Table 1 the Statistical Metrics for Key Differentially Expressed Genes (Degs)
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Table S1. List of Proteins in the BAHD1 Interactome
Table S1. List of proteins in the BAHD1 interactome BAHD1 nuclear partners found in this work yeast two-hybrid screen Name Description Function Reference (a) Chromatin adapters HP1α (CBX5) chromobox homolog 5 (HP1 alpha) Binds histone H3 methylated on lysine 9 and chromatin-associated proteins (20-23) HP1β (CBX1) chromobox homolog 1 (HP1 beta) Binds histone H3 methylated on lysine 9 and chromatin-associated proteins HP1γ (CBX3) chromobox homolog 3 (HP1 gamma) Binds histone H3 methylated on lysine 9 and chromatin-associated proteins MBD1 methyl-CpG binding domain protein 1 Binds methylated CpG dinucleotide and chromatin-associated proteins (22, 24-26) Chromatin modification enzymes CHD1 chromodomain helicase DNA binding protein 1 ATP-dependent chromatin remodeling activity (27-28) HDAC5 histone deacetylase 5 Histone deacetylase activity (23,29,30) SETDB1 (ESET;KMT1E) SET domain, bifurcated 1 Histone-lysine N-methyltransferase activity (31-34) Transcription factors GTF3C2 general transcription factor IIIC, polypeptide 2, beta 110kDa Required for RNA polymerase III-mediated transcription HEYL (Hey3) hairy/enhancer-of-split related with YRPW motif-like DNA-binding transcription factor with basic helix-loop-helix domain (35) KLF10 (TIEG1) Kruppel-like factor 10 DNA-binding transcription factor with C2H2 zinc finger domain (36) NR2F1 (COUP-TFI) nuclear receptor subfamily 2, group F, member 1 DNA-binding transcription factor with C4 type zinc finger domain (ligand-regulated) (36) PEG3 paternally expressed 3 DNA-binding transcription factor with -
Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids
Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10. -
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. -
Datasheet: VPA00491 Product Details
Datasheet: VPA00491 Description: RABBIT ANTI RPLP0 Specificity: RPLP0 Format: Purified Product Type: PrecisionAb™ Polyclonal Isotype: Polyclonal IgG Quantity: 100 µl Product Details Applications This product has been reported to work in the following applications. This information is derived from testing within our laboratories, peer-reviewed publications or personal communications from the originators. Please refer to references indicated for further information. For general protocol recommendations, please visit www.bio-rad-antibodies.com/protocols. Yes No Not Determined Suggested Dilution Western Blotting 1/1000 PrecisionAb antibodies have been extensively validated for the western blot application. The antibody has been validated at the suggested dilution. Where this product has not been tested for use in a particular technique this does not necessarily exclude its use in such procedures. Further optimization may be required dependant on sample type. Target Species Human Species Cross Reacts with: Mouse, Rat Reactivity N.B. Antibody reactivity and working conditions may vary between species. Product Form Purified IgG - liquid Preparation Rabbit polyclonal antibody purified by affinity chromatography Buffer Solution Phosphate buffered saline Preservative 0.09% Sodium Azide (NaN3) Stabilisers 2% Sucrose Immunogen Synthetic peptide directed towards the N terminal region of human RPLP0 External Database Links UniProt: P05388 Related reagents Entrez Gene: 6175 RPLP0 Related reagents Specificity Rabbit anti Human RPLP0 antibody recognizes RPLP0 also known as 60S acidic ribosomal protein P0, 60S ribosomal protein L10E or acidic ribosomal phosphoprotein P0. Page 1 of 2 Ribosomes, the organelles that catalyze protein synthesis, consist of a small 40S subunit and a large 60S subunit. Together these subunits are composed of 4 RNA species and approximately 80 structurally distinct proteins. -
SOX4-Mediated Repression of Specific Trnas Inhibits Proliferation of Human Glioblastoma Cells
