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Identification of human proteins using the linguist's tools
S Chattopadhyay1, J Chakrabarti, D Bandyopadhyay
1Department of Theoretical Physics, Indian Association for the Cultivation of Science, Calcutta 700 032.
Indian Journal of Biochemistry & Biophysics
|September 21, 2001
Summary
Statistical linguistics methods reveal that Zipf's exponent can differentiate and identify distinct human protein sequences derived from exons. This approach shows promise for analyzing genetic information.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Human proteins are constructed from symbolic sequences of exons.
- Statistical linguistics offers tools for analyzing symbolic sequences.
Purpose of the Study:
- To apply statistical linguistics methods, specifically Zipf's laws, to human exon sequences.
- To determine if Zipf's exponent can differentiate and identify disparate human sequences.
Main Methods:
- Applying methods of statistical linguistics, including Zipf's laws, to symbolic exon sequences.
- Analyzing the Zipf's exponent of these sequences.
Main Results:
- Zipf's exponent shows potential for differentiating human protein sequences.
- The Zipf's exponent can be used to identify disparate human sequences.
Conclusions:
- Statistical linguistics, particularly Zipf's exponent, is a promising approach for analyzing human exon sequences.
- Zipf's exponent serves as a distinguishing feature for human genetic sequences.