From DNA to Computation: The Rise of Bio-computers in Biotechnology

Bio-computers are special devices that use biological substances like DNA, enzymes, or proteins to perform calculations. They are also known as molecular computers or DNA computers. Bio-computing is a combination of biotechnology and computer science, where we use computer science principles to understand biological systems better.

Using biological molecules in bio-computers has several advantages. First, they can do many calculations at the same time, which we call high parallelism. Second, they consume less power compared to regular computers. Lastly, they are very accurate in their computations. These qualities make bio-computers potentially faster and more efficient than the computers we commonly use.

One exciting application of bio-computers is in the field of medicine. They could help us monitor and diagnose diseases more effectively. Additionally, bio-computers might enable targeted drug treatments, which means delivering medicines directly to where they are needed in our bodies. They could also contribute to environmental monitoring and help in bioengineering projects.

However, bio-computing is still a young field, and there are many technical challenges to overcome before bio-computers can be widely used. We need to address these challenges to make bio-computers practical and commercially viable. Nonetheless, the possibilities of this technology are enormous, and it is highly likely that bio-computers will play a significant role in the future of computing and biotechnology.

Types of Bio-computers in Biotechnology

In the field of biotechnology, there are various types of bio-computers that are being researched and developed. These bio-computers utilize biological components, such as DNA, enzymes, and cells, to perform computational tasks. Research in the field of bio-computing is ongoing, and future advancements may lead to more sophisticated and practical bio-computers.

DNA-based Computers

• A relatively new form of computing that, instead of using silicon-based technology, utilizes the abilities of the DNA molecule and biochemistry.
• A DNA computer is based on the fact the information is “encoded” within deoxyribonucleic acid (DNA) as patterns of molecules known as nucleotides.
• DNA computers showing enormous potential, especially for medical purposes as well as data processing applications.
• Sloving NP-complete and hard computational problems.
• Storage and Associative memory
• DNA 2 DNA Problems such as DNA Sequencing, DNA Fingerprinting and DNA Mutation detection.
• Still a lot of work and resources required to develop it into a fully fledged product.

Enzyme-based Computers (Biosensors)

• An enzyme biosensor is an analytical device that combines an enzyme with a transducer to produce a signal proportional to target analyte concentration.
• Enzyme-based biosensors use their catalytic activity and binding capabilities for specific detection.
• The catalytic activity of the enzymes provides these types of biosensors with the ability to detect much lower limits than with normal binding techniques.
• This catalytic activity is related to the integrity of the native protein structure.
• There are three types of Biosensors 1. Enzyme biosensor 2. Microbial biosensor 3. Affinity biosensor

Cellular Computers

• Cellular system solves the problem of spectral congestion.
• Offer high capacity in limited spectrum.`
• Replaces high powered transmitter with several low power transmitters.
• Early mobile telephony systems were not cellur. Coverage over a large area was provided by a high powered transmitter mounted on a tall tower. Frequency reuse was not employed that resulted in very low capacity.
• The cellular concept arose in the 1970s from the need to restructure the radio telephone system with the increase in demand. The increase in demand could not be satisfied just by additional spectrum allocations.

Protein-based Computers

• Under a high proton concentration, the formation of ATP takes place and this ATP is used to catalyse a reaction. By measuring the rate of reaction. By measuring the rate of reaction, one can create a logic gate.
• The bR molecule can act as the basis for a molecular binary switch . This can be used to make large optical memories with access time below two nano seconds.

Biomolecular Networks

• Biomolecular networks, also known as biological networks, refer to the interconnected system of biomolecules within a living organism.
• These networks play a crucial role in various biological processes, including cellular signaling, gene regulation, metabolic pathways, and protein-protein interactions.
• They are composed of different types of biomolecules, such as proteins, DNA, RNA, and small molecules.
• Biomolecular networks are often represented as graphs, where nodes represent biomolecules, and edges represent the interactions or relationships between them
• These interactions can be physical, such as protein-protein interactions or DNA-protein interactions, or they can be regulatory, such as transcriptional regulation of gene expression.
• Understanding biomolecular networks is essential for advancing our knowledge of fundamental biological processes and discovering new therapeutic targets for diseases.

Neural Networks

• A series o algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.
• Neural networks do not perform miracles. But if used sensibly they can produce some amazing results.
• Very useful in Data Mining and better results are the hope
• Nodes connect to other and are organized in layers