eChapters

Abstract

Real-time PCR, also known as qPCR, is a highly sensitive technique used to determine the real-time amplification of a target DNA sequence. However, the presence of secondary structures or spurious amplicons can distort the results. When using SYBR Green chemistry, the features of qPCR primers differ from those of standard endpoint PCR primers. As a result, designing primers for SYBR Green qPCR requires extra caution and attention. This chapter outlines the essential features and conditions for designing qPCR primers, including primer length, melting temperature, GC content, specificity, and avoiding primer-dimer formation.

Abstract

FASTA, which stands for “Fast All”, is a sequence alignment tool developed by William R. Pearson and David J. Lipman in 1985. It is commonly used to identify similarities between DNA and protein sequences. FASTA employs a “hashing” strategy to locate matches for short stretches of identical residues with a length of k, referred to as k-tuples or k-tups. This method enables FASTA to quickly search large databases for sequence similarities, making it a popular tool for identifying homologous sequences, predicting gene functions, and analyzing evolutionary relationships. This chapter elaborates some basics of FASTA.

Abstract

Molecular modeling is a computational technique used to simulate the three-dimensional interactions between atoms and molecules. It allows for the visualization, manipulation, and prediction of molecular structures and chemical reactions. In this chapter, we discuss the different types of molecular models used in computational chemistry, including ball-and-stick models, space-filling models, wireframe models, and ribbon models. Ball- and-stick models depict atoms as spheres and bonds as sticks. Molecular modeling has numerous applications in drug discovery, materials science, and other fields of research, making it a valuable tool for computational chemists and molecular biologists. Here, this chapter focuses on different types of molecular models.

Abstract

Synthetic biology is a multidisciplinary field of study that seeks to understand living systems and organisms, and utilizes engineering principles to design and create new biological components, devices, and systems, as well as modify existing natural systems. This chapter provides an introduction to synthetic biology and describes the procedures and methodologies involved in the design and construction of novel biological systems. The applications of synthetic biology are vast and include the development of biosensors, gene circuits, metabolic pathways, and genetically modified organisms for use in a variety of industries, including healthcare, agriculture, energy, and environmental remediation.

Appendix A: Diagrammatic Presentation of Processes Involved in Obtaining an Indian Patent

19.1 Python Turtle Graphics

Turtle is a special feathers of Python. Using Turtle, we can easily draw in a drawing board.

First we import the turtle module. Then create a window, next we create turtle object and using turtle method we can draw in the drawing board.

19.2 Some Turtle Method

Example

from turtle import *

t = Turtle() #object in python

wn=Screen()

wn.title(?my first graphic”)

wn.bgcolor(?yellow”) #color filling in window

t.shape(?turtle”) #turtle shape given

t.color(?red”, “green”)

Project Formulation and Finance
Project Formulation and Finance involves two key aspects of project
management: developing the project’s structure and ensuring it has the necessary financial resources. Here’s a closer look at each part:
1. Project Formulation: This is the initial phase where you define the project, including its scope, objectives, and outcomes. It involves identifying stakeholders, setting goals, and determining the resources required. Effective project formulation ensures that the project is feasible, aligns with organizational strategy, and addresses the stakeholders’ needs.
2. Project Finance: This aspect focuses on securing the financial resources needed to execute the project. It includes planning the budget, analyzing investment requirements, and managing financial risks. Financing strategies might involve obtaining funds through loans, equity, grants, or other financial instruments. This phase also covers the assessment of financial viability and the preparation of financial forecasts to ensure that the project is economically sustainable.

Pie charts are useful to compare different parts of a whole amount. They are often used to present financial information. E.g. A farmer’s expenditure on farm can be shown to be the sum of its parts including different expense cate- gories such as cultivation, irrigation, sowing, harvesting, and general running costs (i.e. rent, electricity, fuel etc).

A pie chart is a circular chart in which the circle is divided into sectors. Each sector visually represents an item in a data set to match the amount of the item as a percentage or fraction of the total data set.

