eChapters

There are many types of intellectual property and its type varies from country to country. The most common types are patents, copyrights, trademarks, design and trade secrets. Intellectual property is an intangible creation of the human intellect and this intangible nature of intellectual property faces problems in comparison of traditional property like land or goods. Unlike traditional property, intellectual property is not dividable therefore a number of people can consume an intellectual good without its consumption. In addition, investments in intellectual goods suffer from appropriation problems, for instance Landowners can surround their land with a robust fence and hire armed guards to protect it, but creators of intellectual property cannot do that to stop their first buyer from replicating it and selling it at a lower price.

Biological Diversity Act, 2002 was passed by Indian government in pursuance of Convention on Biological Diversity, 1993 The Convention on Biological Diversity (CBD) is a legally binding multilateral environmental agreement that has 194 contracting Parties (Countries) as its members with three objectives mentioned below:

1. Conservation of biological diversity
2. Sustainable use of the diversity and
3. Ensuring fair and equitable sharing of benefits of such use.

The recent concept of intellectual property emerged in England in the 17^th & 18^th centuries. The term Intellectual Property came in use in the 19^th century and in the late 20^th century. As of now the Intellectual Property has occupied common position in the global legal systems. There are different forms of Intellectual property rights which include patents, copyright, industrial design, trademarks, plant variety rights, trade dress, geographical indications and in some jurisdictions trade secrets too

The ITPGRFA is a comprehensive international agreement which is poised at guaranteeing food security through the conservation, exchange and sustainable use of the world's plant genetic resources for food and agriculture, instead of fair and equitable benefit sharing arising from its use. It also advocates Farmers' Rights.

13.1. Genesis of the Treaty

The conservation and sustainable use of plant genetic resources for food and agriculture are keys to feed global growing population in the coming future. The Commission on Genetic Resources for Food and Agriculture was established in 1983, and the voluntary International Undertaking on Plant Genetic Resources was adopted here in. Another major step was taken in 1996 with the adoption of the Global Plan of Action at the Leipzig International Technical Conference on Plant Genetic Resources. 

15.1 Sample Objective Question

1. Which one is related to deposition of Micro-organism?
   1. Madrid Agreement
   2. Berne Convention
   3. Budapest Treaty
   4. Patent Cooperation Treaty.
2. WTO was officially commenced in the year...........
   1. 1970
   2. 2003
   3. 2005
   4. 1995
3. Which one is related to protection of Trademarks
   1. Madrid Agreement
   2. Berne Convention
   3. Budapest treaty
   4. None of these
4. One of the four patent office is...........
   1. Patna
   2. Banglore
   3. Varanasi
   4. Mumbai

The Patent Cooperation Treaty provides an overview of an International Treaty which is administered by the World Intellectual Property Organization. The Patent Cooperation Treaty is an international treaty with more than 157 Contracting States by 2022. India deposited its instrument of accession on 7 September 1998 to both international treaties of WIPO in Geneva i.e. Paris convention for the protection of Industrial Property and Patent Cooperation treaty. PCT provides a system for filing a patent application and allow us to obtain patents in multiple countries around the world on the basis of a single patent application.

This is an international convention governing the recognition of deposits in officially approved culture collections for the purpose of patent applications in any country that is a party to it. Because of the difficulties and on occasion of virtual impossibility of reproducing a microorganism from a description of it in a patent specification, it is essential to deposit a strain in a culture collection centre for testing and examination by others.

