DOCSLIB.ORG

Advances and Applications of Bioinformatics in Various Fields of Life

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Advances and Applications of Bioinformatics in Various Fields of Life International Journal of Fauna and Biological Studies 2018; 5(2): 03-10 ISSN 2347-2677 IJFBS 2018; 5(2): 03-10 Advances and applications of Bioinformatics in various Received: 04-01-2018 Accepted: 05-02-2018 fields of life M Younus Wani Temperate Sericulture Research M Younus Wani, NA Ganie, S Rani, S Mehraj, MR Mir, MF Baqual, KA Institute, Mirgund, SKUAST- Kashmir, J&K, India Sahaf, FA Malik and KA Dar NA Ganie Abstract Temperate Sericulture Research Bioinformatics is an interdisciplinary area of the science composed of biology, mathematics and Institute, Mirgund, SKUAST- Kashmir, J&K, India computer science. Bioinformatics is the application of information technology to manage biological data that helps in decoding plant genomes. The field of bioinformatics emerged as a tool to facilitate S Rani biological discoveries more than 10 years ago. With the development of Human Genome Project (HGP), Temperate Sericulture Research the data of biology increased fabulously and marvelously. The ability to capture, manage, process, Institute, Mirgund, SKUAST- analyze and interpret data became more important than ever. Bioinformatics and computers can help Kashmir, J&K, India scientists to solve it. Here are introduced roles of bioinformatics, meanwhile Web tools and resources of bioinformatics are reviewed and its applications in agriculture and relevance with other disciplines is also S Mehraj highlighted. Application of various bioinformatics tools in biological research enables storage, retrieval, Temperate Sericulture Research analysis, annotation and visualization of results and promotes better understanding of biological system Institute, Mirgund, SKUAST- in fullness. This will help in animal and plant health care based disease diagnosis and treatment. Kashmir, J&K, India Keywords: annotation, agriculture, bioinformatics, disease diagnosis, health and web tools MR Mir Temperate Sericulture Research Institute, Mirgund, SKUAST- Introduction Kashmir, J&K, India Term Bioinformatics was coined by Paulien Hogeweg and Ben Hesper in 1970 as the study of informatic processes in biotic systems. Bioinformatics deals with computational management MF Baqual and analysis of biological information (genes, genomes, proteins, cells, ecological systems, Temperate Sericulture Research Institute, Mirgund, SKUAST- medical information, robots, artificial intelligence etc. Kashmir, J&K, India The National Center for Biotechnology Information (NCBI 2001) defined Bioinformatics as the field of science in which biology, computer science, and information technology merge KA Sahaf into a single discipline. Fredj Tekaia at the Institute Pasteur defines bioinformatics the Temperate Sericulture Research mathematical, statistical and computing methods that aim to solve biological problems using Institute, Mirgund, SKUAST- Kashmir, J&K, India DNA and amino acid sequences and related information. Since the sequencing of the first complete microbial genome of Haemophilus influenzae in 1995 hundreds of microbial FA Malik genomes have been sequenced and archived for public research in Gen Bank. The vast amount Temperate Sericulture Research of data generated by genome sequencing projects is becoming unmanageable. Bioinformatics Institute, Mirgund, SKUAST- has silently filled in the role of cost effective data analysis. Bioinformatics analysis has Kashmir, J&K, India enhanced our understandings about the genome structure and the microorganism restructuring KA Dar process. Bioinformatics has emerged as an essential field of science that is facilitating Temperate Sericulture Research biological discoveries since more than a decade. Without the usage of bioinformatics tools it is Institute, Mirgund, SKUAST- merely impossible to capture, manage process, analyse and interpret the huge amounts data Kashmir, J&K, India that is available especially after whole genome sequencing projects. The sequencing of the genomes of plants and animals will have enormous benefits for the agricultural community. Bioinformatics tools can be used to search for the genes within these genomes and to elucidate their functions. This specific genetic knowledge could then be used to