STANDARD NORMAL DISTRIBUTION

If μ = 0 and σ = 1, the distribution is called the standard normal distribution or the unit normal distribution, and a random variable with that distribution is a standard normal deviate. The approximate test is given by

Abstract

Bioinformatics is an important interdisciplinary field that brings together several areas of science, including molecular biology, biostatistics, and computer science (vis-a-vis information technology). With the rapid increase in the sequencing of DNA/RNA/protein molecules, as well as the growing understanding of the interconnections between different areas of biological science, the importance of bioinformatics is only increasing. This chapter seems to provide a thorough introduction to the definition, concept, and importance of bioinformatics. It also appears to highlight the relevance and potential scope of the subject for students interested in pursuing a career in the field. As bioinformatics continues to evolve and expand, it is likely to become an increasingly important area of research and development in the life sciences.

Abstract

This chapter provides a brief overview of the key milestones in the development of bioinformatics that would help to understand the historical context and evolution of a subject. As an interdisciplinary field, bioinformatics has grown gradually from molecular biology, with the development of various algorithms, databases, and other important tools that have helped to advance computational biology. Some important events in the history of bioinformatics might include the development of the first algorithms for sequence alignment and comparison, the creation of early databases such as GenBank and Swiss- Prot, and the development of software tools for molecular modeling and drug design. Other key milestones might include the sequencing of the first genomes, the development of high-throughput sequencing technologies, and the emergence of new areas of research such as systems biology and synthetic biology. By understanding the historical context of bioinformatics, students and researchers can gain a deeper appreciation for the current state of the field and the ongoing efforts to advance our understanding of the molecular mechanisms that underlie life.

Abstract

Biological databases that are composed of a large collection of digital nucleic acid sequences, protein sequences, or other polymer sequences stored on a computer, which is made available to the research community worldwide using web servers. The vast amount of information generated in molecular biology is analyzed, curated, tabulated, and arranged in databases. There are different types of biological databases, based on their contents. Besides, the database management system, a program to manage the databases, can be of two types: distributed DBMS and relational DBMS. This chapter briefly narrates the importance and purpose of biological databases.

Abstract

Molecular phylogeny is an important method for understanding the evolutionary relationships between different organisms. Molecular phylogeny is based on the idea that organisms that share a more recent common ancestor will have more similarities in their DNA or protein sequences. The chapter seems to cover the basic concepts and terminology used in molecular phylogeny, including the difference between rooted and unrooted trees, as well as various methods used for constructing phylogenetic trees. Further, chapter also covers some common tools and software used for analyzing molecular data and constructing phylogenetic trees. Overall, this chapter provides a useful introduction to molecular phylogeny and the methods used for understanding the evolutionary relationships between different organisms. Understanding these concepts is important for many areas of biological research, including evolutionary biology, ecology, and biotechnology.

Abstract

PCR primer design is a crucial skill for molecular biologists, as it enables the study of gene expression, gene amplification, and molecular markers. Primer3 is an online tool widely used for designing optimal PCR primers, which are pairs of short oligonucleotides that initiate DNA synthesis in vitro using a thermocycler. This tool uses a range of parameters to generate high- quality primers, including target sequence length, melting temperature, GC content, specificity, and product size. Understanding and effectively utilizing these parameters is essential for achieving accurate and reliable PCR results. In this chapter, the practical aspect of primer designing using the online tool Primer3 has been discussed. The parameters and the purpose of their usage have been given in a tabulated manner.

Abstract

The Basic Local Alignment Search Tool, or BLAST, is an online tool provided by the National Center for Biotechnology Information (NCBI) that allows users to search for matches between their query sequences and the sequences stored in NCBI databases. BLAST can be used to search for nucleotide sequences against nucleotide sequences, protein sequences against protein sequences, and protein sequences against translated nucleotide sequences in the databases. BLAST is widely used to study sequence similarity, identify target sequences, analyze the functional aspects of molecular sequences, and investigate evolutionary relationships. This chapter details on the BLAST and its applications.

