Bioinformatics An Overview And Its Applications-Books Pdf

Bioinformatics an overview and its applications
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W J S Diniz and F Canduri 2, INTRODUCTION, An unprecedented r evolution has been observed in science with recent technological. advances which have provided a large amount of omic data The crescent generation and. availability of this information available in public databases were and still are a challenge. for professionals from different areas Ritchie et al 2015 However what is the challenge . In biology the main challenge is to make sense of the enormous amount of structural data and. sequences that have been generated at multiple levels of biological systems Pevsner 2015 . Still in bioinformatics development of tools is necessary statistical and computational . capable of assisting in understanding the mechanisms underlying biological questions in the. study Pevsner 2015 Besides if we consider the complexity of science this is a highly. reductionist view , The era of a new biology emerges accompanied by the birth development of. other sciences such as bioinformatics and computational biology which have an integrated. interface of molecular biology Although considered recently bioinformatics and genomics. have evolved interdependently and promoted a historical impact on the available knowledge . Therefore this review aims to present a brief overview of these sciences and provide principles. that support bioinformatics addressing the following aspects i types of biological information. and databases ii sequence analysis and molecular modeling iii genomic analysis and iv . systems biology So these are broad areas we seek to highlight key points in the use of new. techniques as well as provide tools that can be used in data analysis and interpretation of the. results generated by these technologies , BIO WHAT A HISTORICAL AND CONCEPTUAL VISION OF BIOINFORMATICS. Bioinformatics has its origins a decade before DNA sequencing became feasible. Hagen 2000 Historical moments that can be highlighted for its development are the. publication of the structure of DNA by Watson and Crick in 1953 besides the accumulation of. data and knowledge of biochemistry and protein structure with the studies of Pauling Coren . and Ramachandran in the 1960s Verli 2014 , Pioneer in the systematization of knowledge of the protein three dimensional 3 . D structure Margaret O Dayhoff is considered the mother of bioinformatics Hunt 1984 . This fact is due to its role in the development of computers able to determine the peptide. sequence programs to recognize and display structures for use in X ray crystallography and. computational methods for protein sequence comparison allowing us to infer the evolutionary. connections among kingdoms Hagen 2000 Verli 2014 Amongst others authors Dr Dayhoff. published a little book Atlas of Protein Sequence and Structure considered a milestone in. the systematization and sharing of information , Besides these many other researchers have contributed to the development of.
bioinformatics until now which would not have been possible without the evolution of the. computer Thus the significant advances made today are due mainly to advances in computing. power and the genome projects sequencing annotation processing and analysis of data . Verli 2014 The development of large scale capillary DNA sequencers and marking of. dideoxynucleotides with fluorescence in the 90s allowed obtaining a large amount of data. Prosdocimi 2010 However with the advent of next generation sequencing technologies NGS . the list of complete genomes is growing as well as the volume of data As a result it becomes. Genetics and Molecular Research 16 1 gmr16019645, Bioinformatics an overview 3. necessary the use of computers in research to understand the genetic variation and evolutionary. and functional mechanisms underlying the genetic architecture Ritchie et al 2015 . Due to the multidisciplinary character of bioinformatics this can be defined as the. application of computational tools to organize analyze understand visualize and store. information associated with biological macromolecules Luscombe et al 2001 Pevsner . 2015 Pevsner 2015 summarizes the field of bioinformatics and genomics from three. perspectives i the cell and the central dogma of molecular biology From this focus is ii . the organism which shows changes between the different stages of development and regions. of the body Finally the author emphasizes a global perspective iii the tree of life in which. millions of species are grouped into three evolutionary branches . A computational view is presented by Luscombe et al 2001 These authors highlight. as goals of bioinformatics i to organize the data so that researchers can access the information. and create new entries ii to develop tools and resources that help in the data analysis and. iii to use these tools to analyze the data and interpret them significantly Regarding the issues. involved in bioinformatics we can classify them into two classes the first related to the. sequence and the second related to the biomolecular structure Figure 1 . Figure 1 Some of the bioinformatics applications Figure modified from Verli 2014 . The development of NGS technologies associated with bioinformatics has opened. a range of new possibilities such as global gene expression studies methylation patterns . epigenetic markers and others Ritchie et al 2015 There are gathered in the Nature journal . a series of publications that highlight these applications and its evolution since 2009 http . www nature com nrg series nextgeneration index html WT ec id NRG 201403 . Genetics and Molecular Research 16 1 gmr16019645, W J S Diniz and F Canduri 4. ORGANIZATION OF INFORMATION TYPES OF INFORMATION AND DATABASES. Due to the large volume of data that has been generated its organization and. storage become necessary Therefore databases were created which constitute a large. number of biological information stored and processed to allow the scientific community. access Luscombe et al 2001 Prosdocimi 2010 The increasing amount of data has been. accompanied by an increase in the number of biological databases whose compilation . updating and dissemination have been carried out by the Nucleic Acids Research journal . According to the latest update published in January 2017 there are 1739 biological databases . The information sources used by bioinformatics can be divided into i raw DNA sequences . ii protein sequences iii macromolecular structures iv genome sequencing among others . Public databases store big amounts of information and they are classified into primary. and secondary databases The primary databases are composed of results of experimental data. that are published without careful analysis related to previous publications On the other hand . in the secondary databases there is a compilation and interpretation of data called content. curation process Prosdocimi 2010 Besides these there are functional databases such as the. Kyoto Encyclopedia of Genes and Genomes KEGG and Reactome that allow analysis and. interpretation of metabolic maps Prosdocimi et al 2002 . Classified as primary databases GenBank at the National Center for Biotechnology. Information NCBI DNA Database of Japan DDBJ and European Molecular Biology Laboratory. EMBL stand out as the main databases of nucleotide sequences and proteins Pevsner 2015 . These databases are members of the International Nucleotide Sequence Database Collaboration. INSDC and share among each other the deposited information daily Prosdocimi et al 2002 . As examples of secondary databases we can point Protein Information Resource. PIR UniProtKB Swiss Prot Protein Data Bank PDB Structural Classification of Proteins. 