produce stronger, drought, disease and insect resistant crops and improve the quality. In agriculture it helps in the insect resistance, improve nutritional quality, rational plant improvement, waste cleanup, climate change studies, and development of drought resistance varieties (Dahiya and Lata, [4] 2017) and in addition to this it also plays an important roles in biotechnology, antibiotic resistance, and forensic analysis of microbes, comparative studies, evolutionary studies and Correspondence veterinary Sciences M Younus Wani Temperate Sericulture Research History of Bioinformatics Institute, Mirgund, SKUAST- Kashmir, J&K, India 1865: Father of Genetics: Gregor Mendel discovers the concept of genetic inheritance ~ 3 ~ International Journal of Fauna and Biological Studies 1930: Electrophoresis introduced between the various systems of a cell, including the 1953: Watson and Crick suggest double-helix model for DNA interrelationship of DNA, RNA and protein synthesis and 1955: Bovine Insulin is first protein to be sequenced learning how these interactions are regulated. Researchers in 1978: the term Bioinformatics first used molecular biology use specific techniques native to molecular 1984: FASTP algorithm program published biology, but increasingly combine these with techniques and 1990: BLAST program published ideas from genetics and biochemistry. There is not a hard-line 1994: PRINTS database published between these disciplines as there once was. Molecular 1995: First bacterial genomes sequenced biology is the study of molecular underpinnings of the process 2000: EMOTIF database released of replication, transcription and translation of the genetic material. The central dogma of molecular biology where Why is bioinformatics important genetic material is transcribed into RNA and then translated Bioinformatics has developed out of the need to understand into protein, despite being an oversimplified picture of the code of life that is DNA, the massive DNA sequencing molecular biology, still provides a good starting point for projects have evolved and added in the growth of the science understanding the field. Much of the work in molecular of bioinformatics. The ultimate goal of bioinformatics is to biology is quantitative, and recently much work has been uncover the wealth of biological information hidden in the done at the interface of molecular biology and computer mass of sequence, structure, literature and other biological science in bioinformatics and computational biology. data. Genomics Components of Bioinformatics Genomics is an interdisciplinary field of science within the Technology and Computing power field of molecular biology. A genome is a complete set of Technology is the collection of techniques, skills, methods, DNA within a single cell of an organism, and as such, focuses and processes applied to make life easier. Technology can be on the structure, function, evolution, and mapping of the knowledge of techniques, processes. genomes. Genomics aims at the collective characterization Computing power is the ability to undertake or be used for and quantification of genes, which direct the production of computation. Specifically the ability of a computer to perform proteins with the assistance of enzymes and messenger work, often considered in terms of the number of instructions molecules. Genomics also involves the sequencing and that can be carried out in a given time, or with reference to the analysis of genomes. Advances in genomics have triggered a amount of random access memory present. revolution in discovery-based research to understand even the most currently complex biological systems such as the brain. Creation of databases In contrast to genetics, which refers to the study of individual This involves the organizing, storage and management the genes and their roles in inheritance, genomics uses high biological data sets. The databases are accessible to throughput DNA sequencing and bioinformatics to assemble, researchers to know the existing information and submit new and analyze the function and structure of entire genomes. entries, e.g. protein sequence data bank for molecular structure. Databases will be of no use until analysed. Computer sciences The study of the theory, experimentation, and engineering that Development of algorithms and statistics form the basis for the design and use of