Science and Technology Quick Revision Part-2

by | Feb 6, 2025 | APPSC Group-2 Mains Paper-2 Science and Technology

Artificial Intelligence (AI)

  • Definition of AI?
    • AI refers to the simulation of human intelligence in machines that are programmed to think, learn, and make decisions.
    • It includes technologies like machine learning (ML), natural language processing (NLP), and computer vision.
    • AI can be traced back to 1950 when Alan Turing invented the Turing test.
    • Alan Turing introduced Turing Test for evaluation of intelligence of a machine as compared to human intelligence and published Computing Machinery and Intelligence.
  • Types of AI
    • Narrow AI (Weak AI): Designed for specific tasks (e.g., voice assistants like Siri or Alexa).
    • General AI (Strong AI): Hypothetical AI that can perform any intellectual task a human can (not yet achieved).
    • Superintelligent AI: AI that surpasses human intelligence (theoretical).
    • Large Language Models (LLM’s) are a type of underlying AI architecture that are specifically designed to understand and generate human-like language.
  • Key Technologies
    • Machine Learning (ML): Algorithms that learn from data to make predictions or decisions.
    • Deep Learning: A subset of ML using neural networks to model complex patterns.
    • Natural Language Processing (NLP): Enables machines to understand and generate human language (e.g., ChatGPT).
    • Computer Vision: Allows machines to interpret and analyze visual data (e.g., facial recognition).
  • Key Milestones
    • 1956: The term “Artificial Intelligence” was coined at the Dartmouth Conference.
    • 1997: IBM’s Deep Blue defeated chess champion Garry Kasparov.
    • 2011: IBM’s Watson won Jeopardy! against human champions. Siri was announced as a digital assistant by Apple in 2011.
    • 2016: Google’s AlphaGo defeated world champion Lee Sedol in the game of Go.
    • 2022: OpenAI’s ChatGPT brought generative AI into the mainstream.

Blockchain Technology

  • What is Blockchain?
    • Blockchain is a decentralized, distributed ledger technology that records transactions across multiple computers.
    • Ensures transparency, security, and immutability of data.
    • First blockchain was created in 2008 by Satoshi Nakamoto for Bitcoin.
    • Blockchain is not just for cryptocurrencies; it has applications in finance, healthcare, supply chain, and more.
  • Key Features
    • Decentralization: No central authority controls the data.
    • Immutability: Once recorded, data cannot be altered or deleted.
    • Transparency: All participants in the network can view the transactions.
    • Security: Uses cryptographic techniques to secure data.
  • Types of Blockchains
    • Public Blockchain: Open to anyone (e.g., Bitcoin, Ethereum).
    • Private Blockchain: Restricted access, controlled by an organization. (e.g., Hyperledger and Corda).
    • Consortium Blockchain: Controlled by a group of organizations.
    • Hybrid Blockchain: Combines features of public and private blockchains.
  • Popular Blockchain Platforms
    • Bitcoin: The first and most well-known blockchain, primarily for cryptocurrency.
    • Ethereum: Supports smart contracts and decentralized applications (dApps).
    • Hyperledger: An open-source blockchain project for enterprise use.
    • Ripple: Focused on real-time cross-border payment systems.
    • EOSIO: A platform for building high-performance dApps.
    • Stellar: Focuses on fast and low-cost cross-border payments.
    • Tron: Aims to create a decentralized internet.
    • Solana: Known for its high transaction speed and low fees, making it a strong competitor to Ethereum. It has a rapidly growing ecosystem of dApps, particularly in DeFi and NFTs
  • Key Terms
    • Node: A computer connected to the blockchain network.
    • Mining: The process of validating transactions and adding them to the blockchain.
    • Wallet: A digital tool to store and manage cryptocurrencies.
    • Smart Contract: Automated, self-executing contracts with predefined rules.

