Table S12: Genes Identified on GISTIC on the SNP-FASST2 Segmentation Algorithm
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The G Protein-Coupled Receptor Subset of the Dog Genome Is More Similar
BMC Genomics BioMed Central Research article Open Access The G protein-coupled receptor subset of the dog genome is more similar to that in humans than rodents Tatjana Haitina1, Robert Fredriksson1, Steven M Foord2, Helgi B Schiöth*1 and David E Gloriam*2 Address: 1Department of Neuroscience, Functional Pharmacology, Uppsala University, BMC, Box 593, 751 24, Uppsala, Sweden and 2GlaxoSmithKline Pharmaceuticals, New Frontiers Science Park, 3rd Avenue, Harlow CM19 5AW, UK Email: Tatjana Haitina - [email protected]; Robert Fredriksson - [email protected]; Steven M Foord - [email protected]; Helgi B Schiöth* - [email protected]; David E Gloriam* - [email protected] * Corresponding authors Published: 15 January 2009 Received: 20 August 2008 Accepted: 15 January 2009 BMC Genomics 2009, 10:24 doi:10.1186/1471-2164-10-24 This article is available from: http://www.biomedcentral.com/1471-2164/10/24 © 2009 Haitina 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. Abstract Background: The dog is an important model organism and it is considered to be closer to humans than rodents regarding metabolism and responses to drugs. The close relationship between humans and dogs over many centuries has lead to the diversity of the canine species, important genetic discoveries and an appreciation of the effects of old age in another species. The superfamily of G protein-coupled receptors (GPCRs) is one of the largest gene families in most mammals and the most exploited in terms of drug discovery. -
Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. -
Human Recombinant Protein – TP305600
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 TP305600 ZNF165 (NM_003447) Human Recombinant Protein Product data: Product Type: Recombinant Proteins Description: Recombinant protein of human zinc finger protein 165 (ZNF165) Species: Human Expression Host: HEK293T Tag: C-Myc/DDK Predicted MW: 55.6 kDa Concentration: >50 ug/mL as determined by microplate BCA method Purity: > 80% as determined by SDS-PAGE and Coomassie blue staining Buffer: 25 mM Tris.HCl, pH 7.3, 100 mM glycine, 10% glycerol Preparation: Recombinant protein was captured through anti-DDK affinity column followed by conventional chromatography steps. Storage: Store at -80°C. Stability: Stable for 12 months from the date of receipt of the product under proper storage and handling conditions. Avoid repeated freeze-thaw cycles. RefSeq: NP_003438 Locus ID: 7718 UniProt ID: P49910, Q53Z40 RefSeq Size: 2411 Cytogenetics: 6p22.1 RefSeq ORF: 1455 Synonyms: CT53; LD65; ZSCAN7 Summary: This gene encodes a member of the Kruppel family of zinc finger proteins. Members of this DNA-binding protein family act as transcriptional regulators. This gene is located within a cluster of zinc finger family members. The encoded protein may play a role in spermatogenesis. [provided by RefSeq, Jul 2008] Protein Families: Stem cell - Pluripotency, Transcription Factors 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 ZNF165 (NM_003447) Human Recombinant Protein – TP305600 Product images: Coomassie blue staining of purified ZNF165 protein (Cat# TP305600). -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
Table SI. Genes Upregulated ≥ 2-Fold by MIH 2.4Bl Treatment Affymetrix ID
Table SI. Genes upregulated 2-fold by MIH 2.4Bl treatment Fold UniGene ID Description Affymetrix ID Entrez Gene Change 1558048_x_at 28.84 Hs.551290 231597_x_at 17.02 Hs.720692 238825_at 10.19 93953 Hs.135167 acidic repeat containing (ACRC) 203821_at 9.82 1839 Hs.799 heparin binding EGF like growth factor (HBEGF) 1559509_at 9.41 Hs.656636 202957_at 9.06 3059 Hs.14601 hematopoietic cell-specific Lyn substrate 1 (HCLS1) 202388_at 8.11 5997 Hs.78944 regulator of G-protein signaling 2 (RGS2) 213649_at 7.9 6432 Hs.309090 serine and arginine rich splicing factor 7 (SRSF7) 228262_at 7.83 256714 Hs.127951 MAP7 domain containing 2 (MAP7D2) 38037_at 7.75 1839 Hs.799 heparin binding EGF like growth factor (HBEGF) 224549_x_at 7.6 202672_s_at 7.53 467 Hs.460 activating transcription factor 3 (ATF3) 243581_at 6.94 Hs.659284 239203_at 6.9 