Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance
about
Epidermal growth factor receptor potentiates MCM7-mediated DNA replication through tyrosine phosphorylation of Lyn kinase in human cancersGenomic screening with RNAi: results and challengesCancer systems biology: a network modeling perspectiveLogical Modeling and Dynamical Analysis of Cellular NetworksNetwork-based approaches in drug discovery and early developmentSBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and toolsSystems biology approaches for advancing the discovery of effective drug combinationsThe miR-644a/CTBP1/p53 axis suppresses drug resistance by simultaneous inhibition of cell survival and epithelial-mesenchymal transition in breast cancerTraining signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuliA comprehensive, multi-scale dynamical model of ErbB receptor signal transduction in human mammary epithelial cellsDiscovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical ModelingThe Cell Collective: toward an open and collaborative approach to systems biology.Inhibition of mTOR-kinase destabilizes MYCN and is a potential therapy for MYCN-dependent tumorsCellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.Dynamics of p53 and NF-κB regulation in response to DNA damage and identification of target proteins suitable for therapeutic intervention.Deterministic Effects Propagation Networks for reconstructing protein signaling networks from multiple interventionsHER2-positive breast cancer cells expressing elevated FAM83A are sensitive to FAM83A loss.Epidermal Growth Factor Receptor Cell Proliferation Signaling PathwaysBoolean ErbB network reconstructions and perturbation simulations reveal individual drug response in different breast cancer cell lines.Time-resolved human kinome RNAi screen identifies a network regulating mitotic-events as early regulators of cell proliferation.ADAM: analysis of discrete models of biological systems using computer algebra.Dynamic modelling of oestrogen signalling and cell fate in breast cancer cellsConstruction of large signaling pathways using an adaptive perturbation approach with phosphoproteomic data.A new analysis approach of epidermal growth factor receptor pathway activation patterns provides insights into cetuximab resistance mechanisms in head and neck cancerContinuous time Boolean modeling for biological signaling: application of Gillespie algorithm.Bio-logic builder: a non-technical tool for building dynamical, qualitative models.RNAi-based validation of antibodies for reverse phase protein arrays.Global microRNA level regulation of EGFR-driven cell-cycle protein network in breast cancer.Integrating Bayesian variable selection with Modular Response Analysis to infer biochemical network topologyMicroRNA-519a is a novel oncomir conferring tamoxifen resistance by targeting a network of tumour-suppressor genes in ER+ breast cancer.Network based elucidation of drug response: from modulators to targets.Sensitivity analysis of biological Boolean networks using information fusion based on nonadditive set functionsSteady state analysis of Boolean molecular network models via model reduction and computational algebra.Microenvironmental stiffness enhances glioma cell proliferation by stimulating epidermal growth factor receptor signaling.Reconciling molecular regulatory mechanisms with noise patterns of bacterial metabolic promoters in induced and repressed states.MicroRNA-200c represses migration and invasion of breast cancer cells by targeting actin-regulatory proteins FHOD1 and PPM1F.Soluble-E-cadherin activates HER and IAP family members in HER2+ and TNBC human breast cancers.Conditional robustness analysis for fragility discovery and target identification in biochemical networks and in cancer systems biology.Logic-Based and Cellular Pharmacodynamic Modeling of Bortezomib Responses in U266 Human Myeloma Cells.Dynamical systems approach to endothelial heterogeneity.
