A support vector machine based on classification model robustly separated lung cancer from adjacent normal tissues in the validation datasets (accuracy ranged from 91.7% to 98.5%) by using the LCHN gene signatures as predictors.
A support vector machine based on classification model robustly separated lung cancer from adjacent normal tissues in the validation datasets (accuracy ranged from 91.7% to 98.5%) by using the LCHN gene signatures as predictors.
A support vector machine based on classification model robustly separated lung cancer from adjacent normal tissues in the validation datasets (accuracy ranged from 91.7% to 98.5%) by using the LCHN gene signatures as predictors.
Using mRNA differential display to identify cerebral ischemia-responsive mRNAs, we isolated and cloned a cDNA derived from a novel gene, that has been designated LCHN.
Taken together, these data suggest that LCHN could play a role in neuritogenesis, as well as in neuronal recovery and/or restructuring in the hippocampus following transient cerebral ischemia.
Taken together, these data suggest that LCHN could play a role in neuritogenesis, as well as in neuronal recovery and/or restructuring in the hippocampus following transient cerebral ischemia.