FBLIM1 Rabbit Pab

Total Page：16

File Type：pdf, Size：1020Kb

Leader in Biomolecular Solutions for Life Science FBLIM1 Rabbit pAb Catalog No.: A15850 1 Publications Basic Information Background Catalog No. This gene encodes a protein with an N-terminal filamin-binding domain, a central A15850 proline-rich domain, and, multiple C-terminal LIM domains. This protein localizes at cell junctions and may link cell adhesion structures to the actin cytoskeleton. This protein Observed MW may be involved in the assembly and stabilization of actin-filaments and likely plays a 41kDa role in modulating cell adhesion, cell morphology and cell motility. This protein also localizes to the nucleus and may affect cardiomyocyte differentiation after binding with Calculated MW the CSX/NKX2-5 transcription factor. Alternative splicing results in multiple transcript 30kDa/40kDa variants encoding different isoforms. Category Primary antibody Applications WB Cross-Reactivity Human, Rat Recommended Dilutions Immunogen Information WB 1:500 - 1:2000 Gene ID Swiss Prot 54751 Q8WUP2 Immunogen Recombinant fusion protein containing a sequence corresponding to amino acids 180-272 of human FBLIM1 (NP_060026.2). Synonyms FBLIM1;CAL;FBLP-1;FBLP1 Contact Product Information www.abclonal.com Source Isotype Purification Rabbit IgG Affinity purification Storage Store at -20℃. Avoid freeze / thaw cycles. Buffer: PBS with 0.02% sodium azide,50% glycerol,pH7.3. Validation Data Western blot analysis of extracts of rat heart, using FBLIM1 antibody (A15850) at 1:1000 dilution. Secondary antibody: HRP Goat Anti-Rabbit IgG (H+L) (AS014) at 1:10000 dilution. Lysates/proteins: 25ug per lane. Blocking buffer: 3% nonfat dry milk in TBST. Detection: ECL Basic Kit (RM00020). Exposure time: 30s. Antibody | Protein | ELISA Kits | Enzyme | NGS | Service For research use only. Not for therapeutic or diagnostic purposes. Please visit http://abclonal.com for a complete listing of recommended products..

Copy Link

Recommended publications

Mechanical Forces Induce an Asthma Gene Signature in Healthy Airway Epithelial Cells Ayşe Kılıç1,10, Asher Ameli1,2,10, Jin-Ah Park3,10, Alvin T
www.nature.com/scientificreports OPEN Mechanical forces induce an asthma gene signature in healthy airway epithelial cells Ayşe Kılıç1,10, Asher Ameli1,2,10, Jin-Ah Park3,10, Alvin T. Kho4, Kelan Tantisira1, Marc Santolini 1,5, Feixiong Cheng6,7,8, Jennifer A. Mitchel3, Maureen McGill3, Michael J. O’Sullivan3, Margherita De Marzio1,3, Amitabh Sharma1, Scott H. Randell9, Jefrey M. Drazen3, Jefrey J. Fredberg3 & Scott T. Weiss1,3* Bronchospasm compresses the bronchial epithelium, and this compressive stress has been implicated in asthma pathogenesis. However, the molecular mechanisms by which this compressive stress alters pathways relevant to disease are not well understood. Using air-liquid interface cultures of primary human bronchial epithelial cells derived from non-asthmatic donors and asthmatic donors, we applied a compressive stress and then used a network approach to map resulting changes in the molecular interactome. In cells from non-asthmatic donors, compression by itself was sufcient to induce infammatory, late repair, and fbrotic pathways. Remarkably, this molecular profle of non-asthmatic cells after compression recapitulated the profle of asthmatic cells before compression. Together, these results show that even in the absence of any infammatory stimulus, mechanical compression alone is sufcient to induce an asthma-like molecular signature. Bronchial epithelial cells (BECs) form a physical barrier that protects pulmonary airways from inhaled irritants and invading pathogens1,2. Moreover, environmental stimuli such as allergens, pollutants and viruses can induce constriction of the airways3 and thereby expose the bronchial epithelium to compressive mechanical stress. In BECs, this compressive stress induces structural, biophysical, as well as molecular changes4,5, that interact with nearby mesenchyme6 to cause epithelial layer unjamming1, shedding of soluble factors, production of matrix proteins, and activation matrix modifying enzymes, which then act to coordinate infammatory and remodeling processes4,7–10.