computers. It is the This involves the development of tools and resources to scientific and practical approach to computation and its determine the relationship among the members of large data applications and the systematic study of the feasibility, sets e.g. comparison of protein sequence data with the already structure, expression, and mechanization of the existing protein sequences. methodical procedures (or algorithms) that underlie the acquisition, representation, processing, storage, Analysis of data and interpretation communication of, and access to information. An alternate, The appropriate use of components to analyse the data and more succinct definition of computer science is the study of interpret the results in a biologically meaningful manner. This automating algorithmic processes that scale. A computer includes DNA, RNA and protein sequences, protein structure, scientist specializes in the theory of computation and the gene expression profiles and biochemical pathways. design of computational
Load more

Recommended publications
  • (12) Patent Application Publication (10) Pub. No.: US 2003/0211987 A1 Labat Et Al
    US 2003O21, 1987A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2003/0211987 A1 Labat et al. (43) Pub. Date: Nov. 13, 2003 (54) METHODS AND MATERIALS RELATING TO Apr. 7, 2000 (US)........................................... O9545,714 STEM CELL GROWTH FACTOR-LIKE Apr. 11, 2000 (US)........................................... O9547358 POLYPEPTIDES AND POLYNUCLEOTDES Publication Classification (76) Inventors: Ivan Labat, Mountain View, CA (US); Y Tom Tang, San Jose, CA (US); Radoje T. Drmanac, Palo Alto, CA (51) Int. Cl." ....................... A61K 38/18; CO7K 14/475; (US); Chenghua Liu, San Jose, CA C12O 1/68; CO7H 21/04; (US); Juhi Lee, Fremont, CA (US); C12M 1/34; C12P 21/02; Nancy K Mize, Mountain View, CA C12N 5/08 (US); John Childs, Sunnyvale, CA (52) U.S. Cl. ......... 514/12; 435/69.1; 435/6; 435/320.1; (US); Cheng-Chi Chao, Cupertino, CA 435/366; 530/399; 536/23.5; (US) 435/287.2 Correspondence Address: MARSHALL, GERSTEIN & BORUN LLP (57) ABSTRACT 6300 SEARS TOWER 233 S. WACKER DRIVE The invention provides novel polynucleotides and polypep CHICAGO, IL 60606 (US) tides encoded by Such polynucleotides and mutants or variants thereof that correspond to a novel human Secreted (21) Appl. No.: 10/168,365 Stem cell growth factor-like polypeptide. These polynucle otides comprise nucleic acid Sequences isolated from cDNA (22) PCT Filed: Dec. 23, 2000 libraries prepared from human fetal liver Spleen, ovary, adult (86) PCT No.: PCT/US00/35260 brain, lung tumor, Spinal cord, cervix, ovary, endothelial cells, umbilical cord, lymphocyte, lung fibroblast, fetal (30) Foreign Application Priority Data brain, and testis.
    [Show full text]
  • UNIVERSITY of CALIFORNIA, SAN DIEGO Use Solid K-Mers In
    UNIVERSITY OF CALIFORNIA, SAN DIEGO Use Solid K-mers In MinHash-Based Genome Distance Estimation A thesis submitted in partial satisfaction of the requirements for the degree Master of Science in Computer Science by An Zheng Committee in charge: Professor Pavel Pevzner, Chair Professor Vikas Bansal Professor Melissa Gymrek 2017 Copyright An Zheng, 2017 All rights reserved. The thesis of An Zheng is approved, and it is acceptable in quality and form for publication on microfilm and electroni- cally: Chair University of California, San Diego 2017 iii TABLE OF CONTENTS Signature Page . iii Table of Contents . iv List of Figures . v List of Tables . vi Acknowledgements . vii Abstract of the Thesis . viii Chapter 1 Introduction and background . 1 1.1 Genome distance estimation . 1 1.2 Current methods . 2 1.3 MinHash . 3 1.4 Solid k-mer powered MinHash . 5 Chapter 2 Method . 7 2.1 General scheme . 7 2.2 Identification of overlapping read pairs . 8 2.2.1 Workflow . 8 2.2.2 Data . 9 2.2.3 Implementation . 9 2.3 Genome identification . 10 2.3.1 Workflow . 10 2.3.2 Data . 10 2.3.3 Implementation . 10 Chapter 3 Result . 15 3.1 Identification of overlapping read pairs . 15 3.1.1 Performance comparison between solid k-mer pow- ered MinHash and regular MinHash . 15 3.1.2 Selecting the solid k-mer threshold . 17 3.2 Genome identification . 19 Chapter 4 Discussion and future work . 21 Bibliography . 23 iv LIST OF FIGURES Figure 1.1: An example of how to use MinHash to compute the resemblance of two genome sequences.
