Synthetic biology, Artificial intelligence, quantum computing - in genetics
- 1. BHARATHIAR UNIVERSITY MICROBIAL GENETICS AND R-DNA TECHNOLOGY TOPIC : ● SYNTHETIC BIOLOGY ● ARTIFICIAL INTELLIGENCE ● QUANTUM COMPUTING PRESENTED BY : SUMESH. M 21MBTB24 1st. M.Sc., Microbiology
- 2. CONTENTS ➢ SYNTHETIC BIOLOGY ➢ ARTIFICIAL INTELLIGENCE ➢ QUANTUM COMPUTING ➢ SUMMARY AND CONCLUSIONS ➢ REFERENCES
- 4. INTRODUCTION ● Synthetic biology (SynBio) is a multidisciplinary area of research that seeks to create new biological parts, devices, and systems, or to redesign systems that are already found in nature. ● It is a branch of science that encompasses a broad range of methodologies from various disciplines, such as biotechnology, genetic engineering, molecular biology, molecular engineering, systems biology, membrane science, biophysics, chemical and biological engineering, electrical and computer engineering, control engineering and evolutionary biology. Due to more powerful genetic engineering capabilities and decreased DNA synthesis and sequencing costs, the field of synthetic biology is rapidly growing. ● Many scientists suspect that synthetic biology will not only reveal new knowledge about the machinery of life but also bring about new biotechnological applications. Two major applications that are being pursued are biofuels, & pharmaceuticals.
- 5. SYNTHETIC BIOLOGY ● Synthetic Biology is also known as Synbio, Synthetic Genomics, Constructive Biology or Systems Biology) - design and construction of new biological parts, devices and systems that do not exist in the natural world and also the redesign of existing biological systems to perform specific tasks. Advances in Nano scale technologies - manipulation of matter at the level of atoms and molecules - are contributing to advances in synthetic biology. ● The title 'synthetic biology' appeared in the literature in 1980, when it was used by Barbara Hobom to describe bacteria that had been genetically engineered using recombinant DNA technology. These bacteria are living systems (therefore biological) that have been altered by human intervention (that is, synthetically). In this respect, synthetic biology was largely synonymous with bioengineering
- 6. There are many definitions for synthetic biology. Like, ➢ It is an emerging field of biology that aims at designing and building novel biological systems. or ➢ The final goal is to be able to design biological systems in the same way engineers design electronic or mechanical systems. Etc. or ➢ An emerging field of research that aims to combine the knowledge and methods of biology, engineering and related disciplines in the design of chemically synthesized DNA to create organisms with novel or enhanced characteristics and traits
- 7. Subfields of contemporary Synthetic Biology There are 5 main subfields of contemporary synthetic biology ➢ DNA Synthesis ➢ DNA based bio-circuits ➢ Minimal genome ➢ Protocells ➢ Chemical SB/Xenobiology Components of Synthetic Biology . ➢ Genetic Manipulation ➢ Genetic selection carried out for millennia (domestication of animals) ➢ Mendelian selection 'rationalized' process. ➢ Recombinant DNA Technology
- 8. APPLICATIONS ENVIRONMENTALAPPLICATIONS ➢ Synthetic biology has a broad range of applications including the production of photographic bacteria. ➢ They can also be used to detect toxic chemicals such as arsenic. MEDICALAPPLICATIONS ➢ One of the avenues of synthetic biology is that has wide application is the development of alternative production routes for useful compounds, and one of the most discussed of these is the construction of a artificial metabolic pathway in E.coli and Yeast to produce a precursor (artemisinin) for a antimalarial drug.
- 9. ➢ It can be used for development of other therapeutically useful products for cancer and HIV treatment. ➢ It helps for the development of synthetic vaccines for some viral diseases such as SARS (Severe Acute Respiratory Syndrome) and Hepatitis C INDUSTRIALAPPLICATIONS ➢ Synthetic biology is widely used for the production of Biofuels from genetically engineered microorganisms.
