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Abstract:
A Summary: Alternative polyadenylation (APA) is now emerging as a widespread mechanism modulated tissue-specifically, which highlights the need to define tissue-specific poly(A) sites for profiling APA dynamics across tissues. We have developed an R package called TSAPA based on the machine learning model for identifying tissue-specific poly(A) sites in plants. A feature space including more than 200 features was assembled to specifically characterize poly(A) sites in plants. The classification model in TSAPA can be customized by selecting desirable features or classifiers. TSAPA is also capable of predicting tissue-specific poly(A) sites in unannotated intergenic regions. TSAPA will be a valuable addition to the community for studying dynamics of APA in plants.
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BIOINFORMATICS
ISSN: 1367-4803
Year: 2018
Issue: 12
Volume: 34
Page: 2123-2125
4 . 5 3 1
JCR@2018
4 . 4 0 0
JCR@2023
ESI Discipline: BIOLOGY & BIOCHEMISTRY;
ESI HC Threshold:212
JCR Journal Grade:1
CAS Journal Grade:1
Cited Count:
WoS CC Cited Count: 0
SCOPUS Cited Count: 6
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 1
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