SOX4-mediated repression of specific tRNAs inhibits proliferation of human glioblastoma cells Jianjing Yanga,b,c, Derek K. Smithc,d, Haoqi Nia,b,c,KeWua,b, Dongdong Huanga,b, Sishi Pana,b,c, Adwait A. Sathee, Yu Tangc,d, Meng-Lu Liuc,d, Chao Xinge,f,g, Chun-Li Zhangc,d,1, and Qichuan Zhugea,b,1 aDepartment of Neurosurgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China 325000; bZhejiang Provincial Key Laboratory of Aging and Neurological Disorder Research, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China 325000; cDepartment of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390; dHamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390; eMcDermott Center of Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX 75390; fDepartment of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390; and gDepartment of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390 Edited by S. Altman, Yale University, New Haven, CT, and approved February 5, 2020 (received for review November 15, 2019) Transfer RNAs (tRNAs) are products of RNA polymerase III (Pol III) indicates that tRNA expression may also be under cell state- and essential for mRNA translation and ultimately cell growth and dependent regulations (12–16). proliferation. Whether and how individual tRNA genes are specif- In this study, we performed a systematic analysis on how ically regulated is not clear. Here, we report that SOX4, a well- NGN2/SOX4-mediated cell-fate reprogramming leads to cell known Pol II-dependent transcription factor that is critical for neuro- cycle exit of human glioblastoma cells. -
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. -
CD8 T Cell Memory Transition and Maintenance of Functional Foxo1
FoxO1 Controls Effector-to-Memory Transition and Maintenance of Functional CD8 T Cell Memory This information is current as Melba Marie Tejera, Eui Ho Kim, Jeremy A. Sullivan, Erin of October 1, 2021. H. Plisch and M. Suresh J Immunol 2013; 191:187-199; Prepublished online 3 June 2013; doi: 10.4049/jimmunol.1300331 http://www.jimmunol.org/content/191/1/187 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2013/06/03/jimmunol.130033 Material 1.DC1 http://www.jimmunol.org/ References This article cites 52 articles, 7 of which you can access for free at: http://www.jimmunol.org/content/191/1/187.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on October 1, 2021 • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by 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. The Journal of Immunology FoxO1 Controls Effector-to-Memory Transition and Maintenance of Functional CD8 T Cell Memory Melba Marie Tejera, Eui Ho Kim, Jeremy A. -
Genes with 5' Terminal Oligopyrimidine Tracts Preferentially Escape Global Suppression of Translation by the SARS-Cov-2 NSP1 Protein
Downloaded from rnajournal.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press Genes with 5′ terminal oligopyrimidine tracts preferentially escape global suppression of translation by the SARS-CoV-2 Nsp1 protein Shilpa Raoa, Ian Hoskinsa, Tori Tonna, P. Daniela Garciaa, Hakan Ozadama, Elif Sarinay Cenika, Can Cenika,1 a Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA 1Corresponding author: [email protected] Key words: SARS-CoV-2, Nsp1, MeTAFlow, translation, ribosome profiling, RNA-Seq, 5′ TOP, Ribo-Seq, gene expression 1 Downloaded from rnajournal.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract Viruses rely on the host translation machinery to synthesize their own proteins. Consequently, they have evolved varied mechanisms to co-opt host translation for their survival. SARS-CoV-2 relies on a non-structural protein, Nsp1, for shutting down host translation. However, it is currently unknown how viral proteins and host factors critical for viral replication can escape a global shutdown of host translation. Here, using a novel FACS-based assay called MeTAFlow, we report a dose-dependent reduction in both nascent protein synthesis and mRNA abundance in cells expressing Nsp1. We perform RNA-Seq and matched ribosome profiling experiments to identify gene-specific changes both at the mRNA expression and translation level. We discover that a functionally-coherent subset of human genes are preferentially translated in the context of Nsp1 expression. These genes include the translation machinery components, RNA binding proteins, and others important for viral pathogenicity. Importantly, we uncovered a remarkable enrichment of 5′ terminal oligo-pyrimidine (TOP) tracts among preferentially translated genes. -