P2860
Q24294953-5BDB5631-6937-43C4-9B6A-D16A391A9AFCQ24626537-F2F3CAF4-B99F-4901-91C1-C427CB1AC2C1Q24650086-556D1CD1-6FB9-4970-8D0A-7C3566858F81Q26745955-EC2F6F72-E7D3-471A-A88B-F5923FE37E31Q26827940-B51060B4-E955-47BF-8B0A-EEC74A3CD9CFQ27499050-472D8927-9C16-4972-8F90-AE11BFCDACA1Q27702922-31A4B32D-9B90-4D3B-8555-E077440D6819Q28468629-573DF296-EA58-45DD-8530-3A3A270AE56BQ28477321-F796C41E-D346-4711-AF2C-37B7DA3307F3Q28486292-C9AF7163-7358-4662-943F-2BA5A079E924Q28547862-C3E9F858-4936-4886-9E39-C04CEE5145EDQ28727777-4183796E-BF33-43DA-ABED-8E4A50D3EC70Q28817295-BFEA7F15-00A1-453E-8A1A-4B3ADEC6475EQ30573980-AC170429-0032-4BD8-943A-5F30F0203901Q31090728-0573048F-F757-41FE-9CE7-9603B45D996FQ33509376-6BC27A4D-DBD1-4AFB-A923-509E83DB3E35Q33626569-B92146E8-12A4-4429-9AE5-3EB1767ABD35Q33737298-143AE04A-717E-4D59-A9D1-B51EE1B490EFQ33864932-5288D061-30D2-4FE2-86A1-00C777A636F6Q33963929-E9D16F0B-704F-4A78-9A8F-B37D6805C10CQ33966533-88337F91-BC12-4453-B090-199AB85BAF79Q34192940-A1894D78-1EF5-4615-87A7-1277243733B9Q34207814-D76870B3-19B8-4B8F-A757-B8F9610011F2Q34252978-6D654856-D6C6-4E9C-A6BB-EE8AA9A3972FQ34397609-EBC32F84-1879-40FF-AD21-13EEB9603C8DQ34451885-5B94B4BC-1BD6-420D-A82A-485BCCEA269FQ34500104-E60B379C-2EEB-44B4-B1AB-5A71726444D1Q34635861-F523D84F-E420-4729-8000-ED5F2D98BEE6Q34800432-7B9E366A-7A82-40A7-AE45-F5DB3172A30AQ34984068-BAD1062A-7BB1-4488-9017-8F9FA78731BAQ35065347-728DA154-164E-49FF-B668-2025C59CE3B2Q35189160-9D40EEEA-2BE3-48E3-8A3E-5A4892092E4CQ35194958-7F751951-0A7C-4562-9DA6-C379A23747ACQ35202307-F41EB829-3762-4EB0-AFAA-B304198DA257Q35657684-5E012210-F52A-4FF3-9209-4B084222B382Q35697850-21A8E5DB-A654-4307-BC8D-BB99FAD629E6Q35770840-2385C2E5-AB4D-4042-A8FA-13CE669BC639Q35813685-DEFF5B4F-DC85-4A9B-A17B-A3251CD5A987Q35962054-59538FD3-991F-4F15-B170-96813F225C07Q36104888-BC98EADB-B3AB-478A-BCC4-E9F6639A7C66
P2860
Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance
description
2009 nî lūn-bûn
@nan
2009 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
Modeling ERBB receptor-regulat ...... de novo trastuzumab resistance
@ast
Modeling ERBB receptor-regulat ...... de novo trastuzumab resistance
@en
type
label
Modeling ERBB receptor-regulat ...... de novo trastuzumab resistance
@ast
Modeling ERBB receptor-regulat ...... de novo trastuzumab resistance
@en
prefLabel
Modeling ERBB receptor-regulat ...... de novo trastuzumab resistance
@ast
Modeling ERBB receptor-regulat ...... de novo trastuzumab resistance
@en
P2093
P2860
P50
P356
P1433
P1476
Modeling ERBB receptor-regulat ...... de novo trastuzumab resistance
@en
P2093
Christian Löbke
Dorit Arlt
Ingo Schupp
Jens Mattern
Meher Majety
Ozgür Sahin
Sara Burmester
Tim Beissbarth
P2860
P2888
P356
10.1186/1752-0509-3-1
P577
2009-01-01T00:00:00Z
P5875
P6179
1049490622