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Detecting De Novo Plasmodesmata Targeting Signals and Identifying PD Targeting Proteins
- Source :
- Computational Advances in Bio and Medical Sciences ISBN: 9783030461645, ICCABS
- Publication Year :
- 2020
- Publisher :
- Springer International Publishing, 2020.
-
Abstract
- Subcellular localization plays important roles in protein’s functioning. In this paper, we developed a hidden Markov model to detect de novo signals in protein sequences that target at a particular cellular location: plasmodesmata. We also developed a support vector machine to classify plasmodesmata located proteins (PDLPs) in Arabidopsis, and devised a decision-tree approach to combine the SVM and HMM for better classification performance. The methods achieved high performance with ROC score 0.99 in cross-validation test on a set of 360 type I transmembrane proteins in Arabidopsis. The predicted PD targeting signals in one PDLP have been experimentally verified.
- Subjects :
- Signal peptide
0303 health sciences
biology
Computer science
Computational biology
Plasmodesma
Subcellular localization
biology.organism_classification
Transmembrane protein
Support vector machine
03 medical and health sciences
0302 clinical medicine
Arabidopsis
Hidden Markov model
030217 neurology & neurosurgery
Cellular localization
030304 developmental biology
Subjects
Details
- ISBN :
- 978-3-030-46164-5
- ISBNs :
- 9783030461645
- Database :
- OpenAIRE
- Journal :
- Computational Advances in Bio and Medical Sciences ISBN: 9783030461645, ICCABS
- Accession number :
- edsair.doi...........94dd0f187c00105f2b5e530f0725851a