only in affected individuals, both large structural copy number variants and single nucleotide variants. Despite studying large cohorts there has been little recurrence among the genes implicated suggesting that many hundreds of genes may underlie these complex phenotypes. The question
    [Show full text]
  • Identification of Fusion Genes in Breast Cancer by Paired-End RNA
    Edgren et al. Genome Biology 2011, 12:R6 http://genomebiology.com/2011/12/1/R6 RESEARCH Open Access Identification of fusion genes in breast cancer by paired-end RNA-sequencing Henrik Edgren1†, Astrid Murumagi1†, Sara Kangaspeska1†, Daniel Nicorici1, Vesa Hongisto2, Kristine Kleivi2,3, Inga H Rye3, Sandra Nyberg2, Maija Wolf1, Anne-Lise Borresen-Dale1,4, Olli Kallioniemi1* Abstract Background: Until recently, chromosomal translocations and fusion genes have been an underappreciated class of mutations in solid tumors. Next-generation sequencing technologies provide an opportunity for systematic characterization of cancer cell transcriptomes, including the discovery of expressed fusion genes resulting from underlying genomic rearrangements. Results: We applied paired-end RNA-seq to identify 24 novel and 3 previously known fusion genes in breast cancer cells. Supported by an improved bioinformatic approach, we had a 95% success rate of validating gene fusions initially detected by RNA-seq. Fusion partner genes were found to contribute promoters (5’ UTR), coding sequences and 3’ UTRs. Most fusion genes were associated with copy number transitions and were particularly common in high-level DNA amplifications. This suggests that fusion events may contribute to the selective advantage provided by DNA amplifications and deletions. Some of the fusion partner genes, such as GSDMB in the TATDN1-GSDMB fusion and IKZF3 in the VAPB-IKZF3 fusion, were only detected as a fusion transcript, indicating activation of a dormant gene by the fusion event. A number of fusion gene partners have either been previously observed in oncogenic gene fusions, mostly in leukemias, or otherwise reported to be oncogenic. RNA interference-mediated knock-down of the VAPB-IKZF3 fusion gene indicated that it may be necessary for cancer cell growth and survival.
    [Show full text]
  • Identification of Genomic Targets of Krüppel-Like Factor 9 in Mouse Hippocampal
    Identification of Genomic Targets of Krüppel-like Factor 9 in Mouse Hippocampal Neurons: Evidence for a role in modulating peripheral circadian clocks by Joseph R. Knoedler A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Neuroscience) in the University of Michigan 2016 Doctoral Committee: Professor Robert J. Denver, Chair Professor Daniel Goldman Professor Diane Robins Professor Audrey Seasholtz Associate Professor Bing Ye ©Joseph R. Knoedler All Rights Reserved 2016 To my parents, who never once questioned my decision to become the other kind of doctor, And to Lucy, who has pushed me to be a better person from day one. ii Acknowledgements I have a huge number of people to thank for having made it to this point, so in no particular order: -I would like to thank my adviser, Dr. Robert J. Denver, for his guidance, encouragement, and patience over the last seven years; his mentorship has been indispensable for my growth as a scientist -I would also like to thank my committee members, Drs. Audrey Seasholtz, Dan Goldman, Diane Robins and Bing Ye, for their constructive feedback and their willingness to meet in a frequently cold, windowless room across campus from where they work -I am hugely indebted to Pia Bagamasbad and Yasuhiro Kyono for teaching me almost everything I know about molecular biology and bioinformatics, and to Arasakumar Subramani for his tireless work during the home stretch to my dissertation -I am grateful for the Neuroscience Program leadership and staff, in particular
    [Show full text]
  • UC San Diego Electronic Theses and Dissertations
    UC San Diego UC San Diego Electronic Theses and Dissertations Title Cardiac Stretch-Induced Transcriptomic Changes are Axis-Dependent Permalink https://escholarship.org/uc/item/7m04f0b0 Author Buchholz, Kyle Stephen Publication Date 2016 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Cardiac Stretch-Induced Transcriptomic Changes are Axis-Dependent A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioengineering by Kyle Stephen Buchholz Committee in Charge: Professor Jeffrey Omens, Chair Professor Andrew McCulloch, Co-Chair Professor Ju Chen Professor Karen Christman Professor Robert Ross Professor Alexander Zambon 2016 Copyright Kyle Stephen Buchholz, 2016 All rights reserved Signature Page The Dissertation of Kyle Stephen Buchholz is approved and it is acceptable in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California, San Diego 2016 iii Dedication To my beautiful wife, Rhia. iv Table of Contents Signature Page ................................................................................................................... iii Dedication .......................................................................................................................... iv Table of Contents ................................................................................................................ v List of Figures ...................................................................................................................