[Show full text]
The N-Cadherin Interactome in Primary Cardiomyocytes As Defined Using Quantitative Proximity Proteomics Yang Li1,*, Chelsea D
© 2019. Published by The Company of Biologists Ltd | Journal of Cell Science (2019) 132, jcs221606. doi:10.1242/jcs.221606 TOOLS AND RESOURCES The N-cadherin interactome in primary cardiomyocytes as defined using quantitative proximity proteomics Yang Li1,*, Chelsea D. Merkel1,*, Xuemei Zeng2, Jonathon A. Heier1, Pamela S. Cantrell2, Mai Sun2, Donna B. Stolz1, Simon C. Watkins1, Nathan A. Yates1,2,3 and Adam V. Kwiatkowski1,‡ ABSTRACT requires multiple adhesion, cytoskeletal and signaling proteins, The junctional complexes that couple cardiomyocytes must transmit and mutations in these proteins can cause cardiomyopathies (Ehler, the mechanical forces of contraction while maintaining adhesive 2018). However, the molecular composition of ICD junctional homeostasis. The adherens junction (AJ) connects the actomyosin complexes remains poorly defined. – networks of neighboring cardiomyocytes and is required for proper The core of the AJ is the cadherin catenin complex (Halbleib and heart function. Yet little is known about the molecular composition of the Nelson, 2006; Ratheesh and Yap, 2012). Classical cadherins are cardiomyocyte AJ or how it is organized to function under mechanical single-pass transmembrane proteins with an extracellular domain that load. Here, we define the architecture, dynamics and proteome of mediates calcium-dependent homotypic interactions. The adhesive the cardiomyocyte AJ. Mouse neonatal cardiomyocytes assemble properties of classical cadherins are driven by the recruitment of stable AJs along intercellular contacts with organizational and cytosolic catenin proteins to the cadherin tail, with p120-catenin β structural hallmarks similar to mature contacts. We combine (CTNND1) binding to the juxta-membrane domain and -catenin β quantitative mass spectrometry with proximity labeling to identify the (CTNNB1) binding to the distal part of the tail.
[Show full text]
Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins
International Journal of Molecular Sciences Article Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins M. Quadir Siddiqui 1,† , Maulik D. Badmalia 1,† and Trushar R. Patel 1,2,3,* 1 Alberta RNA Research and Training Institute, Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 3M4, Canada; [email protected] (M.Q.S.); [email protected] (M.D.B.) 2 Department of Microbiology, Immunology and Infectious Disease, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive, Calgary, AB T2N 4N1, Canada 3 Li Ka Shing Institute of Virology, University of Alberta, Edmonton, AB T6G 2E1, Canada * Correspondence: [email protected] † These authors contributed equally to the work. Abstract: Members of the human Zyxin family are LIM domain-containing proteins that perform critical cellular functions and are indispensable for cellular integrity. Despite their importance, not much is known about their structure, functions, interactions and dynamics. To provide insights into these, we used a set of in-silico tools and databases and analyzed their amino acid sequence, phylogeny, post-translational modiﬁcations, structure-dynamics, molecular interactions, and func- tions. Our analysis revealed that zyxin members are ohnologs. Presence of a conserved nuclear export signal composed of LxxLxL/LxxxLxL consensus sequence, as well as a possible nuclear localization signal, suggesting that Zyxin family members may have nuclear and cytoplasmic roles. The molecular modeling and structural analysis indicated that Zyxin family LIM domains share Citation: Siddiqui, M.Q.; Badmalia, similarities with transcriptional regulators and have positively charged electrostatic patches, which M.D.; Patel, T.R.
[Show full text]
FBLIM1 Polyclonal Antibody
PRODUCT DATA SHEET Bioworld Technology,Inc. FBLIM1 polyclonal antibody Catalog: BS72779 Host: Rabbit Reactivity: Human,Rat BackGround: munogen and the purity is > 95% (by SDS-PAGE). This gene encodes a protein with an N-terminal fila- Applications: min-binding domain, a central proline-rich domain, and, WB 1:500 - 1:2000 multiple C-terminal LIM domains. This protein localizes Storage&Stability: at cell junctions and may link cell adhesion structures to Store at 4°C short term. Aliquot and store at -20°C long the actin cytoskeleton. This protein may be involved in term. Avoid freeze-thaw cycles. the assembly and stabilization of actin-filaments and Specificity: likely plays a role in modulating cell adhesion, cell mor- FBLIM1 polyclonal antibody detects endogenous levels phology and cell motility. This protein also localizes to of FBLIM1 protein. the nucleus and may affect cardiomyocyte differentiation DATA: after binding with the CSX/NKX2-5 transcription factor. Alternative splicing results in multiple transcript variants encoding different isoforms. Product: Rabbit IgG, 1mg/ml in PBS with 0.02% sodium azide, 50% glycerol, pH7.2 Molecular Weight: 41kDa Western blot analysis of extracts of rat heart, using FBLIM1 antibody. Swiss-Prot: Note: Q8WUP2 For research use only, not for use in diagnostic procedure. Purification&Purity: The antibody was affinity-purified from rabbit antiserum by affinity-chromatography using epitope-specific im- Bioworld Technology, Inc. Bioworld technology, co. Ltd. Add： 1660 South Highway 100, Suite 500 St. Louis Park, Add： No 9, weidi road Qixia District Nanjing, 210046, MN 55416,USA. P. R. China. Email: [email protected] Email: [email protected] Tel: 6123263284 Tel: 0086-025-68037686 Fax: 6122933841 Fax: 0086-025-68035151 .
