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Personal genomics or consumer genetics is the branch of genomics concerned with the sequencing, analysis and interpretation of the genome of an individual. The genotyping stage employs different techniques, including single-nucleotide polymorphism (SNP) analysis chips (typically 0.02% of the genome), or partial or full genome sequencing.
In the field of genetic sequencing, genotyping by sequencing, also called GBS, is a method to discover single nucleotide polymorphisms (SNP) in order to perform genotyping studies, such as genome-wide association studies . [1] GBS uses restriction enzymes to reduce genome complexity and genotype multiple DNA samples. [2]
Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data, [1] including both DNA and RNA sequence as well as other "post-genomic" data (i.e., experimental data obtained with technologies that require the genome sequence, such as genomic DNA microarrays).
Meta-genetic programming is the proposed meta-learning technique of evolving a genetic programming system using genetic programming itself. It suggests that chromosomes, crossover, and mutation were themselves evolved, therefore like their real life counterparts should be allowed to change on their own rather than being determined by a human ...
Due to current technological limitations, almost all genotyping is partial. That is, only a small fraction of an individual's genotype is determined, such as with (epi)GBS (Genotyping by sequencing) or RADseq. New [2] mass-sequencing technologies promise to provide whole-genome genotyping (or whole genome sequencing) in the future.
Next-generation sequencing technologies such as pyrosequencing sequence less than 250 bases in a read which limits their ability to sequence whole genomes. However, their ability to generate results in real-time and their potential to be massively scaled up makes them a viable option for sequencing small regions to perform SNP genotyping.
The calculation of prior probabilities depends on available data from the genome being studied, and the type of analysis being performed. For studies where good reference data containing frequencies of known mutations is available (for example, in studying human genome data), these known frequencies of genotypes in the population can be used to estimate priors.
Gene expression programming (GEP) in computer programming is an evolutionary algorithm that creates computer programs or models. These computer programs are complex tree structures that learn and adapt by changing their sizes, shapes, and composition, much like a living organism.