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Bioinformatics Applications: Genomics, Proteomics and Transcrptiomics
#1
Bioinformatics is a combination of molecular biology and computer sciences. It is that technology in which computers are used to gather, store, analyze and integrate biological and genetic information. The need for Bioinformatics arose when a project to determine the sequence of the entire human genome was initiated. This project was called the Human Genome Project. Bioinformatics is very important for the use of genomic information to understand human diseases and to identify new ways for gene-based drug discovery and development. Therefore, many universities, government institutions and pharmaceutical companies have come forward to form bioinformatics groups to do research related to computational biology so that better ways are used to make processes more efficient and less time consuming.

Application of Bioinformatics:


Bioinformatics in Proteomics

Proteomics is a branch of biotechnology that deals with the techniques of molecular biology, biochemistry, and genetics to analyze the structure, function, and interactions of the proteins produced by the genes of a particular cell, tissue, or organism. This technology is being improved continuously and new tactics are being introduced. In the current day and age it is possible to acquire the proteome data. Bioinformatics makes it easier to come up with new algorithms to handle large and heterogeneous data sets to improve the processes. To date, algorithms for image analysis of 2D gels have been developed. In case of mass spectroscopy, data analysis algorithms for peptide mass fingerprinting and peptide fragmentation fingerprinting have been developed.

Bioinformatics and Genomics

Genomics is the study of complex sets of genes, their expression and the most vital role they play in biology. The most important application of bioinformatics in genomics is the Human Genome Project through which more than 30,000 genes have been identified and secured through the sequencing of chemical base pairs which make up the DNA. It has thus enabled us to obtain necessary knowledge as to how these genes inter-relate and what functions they perform. Cures for many diseases are being discovered through this inter-relation where bioinformatics, no doubt, plays a pivotal role.

Bioinformatics and Transcriptiomics

Transcriptiomics deals with the study of messenger RNA molecules produced in an individual or population of a particular cell type. It is also referred to as Expression Profiling in which the expression level of mRNA, in a given cell population, is determined through DNA microarray technology. Bioinformatics is thus used for transcriptome analysis where mRNA expressions levels can be determined so as to see how a certain disease, like cancer, can be cured.

Parallel to the above mentioned fields, Bioinformatics is also being used in;
Molecular medicine, Personalised medicine, Preventative medicine, Gene therapy, Drug development, Microbial genome applications, Waste cleanup, Climate change Studies, Alternative energy sources, Biotechnology, Antibiotic resistance, Forensic analysis of microbes, Bio-weapon creation, Evolutionary studies, Crop improvement, Insect resistance, Improve nutritional quality, Development of Drought resistance varieties, Veterinary Science etc which are all quite debatable in their own capacity and will be discussed in further detail.
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#2
Very informative post .. keep up your good work.
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#3
Your every article is better than the previous one. Very Informative!!
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#4
This post is really nice, I really like all these information given by you, I think that Bioinformatics has been described as the science of managing, mining, and interpreting information from biological sequences and structures.
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#5
Bioinformatics and Phenomics

Phenomics is the study of the nature of phenotypes and how they are determined, particularly when studied in relation to the set of all genes (genomics) or all proteins (proteomics). Just as the genome and proteome signify all of an organism's genes and proteins, the phenome represents the sum total of its phenotypic traits. Bioinformatics, as in any other field, helps analyze, structure and organize data.

One successful attempt to integrate the constantly growing and scattered phenotypic data is the PhenomicDB (phenomicdb.de)

It's a free multi-organism phenotype-genotype database unifying a variety of primary sources to make phenotypic data from a wide range of species and model organisms simultaneously searchable, visible and comparable. Reported genotype-phenotype relationships are supported by literature evidence, reference links and citations. Each genotype, as well as each phenotype is characterized by varied descriptions allowing more detailed facts exploration.
The phenotypic data clusters mapped to each entry could help further analyze similar phenotypes/diseases caused by different genes or mutations. The gene orthology information appended to each entry could help suggest a known phenotype/disease to a new or orphan genotype/mutation and thus predict a new unreported phenotypic manifestation.
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#6
Bioinformatics is the use of IT in biotechnology for the data storage,data warehousing and analyzing DNA sequence.Basically,Bioinformatics tool can be used for three purposes.

1) Protein sequence can be determined by DNA sequencing.
2) Knowledge of protein sequencing is required,if we want to determine protein structure.
3) A protein structure enables the determination of protein function.

Application of Bioinformatics in molecular medicine:
Pharmacogenomics is a branch of bioinformatics,has enabled to develop more effective clinical medicine.There are some advanced drug in the market but they have failed due to their adverse effect in patient because difference of DNA sequence in different patient. As Pharmagenomics is making advances in the science world,it will be possible for the scientist to prescribe drugs after observing genetic profile of an individual.
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#7
Bioinformatics plays an essential role in today's plant science. As the amount of data grows exponentially, there is a parallel growth in the demand for tools and methods in data management, visualization, integration, analysis, modeling, and prediction.
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