This was the year, 1974, the Director General of WIPO convened a committee of Experts to discuss the possibilities of international cooperation over the deposit of microorganisms for patent purposes

Among several respiratory diseases affecting man, bronchial asthma is the most common disabling syndrome, nearly 7 to 10 per cent of the world population suffer from bronchial asthma, which is a chronic illness involving the respiratory system in which the airway occasionally constricts, becomes inflamed, and is lined with excessive amounts of mucus, often in response to one or more triggers. These episodes may be triggered by such things as exposure to an environmental stimulant (or allergen), cold air, warm air, moist air, exercise or exertion, or emotional stress. In children, the most common triggers are viral illnesses such as those that cause the common cold. A variety of exogenous determinants of asthma were also been, some of which are air pollution, tobacco smoking, diet, occupation and respiratory infection, these pollutants may serve as inciters or triggers of asthmatic reaction in airways that are already hyper responsive, they may exert direct toxic influence on the respiratory epithelium or may augment or modify immune responses to inhaled antigens. During an asthma episode, inflamed airways react to environmental triggers such as smoke, dust, or pollen. The airways narrow and produce excess mucus, making it difficult to breathe. In essence, asthma is the result of an immune response in the bronchial airways. As according to the World Health Organization over 80% of the people in developing countries depend upon traditional medicine for their primary health care. Medicinal plants are considered as source of various alkaloids and other chemical substances essential for mankind.

Mitochondria are key energy generators in most eukaryotic cells. In recent years a number of mitochondrial genomes have been completely sequenced, contributing to the knowledge of molecular features related to function and evolution of this peculiar genome (Boore, 1999). The pathways of mitochondrial DNA evolution are obscured by their extraordinary size. Gene content, gene rearrangement and mode of expression are the characteristics of mitochondrial genomes. The mitochondrial genomes from eukaryotes reveal large size differences between animal, fungal and plant species. The average size of animal mtDNA is ~ 16 kb (Boore, 1999), whereas plant mtDNAs range from 200 to 2500 kb (Palmer, 1990). The size of fungal mtDNA’s range from 19 kb to 176 kb (Hudspeth, 1995).The mtDNA genome has a limited number of protein coding genes such as NADH ubiquinone oxidoreductase (ND2 to ND5), cytochrome c oxidase (COX), succinate dehydrogenease (SDH), ATP synthase (ATP6), cytochrome (CYTB), etc. Among non-coding genes only rRNA and tRNA genes are found.Ribosomal RNA (rRNA) is a component of the ribosomes, the protein synthetic factories in the cell. rRNA molecules are extremely abundant. They make up at least 80% of the RNA molecules found in a typical eukaryotic cell. Synthesis of the three nucleolar rRNA molecules is unusual as they are made on one primary transcript that is chopped up into three mature rRNA molecules.

In the context of molecular biology, a consensus sequence is the minimum nucleotide sequence that shows the characteristics common to most members of the family among a set of related genetic sequences.It serves in representing the results of a multiple sequence alignment, where related sequences are compared to each other, and similar functional sequence motifs are found. It also shows conserved/variable residues. It is found several times in the genome and is thought to play the same role in its different locations. For example, many transcription factors recognize particular consensus sequences in the promoters of the genes they regulate. In the same way restriction enzymes usually have palindromic consensus sequences, usually corresponding to the site where they cut the DNA. Transposons act in much the same manner in their identification of target sequences for transposition. Splice sites, i.e. those sequences immediately surrounding the exon-intron boundaries, can also be considered as consensus sequences. Defining a consensus DNA binding site by examining consensus sequences is a key work carried out by biologists (Harley et al., 1994). Rareness or anomaly detection followed by in depth analyses in such sequences may reveal significant information regarding the structural, functional and biochemical mechanisms of the genes which are of much importance to biologists.

Abstract
In-silico analysis of nucleic acids and proteins from fishes has enriched our understanding to several fundamental problems of classical fish biology and genetics. Mining of data which is analogous to information discovery is the process of automating knowledge discovery. Analysis of data in all possible manner and recognition of a pattern which has a scientific basis by an efficient algorithm is the fundamental principle of Bioinformatics. Ever increasing number of Bioinformatics tools as computational packages are now a days used in tandem to analyze sequence of a loci and to model a novel gene product. High efficiency algorithms with excellent homology searching functions have lead to this advancement. Cat fishes, a group of diverse bony fishes have been studied with respect to genetic analysis in several species and several peptides. Tracking of the evolutionary foot prints using genomic libraries and between expressed sequences has been generating much interest.

