Difference between BIOINFORMATICS and BIOTECHNOLOGY?

Biotechnology:

It is one of the most revolutionary and beneficial scientific developments in the last quarter of the century. It is a multidisciplinary science that includes not only biology but also subjects such as mathematics, physics, chemistry, engineering, and more. It is also a combination of various combined technologies applied to living cells to produce a particular product or enhance its quality according to our preferences. Its application varies from agriculture to industry - food, pharmaceuticals, chemicals, organic products, textiles, medicine, nutrition, environmental protection, animal sciences, etc. Making one of the fastest growing fields.

Biotechnology combines disciplines such as genetics, molecular biology, biochemistry, embryology and cell biology, which in turn are linked to practical sciences such as chemical engineering, information technology and robotics.

Bioinformatics:

It is the application of computer science and computer science in the field of molecular biology. The term bioinformatics was created by Paulien Hogeweg in 1979 to study the computational processes in living systems. Its main use, at least since the late 1980's, has been in genomics and genetics, particularly in those areas of genomics involving the analysis of large-scale DNA sequences. Bioinformatics has so far created and promoted databases, algorithms, computational and statistical techniques and theory to solve formal and practical problems arising from the management and analysis of biological data. In recent decades, rapid advances in genomics and other molecular research technologies and developments in information technologies have been combined to produce enormous information on molecular biology. It is the name given to these mathematical and computational approaches that are used to understand the understanding of biological processes. Common activities in bioinformatics include the mapping and analysis of DNA and protein sequences, aligning different DNA and protein sequences to compare them, and to create and see models of 3-D protein structures.

The primary objective of bioinformatics is to increase understanding of biological processes. What distinguishes it from other approaches, however, is its focus on the development and application of computational intensity techniques (eg pattern recognition, data mining, engineering learning algorithms and visualization) to achieve this goal. Significant research efforts in the field include sequence alignment, genes finding, genome assembly, protein structure alignment, protein structure prediction, gene expression predictions and protein-protein interactions, genomic correlation studies and evolution modeling.

Both fields of Biotechnology and Bioinformatics are as good as work and gain prospects. Both courses have equal opportunities and have their own priorities, I suggest you go for this area you are interested in.

Scope Of Bioinformatics in Pakistan

Majority of the students are not be fully aware of the term bioinformatics! 
Don't need to worried about that at all, in this post we will make sure you learn that what bioinformatics is all about and what sort of scope it is offering for the students for their future.

Introduction to Bioinformatics Field: 

Bioinformatics is actually known the new field of the science which is in simple words the combination of the computer science along with the biology and also the engineering and mathematics. 
Researchers who are involved in this field they do have the knowledge of all about the disciplines of the science. They are also putting their main efforts in order to analyse and also interpret with the data of biological science with computers.

List of Important Jobs Career Options In Bioinformatics in Pakistan:

These are the main & important career employment options in Bioinformatics students in Pakistan:

• Network Administrator 
• Bio Statistician 
• Molecular Model Expert 
• Structural Analyst 
• Bio Mechanics 
• Technician 
• Biotech Expert 
• Research Assistant 
• Scientists 
• Researcher 
• Bioinformatics Analyst Expert 
• Bioinformatics Developer Expert 
• Scientific Curator 
• Gene Analyst 
• Data Base Programmar 
• Computational Biologists 
• Chem-informatician 
• Scientific Writer 
• Pharma-co-genomics

Extraordinary energy efficiency.

Much of our scientific, technological, and economic future depends on the availability of an ever-increasing supply of computational power. However, the increasing demand for such power has pushed electronic technology to the limit of physical feasibility and has raised the concern that this technology may not be able to sustain our growth in the near future. It became important to consider an alternative means of achieving computational power. In this regard, DNA computing was introduced based on the usage of DNA and molecular biology hardware instead of the typical silicon based technology. The molecular computers could take advantage of DNA's physical properties to store information and perform calculations. These include extremely dense information storage, enormous parallelism and extraordinary energy efficiency. One of the main advantages that DNA computations would add to computation is its self - parallel processing while most of the electronic computers now use linear processing. In this paper, the DNA computation is reviewed and its state of the art challenges and applications are presented. Some of these applications are those require fast processing, at which DNA computers would be able to solve the hardest problems faster than the traditional ones. For example, 10 trillion DNA molecules can fit in one cubic centimeter that would result in a computer that holds 10 terabytes of data. Moreover, this work focuses on whether a large scale molecular computer can be built. 

Massively parallel computation

DNA computation investigates the potential of DNA as a massively parallel computing device. Research is focused on designing parallel computation models executable by DNA based chemical processes and on developing algorithms in the models. L. Adleman (1994) initiated this area of research by presenting a DNA based method for solving the Hamilton Path Problem. That contribution raised the hope that parallel computation by DNA could be used to tackle NP-complete problems which are thought of as intractable. The current realization however, is that NP-complete problems may not be best suited for DNA based (more generally, molecule based) computing. A better subject for DNA computing could be large scale evaluation of parallel computation models. Several proposals have been made in this direction. We overview those methods, discuss technical and theoretical issues involved, and present some possible applications of those methods. 

DENSE DATA STORAGE

DNA digital data storage refers to any process to store digital data in the base sequence of DNA. This technology uses artificial DNA made using commercially available oligonucleotide synthesis machines for storage and DNA sequencing machines for retrieval. This type of storage system is more compact than current magnetic tape or hard drive-storage systems due to the data density of the DNA. Currently it was reported that in 1 gram of DNA 215 petabytes (215 million gigabytes) could be stored. It also has the capability for longevity, as long as the DNA is held in cold, dry and dark conditions, as is shown by the study of woolly mammoth DNA from up to 60,000 years ago, and for resistance to obsolescence, as DNA is a universal and fundamental data storage mechanism in biology. These features have led to researchers involved in their development to call this method of data storage "apocalypse-proof" because "after a hypothetical global disaster, future generations might eventually find the stores and be able to read them." It is, however, a slow process, as the DNA needs to be sequenced in order to retrieve the data, and so the method is intended for uses with a low access rate such as long-term archival of large amounts of scientific data.

PROPERTIES OF A DNA COMPUTER

Dense data storage.

Massively parallel computation. 

Extraordinary energy efficiency.

EVOLUTION OF THE DNA COMPUTER

A major improvement in DNA information storage and retrieval has been announced in Science Magazine. Two scientists from Columbia University and the New York Genome Center report a new high bar for DNA data storage — over two orders of magnitude better than previous attempts. They were able to encode text, images, a movie, and an operating system in 2 megabytes of DNA, and retrieve it back perfectly in multiple trials. News from Columbia University Data Science Institute says,

Humanity may soon generate more data than hard drives or magnetic tape can handle, a problem that has scientists turning to nature’s age-old solution for information-storage — DNA.

In a new study in Science, a pair of researchers at Columbia University and the New York Genome Center (NYGC) show that an algorithm designed for streaming video on a cellphone can unlock DNA’s nearly full storage potential by squeezing more information into its four base nucleotides. They demonstrate that this technology is also extremely reliable. [Emphasis added.]