کتاب های Hernández-Tamames, Juan Antonio; Mato Abad, Virginia; García-Álvarez, Roberto; González-Zabaleta, Javier; Pereira-Loureiro, Javier; Álvarez-Linera, Juan

download pdf Effect of water T2 shortening in the quantification of in-vitro proton MR spectroscopy, دانلود Effect of water T2 shortening in the quantification of in-vitro proton MR spectroscopy,Hernández-Tamames, Juan Antonio; Mato Abad, Virginia; García-Álvarez, Roberto; González-Zabaleta, Javier; Pereira-Loureiro, Javier; Álvarez-Linera, Juan, کتاب های Hernández-Tamames, Juan Antonio; Mato Abad, Virginia; García-Álvarez, Roberto; González-Zabaleta, Javier; Pereira-Loureiro, Javier; Álvarez-Linera, Juan,Wiley 2015-05-21, لیست کتاب های Wiley 2015-05-21,WorldCat, کتاب های WorldCat

گت بلاگز Internet Prediction of nucleoitide binding peptides using star graph topological indices / دانلود فایل

مشخصات کلی Prediction of nucleoitide binding peptides using star graph topological indices

نویسنده کتاب (Author):

Liu, Yong; Munteanu, Cristian-Robert; Fernández Blanco, Enrique; Tan, Zhiliang; Santos-del-Riego, Antonino; Pazos, A.

انتشارات (Publisher):

Elsevier 2015-08-05

ویرایش و نوع فایل (Edition/Format):

 Downloadable article : English

منبع (Database):

WorldCat

عنوان ژورنال (Publication):

liu-y-munteanu-cr-fernandez-blanco-e-tan-z-santos-del-riego-a-pazos-a-prediction-of-nucleoitide-binding-peptides-using-star-graph-topological-indices-mol-inform-20153411-12736-741

موضوع (Subject):

QSAR       Nucleotide binding proteins       Star Graph       View all subjects      

توضیحات خلاصه (Summary):

[Abstract] The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this biological function is an important research topic. The current study proposes a mixed methodology to obtain the first classification model that is able to predict new nucleotide binding peptides, using only the amino acid sequence. Thus, the methodology uses a Star graph molecular descriptor of the peptide sequences and the Machine Learning technique for the best classifier. The best model represents a Random Forest classifier based on two features of the embedded and non-embedded graphs. The performance of the model is excellent, considering similar models in the field, with an Area Under the Receiver Operating Characteristic Curve (AUROC) value of 0.938 and true positive rate (TPR) of 0.886 (test subset). The prediction of new nucleotide binding peptides with this model could be useful for drug target studies in drug development.  Read more…

ژانر / فرم:info:eu-repo/semantics/article

موضوع:Internet resource

نوع منبع:Internet Resource, Article

تمام نویسندگان / همکاران: Liu, Yong; Munteanu, Cristian-Robert; Fernández Blanco, Enrique; Tan, Zhiliang; Santos-del-Riego, Antonino; Pazos, A.

شناسه OCLC:979265327

Language Note:English

فهرست محتوا:http://hdl.handle.net/2183/17456

نویسنده : getblogs