Introduction

Spatial planning tools brings together multiple users of the earth to make informed and coordinated decisions about how to use of resources  and helps to organize, analyze and present information from a number of different sources.  Thus, viewing from single interest or multiple use viewpoints is enhanced and can make a very important contribution to environment. Use of Remote Sensing (RS) and Geographical Information Systems (GIS) tools has the capacity to bring together experts from a variety of disciplines to address complex spatial problems.

Introduction
Science and its development have had a great impact on the biological research. The main problem arises to understand and interpret the data which are the results of the higher dimensional research in the above mentioned field, and it is extremely difficult some times to give answers for complex and tedious biological questions generated through the large datasets. Parallel developments of statistical methods provide relaxation over these issues. The statistical method by bioinformatics presents many new and logical problems for researchers, scientists, and scholars related to these communities. Thus the knowledge of statistical concepts and techniques are prime important in this chain. The effort is made to cover stochastic theory, finite Markov chains in learning models to diffusion processes in population genetics, advanced statistical methods with Hidden Markov model and provide some literature on Bayesian computation like MCMC and their resources. Fortunately the applied aspect of probability theory and theory of stochastic processes seem to have been extensively used in the research and development level of biological field but the lacking of required material is a very problematic aspect in the system with proper and systematic ways.

Introduction

The proteome is often described as the set of all expressed proteins in a cell, tissue or organism. It is the systematic analysis of cellular proteins, that is, their identity, quantity and function. One advantage of proteomics over transcriptome is that mRNA represents an early stage of gene expression whereas the study at the proteome level describes the state of protein which is the final functional molecule of the cell. Thus, it gives a clear picture of the cell function that may not be concluded from mRNA study. In fact we can say that proteins are more than just information carriers so it gives more information with respect to only nucleic acid based studies.  Proteomics covers two-dimensional gel electrophoresis (2-DE), image analysis, mass spectrometry, amino acid sequencing, and bio-informatics to resolve comprehensively, to quantify, and to characterize proteins. Biomarker discovery as an important aspect of proteomics technology is highly appreciable when it comes to diseases. Today,  a better understanding of the disease mechanisms leading to discovery of new disease specific biomarkers are very much possible due to the sequencing of the human genome. It has accelerated the proteomic technologies for accepting the challenges so as to meet the diseased related investigations.

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.

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.

The analysis of chromosome behaviour at meiosis can provide valuable information about the genomic composition of both species and hybrids. The basis for this analysis is the idea that chromosomes that pair and undergo chiasma formation are homologous. Where two genomes are present, as in diploids, the expectation is that only bivalents will be observed and where there are multiple genomes, as in polyploids, two general patterns of pairing are possible. In autopolyploids, configurations of multiple chromosomes are to be expected since all the component genomes are homologous and have the possibility of pairing with each other, whereas in allopolyploids, with different genomes, bivalent formation is the expectation. Thus, meiotic analysis can provide an oversight for genome analysis to investigate genetic relationships between the species. Further, chromosomal rearrangements are correlated with pollen fertility in species and F₁ hybrids.  Observations on pollen formation, size and viability can provide useful information, as low pollen viability is often indicative of meiotic irregularities and large sized pollen can indicate the formation of unreduced gametes. In addition, the occurrence of nucleolar dominance has been recorded in many interspecific hybrids.

Computation has become an essential tool in life science research. This is exemplified in genomics, where first microarrays and now massively parallel DNA sequencing have enabled a variety of genome-wide functional assays that require increasingly complex analysis tools. The problem of accessibility of computational tools has long been recognized. Without programming or informatics expertise, scientists needing to use computational approaches are impeded by problems ranging from tool installation; to determining which parameter values to use; to efficiently combining multiple tools together in an analysis chain. The severity of these problems is evidenced by the numerous solutions to address them. Kowledge on software  and web-based interfaces for tools all improve the accessibility of computation. These approaches each have advantages, but do not offer a general solution that enables a computational tool to be easily included in an analysis chain and run by scientists without programming experience.However, making tools accessible does not necessarily address the crucial problem of reproducibility.

