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WELCOME TO ALL

WELCOME TO ALL. BIOINFORMATICS AND BIO-MOLECULAR COMPUTING. Introduction:. What is bioinformatics? Can be defined as the body of tools, algorithms needed to handle large and complex biological information.

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WELCOME TO ALL

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  1. WELCOME TO ALL

  2. BIOINFORMATICS AND BIO-MOLECULAR COMPUTING

  3. Introduction: • What is bioinformatics?Can be defined as the body of tools, algorithms needed to handle large and complex biological information. • Bioinformatics is a new scientific discipline created from the interaction of biology and computer. • The NCBI defines bioinformatics as: "Bioinformatics is the field of science in which biology, computer science, and information technology merge into a single discipline”

  4. Easy Answer - Using computers to solve molecular biology problems.Hard Answer - Computational techniques for management and analysis of biological data and knowledge. Fig 1:The interrelationship of the different subjects of sciences

  5. What do you need to know? It all depends on your background Are you a … ? Biologist with some computer knowledge or Computer scientist with some biology knowledge, Few do both well • Bioinformatics would not possible without advances in computing hardware and software: analysis of algorithms, datastructures and software engineering.

  6. Bioinformatics in Biology Molecular Biology Physics & Chemistry, 1950s Biochemistry Biophysics Biology Computer Sci. & Statistics, 1970s Bioinformatics

  7. BIOINFORMATICS AND COMPUTER SCIENCE CURRICULA • DATA MININIG: PREDICTIVE TECHNIQUE DISCOVERY TECHNIQUE

  8. Bioinformatics is being used in following fields: • Molecular medicine, Antibiotic resistance, Forensic analysis of microbes,Bio-weapon creation,Evolutionary studies,Crop improvement, Insect resistance. • Improve nutritional quality ,Development of Drought resistance varieties,Vetinary Science, Personalised medicine,Preventative medicine. • Gene therapy,Drug development,Microbial genome applications. • Waste cleanup,Climate change Studies,Alternative energy sources,Biotechnology.

  9. APPLICATIONS: Bioinformatics is the use of IT in biotechnology for the data storage, data warehousing and analyzing the DNA sequences. In Bioinfomatics knowledge of many branches are required like biology, mathematics, computer science, laws of physics & chemistry, and of course sound knowledge of IT ... Microbial genome applications ADVANTAGES: • Bioinformatics combines the oppurtunity for a flexible response with ability to determine frequencies,correlations&quantitative analyses.

  10. LIMITATIONS: one persons “strongly agree” may be another’s “weakly agree”. CONCLUSION: The next generation of Bioinformaticians must be trained as Biologist+Computer Scientist challenging the orthogonal traditional view.

  11. BIO-MOLECULAR COMPUTING DEFINITION: • Molecular computing is an emerging field to which chemistry biophysics, molecular biology, electronic engineering,solid state physics and computer science contribute to a large extent. • It involves the encoding, manipulation and retrieval of information at a macromolecular level in contrast to the current techniques, which accomplish the above functions via IC miniaturization of bulk devices.

  12. THE AIM OF THIS ARTICLE: • DNA computing began in 1994 when Leonard Adleman proved thatDNA computing was possible by finding a solution to a real- problem, a Hamiltonian Path Problem, known to us as the Traveling Salesman Problem,with a molecular computer . • Adleman, now considered the father of DNA computing, is a professor at the University of Southern California and spawned the field with his paper,"Molecular Computation of Solutions of Combinatorial Problems."

  13. Adleman's Traveling Salesman Problem • Generate random paths through the graph. • Keep only those paths that begin with the start city (A) and conclude with the end city (G). • If the graph has n cities, keep only those paths with n cities. (n=7) • Keep only those paths that enter all cities at least once. • Any remaining paths are solutions.

  14. APPLICATIONS: • Drug Discovery • Clinical Diagnostics • Pharmacogenomics • Industrial Biotechnology • Agricultural Biotechnology

  15. Advantages : • More parallel: • Advantages of DNA computing include high throughput (lots of information with one test), and good coverage of the genome with the chips that have larger numbers of test spots. Disadvantages: • Slow: • Hydrolysis: • Unreliable: • Not transmittable: • Not practical: • No generality:

  16. CONCLUSION: • DNA computing will require greatly improved DNA surface attachment chemistries. • New research problems in combinatorics, complexity theory and algorithms

  17. THANKING U

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