5 research outputs found
Chromatin interaction neural network (ChINN): a machine learning-based method for predicting chromatin interactions from DNA sequences.
Chromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is limited. We develop a computational method, chromatin interaction neural network (ChINN), to predict chromatin interactions between open chromatin regions using only DNA sequences. ChINN predicts CTCF- and RNA polymerase II-associated and Hi-C chromatin interactions. ChINN shows good across-sample performances and captures various sequence features for chromatin interaction prediction. We apply ChINN to 6 chronic lymphocytic leukemia (CLL) patient samples and a published cohort of 84 CLL open chromatin samples. Our results demonstrate extensive heterogeneity in chromatin interactions among CLL patient samples
QUANTIFICATION OF TELOMERASE COMPLEX PROTEINS AND TRANSCRIPTIONAL REGULATION OF TERT
Ph.DDOCTOR OF PHILOSOPH
Non-canonical roles of canonical telomere binding proteins in cancers
10.1007/s00018-021-03783-0Cellular and Molecular Life Sciences7894235-425