Cargando…
Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning
BACKGROUND: Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also...
Autores principales: | Kaundal, Rakesh, Sahu, Sitanshu S, Verma, Ruchi, Weirick, Tyler |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3851450/ https://www.ncbi.nlm.nih.gov/pubmed/24266945 http://dx.doi.org/10.1186/1471-2105-14-S14-S7 |
Ejemplares similares
-
Predicting genome-scale Arabidopsis-Pseudomonas syringae interactome using domain and interolog-based approaches
por: Sahu, Sitanshu S, et al.
Publicado: (2014) -
LacSubPred: predicting subtypes of Laccases, an important lignin metabolism-related enzyme class, using in silico approaches
por: Weirick, Tyler, et al.
Publicado: (2014) -
Plant-mSubP: a computational framework for the prediction of single- and multi-target protein subcellular localization using integrated machine-learning approaches
por: Sahu, Sitanshu S, et al.
Publicado: (2019) -
PHDcleav: a SVM based method for predicting human Dicer cleavage sites using sequence and secondary structure of miRNA precursors
por: Ahmed, Firoz, et al.
Publicado: (2013) -
A Support Vector Machine based method to distinguish proteobacterial proteins from eukaryotic plant proteins
por: Verma, Ruchi, et al.
Publicado: (2012)