[Show full text]
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine
[Show full text]
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A.
[Show full text]
Protein Interactors from Genome-Wide DNA-Binding Data Using a Knowledge
Prediction and validation of protein– protein interactors from genome-wide rsob.royalsocietypublishing.org DNA-binding data using a knowledge- based machine-learning approach Ashley J. Waardenberg1,2, Bernou Homan1, Stephanie Mohamed1, Research Richard P. Harvey1,3,4 and Romaric Bouveret1,3 Cite this article: Waardenberg AJ, Homan B, 1Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales 2010, Australia Mohamed S, Harvey RP, Bouveret R. 2016 2Children’s Medical Research Institute, University of Sydney, Westmead, New South Wales 2145, Australia 3 4 Prediction and validation of protein–protein St Vincent’s Clinical School, and School of Biotechnology and Biomolecular Science, University of New South Wales, Kensington, New South Wales 2052, Australia interactors from genome-wide DNA-binding data using a knowledge-based machine- AJW, 0000-0002-9382-7490 learning approach. Open Biol. 6: 160183. The ability to accurately predict the DNA targets and interacting cofactors of http://dx.doi.org/10.1098/rsob.160183 transcriptional regulators from genome-wide data can significantly advance our understanding of gene regulatory networks. NKX2-5 is a homeodomain transcription factor that sits high in the cardiac gene regulatory network and is essential for normal heart development. We previously identified Received: 15 June 2016 genomic targets for NKX2-5 in mouse HL-1 atrial cardiomyocytes using Accepted: 5 September 2016 DNA-adenine methyltransferase identification (DamID). Here, we apply machine learning algorithms and propose a knowledge-based feature selection method for predicting NKX2-5 protein : protein interactions based on motif grammar in genome-wide DNA-binding data. We assessed model perform- ance using leave-one-out cross-validation and a completely independent Subject Area: DamID experiment performed with replicates.
[Show full text]
FBLIM1 Polyclonal Antibody
For Research Use Only FBLIM1 Polyclonal antibody Catalog Number:13349-1-AP 1 Publications www.ptgcn.com Catalog Number: GenBank Accession Number: Recommended Dilutions: Basic Information 13349-1-AP BC019895 WB 1:500-1:2000 Size: GeneID (NCBI): IHC 1:20-1:200 650 μg/ml 54751 Source: Full Name: Rabbit filamin binding LIM protein 1 Isotype: Calculated MW: IgG 373 aa, 41 kDa Purification Method: Observed MW: Antigen affinity purification 45-48 kDa Immunogen Catalog Number: AG3907 Applications Tested Applications: Positive Controls: IHC, WB,ELISA WB : HepG2 cells; HEK-293 cells, human heart tissue, K- Cited Applications: 562 cells, HeLa cells IF IHC : human lung cancer tissue; Species Specificity: human Cited Species: human Note-IHC: suggested antigen retrieval with TE buffer pH 9.0; (*) Alternatively, antigen retrieval may be performed with citrate buffer pH 6.0 FBLIM1, also known as CAL, Mig-2-interacting protein or Migfilin, is a cytoplasmic protein that belongs to the LIM Background Information superfamily. FBLIM1 is a protein found in cell-cell and cell-ECM connections where it co-localizes with FLNA/C and FLNB. FBLIM1 was found to bind directly to FLNA/C and to be an important regulator of cell shape and motility. FBLIM1 exerts its influence on cellular functions by interacting with various binding partners; FLN via its N- terminal domain, VASP and Src via its proline-rich region, and kindlin-2 and the cardiac transcription factor, CSX/NKX2-5 via its C-terminal LIM domains. Three isoforms exist for FBLIM1 due to alternative splicing events, namely FBLP-1A, FBLP-1 and FBLP-1B.