    [Show full text]
  • An Evaluation of Cancer Subtypes and Glioma Stem Cell Characterisation Unifying Tumour Transcriptomic Features with Cell Line Expression and Chromatin Accessibility
    An evaluation of cancer subtypes and glioma stem cell characterisation Unifying tumour transcriptomic features with cell line expression and chromatin accessibility Ewan Roderick Johnstone EMBL-EBI, Darwin College University of Cambridge This dissertation is submitted for the degree of Doctor of Philosophy Darwin College December 2016 Dedicated to Klaudyna. Declaration • I hereby declare that except where specific reference is made to the work of others, the contents of this dissertation are original and have not been submitted in whole or in part for consideration for any other degree or qualification in this, or any other university. • This dissertation is my own work and contains nothing which is the outcome of work done in collaboration with others, except as specified in the text and Acknowledge- ments. • This dissertation is typeset in LATEX using one-and-a-half spacing, contains fewer than 60,000 words including appendices, footnotes, tables and equations and has fewer than 150 figures. Ewan Roderick Johnstone December 2016 Acknowledgements This work was funded by the Biotechnology and Biological Sciences Research Council (BBSRC, Ref:1112564) and supported by the European Molecular Biology Laboratory (EMBL) and its outstation, the European Bioinformatics Institute (EBI). I have many people to thank for assistance in preparing this thesis. First and foremost I must thank my supervisor, Paul Bertone for his support and willingness to take me on as a student. My thanks are also extended to present and past members of the Bertone group, particularly Pär Engström and Remco Loos who have provided a great deal of guidance over the course of my studentship.
    [Show full text]
  • Autocrine IFN Signaling Inducing Profibrotic Fibroblast Responses By
    Downloaded from http://www.jimmunol.org/ by guest on September 23, 2021 Inducing is online at: average * The Journal of Immunology , 11 of which you can access for free at: 2013; 191:2956-2966; Prepublished online 16 from submission to initial decision 4 weeks from acceptance to publication August 2013; doi: 10.4049/jimmunol.1300376 http://www.jimmunol.org/content/191/6/2956 A Synthetic TLR3 Ligand Mitigates Profibrotic Fibroblast Responses by Autocrine IFN Signaling Feng Fang, Kohtaro Ooka, Xiaoyong Sun, Ruchi Shah, Swati Bhattacharyya, Jun Wei and John Varga J Immunol cites 49 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2013/08/20/jimmunol.130037 6.DC1 This article http://www.jimmunol.org/content/191/6/2956.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2013 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 23, 2021. The Journal of Immunology A Synthetic TLR3 Ligand Mitigates Profibrotic Fibroblast Responses by Inducing Autocrine IFN Signaling Feng Fang,* Kohtaro Ooka,* Xiaoyong Sun,† Ruchi Shah,* Swati Bhattacharyya,* Jun Wei,* and John Varga* Activation of TLR3 by exogenous microbial ligands or endogenous injury-associated ligands leads to production of type I IFN.
