WELCOME TO ALL

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WELCOME TO ALL
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• BIOINFORMATICS
• AND
• BIO-MOLECULAR COMPUTING

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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

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

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Bioinformatics in Biology
Molecular Biology
Physics Chemistry, 1950s
Biochemistry
Biophysics
Biology
Computer Sci. Statistics, 1970s
Bioinformatics
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BIOINFORMATICS AND COMPUTER SCIENCE CURRICULA

• DATA MININIG
• PREDICTIVE TECHNIQUE
• DISCOVERY TECHNIQUE

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• 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.

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• 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,correlationsquantitative
  analyses.

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• LIMITATIONS
• one persons strongly agree may be
  anothers weakly agree.
• CONCLUSION
• The next generation of Bioinformaticians must
  be trained as BiologistComputer Scientist
  challenging the orthogonal traditional view.

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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.

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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."

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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. (n7)
• Keep only those paths that enter all cities at
  least once.
• Any remaining paths are solutions.

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APPLICATIONS

• Drug Discovery
• Clinical Diagnostics
• Pharmacogenomics
• Industrial Biotechnology
• Agricultural Biotechnology

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• 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

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CONCLUSION

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

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THANKING U