The Insulin Bio Intervals

Dr. Lutvo KuriA
Dr. Lutvo KuriA * §
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The Insulin Bio Intervals

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Abstract

The modern science mainly treats the biochemical basis of sequencing in bio-macromolecules and processes in medicine and biochemistry. One can ask weather the language of biochemistry is the adequate scientific language to explain the phenomenon in that science. Is there maybe some other language, out of biochemistry, that determines how the biochemical processes will function and what the structure and organization of life systems will be? The research results provide some answers to these questions. They reveal to us that the process of sequencing in bio-macromolecules is conditioned and determined not only through biochemical, but also through cybernetic and information principles. Many studies have indicated that analysis of protein sequence codes and various sequence-based prediction approaches, such as predicting drug-target interaction networks (He et al.,

References

37 Cites in Article
  1. K Chou (2002). Gene Cloning & Expression Technologies.
  2. K Chou (2001). Prediction of protein cellular attributes using pseudo amino acid composition.
  3. X Xiao,S Shao,Y Ding,Z Huang,Y Huang,K-C Chou (2005). Using complexity measure factor to predict protein subcellular location.
  4. X Xiao,S Shao,Y Ding,Z Huang,X Chen,K-C Chou (2005). Using cellular automata to generate image representation for biological sequences.
  5. X Xiao,S Shao,Y Ding,Z Huang,X Chen,K Chou (2005). An Application of Gene Comparative Image for Predicting the Effect on Replication Ratio by HBV Virus Gene Missense Mutation.
  6. X Xiao,S Shao,Z Huang,K Chou (2006). Using pseudo amino acid composition to predict protein structural classes: approached with complexity measure factor.
  7. X Xiao,S Shao,Y Ding,Z Huang,K-C Chou (2006). Using cellular automata images and pseudo amino acid composition to predict protein subcellular location.
  8. Kuo-Chen Chou (2005). Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes.
  9. K Chou,Y Cai (2005). Prediction of membrane protein types by incorporating amphipathic effects.
  10. Z Feng (2001). Prediction of the subcellular location of prokaryotic proteins based on a new representation of the amino acid composition.
  11. Z Feng (2002). An overview on predicting the subcellular location of a protein.
  12. M Wang,J Yang,Z Xu,K Chou (2005). SLLE for predicting membrane protein types.
  13. S Wang,J Yang,K Chou (2006). Using stacked generalization to predict membrane protein types based pseudo amino acid composition.
  14. M Wang,J Yang,G-P Liu,Z-J Xu,K-C Chou (2004). Weighted-support vector machines for predicting membrane protein types based on pseudo-amino acid composition.
  15. S-W Zhang,Q Pan,H-C Zhang,Z-C Shao,J-Y Shi (2006). Prediction of protein homo-oligomer types by pseudo amino acid composition: Approached with an improved feature extraction and Naive Bayes Feature Fusion.
  16. Y Gao,S Shao,X Xiao,Y Ding,Y Huang,Z Huang,K-C Chou (2005). Using pseudo amino acid composition to predict protein subcellular location: Approached with Lyapunov index, Bessel function, and Chebyshev filter.
  17. Y-Z Guo,M Li,M Lu,Z Wen,K Wang,G Li,J Wu (2006). Classifying G protein-coupled receptors and nuclear receptors on the basis of protein power spectrum from fast Fourier transform.
  18. Hui Liu,Meng Wang,Kuo-Chen Chou (2005). Low-frequency Fourier spectrum for predicting membrane protein types.
  19. Kuo-Chen Chou (2000). Prediction of Protein Subcellular Locations by Incorporating Quasi-Sequence-Order Effect.
  20. Kuo‐chen Chou (1995). A novel approach to predicting protein structural classes in a (20–1)‐D amino acid composition space.
  21. K Chou,C Zhang (1994). Predicting protein folding types by distance functions that make allowances for amino acid interactions.
  22. Kuo-Chen Chou,Chun-Ting Zhang (1995). Prediction of Protein Structural Classes.
  23. K Chou,D Elrod (1999). Protein subcellular location prediction.
  24. K-C Chou (2000). Prediction of Protein Structural Classes and Subcellular Locations.
  25. Kuo‐chen Chou,David Elrod (1999). Prediction of membrane protein types and subcellular locations.
  26. Kuo-Chen Chou,David Elrod (2003). Prediction of Enzyme Family Classes.
  27. K Chou,Y Cai (2004). Predicting enzyme family class in a hybridization space.
  28. K Chou,D Elrod (2002). Bioinformatical analysis of G-protein-coupled receptors.
  29. K Chou (2005). Prediction of G-protein-coupled receptor classes.
  30. K Chou,Y Cai (2006). Prediction of protease types in a hybridization space.
  31. K Chou,Y Cai (2006). Predicting protein-protein interactions from sequences in a hybridization space.
  32. K Chou,Y Cai,W Zhong (2006). Predicting networking couples for metabolic pathways of Arabidopsis.
  33. Kuo‐chen Chou,Yu‐dong Cai (2003). Predicting protein quaternary structure by pseudo amino acid composition.
  34. L Kurić (2007). The digital language of amino acids.
  35. L Kurić (2009). The Atomic Genetic Code.
  36. L Kurić (1986). La Societe de Statistique de Paris. Notes sur Paris. (A l'Occasion du Cinquantenaire de la Societe et de la XII e Session de l'Institut International de Statistique..
  37. L Kurić (2010). In This Issue—May 15, 2010.
Show All References
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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Lutvo KuriA. 1970. "The Insulin Bio Intervals". Global Journal of Medical Research - B: Pharma, Drug Discovery, Toxicology & Medicine GJMR-B Volume 13 (GJMR Volume 13 Issue B2).

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Journal Specifications

Crossref Journal DOI 10.17406/gjmr

Print ISSN 0975-5888

e-ISSN 2249-4618

Keywords
algorithmbio intervalhuman insulininsulin codeinsulin model
Classification
GJMR-B Classification NLMC Code: WK 820
  • Submission ReceivedDecember 9, 2012
  • Peer Review Double Blind
    Handling Editor
  • Accepted January 2, 2013
  • Published January 15, 2013
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Language
English
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The Insulin Bio Intervals

Dr. KuriA
Dr. KuriA Centro UniversitArio Feevale
  • Submission ReceivedDecember 9, 2012
  • Peer Review Double Blind
    Handling Editor
  • Accepted January 2, 2013
  • Published January 15, 2013