Bioinformatics in Health Sciences Mini Research Project submission

HTI 5052         Bioinformatics in Health Sciences

Mini Research Project

Student Name: Tse Mavis Wing Yee

Student No. : 10677249G

Task 1:

Research topic is Sequential Alignment.

Task 2:

Journal review: Nucleic Acids Research

Journal topic: AlexSys: a knowledge-based expert system for multiple sequence alignment construction and analysis

Mohamed Radhouene Aniba1,2,3,4, Olivier Poch1,2,3,4, Aron Marchler-Bauer5 and Julie Dawn Thompson1,2,3,4,*

1Department of Structural Biology and Genomics, Institut de Ge´ ne´ tique et de Biologie Mole´ culaire et Cellulaire (IGBMC), 2Institut National de la Sante´ et de la Recherche Me´ dicale (INSERM), 3The Centre National de la Recherche Scientifique (CNRS), UMR7104, F-67400 Illkirch, 4Universite´ Louis Pasteur, F-67000 Strasbourg, France and 5NCBI/NLM/NIH, 8600 Rockville Pike, Bldg. 38A, Bethesda, MD 20894, USA

Received January 29, 2010; Revised April 26, 2010; Accepted May 25, 2010

Multiple sequence alignment (MSA) is a sequence alignment of three or more biological sequence, the input set of query sequences are assumed to have share a common ancestor via evolution lineage, to conduct the evolutionary origins of the sequences, phylogenetic analysis can be conducted; as a resulting MSA, phylogenetic analysis can be conducted.  MSAs are more computationally complex, hence require more sophisticated methodologies than pair-wise alignment.

Nowadays many different algorithms are developed to construct MSAs, however a new technology AlexSys is an intelligent engine which based on the sequence input to auto select appropriate aligner a priori, it is suitable for high throughput project according to the good compromise between alignment quality and the operation duration.  Previous studies show that not a single aligner outperform the other; even though previous methods provide more accurate alignment, they are less efficient due to the need to run the sequence and the best solution is said to be a posteriori.  Therefore AlexSys is designed to combine the power of the existing approaches in a single system which is both efficient and easy to use.

Task 3:

AlexSys is therefore designed to combine the power of the existing approaches in a single system which is both efficient and easy to use for the biologist; however, there is no single algorithm that works best on all problems.

The Problem can be solved by alter the system from a combined system to a multiply-step single system, the disadvantage however is the duration of collecting data will be longer.