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In clinical oncology, the primary method for identifying survival factors in high-grade gliomas has been through Cox proportional hazards models.
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We found that dnet is superior over jActivemodules in identifying survival-related genes.
Identifying survival-associated gene sets in a pan-cancer manner could shed light on the links between cancers while also highlighting differences in their molecular composition.
It is reasonable since the identified survival network is not merely a reflection of the survivalness in individual tumour types, but also incorporates all possible combinatorial factors between age, gender and tumour types.
This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K AKT mTOR pathway inhibitors in breast cancer.
In a subset of patients in the modern chemotherapy era group, for which treatment regimen could be definitively identified, survival was even greater-23.8 months.Patients with CRC-associated PC treated with modern combination chemotherapy and biologic therapy have a significantly longer median survival compared to our historical cohort.
To this end we first characterized 32 different mouse strains infected with P. berghei and identified survival as the best trait to discriminate between the strains.
The terms used to identify survival time data were: "survival", "Kaplan", "Cox", "life", and "time".
We also tested the significance of the identified survival network using a novel data randomisation procedure.
The life-cycle model identified survival conditions that favored the yearling smolt-migration tactic over the subyearling tactic.
This method incorporates the genetic pathways into global AUC summary maximization and identifies survival associated pathways instead of individual genes.
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