286006 Hs.396189 leucine rich single-pass membrane protein 1 (LSMEM1) 210800_at 6.7 1678 translocase of inner mitochondrial membrane 8 homolog A (yeast) (TIMM8A) 238956_at 6.48 1943 Hs.741510 ephrin A2 (EFNA2) 242918_at 6.22 4678 Hs.319334 nuclear autoantigenic sperm protein (NASP) 224254_x_at 6.06 243509_at 6 236832_at 5.89 221442 Hs.374076 adenylate cyclase 10, soluble pseudogene 1 (ADCY10P1) 234562_x_at 5.89 Hs.675414 214093_s_at 5.88 8880 Hs.567380; far upstream element binding protein 1 (FUBP1) Hs.707742 223774_at 5.59 677825 Hs.632377 small nucleolar RNA, H/ACA box 44 (SNORA44) 234723_x_at 5.48 Hs.677287 226419_s_at 5.41 6426 Hs.710026; serine and arginine rich splicing factor 1 (SRSF1) Hs.744140 228967_at 5.37 -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
UNIVERSITY of CALIFORNIA RIVERSIDE Investigations Into The
UNIVERSITY OF CALIFORNIA RIVERSIDE Investigations into the Role of TAF1-mediated Phosphorylation in Gene Regulation A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Cell, Molecular and Developmental Biology by Brian James Gadd December 2012 Dissertation Committee: Dr. Xuan Liu, Chairperson Dr. Frank Sauer Dr. Frances M. Sladek Copyright by Brian James Gadd 2012 The Dissertation of Brian James Gadd is approved Committee Chairperson University of California, Riverside Acknowledgments I am thankful to Dr. Liu for her patience and support over the last eight years. I am deeply indebted to my committee members, Dr. Frank Sauer and Dr. Frances Sladek for the insightful comments on my research and this dissertation. Thanks goes out to CMDB, especially Dr. Bachant, Dr. Springer and Kathy Redd for their support. Thanks to all the members of the Liu lab both past and present. A very special thanks to the members of the Sauer lab, including Silvia, Stephane, David, Matt, Stephen, Ninuo, Toby, Josh, Alice, Alex and Flora. You have made all the years here fly by and made them so enjoyable. From the Sladek lab I want to thank Eugene, John, Linh and Karthi. Special thanks go out to all the friends I’ve made over the years here. Chris, Amber, Stephane and David, thank you so much for feeding me, encouraging me and keeping me sane. Thanks to the brothers for all your encouragement and prayers. To any I haven’t mentioned by name, I promise I haven’t forgotten all you’ve done for me during my graduate years. -
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. -
ATAC-Seq Footprinting Unravels Kinetics of Transcription
bioRxiv preprint doi: https://doi.org/10.1101/869560; this version posted February 27, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Beyond accessibility: ATAC-seq footprinting unravels kinetics 2 of transcription factor binding during zygotic genome 3 activation 4 Authors 5 Mette Bentsen1, Philipp Goymann1, Hendrik Schultheis1, Kathrin Klee1, Anastasiia Petrova1, 6 René Wiegandt1, Annika Fust1, Jens Preussner1,3, Carsten Kuenne1, Thomas Braun2,3, 7 Johnny Kim2,3, Mario Looso1,3 8 Affiliation 9 1 Bioinformatics Core Unit (BCU), Max Planck Institute for Heart and Lung Research, Bad 10 Nauheim, Germany 11 2 Department of Cardiac Development and Remodeling, Max-Planck-Institute for Heart and 12 Lung Research, Bad Nauheim, Germany 13 3 German Centre for Cardiovascular Research (DZHK), Partner site Rhein-Main, Frankfurt am 14 Main, 60596 Germany 15 Corresponding author email address 16 [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/869560; this version posted February 27, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 17 Abstract 18 While footprinting analysis of ATAC-seq data can theoretically enable investigation of 19 transcription factor (TF) binding, the lack of a computational tool able to conduct different 20 levels of footprinting analysis has so-far hindered the widespread application of this method. 21 Here we present TOBIAS, a comprehensive, accurate, and fast footprinting framework 22 enabling genome-wide investigation of TF binding dynamics for hundreds of TFs 23 simultaneously. -
The Tumor Suppressor Notch Inhibits Head and Neck Squamous Cell
