eChapters

Biotechnology Products and Technologies
    
Bottlenecks in Fast Progress of Animal Biotechnology
    
Why Biotechnology should be Used in Animal Husbandry and Dairy Production
    
Contribution of Livestock Sector to Food Basket
    
Biotechnology and Environment
    
Biotechnology of Nutrient Partitioning
    
Genetic Programming for Better Animals
    
Biotechnology of Reproduction
    
Biotechnology of Animal Health

This statement signifies that the casualty of people is not due to the earthquake but due to the damage of buildings by earthquake forces. In developed countries, the casualty and loss of property is very minimal in comparison to the death toll and losses in India in the event of earthquakes of same magnitude. It has been experienced in the past that on the event of earthquakes of Richter magnitude scale of 6 or more, the death toll in India is in terms of thousands where as in Western Countries, it is multiple of tens. The less casualty is due to less damage of buildings and other infrastructures which in turn is due to the design and construction of Buildings and other structures as per the earthquake resistant theory. This paper discusses the issues related to the earthquake hazards in India and the concept of earthquake resistant structures.

Influenza a Pandemics

Drug designing is the approach of finding drugs by design based on their biological targets. The substance used for medical purpose, either alone or in mixture that changes the state or function of cells, organs or organism as a whole is known as a drug. So typically a drug target is a key molecule involved in particular metabolic or signaling pathway that is specific to disease condition or pathology, or to the infectivity or survival of a microbial pathogen. Drugs may be designed that bind to the active region and inhibit the key molecule that causes disease. However these drugs would also have to be designed in such a way that they should not affect any other important molecules similar to the key molecule. These can also be used to enhance the normal pathway of metabolism by promoting specific molecules that may have been suppressed in disease state.

In recent years, we have witnessed an explosion of biological information and the bioinformatics data arising from the rapid research and unprecedented progress in molecular biology. The novel genomic technologies have revolutionized the drug designing, discovery and development processes in government as well as private pharmaceutical industries through the use of these technologies. Various databases are doubling in size every year and fortunately we have the complete genome sequences of more than 100 organisms. At present, the pharmaceutical industries have clasped genomics as a source of drug targets. They also distinguish that the field of bioinformatics is crucial for validating these potential drug targets and for determining the ones that are most suitable for entering the drug development pipeline. Due to our increased understanding of molecular biology, there has been a change in the way that medicines are being developed. Once upon a time, new synthetic organic molecules were tested in animals or in whole organ preparations. Now this approach has been replaced with a molecular target in which in-vitro screening of compounds against purified, recombinant proteins or genetically modified cell lines is carried out with a high throughput as a consequence of better and ever improving knowledge of the molecular basis of disease.

The genetic code uses 64 codons to represent the 20 standard amino acids and the translation termination signal. Each codon is recognised by a subset of a cell’s transfer ribonucleotide acid molecules (tRNAs) and with the exception of a few codons that have been reassigned in some lineages (Osawa and Jukes 1989; Osawa et al., 1990) the genetic code is remarkably conserved, although it is still in a state of evolution (Osawa et al.,1992). The genetic code uses 64 codons to represent the 20 standard amino acids and the translation termination signal. Each codon is recognised by a subset of a cell’s transfer ribonucleotide acid molecules (tRNAs) and with the exception of a few codons that have been reassigned in some lineages (Osawa and Jukes 1989; Osawa et al., 1990) the genetic code is remarkably conserved, although it is still in a state of evolution (Osawa et al., 1992).

Insights into the three-dimensional (3D) structure of a protein are of great assistance when we plan experiments to understand protein function and in assistance of the drug design process.

Homology modeling
    
·    Homology modeling consists of the extrapolation of the structure for a new (target) sequence from the known 3D-structure (X-ray crystallographic or NMR) of related family members (templates).
    
·    Homology modeling is for those targets that have homologous proteins with known structure (>30% identity)
    
·    Homology modeling is for easy targets.
    
·    Homology modeling treats the template in an alignment as a sequence and only sequence homology is used for prediction.
    
·    When the sequence identity between the target and template sequence is low (<25%), homology modeling may not produce a significance result.

ANN is a Mathematical model or Computational model based on biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation. Neural Networks are non-linear statistical data modeling tools. That can be used to model complex relationships between inputs and outputs or to find patterns in data.

Objectives
    
·    Creation and use of large databases of Biological information to augment traditional laboratory based biology.
    
·    Analysis and interpretation of genomic and structural data using computational techniques from Mathematics, Statistics and Computer Science.
    
·    Explain the process and mechanism of evolution by comparing the Genomes of different species.
    
·    Development of new methods and technologies for understanding and diagnosis of genetic diseases and design of drugs for their treatment.

Motif

1.    A nucleotide/amino acid sequence pattern having biological significance.

2.    Occurs repeatedly, either in same molecule or in many molecules. Found in upstream intergenic region.

3.    Functionally important regions of genome (gene) can be recognized by searching such patterns.

4.    Used for locating binding sites, regulatory signals, to control gene expression.

5.    Identifying potential drug target sites.

Sequence Alignment

Sequence Alignment is the procedure of comparing two (Pair-wise Alignment) or more (Multiple Sequence Alignment) sequences by searching for a series of individual characters or character patterns that are in the same order in the sequences.

Significance: Discovering functional, structural and evolutionary information in biological sequences.

Biological sequences like the nucleotide and amino acid sequences can be analyzed by means of the sequence alignment. The objective behind this is to obtain knowledge regarding the similarity between the query and the target sequence to decipher the structure, function, homology of the query sequence.