Two schemes of labeling are in common use today. One variant labels a single sample, either radioactively or fluorescently. Radioactive labeling is used, e.g., in conjunction with hybridization on nylon membranes (Lennon and Lehrach, 1991). The company Affymetrix synthesizes sets of short oligomers on a glass wafer and uses a single fluorescent label (Lipshutz et al., 1999). Alternatively, two samples are labeled with a green and a red fluorescent dye, respectively. The mixture of the two mRNA preparations is then hybridized simultaneously to a common array on a glass slide. This technology is usually referred to as the Stanford technology (David Duggan et al., 1999). Quantification utilizes a laser scanner that determines the intensities of each of the two labels over the entire array. Recently, companies like Agilent have immobilized long oligomers of 60 to 70 base pairs length and used two-color labeling.

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

Abstract

Accurate forecasting of the rice yields is very important for the organization to make a better planning and decision making. The aim of the study is to investigate the ability of neural network for yield prediction of rice in Andaman and Nicobar Islands. Field experiments were conducted at the various regions of Andaman and Nicobar Islands during 1980 to 2002 and data collected was subjected to Artificial Neural Networks (ANN) approach for developing a meaningful yield prediction for four varieties of rice C14-8, Quing Livan No.1, Taichung , Sen Yu, Jaya under island conditions with the objective to estimate the crop production a few days or months before harvesting of crop. The observations of all experiments viz., Varietal spectrum, Weather parameters , Yield components, Soil, Abiotic stressors, Biotic stressors for the period of twenty years from 1980 to 2002 were collected from the basic records of experimental field. All the data were used for training data set. Prediction of crop yield, mainly strategic plant of rice has been an interesting research area to agronomists since long for its importance in national and international economic programming. Application of ANN was found to be significant tool for prediction of yield in rice.

Bioinformatics is the application of information technology to the field of molecular biology. The term Bioinformatics was coined by Paulien Hogewag, in 1978 for the study of informatic processes in biotic systems. Bioinformatics nowadays, entails the creation and advancement of databases, algorithms, computational and statistical techniques, and theory to solve formal and practical problems arising from the management and analysis of biological data. Bioinformatics deals with storing and searching of large biological data sets and analysis of these data sets using computers to determine various relationships. 
The rapid developments in genomic and other molecular research technologies and developments in information technologies have been combined to produce tremendous amount of information related to molecular biologists. Now bioinformatics has developed and deals with many other types of biological data like protein structures, sequence alignment, gene finding, genome assembly, gene expression profiles, structure alignment, protein structure prediction, protein–protein interactions and the modelling of evolution. Being an interface between modern biology and informatics, it involves detection, expansion and implementation of computational algorithms and some of the software tools used to provide applications primarily in agriculture and healthcare divisions. In developing countries, bioinformatics play a major role in agricultural area where it can be used for increasing the nutritional content, and increasing the volume of the agricultural products etc.

Introduction 
Plant disease has been highly impacted by the development of new technology. The degree of the impact depends on how much the technology affects the component steps of the system. Many of the steps in plant disease diagnosis and management depend heavily on accurate and timely information and so can greatly benefit from the development of improved methods of accessing and disseminating information. Computers provide a wide range of tools which are extensively used in plant disease diagnosis and management. In fact, they will be a key to improve farm practices in the coming decades as it is scientifically pertinent to organize farm information in spatial databases because agricultural systems are inherently spatial. Biological and physical aspects of agricultural system create spatial heterogeneity, and as a result, patchiness is the rule in the occurrence and distribution of plant pathogens and disease (Campbell and Madden, 1990). In the area of plant diseases computers are useful

Biotechnology in the food processing sector targets the selection and improvement of microorganisms, including bacteria, yeasts and moulds with the objectives of improving process control, yields and efficiency as well as the quality, safety and consistency of bioprocessed products. They perform a series of processes such as fermentation, hydrolysis, etc. and even spoilage of food, depending upon the species of organisms, nature of raw material (food), environmental factors (temperature, pH, salt concentration, etc.), duration, etc.