    [Show full text]
  • Outlier Detection in BLAST Hits∗
    Outlier Detection in BLAST Hits∗ Nidhi Shah1, Stephen F. Altschul2, and Mihai Pop3 1 Department of Computer Science and Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA [email protected] 2 Computational Biology Branch, NCBI, NLM, NIH, Bethesda, MD, USA [email protected] 3 Department of Computer Science and Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA [email protected] Abstract An important task in a metagenomic analysis is the assignment of taxonomic labels to sequences in a sample. Most widely used methods for taxonomy assignment compare a sequence in the sample to a database of known sequences. Many approaches use the best BLAST hit(s) to assign the taxonomic label. However, it is known that the best BLAST hit may not always correspond to the best taxonomic match. An alternative approach involves phylogenetic methods which take into account alignments and a model of evolution in order to more accurately define the taxonomic origin of sequences. The similarity-search based methods typically run faster than phylogenetic methods and work well when the organisms in the sample are well represented in the database. On the other hand, phylogenetic methods have the capability to identify new organisms in a sample but are computationally quite expensive. We propose a two-step approach for metagenomic taxon identification; i.e., use a rapid method that accurately classifies sequences using a reference database (this is a filtering step) and then use a more complex phylogenetic method for the sequences that were unclassified in the previous step.
    [Show full text]
  • Developing Bioinformatics Computer Skills.Pdf
    Safari | Developing Bioinformatics Computer Skills Show TOC | Frames My Desktop | Account | Log Out | Subscription | Help Programming > Developing Bioinformatics Computer Skills See All Titles Developing Bioinformatics Computer Skills Cynthia Gibas Per Jambeck Publisher: O'Reilly First Edition April 2001 ISBN: 1-56592-664-1, 446 pages Buy Print Version Developing Bioinformatics Computer Skills will help biologists, researchers, and students develop a structured approach to biological data and the computer skills they'll need to analyze it. The book covers Copyright the Unix file system, building tools and databases for bioinformatics, Table of Contents computational approaches to biological problems, an introduction to Index Perl for bioinformatics, data mining, data visualization, and tips for Full Description tailoring data analysis software to individual research needs. About the Author Reviews Reader reviews Errata Delivered for Maurice ling Last updated on 10/30/2001 Swap Option Available: 7/15/2002 Developing Bioinformatics Computer Skills, © 2002 O'Reilly © 2002, O'Reilly & Associates, Inc. http://safari.oreilly.com/main.asp?bookname=bioskills [6/2/2002 8:49:35 AM] Safari | Developing Bioinformatics Computer Skills Show TOC | Frames My Desktop | Account | Log Out | Subscription | Help Programming > Developing Bioinformatics Computer Skills See All Titles Developing Bioinformatics Computer Skills Copyright © 2001 O'Reilly & Associates, Inc. All rights reserved. Printed in the United States of America. Published by O'Reilly & Associates, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O'Reilly & Associates books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://safari.oreilly.com). For more information contact our corporate/institutional sales department: 800-998-9938 or [email protected].
