Accurate prediction of cell type-specific transcription factor binding
2019
Keilwagen, Jens | Posch, Stefan | Grau, Jan
Prediction of cell type-specific, in vivo transcription factor binding sites is one of the central challenges in regulatory genomics. Here, we present our approach that earned a shared first rank in the “ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge” in 2017. In post-challenge analyses, we benchmark the influence of different feature sets and find that chromatin accessibility and binding motifs are sufficient to yield state-of-the-art performance. Finally, we provide 682 lists of predicted peaks for a total of 31 transcription factors in 22 primary cell types and tissues and a user-friendly version of our approach, Catchitt, for download.
اظهر المزيد [+] اقل [-]الكلمات المفتاحية الخاصة بالمكنز الزراعي (أجروفوك)
المعلومات البيبليوغرافية
الناشر BioMed Central
الرقم التسلسلي المعياري الدولي (ردمد) 1465-6906 | 1465-6914 | 1474-760X | 0445-9164 | 4532-0094تم تزويد هذا السجل من قبل Julius Kühn-Institut