تفاصيل الوثيقة

نوع الوثيقة : مقال في مجلة دورية 
عنوان الوثيقة :
repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects
repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects
 
لغة الوثيقة : الانجليزية 
المستخلص : In order to develop powerful computational predictors for identifying the biological features or attributes of DNAs, one of the most challenging problems is to find a suitable approach to effectively represent the DNA sequences. To facilitate the studies of DNAs and nucleotides, we developed a Python package called representations of DNAs (repDNA) for generating the widely used features reflecting the physicochemical properties and sequence-order effects of DNAs and nucleotides. There are three feature groups composed of 15 features. The first group calculates three nucleic acid composition features describing the local sequence information by means of kmers; the second group calculates six autocorrelation features describing the level of correlation between two oligonucleotides along a DNA sequence in terms of their specific physicochemical properties; the third group calculates six pseudo nucleotide composition features, which can be used to represent a DNA sequence with a discrete model or vector yet still keep considerable sequence-order information via the physicochemical properties of its constituent oligonucleotides. In addition, these features can be easily calculated based on both the built-in and user-defined properties via using repDNA. 
ردمد : 1367-4811 
اسم الدورية : Bioinformatics 
المجلد : 31 
العدد : 8 
سنة النشر : 1436 هـ
2015 م 
نوع المقالة : مقالة علمية 
تاريخ الاضافة على الموقع : Sunday, April 24, 2016 

الباحثون

اسم الباحث (عربي)اسم الباحث (انجليزي)نوع الباحثالمرتبة العلميةالبريد الالكتروني
Bin LiuLiu, Bin باحث رئيسي  
Fule LiuLiu, Fule باحث مشارك  
Longyun FangFang, Longyun باحث مشارك  
Xiaolong WangWang, Xiaolong باحث مشارك  
Kuo-Chen ChouChou, Kuo-Chen باحث مشارك  

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