    [Show full text]
  • Mrna Expression in Human Leiomyoma and Eker Rats As Measured by Microarray Analysis
    Table 3S: mRNA Expression in Human Leiomyoma and Eker Rats as Measured by Microarray Analysis Human_avg Rat_avg_ PENG_ Entrez. Human_ log2_ log2_ RAPAMYCIN Gene.Symbol Gene.ID Gene Description avg_tstat Human_FDR foldChange Rat_avg_tstat Rat_FDR foldChange _DN A1BG 1 alpha-1-B glycoprotein 4.982 9.52E-05 0.68 -0.8346 0.4639 -0.38 A1CF 29974 APOBEC1 complementation factor -0.08024 0.9541 -0.02 0.9141 0.421 0.10 A2BP1 54715 ataxin 2-binding protein 1 2.811 0.01093 0.65 0.07114 0.954 -0.01 A2LD1 87769 AIG2-like domain 1 -0.3033 0.8056 -0.09 -3.365 0.005704 -0.42 A2M 2 alpha-2-macroglobulin -0.8113 0.4691 -0.03 6.02 0 1.75 A4GALT 53947 alpha 1,4-galactosyltransferase 0.4383 0.7128 0.11 6.304 0 2.30 AACS 65985 acetoacetyl-CoA synthetase 0.3595 0.7664 0.03 3.534 0.00388 0.38 AADAC 13 arylacetamide deacetylase (esterase) 0.569 0.6216 0.16 0.005588 0.9968 0.00 AADAT 51166 aminoadipate aminotransferase -0.9577 0.3876 -0.11 0.8123 0.4752 0.24 AAK1 22848 AP2 associated kinase 1 -1.261 0.2505 -0.25 0.8232 0.4689 0.12 AAMP 14 angio-associated, migratory cell protein 0.873 0.4351 0.07 1.656 0.1476 0.06 AANAT 15 arylalkylamine N-acetyltransferase -0.3998 0.7394 -0.08 0.8486 0.456 0.18 AARS 16 alanyl-tRNA synthetase 5.517 0 0.34 8.616 0 0.69 AARS2 57505 alanyl-tRNA synthetase 2, mitochondrial (putative) 1.701 0.1158 0.35 0.5011 0.6622 0.07 AARSD1 80755 alanyl-tRNA synthetase domain containing 1 4.403 9.52E-05 0.52 1.279 0.2609 0.13 AASDH 132949 aminoadipate-semialdehyde dehydrogenase -0.8921 0.4247 -0.12 -2.564 0.02993 -0.32 AASDHPPT 60496 aminoadipate-semialdehyde
    [Show full text]
  • PSCDBP (CYTIP) Rabbit Polyclonal Antibody – TA308371 | Origene
    OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TA308371 PSCDBP (CYTIP) Rabbit Polyclonal Antibody Product data: Product Type: Primary Antibodies Applications: WB Recommended Dilution: WB:1:500-1:3000 Reactivity: Human Host: Rabbit Isotype: IgG Clonality: Polyclonal Immunogen: Synthetic peptide corresponding to a region within amino acids 1 and 44 of PSCDBP (Uniprot ID#O60759) Formulation: 1XPBS, 10% Glycerol (pH7). 0.01% Thimerosal was added as a preservative. Concentration: lot specific Purification: Purified by antigen-affinity chromatography. Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 40 kDa Gene Name: cytohesin 1 interacting protein Database Link: NP_004279 Entrez Gene 9595 Human O60759 Background: The protein encoded by this gene contains 2 leucine zipper domains and a putative C- terminal nuclear targeting signal, but does not have any hydrophobic regions. This protein is expressed weakly in resting NK and T cells. The encoded protein modulates the activation of ARF genes by CYTH1. This protein interacts with CYTH1 and SNX27 proteins and may act to sequester CYTH1 protein in the cytoplasm. [provided by RefSeq] Synonyms: B3-1; CASP; CYBR; CYTHIP; HE; PSCDBP This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 PSCDBP (CYTIP) Rabbit Polyclonal Antibody – TA308371 Product images: Sample (30 ug of whole cell lysate).
    [Show full text]