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Abstrak :
One of the dominant problems in computational molecular biology is multiple sequence alignment (MSA) of DNA. Many methods have been proposed to solve MSA problem such as dynamic programming and heuristic. A method has been proposed by Althaus et al. to solve MSA problem which is based on integer linear programming (ILP). The general ILP formulation of the MSA is derived from the graph representation of the MSA problem. Although we have the general ILP formulation of the MSA problem, constructing the ILP model of an MSA that can be solved directly using an ILP solver is not straightforward. We develop a MATLAB program that can generate and solve the ILP model of an MSA problem. The method that is used to solve the ILP model is branch-and-bound. The constructed program can generate the ILP model of any given MSA problem but can only solve an MSA problem of a small number of short DNA sequences. The result of the program is the aligned sequences of the MSA problem.

Abstrak :
This skripsi discusses a method known DIALIGN to find the best alignment of two DNA sequences. This algorithm is based on segment-tosegment comparison instead of the commonly used residue-to-residue comparison. Also, this algorithm avoids the wellknown difficulties concerning the choice of appropriate gap penalties. In DIALIGN, all possible diagonals of the input sequences will be weighted and compared to find the diagonals which compose optimal alignment. Diagonal weight is based on match probability of residues in the diagonal. Having the maximum score, the alignment will be constructed by tracing back the components which produce the maximum score. The resulted alignment can be considered as consistent collections of diagonals. In the final, the algorithm is implemented in a program. According to the simulation of the program, DIALIGN algorithm is able to produce optimal sequence alignment from a pair of sequence. And the program performs well on short sequences.

Abstrak :
Penyejajaran barisan DNA dilakukan dengan tujuan melihat tingkat kemiripan antara barisan DNA. Pada tugas akhir ini, dilakukan penyejajaran barisan DNA dengan menggunakan algoritma X-drop dan algoritma greedy. Algoritma X-drop melakukan penyejajaran barisan DNA dengan menggunakan pendekatan pemrograman dinamik. Algoritma greedy merupakan modifikasi algoritma X-drop.

Kedua algoritma ini bekerja dengan menelusuri penyejajaran yang tidak memenuhi kondisi X-drop, yaitu kondisi yang bergantung pada nilai X yang dipilih oleh pengguna, sehingga kinerja dari kedua algoritma ini bergantung pada pemilihan nilai X yang tepat. Pada simulasi yang telah dilakukan, dengan menggunakan nilai X yang sama, kedua algoritma memberikan hasil penyejajaran yang sama, dengan running time algoritma greedy lebih baik dari algoritma X-drop.

Abstrak :
Multiple sequence alignment (MSA) is a sequence alignment of three or more biological sequences, which are assumed to have an evolutionary relationship. Because three or more sequences of biologically relevant length can be difficult and are almost always time-consuming to align by hand, computational algorithm are used to produce and analyze the alignments. Computational algorithm can be constructed by transforming multiple sequence alignment problems into graph problems. The problem of finding an optimal alignment turns into finding a gapped trace of a gapped extended alignment graph. However, this process is difficult to be done manually. Hence, we study the properties of a gapped trace and using these properties to build a general integer linear programming formulation for MSA problem.