This dataset contains the training, validation, and test data used for transcription factor (TF)–DNA binding prediction in the TFBindFormer framework. It integrates genomic DNA sequence bins with tran
BackgroundComputational de novo discovery of transcription factor binding sites is still a challenging problem. The growing number of sequenced genomes allows integrating orthology evidence with coreg
Twenty core C. albicans microcolony genes were analyzed using the PathoYeastract database to predict transcription factors that regulated at least half of the core microcolony genes.
Non-coding genetic variants/mutations can play functional roles in the cell by disrupting regulatory interactions between transcription factors (TFs) and their genomic target sites. For most human TFs
Table 6 indicates the average AUC score across ten classifiers where training data from one TF (rows) was used to train a classifier that classified TFBS for another TF (columns).
