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