PIP3 activates AKT signaling - Pathway Page
Name PIP3 activates AKT signaling
Resource Reactome
Genes ERBB2 FOXO3 PSMD2 PIK3CA PHLPP1 PSMA8 JUN FGF7 HDAC5 PSME4 FGF20 TRAT1 UBB USP13 TNRC6B WWP2 RPS27A MECOM FGFR4 ICOS IL1RAP MTA1 PSMD10 PSMD12 EED RING1 CSNK2A2 EZH2 PSMD9 PIP4K2C FRK HDAC1 PSMB11 RRAGB EGF TRIB3 ESR2 PPP2R5A VAV1 KDM1A PSMB2 FGF6 HDAC7 FYN RBBP4 IER3 PIK3R2 MTOR PPP2R5B IRAK4 MAPKAP1 PSMD8 PSMD4 KIT TRAF6 LAMTOR5 PSMA3 TSC2 TNRC6C PSMA4 GSK3B FGFR1 CD28 CBX4 FGFR2 NRG1 MKRN1 FGF17 CHD4 PSMD14 PTPN11 PTEN AKT1S1 PIK3CB IRS2 REST CREB1 PPP2R5D FGF3 PDGFRB PSMA2 OTUD3 PIP5K1C HBEGF BTC TNKS2 CASP9 FOXO1 RCOR1 LAMTOR1 ATF2 PSMA7 FGF5 MET KITLG MTA2 MYD88 PSMD7 LAMTOR3 SALL4 PSMD13 UBC CD86 PSMB4 ERBB3 AGO2 PSME2 FGF2 CSNK2B CHUK PPP2R5C PSMD3 MDM2 PHLPP2 LCK PSMD1 PIP4K2B PIK3CD CBX2 CDKN1B KLB PSMB1 IL1RL1 RPTOR KL FGF18 PDGFB GATAD2B FGFR3 MOV10 PSMC5 TP53 XIAP EREG UBA52 AGO1 HDAC2 PSMC2 PRR5 SCMH1 PSMA1 CDKN1A NRG2 PSMA5 PSMF1 PSME3 PPP2R1B SLC38A9 PDGFA PSMB9 PIK3AP1 PSME1 BAD FRS2 IRS1 CHD3 SEM1 LAMTOR4 USP7 PHC1 GAB1 INS MAPK3 RRAGD FGF9 ATN1 EGR1 FGF22 FGF8 FGF19 PIK3R1 FGF1 PSMD5 PREX2 FGF23 BMI1 INSR CD19 GSK3A TNRC6A NR2E1 PDGFRA CSNK2A1 MBD3 PIK3R3 PSMD11 HGF PSMD6 RRAGA PSMB10 PHC2 AKT1 TNKS GATAD2A PSMB8 MLST8 PPP2R5E EGFR PPP2CA MAPK1 CBX6 IL33 PIP5K1B RBBP7 NRG4 PSMB5 PML PSMA6 PHC3 AKT2 MTA3 LAMTOR2 RHEB NEDD4 PPARG GRB2 PSMB6 SNAI2 IRAK1 ESR1 TRIM27 STUB1 NR4A1 SUZ12 FGF16 RPS6KB2 SRC PPP2CB SNAI1 PDPK1 ERBB4 PIP5K1A FGF10 RICTOR PSMB3 PPP2R1A FOXO4 THEM4 RNF146 AGO3 PIP4K2A FGF4 RNF2 MAF1 RRAGC PSMC6 PSMB7 AKT3 PSMC4 PSMC1 CBX8 HDAC3 CD80 AGO4 NRG3 PSMC3
Size 256
Hierarchy Landscape

The following plot represents the hierarchical landscape of 'PIP3 activates AKT signaling'. The hierarchical tree allows to click on the pathways with children (black border) and continue the exploration. All nodes are colored by their source (click on the map for the legend) and cross-link to the original pathway page.

Super-Pathways

About

ComPath is developed and maintained in an academic capacity by Daniel Domingo-Fernández and Charles Tapley Hoyt at the Fraunhofer SCAI Department of Bioinformatics. This web application relies on data loaded from KEGG, Reactome, and WikiPathways Restful APIs, as well as MSigDB. More information here.