Cryptocurrency

  • What is Cryptocurrency?
    • A digital or virtual currency secured by cryptography.
    • Operates on decentralized blockchain technology.
    • Not controlled by any government or central authority.
  • Key Features
    • Decentralized – No central authority (e.g., banks, governments).
    • Secure – Uses blockchain and cryptographic hashing (e.g., SHA-256).
    • Immutable – Transactions cannot be altered once recorded.
    • Pseudonymous – No personal identity linked directly to transactions.
    • Limited Supply – Many cryptocurrencies have a fixed supply (e.g., Bitcoin: 21 million coins).
  • Popular Cryptocurrencies
    • Bitcoin (BTC) – First and most valuable cryptocurrency.
    • Ethereum (ETH) – Supports smart contracts & decentralized apps (DApps).
    • Ripple (XRP) – Focuses on fast cross-border payments.
    • Litecoin (LTC) – Faster alternative to Bitcoin.
    • Stablecoins (USDT, USDC, DAI) – Pegged to fiat currency for stability.
    • Tether (USDT): A stablecoin pegged to the US dollar, used to stabilize other cryptos.
  • How Cryptocurrency Works
    • Transactions recorded on a blockchain ledger.
    • Mining (Proof of Work) or Staking (Proof of Stake) validates transactions.
    • Wallets (hardware/software) store crypto assets.
    • Exchanges allow buying/selling (e.g., Binance, Coinbase, WazirX).

Internet of Things (IoT)

  • What is IoT?
    • IoT is a network of physical devices (things) embedded with sensors, software, and connectivity to exchange data over the internet.
    • Enables smart automation and data-driven decision-making.
    • Uses sensors, software, and AI to automate processes.
  • Key Components
    • Devices/Sensors: Collect data (e.g., temperature, motion, light).
    • Connectivity: Transmits data via Wi-Fi, Bluetooth, or cellular networks.
    • Data Processing: Analyzes data using cloud or edge computing.
    • User Interface: Allows users to interact with the system (e.g., mobile apps).
  • How IoT Works
    • Devices collect data using sensors.
    • Data is transmitted to a central system (cloud or local server).
    • Data is processed and analyzed to trigger actions or provide insights.
    • Users can monitor and control devices remotely.
  • Key Technologies
    • Sensors: Detect changes in the environment (e.g., temperature, motion).
    • Cloud Computing: Stores and processes data from IoT devices.
    • Edge Computing: Processes data closer to the source to reduce latency.
    • 5G: Provides faster and more reliable connectivity for IoT devices.
  • Applications of IoT
    • Smart Homes: Smart thermostats, lights, and security systems.
    • Healthcare: Wearable devices, remote patient monitoring.
    • Agriculture: Smart irrigation, soil monitoring.
    • Transportation: Connected vehicles, traffic management.
    • Industrial IoT (IIoT): Predictive maintenance, supply chain optimization.
  • Popular IoT Platforms
    • AWS IoT: Amazon’s cloud-based IoT platform.
    • Google Cloud IoT: Offers data analytics and machine learning integration.
    • Microsoft Azure IoT: Provides end-to-end IoT solutions.
    • IBM Watson IoT: Provides tools for device connectivity, data management, and analytics.

Fourth Industrial Revolution (4IR)

  • What is Fourth Industrial Revolution (4IR)?
    • First three industrial revolutions were driven by steam power, electricity, and digital technology, respectively.
    • 4IR builds on Third Industrial Revolution (the digital revolution) and is marked by a more pervasive and integrated use of technology.
    • Characterized by the fusion of digital, biological, and physical technologies.
    • Driven by automation, AI, IoT, robotics, and big data.
    • Coined by Klaus Schwab (World Economic Forum, 2016).
  • Key Technologies
    • Artificial Intelligence (AI) & Machine Learning – Smart decision-making.
    • Internet of Things (IoT) – Interconnected smart devices.
    • Blockchain – Secure decentralized transactions.
    • 5G & Edge Computing – Faster data processing.
    • Robotics & Automation – Smart manufacturing.
    • 3D Printing (Additive Manufacturing) – Rapid prototyping.
    • Biotechnology & Genetic Engineering – Advances in medicine.
    • Quantum Computing – Ultra-fast computing for complex problem-solving.
  • Key Features
    • Interconnectivity: Seamless integration of systems and devices.
    • Automation: Increased use of AI and robotics to replace human labor.
    • Data-Driven Decision Making: Leveraging big data and analytics for insights.
    • Customization: Mass customization of products and services.