1 AGING Supplementary Table 2
SUPPLEMENTARY TABLES Supplementary Table 1. Details of the eight domain chains of KIAA0101. Serial IDENTITY MAX IN COMP- INTERFACE ID POSITION RESOLUTION EXPERIMENT TYPE number START STOP SCORE IDENTITY LEX WITH CAVITY A 4D2G_D 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ B 4D2G_E 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ C 6EHT_D 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ D 6EHT_E 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ E 6GWS_D 41-72 41 72 100 100 3.2Å PCNA X-RAY DIFFRACTION √ F 6GWS_E 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ G 6GWS_F 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ H 6IIW_B 2-11 2 11 100 100 1.699Å UHRF1 X-RAY DIFFRACTION √ www.aging-us.com 1 AGING Supplementary Table 2. Significantly enriched gene ontology (GO) annotations (cellular components) of KIAA0101 in lung adenocarcinoma (LinkedOmics). Leading Description FDR Leading Edge Gene EdgeNum RAD51, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, CENPW, HJURP, NDC80, CDCA5, NCAPH, BUB1, ZWILCH, CENPK, KIF2C, AURKA, CENPN, TOP2A, CENPM, PLK1, ERCC6L, CDT1, CHEK1, SPAG5, CENPH, condensed 66 0 SPC24, NUP37, BLM, CENPE, BUB3, CDK2, FANCD2, CENPO, CENPF, BRCA1, DSN1, chromosome MKI67, NCAPG2, H2AFX, HMGB2, SUV39H1, CBX3, TUBG1, KNTC1, PPP1CC, SMC2, BANF1, NCAPD2, SKA2, NUP107, BRCA2, NUP85, ITGB3BP, SYCE2, TOPBP1, DMC1, SMC4, INCENP. RAD51, OIP5, CDK1, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, ESCO2, CENPW, HJURP, TTK, NDC80, CDCA5, BUB1, ZWILCH, CENPK, KIF2C, AURKA, DSCC1, CENPN, CDCA8, CENPM, PLK1, MCM6, ERCC6L, CDT1, HELLS, CHEK1, SPAG5, CENPH, PCNA, SPC24, CENPI, NUP37, FEN1, chromosomal 94 0 CENPL, BLM, KIF18A, CENPE, MCM4, BUB3, SUV39H2, MCM2, CDK2, PIF1, DNA2, region CENPO, CENPF, CHEK2, DSN1, H2AFX, MCM7, SUV39H1, MTBP, CBX3, RECQL4, KNTC1, PPP1CC, CENPP, CENPQ, PTGES3, NCAPD2, DYNLL1, SKA2, HAT1, NUP107, MCM5, MCM3, MSH2, BRCA2, NUP85, SSB, ITGB3BP, DMC1, INCENP, THOC3, XPO1, APEX1, XRCC5, KIF22, DCLRE1A, SEH1L, XRCC3, NSMCE2, RAD21. -
Anti-Inflammatory Role of Curcumin in LPS Treated A549 Cells at Global Proteome Level and on Mycobacterial Infection
Anti-inflammatory Role of Curcumin in LPS Treated A549 cells at Global Proteome level and on Mycobacterial infection. Suchita Singh1,+, Rakesh Arya2,3,+, Rhishikesh R Bargaje1, Mrinal Kumar Das2,4, Subia Akram2, Hossain Md. Faruquee2,5, Rajendra Kumar Behera3, Ranjan Kumar Nanda2,*, Anurag Agrawal1 1Center of Excellence for Translational Research in Asthma and Lung Disease, CSIR- Institute of Genomics and Integrative Biology, New Delhi, 110025, India. 2Translational Health Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, 110067, India. 3School of Life Sciences, Sambalpur University, Jyoti Vihar, Sambalpur, Orissa, 768019, India. 4Department of Respiratory Sciences, #211, Maurice Shock Building, University of Leicester, LE1 9HN 5Department of Biotechnology and Genetic Engineering, Islamic University, Kushtia- 7003, Bangladesh. +Contributed equally for this work. S-1 70 G1 S 60 G2/M 50 40 30 % of cells 20 10 0 CURI LPSI LPSCUR Figure S1: Effect of curcumin and/or LPS treatment on A549 cell viability A549 cells were treated with curcumin (10 µM) and/or LPS or 1 µg/ml for the indicated times and after fixation were stained with propidium iodide and Annexin V-FITC. The DNA contents were determined by flow cytometry to calculate percentage of cells present in each phase of the cell cycle (G1, S and G2/M) using Flowing analysis software. S-2 Figure S2: Total proteins identified in all the three experiments and their distribution betwee curcumin and/or LPS treated conditions. The proteins showing differential expressions (log2 fold change≥2) in these experiments were presented in the venn diagram and certain number of proteins are common in all three experiments. -