Fermentation
Is the process of bioconversion of organic substances by microorganisms and/or enzymes (complex proteins) of microbial, plant or animal origin. It is one of the oldest forms of food preservation which is applied globally.

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.

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.

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).

Abstract

The protein classification prediction is an important Problem in molecular biology, and one that has attracted a lot of attention, because there is a gap between sequence and structure of proteins from various resources. The proteins can be usually classified into one of the four structural classes; they are all-a, all-b, a/b and a+b. To address the problem of protein classification, many different algorithms and efforts have been made so far. In this paper, a new rule based data mining method for the prediction of protein structural classes is constructed using Rough Sets algorithm. Rough Sets Theory (RST) is a new mathematical approach to study the realistic information (Z. Pawlak, 1982). It focuses on knowledge reasoning by the whole set directly approximating to the incomplete and uncertain information. There are studies on the knowledge reduction and features selection of mass data. To apply rough sets algorithm, a decision table is constructed using Amino acid compositions and eight physicochemical properties data as conditional attributes. The generated decision rules after reducing the decision system can be used to classify new objects.The classification results of Rough Sets is verified by using self-consistency and jackknife tests on the datasets constructed by G.P. Zhou and comparison is made with some of the previous works.

In recent years, a new branch of biological science, called as bio-informatics receives more attention among its users and calls for application of computational statistical algorithms to a greater extent and needs employment of more sophisticated mathematical/statistical tools. Though biological science and information technology forms a major part in bio-informatics research as applied to agriculture, statistical tools act as their backbone. Its utility is more felt starting from the stage of framing of hypothesis till analyzing/interpreting results of a scientific experiment.  It can also be viewed as a three way multi-disciplinary approach with biotechnology, information technology and statistical technology as its three faces, with the principles of statistics applied to biological science through an interface information technology.

Influenza a Pandemics

Natural Gene Flow in Plants

More than 70% of plant species, for example potato, oat, rape-seed, wheat, and kiwifruit have come from spontaneous interspecific or intergeneric hybridization although the extent of natural hybridization differs among the plant genera and families. It creates genetic variation and produce recombinant genotypes that may exhibit heterosis.The stabilization of these hybrids often through polyploidy (autopolyploidy or allopolyploidy) can result in the formation of new biological species (Masterson, 1994), thereby, having impact on both ecological and evolutionary processes (Martinsen et al., 2001). In addition, species genomes are often differentially permeable to introgression if they are under simple genetic control (unlike many genes contribute to hybrid fitness with linkages) and certain portion of the genome can readily incorporate alien alleles. Introgression is a selective process of gene flow that filters deleterious genes and takes only beneficial genes (incorporating the alleles from one taxon into other).

A gene microarray is a (mxn) matrix, containing n-experimental conditions, also called attributes for m-genes. Gene clustering refers to partitioning a microarray of genes based on the commonality of attributes. Genes belonging to a cluster often do not coexpress or coregulate. This calls for biclustering that segregates the (mxn) matrix into small windows. In other words biclustering refers to simultaneous clustering of rows and columns of the microarray. This chapter reviews some of the well known biclustering algorithms, and proposes an alternative solution to the problem using evolutionary multi-objective optimization technique.

Introduction

Clustering is process to automatically partition a set of p-dimensional data points (p³1) into classes, where the data in each class have similarity with respect to a given distance metric. Each class usually has an ideal member that possesses the necessary characteristics of the class.

INTRODUCTION

Insects are the major group of arthropods and the most diverse group of animals across the Earth. Though some of them are beneficial to environment and to humans, many insects are considered as pests as they transmit diseases and damage the crops and forests. Chemical, biological, cultural and mechanical methods are being used to eradicate, control or manage these pests. The main strategy used for controlling pests has been the use of chemical pesticides because of their long residual action and wide spectrum toxicity (Casida and Quistad, 1998). However, the indiscriminate usage of chemical pesticides are toxic to mammals, birds and fish, also pollute the environment, besides the development of pest resistance and the emergence of secondary recalcitrant insect pest populations (Li et al., 2007). These negative impacts prompted the change of strategies in managing the pests by resorting to ecofriendly and cost effective pest control strategies (Ferre et al., 1991). 