Big Data

  • What is Big Data?
    • Large and complex data sets that cannot be processed using traditional methods.
    • Requires advanced tools like AI, Machine Learning, and Cloud Computing.
  • Key Characteristics (5 Vs of Big Data)
    • Volume – Massive amount of data (terabytes, petabytes).
    • Velocity – High-speed data generation & processing.
    • Variety – Structured (databases), Semi-structured (JSON, XML), Unstructured (videos, social media).
    • Veracity – Accuracy and reliability of data.
    • Value – Extracting useful insights from data.
  • Sources of Big Data
    • Social Media: Posts, likes, shares, and comments.
    • IoT Devices: Sensors, smart devices, and wearables.
    • Transactions: Financial records, e-commerce data.
    • Machine Data: Logs, telemetry, and industrial sensors.
    • Public Data: Government records, weather data, and satellite imagery.
  • Key Technologies
    • Hadoop: Open-source framework for distributed storage and processing.
    • Spark: Fast, in-memory data processing engine.
    • NoSQL Databases: Non-relational databases for unstructured data (e.g., MongoDB, Cassandra).
    • Data Lakes: Centralized repositories for raw data storage.
    • Machine Learning: Algorithms for analyzing and predicting trends.
  • Key Terms
    • Data Mining: Extracting patterns and knowledge from large datasets.
    • Data Analytics: Analyzing data to uncover insights and trends.
    • Data Visualization: Graphical representation of data for easier understanding.
    • ETL (Extract, Transform, Load): Process of preparing data for analysis.

Robotics

  • What is Robotics?
    • Interdisciplinary field that combines AI, mechanical engineering, electronics, and computer science.
    • Robots are programmable machines that can perform tasks autonomously or with human assistance.
    • The word “robot” comes from the Czech word “robota”, meaning forced labor.
    • The first industrial robot, Unimate, was installed in 1961 at a General Motors plant.
    • Sophia, a humanoid robot, became the first robot to receive citizenship (Saudi Arabia, 2017).
  • Types of Robots
    • Industrial Robots – Used in manufacturing, assembly lines (e.g., robotic arms).
    • Autonomous Robots – Self-operating robots (e.g., self-driving cars, drones).
    • Humanoid Robots – Robots resembling humans (e.g., Sophia, Atlas).
    • Service Robots – Used in hospitals, homes (e.g., robotic vacuum cleaners, robotic surgery).
    • Military & Defense Robots – Used for surveillance, bomb disposal (e.g., drones, robotic soldiers).
  • Key Components of Robots
    • Sensors – Detects environment (e.g., cameras, LiDAR).
    • Actuators – Motors that enable movement.
    • AI & Machine Learning – Helps robots make intelligent decisions.
    • Control System – The “brain” of the robot (microcontrollers, processors).
    • Power Supply – Batteries, solar energy, or electricity.
    • End Effectors: Tools or hands that interact with the environment.
  • Key Technologies
    • Artificial Intelligence (AI): Enables robots to learn and make decisions.
    • Machine Learning (ML): Improves robot performance through data analysis.
    • Computer Vision: Allows robots to interpret visual information.
    • Natural Language Processing (NLP): Enables robots to understand and respond to human language.

Quantum Computing

  • What is Quantum Computing?
    • A type of computing that uses quantum mechanics to process information.
    • Unlike classical computers (which use bits), quantum computers use qubits (quantum bits).
    • Quantum computers use qubits that can exist in superposition (both 0 and 1 simultaneously).
    • Quantum computing could break RSA encryption, which secures most of today’s internet.
    • The concept of quantum computing was first proposed by Richard Feynman in 1982.
  • Key Concepts
    • Qubit: The basic unit of quantum information (can be 0, 1, or both).
    • Superposition: A qubit can exist in multiple states at once.
    • Entanglement: Qubits can be correlated, so the state of one affects the state of another, even at a distance.
    • Quantum Interference: Enhances correct computation paths and cancels out incorrect ones.
  • How It Works
    • Quantum Gates: Perform operations on qubits (similar to classical logic gates).
    • Quantum Circuits: Sequences of quantum gates to perform computations.
    • Measurement: Collapses the qubit’s state to either 0 or 1, providing the result.
  • Key Players in QC field
    • IBM: IBM Quantum Experience and Qiskit framework.
    • Google: Achieved quantum supremacy in 2019 with its Sycamore processor.
    • Rigetti Computing: Focuses on hybrid quantum-classical systems.
    • D-Wave: Specializes in quantum annealing for optimization problems.
    • Microsoft: Develops quantum software and the Q# programming language.

