Interactome Analyses Revealed That the U1 Snrnp Machinery Overlaps Extensively with the RNAP II Machinery and Contains Multiple
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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. -
NCAPD3 Antibody (C-Term) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP16786B
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 NCAPD3 Antibody (C-term) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP16786B Specification NCAPD3 Antibody (C-term) - Product Information Application WB,E Primary Accession P42695 Other Accession NP_056076.1 Reactivity Human Host Rabbit Clonality Polyclonal Isotype Rabbit Ig Calculated MW 168891 Antigen Region 1050-1078 NCAPD3 Antibody (C-term) - Additional Information NCAPD3 Antibody (C-term) (Cat. Gene ID 23310 #AP16786b) western blot analysis in K562 cell line lysates (35ug/lane).This Other Names Condensin-2 complex subunit D3, Non-SMC demonstrates the NCAPD3 antibody detected condensin II complex subunit D3, hCAP-D3, the NCAPD3 protein (arrow). NCAPD3, CAPD3, KIAA0056 Target/Specificity NCAPD3 Antibody (C-term) - Background This NCAPD3 antibody is generated from rabbits immunized with a KLH conjugated Condensin complexes I and II play essential synthetic peptide between 1050-1078 roles in amino acids from the C-terminal region of mitotic chromosome assembly and human NCAPD3. segregation. Both condensins contain 2 invariant structural maintenance of Dilution chromosome (SMC) WB~~1:1000 subunits, SMC2 (MIM 605576) and SMC4 (MIM 605575), but they contain Format different sets of non-SMC subunits. NCAPD3 is Purified polyclonal antibody supplied in PBS 1 of 3 non-SMC with 0.09% (W/V) sodium azide. This subunits that define condensin II (Ono et al., antibody is purified through a protein A 2003 [PubMed column, followed by peptide affinity 14532007]). purification. NCAPD3 Antibody (C-term) - References Storage Maintain refrigerated at 2-8°C for up to 2 Rose, J.E., et al. -
A Commercial Antibody to the Human Condensin II Subunit NCAPH2 Cross-Reacts with a SWI/SNF Complex Component
bioRxiv preprint doi: https://doi.org/10.1101/2020.11.07.372599; this version posted November 9, 2020. 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-ND 4.0 International license. A commercial antibody to the human condensin II subunit NCAPH2 cross-reacts with a SWI/SNF complex component Erin E. Cutts1*, Gillian C Taylor2*, Mercedes Pardo1, Lu Yu1, Jimi C Wills3, Jyoti S. Choudhary1, Alessandro Vannini1#, Andrew J Wood2# 1 Division of Structural Biology, The Institute of Cancer Research, London SW7 3RP, United Kingdom 2 MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, EH4 2XU, UK. 3 Cancer Research UK Edinburgh Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK. * Equal contribution # correspondence to: [email protected], [email protected]. Summary Condensin complexes compact and disentangle chromosomes in preparation for cell division. Commercially available antibodies raised against condensin subunits have been widely used to characterise their cellular interactome. Here we have assessed the specificity of a polyclonal antibody (Bethyl A302- 276A) that is commonly used as a probe for NCAPH2, the kleisin subunit of condensin II, in mammalian cells. We find that, in addition to its intended target, this antibody cross-reacts with one or more components of the SWI/SNF family of chromatin remodelling complexes in an NCAPH2- independent manner. This cross-reactivity with an abundant chromatin- associated factor is likely to affect the interpretation of protein and chromatin immunoprecipitation experiments that make use of this antibody probe. -
Condensation of Prometaphase Chromo-Somes
Condensation of Prometaphase Chromo- somes D'Eustachio, P., Matthews, L., Orlic-Milacic, M. European Bioinformatics Institute, New York University Langone Medical Center, Ontario Institute for Cancer Research, Oregon Health and Science University. The contents of this document may be freely copied and distributed in any media, provided the authors, plus the institutions, are credited, as stated under the terms of Creative Commons Attribution 4.0 Inter- national (CC BY 4.0) License. For more information see our license. 