Introduction

Saffron is a naturally derived plant product from the dried stigma of the Crocus sativus flower  (Gresta et al., 2009).The saffron (Crocus sativus L.) is an Iridaceae family member, herbal perennial, sterile (2n=3x=24) geophyte, traditionally propagated by vegetative corms. Its cultivation dates back to late Bronze Age in the Mediterranean region (Negbi, 1999) in Anatolia since the ancient times (Arslan et al., 2007) and for at least 3500 years in Egypt and Middle East. Saffron contains more than 150 volatile and aroma yielding compounds. The chemical components mainly include carotenoids, crocin, picrocrocin, safranal etc (Abdullaev, 1993, Tarantalis et al., 1995, Karaoglu 
et al., 2007). Saffron is mostly used as spice, food colorant, dye or perfume. The dried stigmas introduce unique color, taste and fragrance and thus making it the world’s most expensive spice (Baghlian et al., 2010). Saffron has been used in folklore herbal medicines for centuries (Basker and Negbi, 1983).

Bioinformatics is a recently emerged frontier discipline, which helps in analyzing biological data with the help of information technology and statistical software packages. In a broader sense, bioinformatics is the application of computer technology in management of biological information. This interdisciplinary scientific tool having no barriers between different branches of science like biology, biotechnology, mathematics, computer science and information technology, has great influence on advanced bio-science research, particularly dealing with genes, proteins and cell biology.

Bioinformatics is the branch of study that deals with the use of information technology (IT) for managing data of biological science. Bioinformatics drew public attention with the announcement of the draft sequence of human genome by the then US President Bill Clinton along with Craig Venter and Francis Collins in 2000 (Uma and Sathyanathan, 2004).

Since the dawn of the Industrial Revolution, mankind has been introducing numerous hazardous compounds into the environment at an exponential rate.  Environmental pollutants have become a major global concern. The modern growth of industrialization, urbanization, modern agricultural development, energy generation, have resulted in indiscriminate exploitation of natural resources for fulfilling the human desires and need, which have contributed in disturbing the ecological balance on which the quality of our environment depends.
 
Technological revolution has brought new changes in products and processes in industry. The waste generated from the development of products and processes are of concern to the environmental list. A variety of pollutants such as heavy metals, xenobiotics, polycyclic aromatic hydrocarbons (PAHs), chlorinated and nitro-aromatic compounds are found to be highly toxic, mutagenic and carcinogenic for living organisms (Zhang and Bennett. 2005; Samanta et al., 2002).

Bioinformatics is a multidisciplinary approach that combines computational and biological expertise to analyze biological data to advance research and development and it drew public attention with the announcement of the draft sequence of human genome by the then US President, Bill Clinton along with Craig Venter and Francis Collins in 2000. Bioinformatics and life sciences research are gaining attention in the government, industries and academic sectors. India was the first country in the world to establish a biotechnology information system (BTIS) network in 1987 through the Dept. of Biotechnology and created an infrastructure that enables it to harness biotechnology through the application of bioinformatics. Through this branch of science, biological data are acquired, stored and then analyzed. Bioinformatics can be used to store huge bioscience data for their future uses. By exploring computational tools, databases and new strategies for pests and diseases, resistant genes can be identified and plants with desired traits can be engineered to enhance agricultural productivity. Bioinformatics can be utilized in two ways for agriculture, viz., (i) at molecular level for application in breeding strategies and (ii) agri-informatics for land use planning, farmers window, early warning system, impact assessment and environmental applications.