Supercomputing

  • What is Supercomputing?
    • Supercomputers are the fastest, most powerful computers used for complex computations.
    • Capable of performing quadrillions of calculations per second (measured in petaflops or exaflops).
    • Used in fields requiring high-performance computation, like scientific research, simulations, and AI.
    • As of November 2024, the world’s fastest supercomputer is El Capitan (USA). Built by HP Enterprise & AMD.
    • Frontier is the second fastest supercomputer in the world, located at Oak Ridge National Laboratory, USA. Built by HP Enterprise & AMD.
    • Aurora is the third fastest supercomputer in the world, located at Argonne National Laboratory, USA. Built by HP Enterprise & Intel.
  • Applications of Supercomputing
    • Weather Forecasting & Climate Modeling – Predicting storms, climate change simulations.
    • Scientific Research – Simulating biological processes, nuclear physics experiments.
    • Astronomy & Space Exploration – Simulating cosmic phenomena and analyzing large data sets (e.g., from telescopes).
    • Healthcare – Drug discovery, protein folding simulations (e.g., protein structure predictions for diseases).
    • AI & Machine Learning – Training large AI models (e.g., natural language processing, autonomous vehicles).
    • Cryptography & Security – Testing encryption systems.

5G technology

  • What is 5G Technology?
    • 5G is the fifth generation of mobile network technology, succeeding 4G.
    • Designed to provide faster speeds, lower latency, and higher capacity for connected devices.
    • Enables the Internet of Things (IoT), smart cities, autonomous vehicles, and advanced healthcare systems.
    • First 5G network was launched in 2019 by South Korea.
    • 5G can support up to 1 million devices per square kilometer.
  • Key Features
    • High Speed: Up to 10 Gbps (100 times faster than 4G).
    • Low Latency: As low as 1 millisecond (ideal for real-time applications).
    • Increased Capacity: Supports more devices per square kilometer.
    • Energy Efficiency: Reduces power consumption for devices and networks.
    • Network Slicing – Allows customization of network parameters for different use cases (e.g., smart cities, industrial IoT).
  • How It Works
    • Uses higher frequency bands (millimeter waves) for faster data transmission.
    • Employs small cells (mini base stations) to enhance coverage and capacity.
    • Utilizes MIMO (Multiple Input Multiple Output) technology for improved signal quality.
  • Technology Behind 5G
    • Millimeter Waves – High-frequency waves (24 GHz and above) for ultra-fast data transmission.
    • Small Cells – Smaller cell towers (mini base stations) that improve coverage and speed.
    • Massive MIMO (Multiple Input Multiple Output) – Increases network capacity by allowing more devices to connect simultaneously.
    • Beamforming – Directs signals to specific devices for better efficiency.
  • Applications
    • Enhanced Mobile Broadband (eMBB): Faster internet for smartphones and tablets.
    • Internet of Things (IoT): Connects billions of devices (e.g., smart homes, wearables).
    • Autonomous Vehicles: Enables real-time communication for self-driving cars.
    • Smart Cities: Supports infrastructure like traffic management and energy grids.

Augmented Reality (AR) vs. Virtual Reality (VR)

Augmented Reality (AR)

  • AR enhances the real world by overlaying digital elements  (e.g., images, videos, 3D models).
  • Enhances reality: AR overlays digital information onto the real world.  
  • Uses existing environment: It uses the real-world environment as the backdrop.  
  • Interaction: Users interact with digital elements within the real world.  
  • Devices: Often accessed through smartphones, tablets, or specialized AR glasses.  
  • Immersion Level: Partial
  • Examples:
    • Pokémon Go  
    • IKEA Place app (visualizing furniture in your home)  
    • AR filters on social media  

Virtual Reality (VR)

  • VR creates a virtual world which is a fully immersive, computer-generated environment that replaces the real world.
  • Creates a virtual world: VR immerses users in a completely computer-generated environment.  
  • Replaces reality: It shuts out the real world and replaces it with a simulated one.  
  • Devices: Typically requires a VR headset and sometimes controllers or other input devices.  
  • Immersion Level: Users are fully immersed in the virtual world and interact with it.  
  • Examples:
    • VR games (Beat Saber, Half-Life: Alyx)  
    • VR simulations for training (flight simulators, medical training)  
    • VR experiences for tourism or education  