2 SCOP and Prosite These databases are curated and present only information related to. proteins describing aspects of its structure domains function and classification . To standardization the INSDC adopted some identification systems of the sequences. deposited that bring relevant information about the origin and nature of the data Amaral. et al 2007 Some of these identifiers are the accession number AN represented by the. combination of one to three letters and five or six digits depending on the data type The. sequence identifier GI GenInfo Identifier corresponds to a simple number assigned to every. nucleotide or protein sequence Protein ID Prosdocimi 2010 The GI is individual non . transferable and non modifiable Amaral et al 2007 About the origin of the sequence it. can be represented by codes or prefixes for example GB GenBank emb EMBL As an. example human beta hemoglobin has the following GI origin and AN 455025 gb U01317 1 . GenBank is the most accessed and known throughout the world public database. Pevsner 2015 with over 198 565 475 million sequences deposited release 217 December. 2016 Given the enormous amount of molecular data they are categorized according to their. nature DNA RNA protein and are used among other applications in the analysis of. sequence comparison Amaral et al 2007 Amaral et al 2007 present some databases to. nucleotide and protein analyses that belong to GenBank . Luscombe et al 2001 summarize the organization and understanding of biological. data from the bioinformatics in two dimensions i depth and ii breadth Firstly for example . regarding the protein we seek to maximize the understanding of its function from the gene. sequence to its final structure and its ligands Like the second the aim is to compare a gene to. another and determine protein structures related and evolutionary mechanisms between species . Genetics and Molecular Research 16 1 gmr16019645, Bioinformatics an overview 5. ANALYSIS OF BIOLOGICAL SEQUENCES, Widely used and essential for biological sequence comparison alignment has been. processed by the increase in availability of data generated by NGS technologies Daugelaite et. al 2013 This process consists of comparing two or more nucleotide sequences DNA or RNA . or amino acids peptides or proteins by seeking a series of individual characters or patterns that. are also arranged in the sequences Manohar and Shailendra 2012 Junqueira et al 2014 . However why compare sequences There are some applications for this procedure. that allow information of the evolutionary relationship between organisms individuals . genes prediction functions and structures among others Junqueira et al 2014 Figure 2 . Furthermore alignment techniques are necessary to whole genome analysis in which the. comparison between different genomes or from the same species allows us to identify variations. in the sequences and associate them with specific phenotypes . Figure 2 Sequence alignment and some of its applications Figure modified from Junqueira et al 2014 . Key concepts, Algorithm A logical sequence of instructions needed to execute a task .
Gaps Regions identified by that represent indels . Indels Insertions and deletions of character , Matches Corresponding regions between two different sequences . Mismatches Regions with non identical characters in different sequences . Gap penalty GP Parameter needed to assign a score to a gap . Identity Percentage of similar characters between two sequences . Similarity Degree of resemblance between sequences based on identity . Homology Evolutionary hypothesis between two sequences that can be derived from a common ancestor . Paralogs Genes that diverged by duplication in the genome of the same species . Orthologs Genes from a common ancestor that diverged by speciation . Genetics and Molecular Research 16 1 gmr16019645, W J S Diniz and F Canduri 6. Regarding proteins the alignment of structures also stands out as an important. bioinformatics tool While the comparison of structures refers to the analysis of similarities. and differences between two or more structures alignment refers to the determination of what. amino acids would be equivalent between such structures Junqueira et al 2014 Although. apparently trivial sequence similarity analysis is complex since the algorithm used calculates. a cost to the alignment of such sequences to minimize the differences and obtain the best. possible result Manohar and Shailendra 2012 , The sequence alignment is arranged in rows and the characters in columns Figure 2 It. is up to the algorithm used to search for the best match for the sequences sometimes inserting. gaps representing one or more nucleotide indel events Prosdocimi 2010 However for. the same sequences n alignments are possible , Therefore to solve this question a scoring system in which the matches are. positively and the mismatches are negatively punctuated was created The most widely used. punctuation substitution matrices are those belonging to the PAM Point Accepted Mutation . Dayhoff et al 1978 Pevsner 2009 Sung 2010 and BLOSUM Blocks Substitution Matrix . families that relate the probability of substitution of one amino acid or nucleotide for another. Prosdocimi et al 2002 Prosdocimi 2010 Therefore the best possible alignment will be. one that maximizes the overall score Junqueira et al 2014 . Alignment can be categorized by type according to the number of sequences that. are compared which can be i simple and ii multiple By definition the simple alignment. specifically depicts the similarity relation between two sequences while the multiple considers. a value greater than three sequences Concerning the extent of alignment these can still be. classified as global consider the full extent of the sequ. Although considered recently bioinformatics and genomics have evolved interdependently and promoted a historical impact on the available knowledge Therefore this review aims to present a brief overview of these sciences and provide principles that support bioinformatics addressing the following aspects i types of biological information

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