ANTIBIOTICS

Antibiotic is a drug used to treat infections caused by bacteria and other microorganisms. Technically an antibiotic is a substance produced by a microorganism that selectively inhibits the growth of another. Penicillin was the first antibiotic discovered by Alexander Fleming in 1928, a significant breakthrough for medical science. Antibiotics had saved thousands of wounded soldiers in the I and II world wars. Also, use of it made surgery safer and increased the average life expectancy of human beings. Antibiotics are among the most frequently prescribed medications in modern medicine. Some antibiotics are ‘bactericidal’, meaning that they work by killing bacteria. Each type of antibiotic affects different bacteria in a different way. Some antibiotics can be used to treat a wide range of infections and are known as ‘broad-spectrum’ antibiotics. Others are only effective against a few types of bacteria and are called ‘narrow-spectrum’ antibiotics.

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.

Bioinformatics can be defined as the application of computer technology for the management and analysis of biological data using computer to gather, store, analyze and merge the biological data. It consists of the organization of many kinds of large-scale biological data, particularly that based on DNA and protein sequence, into web-accessible databases and the methods required analyzing these data. Bioinformatics is a fast growing field within the biological sciences that was developed because of the need to handle large amounts of genetic and biochemical data. The goal of bioinformatics is to uncover the wealth of biological information hidden in the mass of data and to obtain a clearer insight into the fundamental biology of organism. This knowledge can have profound impact on various fields such as human health, agriculture, environment, energy and biotechnology. Bioinformatics involves use of various biological databases, which are archives of consistent data that are stored in a uniform and efficient manner. Biological databases are large collections of data that are relatively different to maintain outside the centers and institutions that produce them. These data are traditionally accessed and analysed using browser-based World Wide Web (www) interfaces. There are two types of databases i.e. Primary database and Secondary database. Primary databases contain information and annotations of DNA and Protein sequences, DNA and Protein structure and DNA and Protein expression profiles catalogued for the end users.

Biotechnology provides significant opportunities and greater effects in horticulture, where even minor changes such as quality, colour, aroma, flavour, structure, disease-pest resistance and postharvest behaviour bring tremendous achievements commercially. Tissue culture, genetic engineering, molecular breeding, biofertilizers, biopesticides and postharvest biotechnology are important aspects of biotechnology in horticulture such as fruit, vegetable, ornamental, spice, medicinal, aromatic and plantation crops.

Tissue Culture

Tissue culture is the true reality of the plant biotechnology. The annual demand of tissue cultured production constitutes nearly 10 per cent of the total world biotech business, amounting to 15 billion US dollars. The global production of tissue culture industry is expanding @ 15% per annum (Chadha, 2000). In India, more than 130 tissue culture units are presently producing > 300 million plantlets per annum (Choudhury and Tejaswini, 2000).

Chromosome number and nuclear DNA amount are important biodiversity characters together provide a very powerful method for determining evolutionary relationships. Furthermore provide an estimate of relatedness between species that in turn suggest reasons underlying the success or failure of crosses, even for interploidy hybridization. It is expected that species that are cytogenetically most similar will be easiest to hybridize and produce viable interspecific offspring (Thomas, 1993). Hence, it is important to study karyotypes and other characters of the genome of the species involved in a breeding programme.

According to Jackson (1971) and Stebbins (1950) the karyotype is the phenotypic appearance of the somatic chromosomes in contrast to their genic content.

Abstract
Proteins are comprised of domains, folds and motifs, which form its basic building blocks. Most efforts to understand protein evolution and its function have focused on domains as these can fold into a stable three-dimensional structure independent of the rest of the protein chain and generally perform a unique function conserved over the evolution. Genetic recombinant techniques allow reorganization of domains, called domain shuffling, resulting in different combinations of domains in different proteins. This along with swapping and insertion of domains results in complex architectures and are responsible for new protein functions in evolution. Protein domains are very useful in analyzing the mechanisms of protein folding and their stability and structural transformations in various conditions. This can be done reliably if a multi-domain target is considered only in terms of its constituent domains. The underlying goal is to reduce a complex protein structure to a set of simpler yet structurally meaningful units, each of which can be analyzed independently.

