It wouldn’t be wrong when I say, the world is a better place today because of the discoveries and inventions in the field of science and technology. Starting from the food we eat, medical care we get and to the new advancements in our daily hood, the influence of science has been phenomenal.
The major credits for this growth goes to the branch of science called Bioinformatics. Bioinformatics, as the name suggests, is a combination of biology and information science. This field is specifically designed to use computational tools to analyze, interpret and manage huge volumes of biological information.
In this blogpost, we will discuss in detail about the top 5 components of bioinformatics.
Functional Genomics
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Functional genomics is one of the components of bioinformatics. It is a branch of molecular biology that defines the functions and interactions of the genes.
This component of bioinformatics utilizes the vast amount of data generated by genomic and transcriptomic datasets. This information explains the dynamic behavior of genes including gene expression, gene regulation and even protein -protein interaction. Researchers can analyze and understand the different levels of gene expression in gene expression profiling by using techniques like microarray analysis and RNA-sq. They can also understand protein interactions and draw conclusions about linking genetic variations to specific traits and diseases.
Functional genomic component of Bioinformatics has its purpose mainly in Bioinformatics drug discovery process, agriculture bioinformatics and DNA sequence analysis in bioinformatics.
Bioinformatics drug discovery process involves identifying potential new drug targets and designing more effective therapies and treatments.
Agricultural bioinformatics has also benefited from this component of bioinformatics, where the technology is used to improve the yield of the crop and the discovery and development of crops that are resistant to pets.
There are tremendous advancements in the field of DNA sequence and analysis that have led to inventions of bioinformatics drug discovery and developing new diagnostic tools for diseases.
Structural Genomics
Credit: Karthik C (Graphic Designer at CliniLaunch)
Structural genomics is another important component of bioinformatics, that helps in studying the three dimensional structure of the proteins. This study is particularly useful in understanding the structure, function and interaction of a protein with other drug molecules.
To study the structure of a protein, scientists use techniques like X- ray crystallography, where a protein structure is crystallized and then it is bombarded with the x-rays producing a diffraction pattern deterring the 3 D structure of the protein.
Other techniques include Nuclear magnetic resonance [NR] spectroscopy, cyclo electron microscopy.
The most important application of this component of bioinformatics can be seen in bioinformatics drug discovery and development. This process typically begins by identification and validation of potential drug targets and then subject to screening against a library of drug-like compounds.
Studying the structure of proteins involved in the disease, the scientists can provide insights in the disease’s progression and potential treatment options.
Comparative Genomics
Comparative genomics is that component of bioinformatics, where researchers use a variety of computational tools to compare the complete genome sequence of different species of organisms.
This understanding of comparison of different genes of different species helps the researchers gain insight into their evolutionary relationships. Also they can identify conserved genes and genetic basis of phenotypic differences.
The implication of Comparative components of bioinformatics can be seen mainly in the bioinformatics drug discovery field, agricultural bioinformatics, application of bioinformatics in biotechnology and DAN sequence analysis in bioinformatics.
Bioinformatics drug discovery and development is one area of bioinformatics that is believed to excel as a result of development of computational tools like Alpha fold 2, and comparative tools like RoseTTAfold.
With new approaches and tools as well as developments in previously existing components of bioinformatics, the agricultural bioinformatics, DNA sequence analysis in bioinformatics and bioinformatics drug discovery applications in immunology,as well as virology, has lead to the therapeutic intervention targets and the results have been described in various scientific literature.
Particularly in agricultural bioinformatics, the cooperative genoe component of bioinformatics has been able to improve crop yields and disease resistance by identifying genes responsible for these traits.
DNA Microarrays
A DNA microarray, also known as a chip or a biochip is a collection of microscopic DNA spots attached to a solid surface. Scientists use these chips or DNA microarrays to measure the expression levels of a large number of genes simultaneously or to genotype multiple regions of a genome.
The DNA microarray has revolutionized bioinformatics drug discovery by employing the study of genetic variation in a sample or by deterring the expression levels of genes. These studies can provide important information on the biochemical pathways involved in the field of bioinformatics in biotechnology. This also helps in the field of bioinformatics drug discovery by helping researchers understand and analyse the description of genes involved in physiological and pathological processes.
Another huge contributing factor in DNA analysis in bioinformatics is identification of signature genes responsible for disease process and identification of disease related genes that may become targets for therapeutic intervention and monitoring.
The revolutionary advancements in agricultural bioinformatics is Hybridization. This extension has enabled researchers to study complex biological processes and possible disease traits and resistant breeds at a large scale.
Medical Informatics
Credit: Karthik C (Graphic Designer at CliniLaunch)
This is another extension of components of bioinformatics that deals with the application of information of biomedical data with particular reference to biomolecules, in vitro studies and clinical trials majorly in the field of application of bioinformatics in biotechnology.
It involves acquisition, storage and retrieval of genome information for DNA analysis in bioinformatics and bioinformatics drug discovery.
The process involves creation of a database for organizing, storage and management of biological genome based data sets. Researchers can access the datasets to retrieve the existing information for DNA analysis in bioinformatics or bioinformatics drug discovery. They can also yield new research information like protein sequence data banks for molecular structure in bioinformatics in biotechnology.
DNA analysis in bioinformatics involves the use of medical informatic tools like development of data algorithms and statistics to analyse and interpret the genome data sets.
This includes analysis of the DNA and RNA sequence and study of other protein structure and sequence, gene expression profiles and biochemical pathways. This information is widely used across the bioinformatics in biotechnology arena to interpret and guide the inventions using DNA analysis in bioinformatics which aids in drug discovery by disease surveillance and researches on public health.
Conclusion
Bioinformatics and components of bioinformatics nerges biology and computer science has become indispensable in the field of biotechnology.
Bioinformatics and components of bioinformatics nerges biology and computer science has become indispensable in the field of biotechnology. By applying computational tools to biological data, agricultural bioinformatics has seen immense growth as in hybridization. DNA analysis in bioinformatics has taken the disease prediction to a more realistic level where scientists can analyse gene expression profiles to locate the disease linked genes. Bioinformatics in drug discovery is another area which has benefitted in the sense of scanning and identifying potential drug targets. Join a Bioinformatics Course at CliniLaunch.
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