[Show full text]
Supplementary Table 1. Demographics and Clinical
Supplementary material J Med Genet Supplementary Table 1. Demographics and clinical characteristics of AIS patients AIS trios (n=40) Sporadic AIS (n=183) In-house controls (n=153) Sex, n (%) Male 3 (7.5%) 21 (11.48%) 14 (9.15%) Female 37 (92.5%) 162 (88.52%) 139 (90.85%) Age of curve onseta, yrs, mean ± SD 12.48 ± 1.77 12.50 ± 1.74 12.76 ± 1.86 Age at menarche, yrs, mean ± SD 13.60 ± 0.50 13.18 ± 1.34 13.46 ± 1.52 Lenke classification, n (%) 1 2 (5%) 21 (11.48%) 2 20 (50%) 90 (49.18%) 3 5 (12.5%) 23 (12.57%) 4 5 (12.5%) 22 (12.02%) 5 5 (12.5%) 24 (13.11%) 6 3 (7.5%) 3 (1.64%) Spinal curve at first presentation, °, 18.18 ± 4.07 18.14 ± 4.06 mean ± SD Body mass index, Kg/m2, mean ± SD 21.88 ± 2.62 21.97 ± 2.52 22.53 ± 3.70 aIn case of In-house controls, it means the age of individuals when enrolled. Jiang H, et al. J Med Genet 2020; 57:405–413. doi: 10.1136/jmedgenet-2019-106411 Supplementary material J Med Genet Supplementary Table 2. Summary data and technical characters of exome sequencing data Average Raw Average Average Average Total Average Total Average Target Average Target Average Target Average TC Average bases (Mb) QC rates (%) Target average reads mapping bases mapping bases capture rate mean depth covered mean 10%X Ti/Tv read length rate (%) rate (%) (%) depth coverage rate (%) 11729.02 96.03 147 99.58 98.84 76.78 130.28 130.54 99.47 2.30 Jiang H, et al.
[Show full text]
The Human Gene Connectome As a Map of Short Cuts for Morbid Allele Discovery
The human gene connectome as a map of short cuts for morbid allele discovery Yuval Itana,1, Shen-Ying Zhanga,b, Guillaume Vogta,b, Avinash Abhyankara, Melina Hermana, Patrick Nitschkec, Dror Friedd, Lluis Quintana-Murcie, Laurent Abela,b, and Jean-Laurent Casanovaa,b,f aSt. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065; bLaboratory of Human Genetics of Infectious Diseases, Necker Branch, Paris Descartes University, Institut National de la Santé et de la Recherche Médicale U980, Necker Medical School, 75015 Paris, France; cPlateforme Bioinformatique, Université Paris Descartes, 75116 Paris, France; dDepartment of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; eUnit of Human Evolutionary Genetics, Centre National de la Recherche Scientifique, Unité de Recherche Associée 3012, Institut Pasteur, F-75015 Paris, France; and fPediatric Immunology-Hematology Unit, Necker Hospital for Sick Children, 75015 Paris, France Edited* by Bruce Beutler, University of Texas Southwestern Medical Center, Dallas, TX, and approved February 15, 2013 (received for review October 19, 2012) High-throughput genomic data reveal thousands of gene variants to detect a single mutated gene, with the other polymorphic genes per patient, and it is often difficult to determine which of these being of less interest. This goes some way to explaining why, variants underlies disease in a given individual. However, at the despite the abundance of NGS data, the discovery of disease- population level, there may be some degree of phenotypic homo- causing alleles from such data remains somewhat limited. geneity, with alterations of specific physiological pathways under- We developed the human gene connectome (HGC) to over- come this problem.