Introduction

Natural evolution gifted the biological world a treasure of diverse bio-molecules that take part in various cellular activities. Proteins, one of the vital molecules of biological function are wisely folded polymers comprising 20 different aminoacids. Function of each protein is encoded in its aminoacid sequence. Aminoacid residues can indulge in bonded or non-bonded interactions depending on the environment. These inter residue interactions with in a polypeptide drive its folding in to a compact conformation from a linear molecule. Biochemical properties as well as the linear arrangement of the aminoacids determines the three dimensional structure of a protein. These determinants of defined structure directly or indirectly dictates functional fate of the folded protein also.

Abstract

Biological Pathways represent system level sophistication of organisms. An exclusive peek into the extent of sophistication of an organism may provide proof of its past evolutionary struggle and position in the developmental trend from pathway point of view. This knowledge may not align with the traditional universally acknowledged standard 16s rRNA trend. Analyzing the reasons behind such discrepancy can constitute an important research work. To map sophistication of one organism with respect to other organisms, phylogeny is required. Here, we are mapping the level of sophistication in terms of enzymes among a set of TCA cycles belonging to different species, arbitrarily chosen from the KEGG/PATHWAY database. For this purpose, we converted the metabolic pathway information into simplified enzyme-enzyme relational (E-E-R) graphs. Similarity scores obtained from inter-genus, intra-genus as well as inter-species comparison of these graphs are used for phylogenetic tree construction. These phylogenetic trees throw light on the trend of development of metabolic pathways among different species. But peculiarly, these trees have less similarity with the conventional evolutionary phylogenetic trees constructed from NCBI taxonomy data. In this paper, we have tried to find some justifications for this dissimilarity among phylogenetic trees, by considering their habitats.

Abstract
Combined advancement in computer sciences and hardware with uniformly significant developments in molecular biology and chemistry are providing toxicology with a powerful new tool box. This tool box of computational models promises to increase the efficiency and the effectiveness by which the hazards and risks of environmental chemicals are determined. Computational toxicology focuses on applying these tools across many scales, including vastly increasing the numbers of chemicals and the types of biological interactions that can be evaluated. Apart from that, knowledge of toxicity pathways gathered within the tool box will be directly applicable to the study of the biological responses across a range of dose levels, including those more likely to be representative of exposures to the human population.  Although inappropriate pharmacokinetic properties are a major cause of abrasion in the safety issues are recognized as today’s single largest cause of drug candidate failure. It is expected that the right balance of in vivo, in vitro and computational toxicology predictions applied as early as possible in the discovery process will help to reduce the number of safety issues.

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).

Modern research on life science is progressing at the nanoscale not only with the objective to reduce time and cost but also to ease the handling and working conditions. Application of nanotechnology in various domains of science has led to the enormous innovations. This field facilitates better understanding as well as treatment of living system, activate biotechnological processes, synthesizing new drugs for targeted delivery and biocompatible materials for sustainable environment. Throughout the world nano science is getting wide propaganda. Its application to medicine is increasing rapidly in order to develop nano-drugs with prolonged availability and efficient delivery through rearrangement of molecules at the nanoscale using molecular interactions for example van der Waals forces, H bonds, electrostatic dipoles and various surface forces.

Introduction

The branch of science that deals with resolving the evolutionary relationships among organisms is phylogenetics. Phylogeny is the description of biological relationships, usually expressed as a tree. A statement of phylogeny among objects assumes homology and depends on classification. Phylogeny states a topology of the relationships based on classification according to similarity of one or more sets of characters, or on a model of evolutionary processes. In many cases, phylogenetic relationships based on different characters are consistent, and support one another. If different characters induce inconsistent phylogenetic relationships, they all are dubious. Conversely, note that the same similarity data may be consistent with different possible topologies or trees.
 
Molecular approaches to phylogeny developed against a background of traditional taxonomy, based on a variety of morphological characters, embryology, and from fossils, information about the geological context (stratigraphy).