Gene Symbol Category ACAN ECM ADAM10 ECM Remodeling-Related ADAM11 ECM Remodeling-Related ADAM12 ECM Remodeling-Related ADAM15 E
Supplementary Material (ESI) for Integrative Biology This journal is (c) The Royal Society of Chemistry 2010 Gene symbol Category ACAN ECM ADAM10 ECM remodeling-related ADAM11 ECM remodeling-related ADAM12 ECM remodeling-related ADAM15 ECM remodeling-related ADAM17 ECM remodeling-related ADAM18 ECM remodeling-related ADAM19 ECM remodeling-related ADAM2 ECM remodeling-related ADAM20 ECM remodeling-related ADAM21 ECM remodeling-related ADAM22 ECM remodeling-related ADAM23 ECM remodeling-related ADAM28 ECM remodeling-related ADAM29 ECM remodeling-related ADAM3 ECM remodeling-related ADAM30 ECM remodeling-related ADAM5 ECM remodeling-related ADAM7 ECM remodeling-related ADAM8 ECM remodeling-related ADAM9 ECM remodeling-related ADAMTS1 ECM remodeling-related ADAMTS10 ECM remodeling-related ADAMTS12 ECM remodeling-related ADAMTS13 ECM remodeling-related ADAMTS14 ECM remodeling-related ADAMTS15 ECM remodeling-related ADAMTS16 ECM remodeling-related ADAMTS17 ECM remodeling-related ADAMTS18 ECM remodeling-related ADAMTS19 ECM remodeling-related ADAMTS2 ECM remodeling-related ADAMTS20 ECM remodeling-related ADAMTS3 ECM remodeling-related ADAMTS4 ECM remodeling-related ADAMTS5 ECM remodeling-related ADAMTS6 ECM remodeling-related ADAMTS7 ECM remodeling-related ADAMTS8 ECM remodeling-related ADAMTS9 ECM remodeling-related ADAMTSL1 ECM remodeling-related ADAMTSL2 ECM remodeling-related ADAMTSL3 ECM remodeling-related ADAMTSL4 ECM remodeling-related ADAMTSL5 ECM remodeling-related AGRIN ECM ALCAM Cell-cell adhesion ANGPT1 Soluble factors and receptors -
EIF4E Antibody Cat
EIF4E Antibody Cat. No.: 60-600 EIF4E Antibody Formalin-fixed and paraffin-embedded human breast carcinoma reacted with EIF4E antibody (N-term), which was peroxidase- conjugated to the secondary antibody, followed by DAB staining. Specifications HOST SPECIES: Rabbit SPECIES REACTIVITY: Human Predicted species reactivity based on immunogen sequence: Zebrafish, Bovine, Mouse, HOMOLOGY: Rabbit, Rat, Xenopus This EIF4E antibody is generated from rabbits immunized with a KLH conjugated synthetic IMMUNOGEN: peptide between 32-61 amino acids from the N-terminal region of human EIF4E. TESTED APPLICATIONS: IHC-P, WB For WB starting dilution is: 1:1000 APPLICATIONS: For IHC-P starting dilution is: 1:50~100 September 27, 2021 1 https://www.prosci-inc.com/eif4e-antibody-60-600.html PREDICTED MOLECULAR 25 kDa WEIGHT: Properties This antibody is prepared by Saturated Ammonium Sulfate (SAS) precipitation followed by PURIFICATION: dialysis CLONALITY: Polyclonal ISOTYPE: Rabbit Ig CONJUGATE: Unconjugated PHYSICAL STATE: Liquid BUFFER: Supplied in PBS with 0.09% (W/V) sodium azide. CONCENTRATION: batch dependent Store at 4˚C for three months and -20˚C, stable for up to one year. As with all antibodies STORAGE CONDITIONS: care should be taken to avoid repeated freeze thaw cycles. Antibodies should not be exposed to prolonged high temperatures. Additional Info OFFICIAL SYMBOL: EIF4E Eukaryotic translation initiation factor 4E, eIF-4E, eIF4E, eIF-4F 25 kDa subunit, mRNA cap- ALTERNATE NAMES: binding protein, EIF4E, EIF4EL1, EIF4F ACCESSION NO.: P06730 PROTEIN GI NO.: 1352435 GENE ID: 1977 USER NOTE: Optimal dilutions for each application to be determined by the researcher. Background and References eIF4F is a multi-subunit complex, the composition of which varies with external and internal environmental conditions.