Sequence analysis
Sequence analysis is a method used in bioinformatics to identify and predict the properties of biomolecules. It is a broad field that encompasses many techniques and sub-disciplines.
Overview[edit | edit source]
Sequence analysis involves the study of DNA, RNA, and protein sequences, primarily to understand their structure, function, and evolution. It is a fundamental method in the field of bioinformatics, with applications in genomics, proteomics, and metabolomics.
Techniques[edit | edit source]
There are several techniques used in sequence analysis, including:
- Sequence alignment: This is the process of arranging two or more sequences to identify regions of similarity. These similarities could be a result of functional, structural, or evolutionary relationships between the sequences.
- Phylogenetic analysis: This involves the use of sequence data to construct phylogenetic trees, which depict the evolutionary relationships among various biological species or other entities.
- Motif detection: This is the process of finding recurring patterns, or motifs, in DNA, RNA, or protein sequences. Motifs can have biological significance and can be used to predict the function of unknown sequences.
- Gene prediction: This is the process of identifying the regions of genomic DNA that encode genes. This is done using both computational prediction methods and experimental evidence.
Applications[edit | edit source]
Sequence analysis has a wide range of applications in biological research and medicine. For example, it is used in genetic testing to identify genetic disorders, in vaccine development to design effective vaccines, and in drug discovery to identify potential drug targets.
See also[edit | edit source]
References[edit | edit source]
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Contributors: Prab R. Tumpati, MD