Introduction to BIOINFORMATICS

Transcription

1 Introduction to BIOINFORMATICS

2 Antonella Lisa CABGen Centro di Analisi Bioinformatica per la Genomica Tel

3 What is Bioinformatics? The marriage between biology and informatics

4 What is Bioinformatics? Bioinformatics is a field which uses computers to store and analyze molecular biological information. Using this information in a digital format, bioinformatics can then solve problems of molecular biology.

5 Understanding nature s mute elegant language of living cells is the question of modern molecular biology. From an alphabet of only four letters representing the chemical subunits of DNA, emerges a syntax of life processes whose most complex expression is man. From the National Centre for Biotechnology Information (NCBI),

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7 Information Complexity

8 Components of Bioinformatics

9 Factors that made bioinformatics so important Rapid and cheap techniques for DNA sequencing The development of powerful computers Internet and the Wide World Web

10 Bioinformatics has three principal components: The creation of databases allowing the storage and management of large biological data sets. The development of algorithms and statistics to determine relationships among members of large data sets. The use of these tools for the analysis and interpretation of various types of biological data, including DNA, RNA and protein sequences, protein structures, gene expression profiles, and biochemical pathways

11 Bioinformatic Developers They develop tools for bioinformatics Experts in Mathematics, Statistics and Informatics Computational biologists Bioinformatics Users They use the tools of bioinformatics Researchers (Biologists, Biotechnologist, )

12 2007 marked the 30th anniversary of the development of the 'dideoxy' sequencing methods of Fred Sanger and his colleagues at the MRC Laboratory of Molecular Biology in Cambridge, UK that formed the basis for automated DNA sequencing technology and which led to the establishment of human and many other genome sequences. Although other methods were also invented (notably that of Maxam/Gilbert), Sanger's methods have stood the test of time and it is only in recent years that newer DNA sequencing techniques have started to emerge as contenders. NAR 35 (2007), no.12

13 Sanger DNA analyzer can process: 96 samples a time 800 bp read lenght 1,6 Mbp/day Human Genome sequencing / = days!

14 2001: draft sequence of human genome 10 years + $3 bilions

15 Next generation sequencing High-throughput sequencing technologies that parallelize the sequencing process, producing thousands or millions of sequences at once. Metzker ML Sequencing technologies - the next generation. Nat Rev Genet. 11(1):31-46.

16 2008: DNA sequence of a diploid genome of a single individual, James D. Watson, in two months using massively parallel sequencing and spending $ !

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21 For individuals, the new price will be $19,500, while groups of five or more customers using the same ordering physician will pay $14,500 per person. In addition, individuals with serious medical conditions for whom whole-genome sequencing could be of clinical value will pay $9,500 to have their genome sequenced. (June 2010)

22 Drew Sheneman, New Jersey -- The Newark Star Ledger

23 Speed in the capability of Data production Data interpretation

24 Bioinformatics application areas BEFORE THE GENOMIC REVOLUTION Creation and maintenance of databases to store biological information, such as nucleotide and amino acid sequences. Development of complex interfaces whereby researchers could both access existing data as well as submit new or revised data.

25 Bioinformatics application areas AFTER THE GENOMIC REVOLUTION Analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology.

26 development and implementation of tools that enable efficient access to, and use and management of, various types of information. development of new algorithms (mathematical formulas) and statistics with which to assess relationships among members of large data sets, such as methods to locate a gene within a sequence, predict protein structure and/or function, and cluster protein sequences into families of related sequences

27 Sequence analysis Genome annotation Literature analysis Analysis of gene expression Analysis of regulation Analysis of protein expression Analysis of mutations in cancer Comparative genomics Computational evolutionary biology Modeling biological systems High-throughput image analysis

28 Bioinformatics challenges Biological redundancy and multiplicity Different sequences with similar structures Organism with similar genes Multiple functions of similar genes Grouping of genes in pathways Sequence redundancy in genomes Significance of relationships and similarities Signal vs Noise Lack of data

29 What is database?

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31 Database is a collection of data that has a regular structure and is organized in such a way that a computer can easily find and retrieve information.

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33 Redundancy - Errors

34 Relational databases Data are stored in tables with rows and columns. Each table is composed of records and each record is identified by a field (attribute) containing a unique value.

35 Table Row = Record Column = Field that describe each record

36 Relational databases Every table shares at least one field with another table in 'one to one,' 'one to many,' or 'many to many' relationships.

37 These relationships allow the database user to access the data in almost an unlimited number of ways, and to combine the tables as building blocks to create complex and very large databases.

38 A database management system (DBMS) such as Access, FileMaker, Oracle or SQL Server provides the software tools needeed to organize that data in a flexible manner. It includes tools to add, modify or delete data from the database, ask questions (or queries) about the data stored in the database and produce reports summarizing selected contents.

39 1965 First idea of molecular database M. Dayhoff et al. published Atlas of Protein Sequences and Strucures

40 When does DNA sequence collection start? 1982 EMBL - Heidelberg 1983 GenBank USA 1984 DDBJ - Japan

41 Sites where the integration among and between databases is developed USA NCBI (National Center for Biotechnology Information) Europe EBI (European Bioinformatics Institute,Hinxton, UK) Japan NIG (National Institute of Genetics)

42 1988: The International Sequence Database Collaboration Entrez Submissions Updates CIB NCBI GenBank DDBJ EMBL EBI Submissions Updates Submissions Updates SRS Getentry

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47 NCBI (National Center for Biotechnology Information) Bethesda,Maryland

48 The National Center for Biotechnology Information (NCBI) Created as a part of the National Library of Medicine in 1988 Establish public databases Research in computational biology Develop software tools for sequence analysis Disseminate biomedical information Tools: BLAST(1990), Entrez (1992) GenBank (1992) Free MEDLINE (PubMed, 1997) Other databases: dbest, dbgss, dbsts, MMDB, OMIM, UniGene, GeneMap, Taxonomy, CGAP, SAGE, Gene, RefSeq

49 Data Resources at NCBI Databases: Primary and Derivative Primary Databases Archival submissions of experimental results Database staff organize but don t add additional information Genbank dbest dbsnp Probe Derivative Databases Curated/expert review Computationally derived Combinations Refseq Genomes UniGene UniSTS Homologene

50 Biological complexity COMPLEXITY Ecological processes & populations Tissue & organism physiology Cellular & developmental processes Biochemical pathways & processes Complete genomes Genes, Proteins, RNA. Introduction to Bioinformatics:

51 Database Retrieval Sequencing Project Management Restriction Mapping DNA/RNA Folding Seeking Coding regions Translation to amino acids Protein Sequence analysis Nucleic Acid Sequences Database Retrieval Protein Sequences Pair wise Sequence Comparison Nucleic Acid Sequence Analysis Database Similarity Searching Multiple Sequence Alignment Prediction of Function Phylogeny Motifs and Patterns Structure prediction Structure analysis

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56 Databases connections