09/03/2019 Introduction Reactome is open-source, open access, manually curated and peer-reviewed pathway database. Pathway annotations are authored by expert biologists, in collaboration with Reactome editorial staff and cross- referenced to many bioinformatics databases. A system of evidence tracking ensures that all assertions are backed up by the primary literature. Reactome is used by clinicians, geneticists, genomics research- ers, and molecular biologists to interpret the results of high-throughput experimental studies, by bioin- formaticians seeking to develop novel algorithms for mining knowledge from genomic studies, and by systems biologists building predictive models of normal and disease variant pathways. The development of Reactome is supported by grants from the US National Institutes of Health (P41 HG003751), University of Toronto (CFREF Medicine by Design), European Union (EU STRP, EMI-CD), and the European Molecular Biology Laboratory (EBI Industry program). Literature references Fabregat, A., Sidiropoulos, K., Viteri, G., Forner, O., Marin-Garcia, P., Arnau, V. et al. (2017). Reactome pathway ana- lysis: a high-performance in-memory approach. BMC bioinformatics, 18, 142. ↗ Sidiropoulos, K., Viteri, G., Sevilla, C., Jupe, S., Webber, M., Orlic-Milacic, M. -
A Yeast Phenomic Model for the Influence of Warburg Metabolism on Genetic Buffering of Doxorubicin Sean M
Santos and Hartman Cancer & Metabolism (2019) 7:9 https://doi.org/10.1186/s40170-019-0201-3 RESEARCH Open Access A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin Sean M. Santos and John L. Hartman IV* Abstract Background: The influence of the Warburg phenomenon on chemotherapy response is unknown. Saccharomyces cerevisiae mimics the Warburg effect, repressing respiration in the presence of adequate glucose. Yeast phenomic experiments were conducted to assess potential influences of Warburg metabolism on gene-drug interaction underlying the cellular response to doxorubicin. Homologous genes from yeast phenomic and cancer pharmacogenomics data were analyzed to infer evolutionary conservation of gene-drug interaction and predict therapeutic relevance. Methods: Cell proliferation phenotypes (CPPs) of the yeast gene knockout/knockdown library were measured by quantitative high-throughput cell array phenotyping (Q-HTCP), treating with escalating doxorubicin concentrations under conditions of respiratory or glycolytic metabolism. Doxorubicin-gene interaction was quantified by departure of CPPs observed for the doxorubicin-treated mutant strain from that expected based on an interaction model. Recursive expectation-maximization clustering (REMc) and Gene Ontology (GO)-based analyses of interactions identified functional biological modules that differentially buffer or promote doxorubicin cytotoxicity with respect to Warburg metabolism. Yeast phenomic and cancer pharmacogenomics data were integrated to predict differential gene expression causally influencing doxorubicin anti-tumor efficacy. Results: Yeast compromised for genes functioning in chromatin organization, and several other cellular processes are more resistant to doxorubicin under glycolytic conditions. Thus, the Warburg transition appears to alleviate requirements for cellular functions that buffer doxorubicin cytotoxicity in a respiratory context. -
Identification and Validation of an Immune-Associated RNA-Binding Proteins Signature to Predict Clinical Outcomes and Therapeuti
cancers Article Identification and Validation of an Immune-Associated RNA-Binding Proteins Signature to Predict Clinical Outcomes and Therapeutic Responses in Glioma Patients Ruotong Tian 1,† , Yimin Li 2,†, Qian Liu 1 and Minfeng Shu 1,* 1 Department of Pharmacology, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, No.131 Dong’an Road, Xuhui District, Shanghai 200032, China; [email protected] (R.T.); [email protected] (Q.L.) 2 Department of Pathology, Fudan University Shanghai Cancer Center, No.270 Dong’an Road, Xuhui District, Shanghai 200032, China; [email protected] * Correspondence: [email protected]; Tel.: +86-21-54237380-2 † These authors contributed equally to this work. Simple Summary: Both of tumor-infiltrating immune cells and the RNA-binding proteins (RBPs) that are able to mediate immune infiltration contribute to the prognosis of patients with glioma. However, immune-associated RBPs in glioma remain unexplored. In this study, we developed a method to identify RBPs associated with immune infiltration in glioma and 216 RBPs were defined as immune- associated RBPs. Among them, eight RBPs were selected to construct a risk signature that proved to be a novel and independent prognostic factor. Higher risk scores meant worse overall survival and higher expression of human leukocyte antigen and immune checkpoints. Additionally, analyses of pathway enrichment, somatic mutation, copy number variations, and immuno-/chemotherapeutic Citation: Tian, R.; Li, Y.; Liu, Q.; Shu, response prediction were performed to evaluate the differences between high- and low-risk groups. M. Identification and Validation of an Generally, we demonstrated an eight immune-associated RBPs prognostic signature that was valuable Immune-Associated RNA-Binding in predicting the survival of glioma patients and directing immunotherapy and chemotherapy. -