Deepfake Technology

  • What is Deepfake Technology?
    • AI-based technology that creates realistic fake videos, images, or audio.
    • Uses deep learning (GANs – Generative Adversarial Networks) to manipulate media.
    • Can make a person appear to say or do something they never did.
  • How Does It Work?
    • Generative Adversarial Networks (GANs): Two AI models compete—one creates fake content, the other detects it.
    • Facial Mapping & Synthesis: AI captures facial movements & expressions.
    • Voice Cloning: AI replicates speech patterns.
  • Uses of Deepfake Technology
    • Entertainment & Film Industry – CGI, recreating deceased actors.
    • Education & Training – AI-generated historical figures.
    • Marketing & Advertising – Personalized AI avatars.
  • Risks & Threats
    • Misinformation & Fake News – Spreading false political narratives.
    • Cybercrime & Fraud – Identity theft, financial scams.
    • Privacy Violations – Fake explicit content (deepfake pornography)
  • Countermeasures Against Deepfakes
    • AI-based Deepfake Detection Tools (Microsoft’s Deepfake Detection, Google’s FaceForensics++).
    • Blockchain for Content Verification.
    • Legal Regulations (Bans in some countries, digital watermarking).

3D Printing

  • What is 3D Printing?
    • A manufacturing process that creates three-dimensional objects by layering material based on a digital model.
    • Also known as additive manufacturing (as opposed to subtractive methods like cutting or drilling).
    • The first 3D printer was invented in 1984 by Charles Hull.
    • NASA has tested 3D printers in space to create tools and parts on-demand.
    • 3D printing is used to create custom-fit shoes and orthopedic implants.
  • How It Works
    • Design: A 3D model is created using CAD (Computer-Aided Design) software.
    • Slicing: The model is sliced into thin layers using specialized software.
    • Printing: The 3D printer builds the object layer by layer using materials like plastic, metal, or resin.
  • Key Technologies
    • Fused Deposition Modeling (FDM): Melts and extrudes thermoplastic filament.
    • Stereolithography (SLA): Uses UV light to cure liquid resin into solid layers.
    • Selective Laser Sintering (SLS): Uses a laser to fuse powdered material (e.g., nylon, metal).
    • Digital Light Processing (DLP): Similar to SLA but uses a digital light projector.
  • Key Terms
    • Additive Manufacturing: Building objects by adding material layer by layer.
    • CAD (Computer-Aided Design): Software used to create 3D models.
    • STL File: Standard file format for 3D printing.
    • Support Structures: Temporary structures used during printing to support overhangs.

Cloud Computing

  • What is Cloud Computing?
    • The delivery of computing services (storage, servers, databases, networking, software) over the internet.
    • Eliminates the need for on-premises hardware.
    • Pay-as-you-go model (scalable and cost-effective).
  • Types of Cloud Computing
    • Public Cloud – Services provided by third parties (AWS, Google Cloud).
    • Private Cloud – Dedicated for a single organization (IBM Cloud, VMware).
    • Hybrid Cloud – Combination of public & private clouds.
    • Community Cloud: Shared by a specific community with similar requirements (e.g., industry, security standards).
  • Cloud Service Models (SPI Model)
    • Infrastructure as a Service (IaaS): Provides access to fundamental computing resources like virtual machines, storage, and networks. You manage the operating systems and applications. (Think AWS EC2, Azure Virtual Machines, Google Compute Engine)
    • Platform as a Service (PaaS): Offers platforms for developing, testing, and deploying applications (e.g., Google App Engine, Microsoft Azure).
    • Software as a Service (SaaS): Delivers software applications over the internet. Here you just use the software. (e.g., Gmail, Salesforce, Microsoft 365, Dropbox, Zoom).
  • Key Players
    • Amazon Web Services (AWS): Leading cloud service provider.
    • Microsoft Azure: Popular for enterprise solutions.
    • Google Cloud Platform (GCP): Known for data analytics and machine learning.
    • IBM Cloud: Focuses on AI and enterprise solutions.
    • Oracle Cloud: Specializes in database and enterprise applications.