    [Show full text]
  • The Scientist :: Blast, Aug. 29, 2005 09/18/2005 04:42 PM
    The Scientist :: Blast, Aug. 29, 2005 09/18/2005 04:42 PM Volume 19 | Issue 16 | Page 21 | Aug. 29, 2005 Previous | Issue Contents | Next FEATURE | SEVEN TECHNOLOGIES How 90,000 lines of code helped spark the bioinformatics explosion By Anne Harding You've just cloned and sequenced a gene, but you don't know what it does. Now Sponsored by: what do you do? In the absence of functional clues, it's hard to know where to start. One approach is to ask what other known sequences are similar to yours, thereby inferring function from homology. Each weekday, some 200,000 or so researchers do just that, asking a server at the National Center for Biotechnology Information (NCBI) in Bethesda, Md., to compare their particular sequence against GenBank, a DNA database that, at the end of 2004, held more than 40 million sequences totaling 44.5 billion nucleotides. The NCBI devotes 158 two-processor computers to those queries, 75% of which return within 22 seconds. The software these servers use, a sturdy 15-year-old program known as the Basic Local Alignment Search Tool, or BLAST, remains, for many, bioinformatics' "killer app." It wasn't the first DNA database search tool, but it was fast, and it provided metrics to assess the significance of the matches it found--all in 90,000 lines of C code. "The fact that every biologist has been using BLAST tells everything," says Jin Billy Li of the Washington University Genome Sequencing Center in St. Louis, who has used BLASTP (a protein homology tool) to identify flagellar genes in several species, including the human gene that causes Bardet-Biedl syndrome, a ciliation disorder.
    [Show full text]
  • Msc THESIS Genetic Sequence Alignment on a Supercomputing Platform
    Computer Engineering 2011 Mekelweg 4, 2628 CD Delft The Netherlands http://ce.et.tudelft.nl/ MSc THESIS Genetic sequence alignment on a supercomputing platform Erik Vermij Abstract Genetic sequence alignment is an important tool for researchers. It lets them see the differences and similarities between two genetic sequences. This is used in several fields, like homology research, auto immune disease research and protein shape estimation. There are various algorithms that can perform this task and several hard- ware platforms suitable to deliver the necessary computation power. CE-MS-2011-02 Given the large volume of the datasets used, throughput is nowadays the major bottleneck in sequence alignment. In this thesis we discuss some of the existing solutions for high throughput genetic sequence alignment and present a new one. Our solution implements the well known Smith-Waterman optimal local alignment algorithm on the HC-1 hybrid supercomputer from Convey Computer. This platform features four FPGAs which can be used to accelerate the problem in question. The FPGAs, and the CPU that controls them, live in the same virtual memory space and share one large memory. We developed a hardware description for the FPGAs and a software program for the CPU. Some focus points were: a sustainable peak performance, being able to align sequences of any length, FPGA area efficient computations and the cancellation of unnecessary workload. The result is a Smith-Waterman FPGA core that can run at 100% utilization for many alignments long. They are packed per six on a FPGA running on 150 MHz, which results in a full system performance of 460 GCUPS (billion elementary operations per second).
    [Show full text]
  • Computation Resources for Molecular Biology: a Special Issue
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE Editorial provided by Elsevier - Publisher Connector Computation Resources for Molecular Biology: A Special Issue Increasingly, computational approaches are hav- ubiquitin-like folds in the protein databank (UbSRD). ing a central role across many areas of research The resource quantifies the structures of ubiquitins tackling the challenges of understanding the com- and SUMOs (small ubiquitin-like modifier proteins) plexity of biological systems. A resource such as and their different modes of protein–protein interac- BLAST (Basic Local Alignment Search Tool) [1], tions. The database allowed the authors to identify which was published in this journal in 1990, has that the ubiquitin tail is flexible and adopts a range of transformed sequence searching because of its conformations on binding. Users can browse the speed and power in detecting distant but biologically database by phylogeny, by structural properties and significant relationships. Since then, high-throughput by residue interactions. molecular biology technologies have led to a rapid The third database [4] in this Special Issue, expansion in available sequence, structural and authored by Keerthikumar et al., is ExoCarta that is -omics data for many systems being studied. a manually curated compendium of exosomal Computational biologists, statisticians and mathe- proteins, RNAs and lipids. The current version maticians have been motivated by this exponential details more than 41,000 protein, 7000 RNA and growth of data to develop enhanced novel compu- 1000 lipid molecules. Users can browse the data- tational tools. Challenges include the storage and base by organism, content type or gene.
