Bioinformatics
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The document provides an overview of bioinformatics, detailing its definition, historical development, and relevance in analyzing biological data through computational techniques. It highlights the integration of biology, computer science, and information technology, as well as notable achievements in the field, including the mapping of human genes and the creation of major databases. Additionally, it discusses the use of various software tools and algorithms in bioinformatics applications such as evolutionary biology and cancer research.
Bioinformatics
- 2. • Introduction • History • Need for bioinformatics • Computational evolutionary biology • Success • Software and tools CONTENTS
- 3. • Bioinformatics is the application of Information technology to store, organize and analyse the vast amount of biological data. • The stored data is available in the form of sequences and structures of proteins and nucleic acids (the information carrier). • The biological information of nucleic acids is available as sequences while the data of proteins is available as sequences and structures INTRODUCTION
- 4. • Sequences are represented in single dimension where as the structure contains the three dimensional data of sequences.
- 5. Biologists collect molecular data: DNA & Protein sequences, gene expression, etc. Computer scientists (+Mathematicians, Statisticians, etc.) Develop tools, soft wares, algorithms to store and analyze the data. Bioinformaticians Study biological questions by analyzing molecular data The field of science in which biology, computer science and information technology merge into a single discipline .
- 6. • By course of 10 years starting from 1981, following events occurred… • 579 human genes had been mapped. • Invented a method for automated DNA sequencing. • The Human Genome organization (HUGO) was founded. This is an international organization of scientists involved in Human Genome Project. • The first complete genome map was published for the bacteria Haemophilus influenza . HISTORY
- 7. • After 10 years… • By 1991, a total of 1879 human genes had been mapped. • In 1993, Genethon , a human genome research center in France Produced a physical map of the human genome. • After 3 years… • Genethon published the final version of the Human Genetic Map. This concluded the end of the first phase of the Human Genome Project.
- 8. • Bioinformatics was fuelled by the need to create huge databases. • GenBank and EMBL and DNA Database of Japan. • They store and compare the DNA sequence data coming from the human genome and other genome sequencing projects. • Today, bioinformatics enhances protein structure analysis, gene and protein functional information, data from patients, pre-clinical and clinical trials, and the metabolic pathways of numerous species.
- 9. • The first bioinformatics databases were constructed a few years after the first protein sequences began to become available. • Now, A huge variety of divergent data resources of different types and sizes are now available either in the public domain information through Internet(www.ncbi.nlm.nih.gov). • All of the original databases were organized in a very simple way with data entries being stored in flat files, as a single large text file. Re-write - Later on lookup indexes were added to allow convenient keyword searching of header information.
- 10. • Bioinformatics uses many areas of computer science, statistics, mathematics and engineering to process biological data. • Complex machines are used to read in biological data at a much faster rate than before. • Analyzing biological data may involve algorithms in artificial intelligence, soft computing, data mining, image processing, and simulation. • The algorithms in turn depend on theoretical foundations such as discrete mathematics, control theory, system theory, information theory, and statistics. • Commonly used software tools and technologies in the field include Java, C#, XML, Perl, C, C++, Python, R, SQL, CUDA, MATL AB, and spreadsheet • the development of new algorithms (mathematical formulas) and NEED FOR BIOINFORMATICS
- 11. • Evolutionary biology is the study of the origin and species, as well as their change over time. Informatics has assisted evolutionary biologists by enabling researchers. COMPUTATIONAL EVOLUTIONARY BIOLOGY
- 12. • 1) Analysis of gene expression SUCCESS
- 13. • 2) Analysis of regulation • One can then apply clustering algorithms to that expression data to determine which genes are co-expressed
- 14. • 3) Analysis of protein expression • Bioinformatics is very much involved in making sense of protein microarray and HT MS data. • involves the problem of matching large amounts of mass data against predicted masses from protein sequence databases.
- 15. • 4) Analysis of mutations in cancer • Bioinformaticians continue to produce specialized automated systems to manage the sheer volume of sequence data produced, and they create new algorithms and software to compare the sequencing results to the growing collection of human genome sequences and germline polymorphisms
- 16. • 5) Comparative genomics
- 17. • 6) High-throughput image analysis • Computational technologies are used to accelerate or fully automate the processing, quantification and analysis of large amounts of high-information-content biomedical imagery. • accuracy, simple objective and high speed
- 18. • Open-source bioinformatics software • Many free and open-source software tools have existed and continued to grow up till now. • The range of open-source software packages includes titles such as Bioconductor, BioPerl, Biopython, BioJava, BioR uby, Bioclipse, EMBOSS, .NET Bio, Taverna workbench, and UGENE. • In order to maintain this tradition and create further opportunities, the non-profit Open Bioinformatics Foundation have supported the annual Bioinformatics Open Source Conference (BOSC) SOFTWARE AND TOOLS
- 19. • Web services in bioinformatics • The main advantages is that end users do not have to deal with software and database maintenance overheads.
- 20. • Bioinformatics workflow management systems • A Bioinformatics workflow management system is a specialized form of a workflow management system designed specifically to compose and execute a series of computational or data manipulation steps, or a workflow, in a Bioinformatics application.
- 21. • Rosalind • Rosalind is an educational resource and web project for learning bioinformatics through problem solving and computer programming.
- 22. • bioinfo.mbb.yale.edu • www.ncbi.nlm.nih.gov • bioinformaticsweb.net • www.oxfordjournals.org • www.umass.edu REFERENCES