LiDAR (Light Detection and Ranging)

  • What is LiDAR?
    • LiDAR is a remote sensing technology that uses laser light to measure distances to the Earth’s surface.
    • Generates precise, three-dimensional information about the shape of the Earth and its surface characteristics.
  • How Does LiDAR Work?
    • Emits laser pulses from a sensor and measures the time it takes for each pulse to bounce back.
    • Calculates the distance to the target using the time delay (speed of light).
    • Can create a 3D point cloud of data representing the scanned area.
  • Key Components of LiDAR
    • Laser – Emits light pulses.
    • Scanner – Detects returning light pulses.
    • GPS – Provides location information for accuracy.
    • Inertial Measurement Unit (IMU) – Tracks the orientation of the sensor.
    • Types of LiDAR
    • Airborne LiDAR – Mounted on aircraft or drones for large-scale mapping (e.g., topography, forests).
    • Terrestrial LiDAR – Ground-based, used for high-precision scans of smaller areas (e.g., buildings, roads).
    • Mobile LiDAR – Mounted on moving vehicles, often used for road surveys and urban mapping.

Nanotechnology

  • What is Nanotechnology?
    • Nanotechnology is the manipulation of matter at the atomic or molecular scale, typically involving structures between 1 and 100 nanometers (nm).
    • It focuses on creating materials, devices, and systems with unique properties arising from their small size and large surface area.
    • Nanometer (nm): 1 nm = 10⁻⁹ meters (a billionth of a meter).
    • Key Concept: At the nanoscale, materials exhibit unique physical, chemical, and biological properties due to increased surface area and quantum effects.
    • Nanotech is key to realizing the potential of quantum computers, which could revolutionize computing power.
  • Key Principles of Nanotechnology
    • Nano-Scale Size – Materials and structures at the nanometer scale (1 nanometer = 1 billionth of a meter).
    • Quantum Effects – At the nano scale, materials exhibit quantum mechanical properties, such as increased strength, electrical, and thermal conductivity.
    • Self-Assembly – Molecules spontaneously organize themselves into desired structures, a key feature for fabricating nanomaterials.
    • Surface Area to Volume Ratio – At the nanoscale, materials have a larger surface area relative to their volume, which enhances their reactivity and properties.
  • Types of Nanomaterials
    • Carbon-Based: Fullerenes, carbon nanotubes (CNTs), and graphene.
    • Carbon Nanotubes (CNTs) – Cylindrical nanostructures made from carbon atoms, known for their strength and conductivity.
    • Quantum Dots – Nanoscale semiconductor particles with unique optical and electronic properties.
    • Metal-Based: Gold and silver nanoparticles (used in medicine and electronics).
    • Dendrimers: Branched nanoparticles for drug delivery.
    • Composites: Combination of nanomaterials for enhanced properties.
    • Graphene – A one-atom-thick layer of carbon atoms, known for its strength, electrical conductivity, and flexibility.

Biotechnology

  • What is Biotechnology?
    • Biotechnology is the use of biological organisms or systems to develop or create products for specific uses, particularly in fields like medicine, agriculture, and industry.
    • It combines biology with technology to develop solutions that improve human life and the environment.
  • Types of Biotechnology
    • Red Biotechnology – Medical Biotechnology; applications in drug production, gene therapy, diagnostics (e.g., insulin production using bacteria).
    • Green Biotechnology – Agricultural Biotechnology; involves the use of genetically modified organisms (GMOs) for crop improvement (e.g., pest-resistant crops).
    • White Biotechnology – Industrial Biotechnology; the use of microorganisms to produce biofuels, biodegradable plastics, and other industrial products.
    • Blue Biotechnology – The application of biotechnology to marine and aquatic environments, such as in aquaculture or the production of marine bio-products.

Genetic Engineering

  • What is Genetic Engineering?
    • Genetic engineering is the direct manipulation of an organism’s DNA using biotechnology. It involves altering the genetic makeup of cells to produce desired traits.
    • It enables the transfer of specific genes between organisms, creating genetically modified organisms (GMOs).
    • Tools: Restriction enzymes, CRISPR-Cas9, plasmids, and vectors.
    • Process: Isolation of DNA → Cutting with restriction enzymes → Insertion into a vector → Transformation into a host organism.
  • Techniques in Genetic Engineering
    • Recombinant DNA Technology – Inserting a gene from one organism into the DNA of another.
    • CRISPR-Cas9 – A modern gene-editing tool that allows precise DNA editing.
    • Gene Cloning – Creating copies of specific genes for further study or use.
    • Polymerase Chain Reaction (PCR) – Amplifying small segments of DNA for analysis or modification.
    • Electroporation – Introducing foreign DNA into cells by applying an electric field.
    • Gene Therapy – Inserting, altering, or removing genes within a patient’s cells to treat diseases.
    • Gel Electrophoresis: Separates DNA fragments by size.
  • Key Terms to Remember
    • Plasmid: Small, circular DNA used in genetic engineering.
    • Vector: A vehicle (e.g., plasmid or virus) used to transfer genetic material.
    • Transgenic Organism: An organism with genes from another species.
    • Genome: The complete set of genes in an organism.