    [Show full text]
  • Coding Sequences: a History of Sequence Comparison Algorithms As a Scientiªc Instrument
    Coding Sequences: A History of Sequence Comparison Algorithms as a Scientiªc Instrument Hallam Stevens Harvard University Sequence comparison algorithms are sophisticated pieces of software that com- pare and match identical or similar regions of DNA, RNA, or protein se- quence. This paper examines the origins and development of these algorithms from the 1960s to the 1990s. By treating this software as a kind of scien- tiªc instrument used to examine sets of biological objects, the paper shows how algorithms have been used as different sorts of tools and appropriated for dif- ferent sorts of uses according to the disciplinary context in which they were deployed. These particular uses have made sequences themselves into different kinds of objects. Introduction Historians of molecular biology have paid signiªcant attention to the role of scientiªc instruments and their relationship to the production of bio- logical knowledge. For instance, Lily Kay has examined the history of electrophoresis, Boelie Elzen has analyzed the development of the ultra- centrifuge as an enabling technology for molecular biology, and Nicolas Rasmussen has examined how molecular biology was transformed by the introduction of the electron microscope (Kay 1998, 1993; Elzen 1986; Rasmussen 1997).1 Collectively, these historians have demonstrated how instruments and other elements of the material culture of the labora- tory have played a decisive role in determining the kind and quantity of knowledge that is produced by biologists. During the 1960s, a versatile new kind of instrument began to be deployed in biology: the electronic computer (Ceruzzi 2001; Lenoir 1999). Despite the signiªcant role that 1. One could also point to Robert Kohler’s (1994) work on the fruit ºy, Jean-Paul Gaudillière (2001) on laboratory mice, and Hannah Landecker (2007) on the technologies of tissue culture.
    [Show full text]
  • STUDY of the RELATIONSHIP BETWEEN Mus Musculus PROTEIN SEQUENCES and THEIR BIOLOGICAL FUNCTIONS a Thesis Presented to the Gradua
    STUDY OF THE RELATIONSHIP BETWEEN Mus musculus PROTEIN SEQUENCES AND THEIR BIOLOGICAL FUNCTIONS A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Pawan Seth May, 2007 STUDY OF THE RELATIONSHIP BETWEEN Mus musculus PROTEIN SEQUENCES AND THEIR BIOLOGICAL FUNCTIONS Pawan Seth Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Dean of the College Dr. Zhong-Hui Duan Dr. Ronald F. Levant _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Chien-Chung Chan Dr. George R. Newkome _______________________________ _______________________________ Committee Member Date Dr. Xuan-Hien Dang _______________________________ Committee Member Dr. Yingcai Xiao _______________________________ Department Chair Dr. Wolfgang Pelz ii ABSTRACT The central challenge in post-genomic era is the characterization of biological functions of newly discovered proteins. Sequence similarity based approaches infer protein functions based upon the homology between proteins. In this thesis, we present the similarity relationship between protein sequences and functions for mouse proteome in the context of gene ontology slim. The similarity between protein sequences is computed using a novel measure based upon the local BLAST alignment scores. The similarity between protein functions is characterized using the three gene ontology categories. In the study, the ontology categories are represented using a general tree structure. Three ontology trees are constructed using the definitions provided in gene ontology slim. The mouse protein sequences are then mapped onto the trees. We present the sequence similarity distributions at different levels of GO tree. The similarities of protein sequences across gene ontology levels and traversing branches are studied.