Introduction

After the advent of Post Genomic era, Biological data is accumulating at an electrifying pace every day. Storage and analysis of these data serve as a major source for scientific research to understand the phenomena of origin, evolution and existence of various forms of life. The management of these data requires different statistical techniques used for retrieval, storage, analysis and extraction of precise information from small as well as large biological datasets. Application of statistical tools in Bioinformatics especially in fisheries data has been reported (Roy and Martha, 2008).

The advances in science and technology are deeply intertwined. Researchers can use the semiconductor manufacturing techniques that underlie miniaturization to build radios and exceptionally small mechanical structures that sense fields and forces in the physical world. These inexpensive, low-power communication devices can be deployed throughout a physical space, providing dense sensing close to physical phenomena, processing and communicating this information, and coordinating actions with other nodes. These multifunction devices are battery operated and are connected wirelessly with sensing, processing and communicating capabilities and are known as the wireless sensors. If we use these sensors with biological issues or Biotechnology, then we can find the new concepts biosensors. If we really implement these concepts in real life we can get rid of many diseases like heart attack, blood sugar level, gene reaction and other changes that happens in our body much before its shows to outside.

Nanotechnology is a field of applied science focused on the design, synthesis, characterization and application of materials and devices on the nanoscale. It is a sub classification of technology in colloidal science, biology, physics, chemistry and other scientific fields and involves the study of phenomena and manipulation of material at the nanoscale. This is involved in the creation of useful materials, devices, and systems used to manipulate matter at an incredibly small scale; between 1 and 100 nanometers. With nanotechnology, a large set of materials with distinct properties (optical, electrical, or magnetic) can be fabricated. Nanotechnologically improved products rely on a change in the physical properties when the feature sizes are shrunk.

The advancements in the field of informatics, biology and allied fields of technology led to the emergence of an inter-disciplinary field known as ‘Bioinformatics’. This field is an expanding and challenging tool for the collection, storage, organization, integration, analysis and simulation of biological data for utilization in biotechnology.

Collection of Data for Bioinformatics

An epoch making revolution in Genomics in recent years in deciphering plant, animal and microbial genome sequences, Proteomics, Statistics, Instrumental techniques, Structural and Computational Biology have given input to fragmented pieces-and-bits of information on biological materials. Each data is a discrete piece of important but defragmented information regarding a molecule (protein, RNA, DNA, sugars or lipids etc) or a reaction or at best a pathway, supposed to be occurring in a living system independently at a given time and space. However, as in a living system each molecule or a process exists in unison with other entities of its kind, these fragmented data are to be stored, organized, and then integrated and analysed to form an integrated part of a whole chain of events – now called a ‘SYSTEM’. Storage and organisation of data Explosion of knowledge in the field of biology and generation of new informations (data) needs well storage, organization and a faster distribution among the scientific workers. The advent of super computers, high speed computing and development of algorithms for data formatting, assists in the storage of data at the site of origin and distributed through the hyperlinks in world wide web (www).

Bioinformatics is a discipline that deals with computation of biological information. Bioinformatics is a newly emerging interdisciplinary research area spanning a range of specialties that include biology, biophysics, computer science, mathematics & statistics. It makes use of scientific and technological advances in the area of computer science, information technology and communication technology to solve complex problems in life sciences particularly problem in Biotechnology.

Explosive growth in biological data from large sequencing projects that are producing nucleotide sequences continuously at a faster rate and the content of the nucleotide database is doubling in every 14 months. The latest release of Gene bank (v.102) exceeded one billion base pairs. To cope with this huge volume of data, a new scientific discipline has emerged comprising bioinformatics, biocomputing & computational biology.

The focus of world’s trade and economic activities is increasingly being shifted from resource-based economics to knowledge-based economics. This paradigm shift has been triggered due to the implementation of Convention on Biodiversity (CBD) and other related international treaties and policy frameworks. CBD for the first time states that bio-resources are the sovereign property of the countries in which they are found. It further stipulates that access to bio-resources by outside parties can be made only after prior approved consent of the concerned stakeholders and also with mutually agreed terms and conditions for equitable sharing of benefits accrued from the commercialization of biodiversity. To realize such proclaimed rights given in CBD and to fulfill obligations of various other relevant treaties, particularly in the context WTO regulation, it is imperative that the bio-resources-rich nations like India have comprehensive knowledgebase of the biodiversity and associated information systems in accessible form.

The importance of Plant Pathology has been realized over the years owing to number of crop failures in different parts of the world. Plant disease control is indispensable for qualitative production and to compete in global agricultural trade. There is great need of sensitization of our research in various aspects which shall guide the generation to come for managing plant diseases not only for enhancing crop production but also in facilitating trade by conserving the biodiversity and environment.

Research Trend in Plant Pathology

Like in other sciences, there has been a change in the trend of research in Plant Pathology with passage of time. Up to the late 1960s most of the interest in plant pathology was concentrated in crop diseases mostly caused by fungi. Physiology of microorganisms and physiology of parasitism became increasingly popular fields of interest in 1960s.

The success of any crop improvement programme springs mainly from sound and genetically investigations carried out in the fields. However, the moment such biological populations are subjected to field evaluation, some external and non-heritable agencies come into active role. As a result, these agencies or factors mask real differences among the tested populations which stem purely from heritable or genetic factors. Their influence gets confounded with the latter. Consequently authentic data related to genetic differences are not available due to controllable and non-controllable errors. Further, physical data that are assembled in an experiment are often so voluminous and so vast that is perhaps humanly not possible to arrive at meaningful conclusions. Hence, an adequate knowledge of statistical principles and their appropriate use warrant perfection to a point where all possible sources of error can be well accounted for.