- 11. INTRODUCTION ● Artificial Intelligence - It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. ● Artificial Life is a Field of study and an associated art form which examines systems related to life, its processes, and its evolution through simulations using computer models, robotics, and biochemistry. Soft (software) Hard (hardware) Wet (biochemistry).
- 12. ARTIFICIAL INTELLIGENCE ● Artificial intelligence is at the forefront of modern technology and has begun to parallel in the world of biotechnology. Machine learning has also been the heart of many tech startups which is driven by increasing availability and cheaper data paired with more efficient computers. Throughout the years, Al and ML have started to find their way into the realm of biotechnology due to the growth of biotechnology data. ● Artificially intelligent machines can perform tasks far better and in a very fast manner than humans. It has a large number of applications in the field of genetics and biology ● Lab assistants are known for carrying out tedious tasks ranging from gene editing or data analysis. Many of these tasks are now being passed over to the responsibility of Al.
- 13. ● The power of artificial intelligence now allows stronger experiments and data to be collected in any area of science. This advancement and collaboration between biotechnology and artificial intelligence can increase the time of getting better results back.
- 14. APPLICATIONS AI has two main applications in genetics: identification of harmful genes and treatment of disease. IDENTIFICATION ● For human beings, it is an extremely tedious and time-consuming process to analyze the vast amount of data that is present in a single person’s DNA. This analysis can be made much more efficient and accurate by utilizing machines for their core purpose- to make tiresome tasks less challenging. ● By using machine learning algorithms to compare the different gene expression levels in malignant and normal tissue samples of a patient diagnosed with cancer, predictions can be made about which genes have been mutated in that patient’s DNA.
- 15. ● Various imaging techniques are used to detect the mutations and diseases in different organisms like magnetic resonance imaging, fluorescent imaging, and thermography Magnetic resonance imaging ● Also called as NMR, meaning nuclear magnetic resonance scanner, it is mostly known as magnetic resonance imaging device, and is usually identified for its powerful magnets. These magnets are good as they efficiently polarize and further excites the focused proton singly included in water molecules present in the tissue, helping in a detectable signal spatially encoded giving various images of the body. Fluorescence imaging ● Fluorescence imaging is used to detect tumors, and cancer. Fluorescence techniques are also used in a variety of genetic techniques like PCR, Blotting techniques, DNA sequencing, medical imaging and surgery.
- 16. Thermography ● One of the most common applications of it is breast imaging. Usually one of the three approaches are being used commonly, the tele-thermography, the dynamic angio-thermography and the contact thermography type. The imaging thermographic digital methods involve the advantage of the principle derived from metabolic activity. Also vascular circulation within the area surrounding a developing breast cancer is studied to detect the higher value.
- 17. TREATMENT ● Diagnosis ● Treatment protocol development ● Drug development ● Personalized medicine ● Patient monitoring and caring
- 19. INTRODUCTION ● Quantum computing is a promising field that emerged out of a combination of quantum physics and computer science. With ever expanding data across different areas, the conventional computer will run out of its capacity to handle such big data. Further, extracting the meaningful from big complex data still, accompany challenges with it. Quantum computing's main goal is to provide such algorithms which are robust and faster in solving problems as compared to classical computers.
- 20. QUANTUM COMPUTING ● Quantum computing is an interdisciplinary research area that utilizes the principles of quantum mechanics. ● David Deutsch is known as the father of quantum computing. ● Quantum computers possess unique abilities such as entanglement, superposition that enable to surpass some of the limitations of today’s classical computer. For instance, their ability to perform extremely faster computations by reducing the number of calculations needed to complete a task. Further, it can help in solving problems that are currently unsolvable in varied disciplines such as bioinformatics, artificial intelligence, drug discovery, personalized medicine, biological system, and many others
- 22. QUANTUM COMPUTERS AND ITS BASIC FEATURES Well-known high technology using companies like IBM, Microsoft, Google is investing in research and development towards quantum computing. Recently, IBM Q System OneTM has been developed by IBM which is the first commercial Quantum computer. Following are some of the basic features possessed by quantum computing that make it lucrative : ➢ Qubits ● In contrast to bit can have only one possible electronic state out of two (|0⟩ and |1⟩ ) at a time in classical computing’s, quantum computing leverages the advantage of subatomic particles where each state is represented by ‘quantum bit’ or ‘qubit’ that can attain 1,0 or any values in between them at a time. Such a system is called as “complex two-state system” where a state space has infinitely many possible states.
