Applications of computational algorithm tools to identify functional SNPs

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variations in humans. Understanding the functions of SNPs can greatly help to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. The method to identify functio...

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Veröffentlicht in:	Functional & integrative genomics Jg. 8; H. 4; S. 309 - 316
Hauptverfasser:	George Priya Doss, C, Sudandiradoss, C, Rajasekaran, R, Choudhury, Parikshit, Sinha, Priyanka, Hota, Pragnya, Batra, Udit Prakash, Rao, Sethumadhavan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Berlin/Heidelberg : Springer-Verlag 01.11.2008 Springer-Verlag Springer Springer Nature B.V
Schlagworte:	3' untranslated regions Algorithms Animal Genetics and Genomics Biochemistry Bioinformatics Biological and medical sciences Biomedical and Life Sciences Cell Biology chemistry Fundamental and applied biological sciences. Psychology General aspects Genetic research genetics Genotype Genotype & phenotype human genetics Humans in vivo studies Life Sciences Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Microbial Genetics and Genomics Modeled structure Molecular Sequence Data Phenotype phenotypic variation Plant Genetics and Genomics Polymorphism Polymorphism, Single Nucleotide Protein Conformation Review single nucleotide polymorphism SNPs Software TP53 gene transcription factors Tumor Suppressor Protein p53 Tumor Suppressor Protein p53 - chemistry Tumor Suppressor Protein p53 - genetics Modeled structure SNPs TP53 gene TP53 Gene Identification Models Single nucleotide polymorphism Structure Algorithm Application
ISSN:	1438-793X, 1438-7948
Online-Zugang:	Volltext
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