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BIOINFORMATICS >> LIFE INSILICO
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>> DREAM FASTER (Click on image)
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" It is God's privilege to conceal things, but the king's pride is to research them "
Welcome to the homepage of Mohamed Tanwir Kashif, where I share across with you the most happening thing in the world of Healthsciences and more specifically - Bioinformatics. Life Sciences encompasses techniques like cell fusion techniques, hybridomas, recombinant DNA technology, protein engineering, structure based molecular design, etc. One of the greatest achievements in Genomics is deciphering the complete human genome / popularly termed the HGP - Human Genome Project. It has been identified that there are between 30,000 and 35,000 (3.5 billion basepairs of DNA) genes in our body.
Comparative analysis of gene sequences from hundreds of organisms have revolutionized our concepts of biological diversity. The sequence of the first complete genome (Haemophilus influenzae) was published in 1995 and it is expected that complete genome sequence information for 50-100 organisms will be available during the next few years. The exponential increase in the amount of sequence data stored in the public databases and the continuous development of novel methods and tools for the analysis of DNA sequences represent new challenges for modern molecular biologists. An understanding of bioinformatic methods is required in order to be able to handle, analyze and interpret the large volumes of sequence data that will be generated in the near future. Bioinformatics is thus emerging as a new field of research of relevance for basic sciences as well as for the many projects initiated on the design of new antibiotics and vaccine strategies by the pharmaceutical industries.
Drug research is data rich, but information poor. Genomics or gene-sequencing projects, high throughput screening, combinatorial chemical synthesis, gene-expression investigations, pharmacogenomics, and proteomics studies have created massive volumes and multiple sources of biological and chemical data. This data is threatening to create a bottleneck that might hamper drug discovery and development. The primary goal of bioinformatics is to link and convert this complex data into useful information and knowledge. As computing and biology have converged, software tools for data capture, management, analysis, mining, and dissemination have also emerged. The convergence of biotech and infotech has become inevitable.
It has been estimated that about 20 percent of the current novel discovery programs are based on genomics, and this is fueling the growth of bioinformatics. It is predicted that virtually all new discovery programs will be genomics-based in the near future. Currently, there is an increased pressure to develop breakthrough drugs and shorten the drug discovery time and costs involved. This presents an opportunity to bioinformatics companies as data capture, management, analysis, and dissemination could play a vital role for drug discovery companies in containing both cost and time.
Analysing this information in a wet lab would take an extraordinary amount of time and investment. This has lead to the evolution of a new area in biology, namely BIOINFORMATICS wherein genetic information is analysed IN SILICO and probable protein products are identified and engineered in a very short time span. As we are trying to study a biological process in a computer, it is very much essential that we have a thorough understanding of what exactly happens in our body.
If this information is properly analyzed and computed, it would definitely take us a long way in curing a whole lot of metabolic and genetic disorders, even conquer AIDS and cancer.
Only time will say !!
BIOINFORMATICS : WHAT IS THE INDIAN PROMISE ???
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WHAT IS THE THEME ?
Biotechnology can be defined as an area covering one or more of the following :
1. Research and development of products or processes using living systems or their by-products as a model.
2. Genetic engineering, Molecular biology, Microbiolology or Biochemistry.
3. Bioinformatics.
Roughly, bioinformatics describes any use of computers to handle biological information. In practice the definition used by most people is narrower; bioinformatics to them is a synonym for "computational molecular biology"--- the use of computers to characterise the molecular components of living things.
There are three important sub-disciplines within bioinformatics namely:
1. The development of new algorithms and statistics with which to assess relationships among members of large data sets;
2. The analysis and interpretation of various types of data including nucleotide and amino acid sequences, protein domains, and protein structures; and
3. The development and implementation of tools that enable efficient access and management of different types of information.
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IT IS EASIER TO BELIEVE THAN DOUBT ........
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TIGHT DEFINITION :
Fredj Tekaia at the Institute Pasteur offers this definition of bioinformatics:
"The mathematical, statistical and computing methods that aim to solve biological problems using DNA and amino acid sequences and related information."
There are other fields---for example medical imaging / image analysis which might be considered part of bioinformatics. There is also a whole other discipline of biologically-inspired computation; genetic algorithms, AI, neural networks. Often these areas interact in strange ways. Neural networks, inspired by crude models of the functioning of nerve cells in the brain, are used in a program called PHD to predict, surprisingly accurately, the secondary structures of proteins from their primary sequences.
What almost all bioinformatics has in common is the processing of large amounts of biologically-derived information, whether DNA sequences or breast X-rays.
BIOCOMPUTING : GET CONNECTED !
Bioinformatics is defined as the body of tools, algorithms and know-how needed to handle complex biological information. Bioinformatics can contribute to the understanding of molecular evolution, origin of life, genomics & proteomics - the Human Genome Project, theoretical biology, complexity & information theory and most notably Lead Drug discovery (lead informatics). Since this is a relatively new field, there is an acute shortage of qualified manpower in this field at this time.
Foundation courses on cross-domain areas are offered to candidates from both disciplines.
* Foundation courses: Basics & relevance of Bioinformatics, brief introduction to molecular biology, biological pathways, biostatistics, computer networking, database concepts and various biological databases.
* Machine Learning : Networking of database resources, data warehousing, query, various models and algorithms (viz. HMM, dynamic programming etc.) and their relevance in biocomputing. Biocomputing : DNA sequence analysis, multiple alignments with various algorithms, gene finding, gene modeling, molecular modeling & structure prediction, biomolecular interactions (viz. DNA-protein interaction, protein-protein interaction, protein-ligand interaction and protein-cofactor interaction) and high throughput screening.
The materials of bioinformatics are biological data, and its methods are derived from a wide variety of computational and mathematical methods. These methods are necessary for research in areas as different as molecular evolution, genomics, structural biology and structure-based drug design. For molecular biologists, training in bioinformatics is likely to be as essential as training in how to handle a Gilson pipette.
WHAT ARE THE PRIME ACCOMPLISHMENTS OF BIOINFORMATICS THE LAST YEARS?
1. The most important task in bioinformatics is the creation of nucleotide and protein databases, and making them accessible to the bioinformatics community. Especially good software to seach the databases and to obtain relevant data is very important.
2. The second accomplishment is the provision of computer support for the genome projects. Large scale genome sequencing projects were only possible because of advances in computer technology the last 10 years. We are currently keeping in step with the advances in computer technology; it might even be a limiting factor for the advancement of bioinformatics.
3. Thirdly, advances in protein structure and prediction, which is in my opinion a gradual process - there are few dramatic leaps forward but still it is an important accomplishment.
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Disclaimer
This site provides free information for the biocsiences community for educational purpose only and is not provided as a professional service. Persons accessing this information assume full responsibility for the use of the information and understand and agree that I am not responsible or liable for any claim, loss or damage arising from the use of information provided at this site. If any institution or person's rights have been infringed by this site, it is purely accidental, in which case, please inform me and I will try to rectify the problem.
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