- 23. ➢ Superposition ● In quantum computing, pure qubit (|Ψ⟩ ) can attain any superposition or linear combination of two basic states represented by Dirac notation |0⟩ and |1⟩ , a|0⟩ + b|1⟩ ), where a and b denote complex numbers given |a| 2 + |b| 2 = 1. Further, two bits in classical computing can be indicated as 00, 01, 10 and 11. In contrast, a qubit can be represented by any of those numbers at the same time. As a result, greater number of qubits will lead to an exponential increase in the number of superpositions that facilitates faster calculations involving very complicated numbers. ➢ Quantum parallelism ● The superposition feature imparts an ability to run a computation on possible classical states at a time that provides enormous computational power to quantum computing, and the process is referred to as quantum parallelism.
- 24. Consequently, parallelism in quantum computing can perform some tasks shown to have advantages over classical computing. Some of these advantages include factorization of large numbers and searching large databases. ➢ Entanglement ● Quantum entanglement refers to a process where a change in the state of one qubit is inseparable from the change in the state of others regardless of their spatial separation. ● Entanglement enables quantum computing to solve problems quickly to get to the right answer and fosters role in a variety of applications including teleportation, quantum cryptography, and others.
- 25. APPLICATIONS ● Solving biological problems ● Drug designing ● Drug development ● Storing Genomic data and genetic informations ● Cancer disease detection
- 26. SUMMARY AND CONCLUSIONS According to Synthetic biology, It is a multidisciplinary area of research that seeks to create new biological parts, devices, and systems, or to redesign systems that are already found in nature. Synthetic Biology is used to design and construct new biological parts, devices and systems that do not exist in the natural world and also the redesign of existing biological systems to perform specific tasks. Advances in Nano scale technologies - manipulation of matter at the level of atoms and molecules - are contributing to advances in synthetic biology. According to Artificial Intelligence, It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.
- 27. According to Quantum Computing, Quantum computing is an interdisciplinary research area that utilizes the principles of quantum mechanics. Quantum computers possess unique abilities such as entanglement, superposition that enable to surpass some of the limitations of today’s classical computer. For instance, their ability to perform extremely faster computations by reducing the number of calculations needed to complete a task. Further, it can help in solving problems that are currently unsolvable in varied disciplines such as bioinformatics, artificial intelligence, drug discovery, personalized medicine, biological systems, and many others Synthetic biology, Artificial intelligence and Quantum computing, These three have their own importance and applications in the field of life sciences.
- 28. REFERENCES Bennett, H. C. 1995. Quantum information and computation. Physics Today. 24-30 Britannica.com/syntheticbiology Bueso, F. Y.; Tangney, M. (2017). "Synthetic Biology in the Driving Seat of the Bioeconomy". Trends in Biotechnology. 35(5): 373–378. Garfinkel et al. 2007 John McCarthy, 2007 Levskaya, A.; et al. (2005). ""Synthetic biology " engineering Escherichia coli to see light". Nature. 438 (7067): 441–442.
- 29. Martin, V. J., Pitera, D. J., Withers, S. T., Newman, J. D. & Keasling, J. D. Engineering a mevalonate pathway in Escherichia coli for production of terpenoids. Nature Biotech. 21, 796–802 (2003) Olmschenk, S. et al. 2009. Quantum teleportation between distant matter qubits. Science, 323(5913), 486–489 Synthetic Biology/wikipedia Sutor, B. 2018. Scientists Prove a Quantum Computing Advantage over Classical. IBM Research Blog. Yeager, Ashley. “Could AI Make Gene Editing More Accurate?” Thescientist.com.
- 30. THANK YOU