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Knowledge-based System for Amyloidogenic Protein Sequence Analysis using Soft Computing Approach

Nair, Smitha Sunil Kumaran (2014) Knowledge-based System for Amyloidogenic Protein Sequence Analysis using Soft Computing Approach. Phd. Thesis thesis, Manipal Institute of Technology, Manipal.

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Abstract

Computational biology is a general approach toward the solu- tion of scienti�c problems through which advanced computational techniques are utilized to decipher the languages of biology. The technological advances in the �eld of computers empowered researchers in collecting and analyzing enormous volume of data to a scale previously impossible. The impact of this advancement is now felt in the biological sciences. Now a days, one of the most challenging problems in computational biology is to transform the enormous volume of data into knowledge. Machine learning algorithms have become an important tool to carry out this transformation. The area of computational biology contributes to biological sequence analysis by constructing algorithms that address relevant problems. This thesis concerns with the design and im- plementation of knowledge-based system to solve a problem in the domain of molecular biology. Amyloid-like �brils may be formed from amylome, the universe of protiens. Today the association between protein �brils and amyloid diseases, including Alzheimer's and prion diseases has been established. In such cases, proteins aggregate into speci�c �brous structures to form insoluble plaques known as amyloid leading to progressive neuronal degeneration and death. The infer-ence that there is a predisposition for primary sequence-speci�c formation of amyloidal �brils is made from the wet lab proven experimental remarks that not all proteins are amyloidogenic and that only precise continuous stretches of amyloid �bril forming peptides are more amyloidogenic than other regions. Prediction of such short stretches in protein sequences capable of form-ing amyloid-like �brils is important in understanding the underlying cause of amyloid illnesses thereby aiding in the discovery of sequence-targeted anti- aggregation pharmaceuticals. Moreover, methodologies identifying aggregation- prone motifs have a wide range of biotechnological applications such as to improve the solubility of recombinant proteins for industrial and pharmaceutical purposes and in peptide-based biomaterial engineering. Processing of biological samples in vitro is very expensive in terms of cost, time and e�ort. Due to these constraints of experimental molecular techniques in identifying such mo- tif segments, it is highly desirable to develop computational models to provide better and a�ordable in silico predictions.

Item Type: Thesis (Phd. Thesis)
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Depositing User: MIT Library
Date Deposited: 22 May 2014 09:14
Last Modified: 07 Nov 2014 09:12
URI: http://eprints.manipal.edu/id/eprint/139560

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