10-08-2012, 11:13 AM
bio molecular computing
bio-molecular-computing.ppt (Size: 670.5 KB / Downloads: 17)
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”
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.
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.
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.
CONCLUSION:
DNA computing will require greatly improved DNA surface attachment chemistries.
New research problems in combinatorics, complexity theory and algorithms