Applications of Biotechnology and Genetic Engineering

  • Medicine:
    • Insulin Production – Genetically engineered bacteria producing human insulin.
    • Gene Therapy – Treating genetic disorders by modifying the patient’s genes (e.g., CRISPR).
    • Vaccines – Development of recombinant vaccines (e.g., hepatitis B vaccine).
    • Antibiotics – Production of antibiotics and other medicines using engineered microorganisms.
  • Agriculture:
    • GM Crops – Crops modified for pest resistance (e.g., Bt cotton), drought tolerance, and enhanced nutrition.
    • Gene Editing in Crops – Editing plant genes to increase yields, improve nutritional value, or resistance to diseases.
    • Animal Cloning – Cloning livestock with desired traits, such as disease resistance or higher productivity.
  • Industry:
    • Biofuels – Using microorganisms to produce biofuels (e.g., ethanol, biodiesel).
    • Bioremediation – Using engineered microorganisms to clean up environmental pollutants.
    • Bioplastics – Developing biodegradable plastics using biological processes.

Synthetic Biology

  • What is Synthetic Biology?
    • Synthetic biology is an interdisciplinary field that combines biology, engineering, and computer science to design and construct new biological parts, devices, and systems or to redesign existing biological systems.
    • Involves creating artificial life forms or engineering organisms to perform specific tasks.
  • Key Concepts
    • Gene Synthesis – Creating new DNA sequences from scratch to design genes with desired functions.
    • Synthetic Organisms – Designing organisms with entirely synthetic or engineered genomes.
    • Biological Parts (Bio-bricks) – Standardized genetic components that can be combined to form new systems.
    • Metabolic Pathway Engineering – Modifying an organism’s pathways to produce useful compounds (e.g., biofuels, pharmaceuticals).
  • Methods in Synthetic Biology
    • DNA Assembly – Assembling DNA sequences in the lab using various techniques (e.g., Gibson Assembly, Golden Gate Assembly).
    • Gene Editing – Editing genes to add, delete, or modify biological functions (often using CRISPR technology).
    • Cellular Engineering – Modifying cells to create new biological functions or systems (e.g., bacteria engineered to produce drugs).
    • Synthetic Genomes – Creating entire genomes from scratch and transplanting them into cells to create synthetic life.

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) technology

  • What is CRISPR?
    • CRISPR technology is a revolutionary gene editing tool that allows precise modification of DNA within living organisms.
    • Often referred to as “genetic scissors”, it enables scientists to add, remove, or alter genetic material at specific locations in the genome.
    • It can be used to edit mitochondrial DNA (mtDNA) and can treat mitochondrial diseases.
    • CRISPR was originally discovered as part of the bacterial immune system to fight viruses.
    • First CRISPR-edited humans were born on November 25, 2018, sparking global ethical debates.
    • CRISPR has been used to create glow-in-the-dark plants and muscular dogs.
  • How CRISPR Works
    • Cas9 Protein – Acts as molecular scissors that cut DNA at a targeted location.
    • Guide RNA – A short RNA sequence that guides Cas9 to the specific location on the DNA strand.
    • After the cut, the cell’s natural repair mechanism is triggered, which can be harnessed to insert or delete specific genes.
    • DNA Repair: The cell repairs the cut, either by:
      • Non-Homologous End Joining (NHEJ): Introduces small insertions or deletions.
      • Homology-Directed Repair (HDR): Inserts a new DNA sequence.
  • Key Components
    • CRISPR Sequence – A part of the genome with repeating DNA sequences used to store information about viruses.
    • Cas9 Enzyme – The protein that performs the DNA cutting.
    • Guide RNA (gRNA) – The sequence that leads Cas9 to the correct DNA location.
    • PAM Sequence: Short DNA sequence required for Cas9 binding.
    • Knockout: Disrupting a gene to study its function.
    • Knockin: Inserting a new gene into a specific location.

Source: Internet, GOI Websites, PIB