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 12-2015 THE TUMOR SUPPRESSOR NOTCH INHIBITS HEAD AND NECK SQUAMOUS CELL CARCINOMA (HNSCC) TUMOR GROWTH AND PROGRESSION BY MODULATING PROTO-ONCOGENES AXL AND CTNNAL1 (α-CATULIN) Shhyam Moorthy Shhyam Moorthy Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Biochemistry, Biophysics, and Structural Biology Commons, Cancer Biology Commons, Cell Biology Commons, and the Medicine and Health Sciences Commons Recommended Citation Moorthy, Shhyam and Moorthy, Shhyam, "THE TUMOR SUPPRESSOR NOTCH INHIBITS HEAD AND NECK SQUAMOUS CELL CARCINOMA (HNSCC) TUMOR GROWTH AND PROGRESSION BY MODULATING PROTO-ONCOGENES AXL AND CTNNAL1 (α-CATULIN)" (2015). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 638. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/638 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]. THE TUMOR SUPPRESSOR NOTCH INHIBITS HEAD AND NECK SQUAMOUS CELL CARCINOMA (HNSCC) TUMOR GROWTH AND PROGRESSION BY MODULATING PROTO-ONCOGENES AXL AND CTNNAL1 (α-CATULIN) by Shhyam Moorthy, B.S. -
An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors
Ecology and Evolutionary Biology 2021; 6(3): 53-77 http://www.sciencepublishinggroup.com/j/eeb doi: 10.11648/j.eeb.20210603.11 ISSN: 2575-3789 (Print); ISSN: 2575-3762 (Online) An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors Miguel Angel Fuertes*, Carlos Alonso Department of Microbiology, Centre for Molecular Biology “Severo Ochoa”, Spanish National Research Council and Autonomous University, Madrid, Spain Email address: *Corresponding author To cite this article: Miguel Angel Fuertes, Carlos Alonso. An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors. Ecology and Evolutionary Biology. Vol. 6, No. 3, 2021, pp. 53-77. doi: 10.11648/j.eeb.20210603.11 Received: April 24, 2021; Accepted: May 11, 2021; Published: July 13, 2021 Abstract: Capturing conserved patterns in genes and proteins is important for inferring phenotype prediction and evolutionary analysis. The study is focused on the conserved patterns of the G protein-coupled receptors, an important superfamily of receptors. Olfactory receptors represent more than 2% of our genome and constitute the largest family of G protein-coupled receptors, a key class of drug targets. As no crystallographic structures are available, mechanistic studies rely on the use of molecular dynamic modelling combined with site-directed mutagenesis data. In this paper, we hypothesized that human-mouse orthologs coding for G protein-coupled receptors maintain, at speciation events, shared compositional structures independent, to some extent, of their percent identity as reveals a method based in the categorization of nucleotide triplets by their gross composition. The data support the consistency of the hypothesis, showing in ortholog G protein-coupled receptors the presence of emergent shared compositional structures preserved at speciation events. -
Antibody List
產品編號 產品名稱 PA569955 1110059E24Rik Polyclonal Antibody PA569956 1110059E24Rik Polyclonal Antibody PA570131 1190002N15Rik Polyclonal Antibody 01-1234-42 123count eBeads Counting Beads MA512242 14.3.3 Pan Monoclonal Antibody (CG15) LFMA0074 14-3-3 beta Monoclonal Antibody (60C10) LFPA0077 14-3-3 beta Polyclonal Antibody PA137002 14-3-3 beta Polyclonal Antibody PA14647 14-3-3 beta Polyclonal Antibody PA515477 14-3-3 beta Polyclonal Antibody PA517425 14-3-3 beta Polyclonal Antibody PA522264 14-3-3 beta Polyclonal Antibody PA529689 14-3-3 beta Polyclonal Antibody MA134561 14-3-3 beta/epsilon/zeta Monoclonal Antibody (3C8) MA125492 14-3-3 beta/zeta Monoclonal Antibody (22-IID8B) MA125665 14-3-3 beta/zeta Monoclonal Antibody (4E2) 702477 14-3-3 delta/zeta Antibody (1H9L19), ABfinity Rabbit Monoclonal 711507 14-3-3 delta/zeta Antibody (1HCLC), ABfinity Rabbit Oligoclonal 702241 14-3-3 epsilon Antibody (5H10L5), ABfinity Rabbit Monoclonal 711273 14-3-3 epsilon Antibody (5HCLC), ABfinity Rabbit Oligoclonal PA517104 14-3-3 epsilon Polyclonal Antibody PA528937 14-3-3 epsilon Polyclonal Antibody PA529773 14-3-3 epsilon Polyclonal Antibody PA575298 14-3-3 eta (Lys81) Polyclonal Antibody MA524792 14-3-3 eta Monoclonal Antibody PA528113 14-3-3 eta Polyclonal Antibody PA529774 14-3-3 eta Polyclonal Antibody PA546811 14-3-3 eta Polyclonal Antibody MA116588 14-3-3 gamma Monoclonal Antibody (HS23) MA116587 14-3-3 gamma Monoclonal Antibody (KC21) PA529690 14-3-3 gamma Polyclonal Antibody PA578233 14-3-3 gamma Polyclonal Antibody 510700 14-3-3 Pan Polyclonal