Advancing Flowering-Time Gene Identification: A Breakthrough in Machine Learning Models
Chinese Academy of SciencesA research team created seven learning models using Support Vector Machine (SVM) algorithms to discern flowering-time-associated genes (FTAGs) from non-FTAGs, with the SVM-Kmer-PC-PseAAC model performing the best (F1 score = 0.934, accuracy = 0.939, and receiver operating characterstic = 0.943).