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"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 anoptimal 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."

"Tree Based Of Consistency Objective Function For Evaluation Alignment (T-COFFEE) merupakan algoritma untuk menyelesaikan permasalahan multiple sequence alignment (MSA). Algoritma ini menggabungkan dua teknik, pertama Tree Based yang merupakan Progressive Alignment dan kedua Consistency Objective Function berupa extending library. Pada pembahasan skripsi ini akan digunakan data sequence dari database ensembl yang terdiri dari database DNA atau protein yang akan diproses dengan global alignment (Needleman-Wunsch) dan local alignment (Smith- Waterman) dengan harapan informasi yang dihasilkan pada akhir pensejajaran akan menggambarkan hasil penyejajaran yang optimal. Proses pembentukan primary dan extended library pada T-COFFEE membutuhkan waktu lama sehingga untuk mempercepat waktu proses T-COFFEE digunakan teknik komputasi paralel Graphic Processing Unit (GPU). Skripsi ini akan menjelaskan algoritma T-COFFEE, algoritma paralel T-COFFEE, serta mengukur efisiensi dari kedua algoritma tersebut.

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Tree Based Of Consistency Objective Function For Evaluation Alignment (T-COFFEE) is an algorithm to solve the problem of multiple sequence alignment (MSA). This algorithm combines two techniques, first is Tree-Based with Progressive Alignment and second is Consistency of Objective Function by extending library. In this skripsi, we use the data from the ensembl database that consisting of DNA or protein data. Those data will be processed by the global alignment (Needleman-Wunsch) and local alignment (Smith-Waterman) that is expected to give optimal alignment result at the end of the alignment process. The generating of Primary and Extended Library is the most time consuming, hence to speed up the T-COFFEE process, a parallel version of T-COFFEE algorithm is needed by implementing parallel computing on Graphic Processing Unit (GPU). In this skripsi, the T-COFFEE algorithm, the parallel T-COFFEE algorithm, and the measurement of their speed up and efficiency will be discuss."

"Salah satu dari masalah-masalah dominan pada komputasi biologi molekuler adalah penyejajaran barisan berganda (Multiple Sequence Alignment - MSA) dari DNA. Banyak metode yang telah diajukan untuk menyelesaikan masalah MSA seperti pemrograman dinamik dan heuristik. Satu metode telah diajukan oleh Althaus et al. untuk menyelesaikan masalah MSA yang didasarkan pada pemrograman linear bilangan bulat (Integer Linear Programming - ILP). Formulasi ILP umum dari masalah MSA diturunkan dari representasi graf dari masalah MSA. Walaupun formulasi ILP umum dari masalah MSA diketahui, membentuk model ILP dari suatu masalah MSA yang dapat diselesaikan langsung menggunakan suatu solver ILP tidaklah mudah. Sebuah program yang dapat membangun dan menyelesaikan model ILP dari sebuah masalah MSA menggunakan MATLAB telah dibuat. Metode yang digunakan untuk menyelesaikan model ILP tersebut adalah branch-and-bound. Program yang telah dibuat dapat menghasilkan model ILP dari sembarang masalah MSA yang diberikan tetapi hanya dapat menyelesaikan masalah MSA dari sejumlah kecil barisanbarisan DNA yang pendek. Hasil dari program tersebut adalah penejajaran barisan-barisan DNA dari masalah MSA yang diberikan.

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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."

"One of the dominant problems in computational molecular biology ismultiple sequence alignment (MSA) of DNA. Many methods have beenproposed to solve MSA problem such as dynamic programming and heuristic.A method has been proposed by Althaus et al. to solve MSA problem which isbased on integer linear programming (ILP). The general ILP formulation ofthe 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 anILP solver is not straightforward. We develop a MATLAB program that cangenerate and solve the ILP model of an MSA problem. The method that isused to solve the ILP model is branch-and-bound. The constructed programcan generate the ILP model of any given MSA problem but can only solve anMSA problem of a small number of short DNA sequences. The result of theprogram is the aligned sequences of the MSA problem."

"Skripsi ini membahas suatu metode yang biasa dikenal dengan nama DIALIGN untuk mencari penyejajaran terbaik dari dua barisan DNA. Algoritma ini berdasarkan pada perbandingan segmen dengan segmen bukan seperti yang biasa dilakukan yaitu perbandingan residu dengan residu. Selain itu, algoritma ini juga menghindari kesulitan dalam menentukan pemilihan untuk memberikan penalti yang tepat bagi gap. Pada DIALIGN, seluruh diagonaldiagonal yang mungkin dari input barisan yang diberikan akan diberi bobot dan dibandingkan dengan diagonal yang lain untuk mendapatkan diagonaldiagonal yang akan membentuk penyejajaran optimal. Penghitungan bobot dari diagonal berdasarkan pada probabilitas kesamaan residu pada diagonal. Setelah diperoleh skor maksimum, penyejajaran akan dibangun dengan cara menelusuri kembali komponen-komponen yang telah memproduksi skor maksimum. Penyejajaran yang telah dihasilkan merupakan sehimpunan diagonal-diagonal yang konsisten. Di akhir, algoritma DIALIGN diimplementasikan pada suatu program. Berdasarkan simulasi program, algoritma DIALIGN mampu memproduksi penyejajaran optimal dari sepasang barisan. Dan kinerja program sangat baik untuk barisan-barisan pendek.

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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."

"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 matchprobability 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."

"Explores modern topics in graph theory and its applications to problems in transportation, genetics, pollution, perturbed ecosystems, urban services, and social inequalities. The author presents both traditional and relatively atypical graph-theoretical topics to best illustrate applications."

"This book focuses on the role of interdependent infrastructure systems in such smart cities especially as it relates to timely and poignant questions about resilience and sustainability. In particular, the goal of this book is to present, in one volume, a consistent Hetero-Functional Graph Theoretic (HFGT) treatment of interdependent smart city infrastructures as an overarching application domain of engineering systems. This work may be contrasted to the growing literature on multi-layer networks, which despite significant theoretical advances in recent years, has modeling limitations that prevent their real-world application to interdependent smart city infrastructures of arbitrary topology. In contrast, this book demonstrates that HFGT can be applied extensibly to an arbitrary number of arbitrarily connected topologies of interdependent smart city infrastructures. It also integrates, for the first time, all six matrices of HFGT in a single system adjacency matrix. The book makes every effort to be accessible to a broad audience of infrastructure system practitioners and researchers (e.g. electric power system planners, transportation engineers, and hydrologists, etc.). Consequently, the book has extensively visualized the graph theoretic concepts for greater intuition and clarity. Nevertheless, the book does require a common methodological base of its readers and directs itself to the Model-Based Systems Engineering (MBSE) community and the Network Science Community (NSC). To the MBSE community, we hope that HFGT will be accepted as a quantification of many of the structural concepts found in model-based systems engineering languages like SysML. To the NSC, we hope to present a new view as how to construct graphs with fundamentally different meaning and insight. Finally, it is our hope that HFGT serves to overcome many of the theoretical and modeling limitations that have hindered our ability to systematically understand the structure and function of smart cities. "