[Show full text]
FBLIM1 CRISPR Activation Plasmid (M): Sc-428788-ACT
SANTA CRUZ BIOTECHNOLOGY, INC. FBLIM1 CRISPR Activation Plasmid (m): sc-428788-ACT BACKGROUND APPLICATIONS The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and Either FBLIM1 CRISPR Activation Plasmid (m) or FBLIM1 CRISPR Activation CRISPR-associated protein (Cas9) system is an adaptive immune response Plasmid (m2) is recommended to increase activation of gene expression in defense mechanism used by archea and bacteria for the degradation of for- mouse cells. eign genetic material. This mechanism can be repurposed for other functions, including genomic engineering for mammalian systems, such as gene knock- SUPPORT REAGENTS out (KO) (1,2) and gene activation (3-6). CRISPR Activation Plasmid products For optimal reaction efficiency with CRISPR Activation Plasmids, Santa Cruz enable the identification and upregulation of specific genes by utilizing a Biotechnology’s UltraCruz® Transfection Reagent: sc-395739 (0.2 ml) and D10A and N863A deactivated Cas9 (dCas9) nuclease fused to a VP64 acti- Plasmid Transfection Medium: sc-108062 (20 ml) are recommended. vation domain, in conjunction with sgRNA (MS2), a target-specific sgRNA Hygromycin B solution: sc-29067 (1 g), Blasticidin S HCl solution: sc-495389 engineered to bind the MS2-P65-HSF1 fusion protein (6). This synergistic (1 ml) and Puromycin dihydrochloride: sc-108071 (25 mg) are recommended activation mediator (SAM) transcription activation system provides a robust for selection. Control CRISPR Activation Plasmid: sc-437275 (20 µg) negative system to maximize the activation of endogenous gene expression (6). control is also available. REFERENCES GENE EXPRESSION MONITORING 1. Cong, L., et al. 2013. Multiplex genome engineering using CRISPR/Cas FBLIM1 (G-7): sc-271417 is recommended as a control antibody for moni- systems.
[Show full text]
Supplementary Table 5A
CE2/+ f/f CA/+ CE2/+ f/f Supplementary Table 5A: Pathway enrichment analysis for differentially expressed genes between Nkx3.1 ; Pten ; Braf and Nkx3.1 ; Pten mouse prostate tumors Pathway Gene Number Enrichment Normalized p-value False Family-wise Rank Leading Edge Genes Set of genes Score enrichment Discovery Error Rate at Details in the score Rate p-value Max pathway q-value TPM2 ACTG2 MYL9 ACTA2 VCL DES MYLK ITGA1 Details TPM4 SORBS1 CALM2 ITGB5 PXN LMOD1 TNNC2 1 REACTOME_MUSCLE_CONTRACTION ... 30 0.78 2.58 0 0 0 2180 MYL1 MYH11 Details TPM2 ACTG2 MYL9 ACTA2 VCL MYLK ITGA1 2 REACTOME_SMOOTH_MUSCLE_CONTRACTION ... 20 0.81 2.39 0 0 0 1609 TPM4 SORBS1 CALM2 ITGB5 PXN LMOD1 MYH11 ITGA3 LAMB3 ITGB4 THBS1 LAMA3 CD44 ITGA6 ITGAV ITGB1 SPP1 LAMC2 ITGA1 SDC1 RELN LAMC1 FN1 ITGB5 THBS2 COL1A2 ITGA9 ITGB6 SDC2 HSPG2 TNC COL6A1 COL4A2 COL6A2 Details COL4A6 ITGA5 COL4A1 LAMA1SV2B COL5A1 3 KEGG_ECM_RECEPTOR_INTERACTION ... 59 0.63 2.32 0 0 0 3812 COL6A3 COL3A1 ITGA11 COL5A2 ITGA10 Details ACTIN1 FLNC FBLIM1 ITGB1 FLNA RSU1 FERMT2 4 REACTOME_CELLEXTRACELLULAR_MATRIX_INTERACTIONS ... 13 0.81 2.16 0 0 0.001 1193 PXN ILK ITGA3 ITGB4 THBS1 ITGA6 ITGAV ITGB1 SPP1 ITGA1 LAMC1 FN1 ITGB5 COL1A2 CDH1 BCRAR1 ITGA9 ITGB6 COL4A5 TNC COL4A2 ITGA5 COL4A1 Details LAMA1 PTPN1 FGG PECAM1 FGA FBN1 ITGA11 5 REACTOME_INTEGRIN_CELL_SURFACE_INTERACTIONS ... 62 0.57 2.09 0 0 0.002 3812 ITGA10 COL1A1 LAMA2 LAMB2 ITGA3 CCND1 LAMB3 ITGB4 THBS1 FLNB LAMA3 ACTN1 IGF1R CCND2 ITGA6 ITGAV FLNC MYL9 CAV1 ITGB1 VEGF1 PDGFRA SPP1 FLNA MAP2K1 PDGFC VCL PPP1CC MYLK LAMC2 CAPN2 CDC42 ITGA1 RELN LAMC1 AKT3 FN1 CAV2 PDGFRB ITGB5 PXN ILK PDGFB THBS2 DOCK1 COL1A2 FLT1 FIGF BCAR1 ITGA9 ITGB6 PAK3 TNC COL6A1 COL4A2 COL6A2 COL4A6 ITGA5 COL4A1 LAMA1 Details BCL2 COL5A1 PGF ZYX COL6A3 COL3A1 ITGA11 6 KEGG_FOCAL_ADHESION ..
[Show full text]