    [Show full text]
  • K-Mulus: a Database-Clustering Approach to Protein BLAST in the Cloud
    K-mulus: A Database-Clustering Approach to Protein BLAST in the Cloud Carl H. Albachy Sebastian G. Angely Christopher M. Hilly Mihai Pop Department of Computer Science University of Maryland, College Park College Park, MD 20741 fcalbach, sga001, cmhill, [email protected] ABSTRACT with the intention of efficiently searching for these similar- With the increased availability of next-generation sequenc- ities. The most widely used application is the Basic Local ing technologies, researchers are gathering more data than Alignment Search Tool, or BLAST[3]. they are able to process and analyze. One of the most widely performed analyses is identifying regions of similar- With the increased availability of next-generation sequenc- ity between DNA or protein sequences using the Basic Local ing technologies, researchers are gathering more data than Alignment Search Tool, or BLAST. Due to the large scale ever before. This large influx of data has become a ma- of sequencing data produced, parallel implementations of jor issue as researchers have a difficult time processing and BLAST are needed to process the data in a timely manner. analyzing it. For this reason, optimizing the performance In this paper we present K-mulus, an application that per- of BLAST and developing new alignment tools has been a forms distributed BLAST queries via Hadoop and MapRe- well researched topic over the past few years. Take the ex- duce and aims to generate speedups by clustering the database. ample of environmental sequencing projects, in which the Clustering the sequence database reduces the search space bio-diversity of various environments, including the human for a given query, and allows K-mulus to easily parallelize microbiome, is analyzed and characterized to generate on the remaining work.
    [Show full text]
  • In Its Most Basic Form a Sequence Alignment Is Simply Comparing Two Or More Sequences by Searching for Character Patterns and Other Similarities
    In its most basic form a sequence alignment is simply comparing two or more sequences by searching for character patterns and other similarities. Blasting some sequence is often the first step a researcher will take to characterize an unknown sequence or even a whole genome, but in 1970, when Needleman and Wunsch first introduced their algorithm for automated global alignment of sequences, there were still very few sequences to work with. Throughout the late seventies, determining nucleotide sequences was a torturous tedious process, but in 1977 there were two major technological breakthroughs, one pioneered by Maxam and Gilbert and the other by Sanger that opened the door for automated sequencing. These two developments represent the bedrock on which high through put sequencing is built. Alignment techniques can be broken into two components. The first is construction of a scoring matrix, and the second is the actual algorithms used to compute a score. The simplest scoring matrix is a unitary matrix. If the character matches a one is assigned, and if not the matrix element is zero. In this most fundamental case, the alignment would simply be the path through this matrix. The two most commonly used scoring matrices today are PAM and BLOSUM. PAM or percent accepted mutation rate different substitution rates of amino acids were calculated based on alignments of protein sequences that were at least eight-five percent identical (Heinkoff, 1992). Rates for PAMs correlating to different evolutionary distances were then extrapolated from these original calculations. BLOSUM takes a slightly different approach. Instead of relying on extrapolated data, the various BLOSUMs are calculated directly.
    [Show full text]
  • Thesis by Submitted in Partial Fulfillment of the Requirements For
    Sequential Optimization of Global Sequence Alignments Relative to Different Cost Functions Thesis by Enas Mohammad Odat, Master Degree in Computer Science Submitted in Partial Fulfillment of the Requirements for the degree of Masters of Computer Science King Abdullah University of Science and Technology Mathmatical and Computer Sciences and Engineering Division Computer System Thuwal, Makkah Province, Kingdom of Saudi Arabia May, 2011 2 The dissertation/thesis of Enas Mohammad Odat is approved by the examination committee Committee Chairperson: Committee Co-Chair: Committee Member: King Abdullah University of Science and Technology 2011 ABSTRACT Sequential Optimization of Global Sequence Alignments Relative to Different Cost Functions Enas Mohammad Odat The purpose of this dissertation is to present a methodology to model global sequence alignment problem as directed acyclic graph which helps to extract all pos- sible optimal alignments. Moreover, a mechanism to sequentially optimize sequence alignment problem relative to different cost functions is suggested. Sequence alignment is mostly important in computational biology. It is used to find evolutionary relationships between biological sequences. There are many algo- rithms that have been developed to solve this problem. The most famous algorithms are Needleman-Wunsch and Smith-Waterman that are based on dynamic program- ming. In dynamic programming, problem is divided into a set of overlapping sub- problems and then the solution of each subproblem is found. Finally, the solutions to these subproblems are combined into a final solution. In this thesis it has been proved that for two sequences of length m and n over a fixed alphabet, the suggested optimization procedure requires O(mn) arithmetic operations per cost function on a single processor machine.
    [Show full text]