Abstract

Proteins are complex molecules composed of one or more polypeptide chains made up of amino acid residues. These molecules perform a variety of essential functions in living organisms, including DNA replication, molecule transport, catalyzing metabolic processes, and providing structural support to cells. In this chapter, we explore the four levels of protein structure: primary, secondary, tertiary, and quaternary. Primary structure refers to the specific sequence of amino acids in a polypeptide chain, while secondary structure describes the folding of the chain into alpha-helices, beta-sheets, or other patterns. Tertiary structure is the three-dimensional shape of a single polypeptide chain, and quaternary structure refers to the interactions between multiple polypeptide chains to form a larger protein complex. Additionally, this chapter covers various methods used to predict protein structure, including homology modeling, ab initio prediction, and threading algorithms.

Abstract

When only sequence data is available, homology modeling has become a useful tool for predicting protein structure. Protein structure is often more important than sequence data when evaluating protein function. Homology modeling, also known as comparative modeling, is based on the principle that two sequences that exhibit a high degree of identity or similarity will also share similar structures. This chapter explores the steps involved in homology modeling, including template selection, alignment, model building, refinement, and validation. The Ramachandran plot is a valuable tool for assessing the conformation and bond angles in a protein model, and we discuss its significance in the context of homology modeling. Ultimately, homology modeling is an effective method for predicting protein structure and has numerous applications in protein engineering, drug discovery, and other fields.

Technology Scouting and Innovations in Technology Incubation
Technology scouting and innovations in technology incubation have a symbiotic relationship, fuelling each other for the benefit of budding startups and the broader technology ecosystem. Let’s dive deeper into their individual roles and how they interact:
Technology Scouting
Technology Scouting is the process of discovering, analyzing and evaluating new or existing technologies that will help them with their innovation process. In simple terms, it is a process for companies to find the necessary technology outside the company.
Hunting for promising technologies: Scouts actively search for emerging technologies, patents, research advancements, and market trends across various sectors.
Evaluating potential and fit: They assess the technical feasibility, market potential, and compatibility with the needs of incubators and their supported startups.
Connecting innovators and ventures: Scouts bridge the gap between technology creators (researchers, inventors, startups) and potential users (incubators, established companies).
Fuelling innovation pipelines: Technology scouting helps incubators access a wider range of technologies and ideas, enriching their portfolio and diversifying the innovations supported.

To understand IoT “Internet of Things” it is important to understand internet first. Internet is connecting a device to other device anywhere in the world. When two devices are connected with the Internet, they can send and receive all kinds of information such as text, graphics, voice, and video. The high-speed, fiber-optic cables are used, through which the bulk of the Internet data travels. The Internet has revolutionized the communication world. In today’s scenario the internet is an important part for people around the world. The Internet is a global network of billions of electronic devices. The World Wide Web (www) is most widely used part of the Internet.

The “Internet of Things is a potentially integrated part of the ‘Future Internet’. IoT can be defined as a dynamic global network with self - configuring capabilities based on communication protocols where physical and virtual ‘Things’ interact with each other.

The Internet of Things (IoT) is inter-connecting the networks of smart devices. Smart devices may be embedded with vehicles, buildings, or other electronics object with software, sensors, actuators, and network connectivity. Network connectivity enables smart devices to collect and exchange data. The Internet of Things (IoT), also referred to as the Internet of Everything (IoE) which comprises of the web-enabled devices. IoT has its applications in smart city, smart surveillance, automated transportation, smarter energy management systems, water distribution, urban security and environmental monitoring. Agriculture is another new area of IoT application.

Due to advancement in technology the processing power and storage capacity has been increased, in the recent years. At the same time technology is making the devices pervasive, wearable and mobile. Smart devices are fitted with sensors, actuators which enable devices to sense, compute and act intelligently. They are able to exchange information with environment.