eChapters

For most of the past 50 years world food production has outpaced rising demand. World population has doubled since World War II, whereas food production has tripled. In the developing world the calories available per person per day increased from an average of 1,925 calories in 1961 to 2,540 in 1992. World food production has expanded due to the Green Revolution—adoption of crop rotation, the mass production and use of petroleum-based fertilizers and chemical pesticides, expanded irrigation, and the introduction of genetically superior, disease-resistant cultivars. The trend may now be changing for the worse, however. Since about 1990 global grain production has risen only slightly and, despite slower rates of population growth, grain supplies per capita have fallen. In the worst case, Africa now produces nearly 30% less food per person than it did in 1967. As per FAO estimates, world food production would have to double to provide food security for the 8 billion people projected for 2025. By 2050, when world population is projected to be over 9 billion, the situation would be even more challenging.

Data Mining is the process of automatic discovery of novel and understandable models and patterns from large amounts of data. Bioinformatics is the science of storing, analyzing and utilizing information from biological data such as sequences, molecules, gene expressions, and pathways. Development of novel data mining methods will play a fundamental role in understanding these rapidly expanding sources of biological data. Data mining techniques are an automated means of reducing the complexity of data in large bioinformatics databases and of discovering meaningful and useful patterns and relationships in data. Bioinformatics, the application of computational techniques to analyze the information associated with biomolecules on a large-scale, has now firmly established itself as a discipline in molecular biology, and encompasses a wide range of subject areas from structural biology, genomics to gene expression studies. It provides an introduction and overview of the current state of the field. The main principles that underpin bioinformatics analyses look at the Data Mining in Bioinformatics and databases that are commonly used, and finally examine some of the studies that are being conducted, particularly with reference to transcription regulatory systems.

Introduction
Recently, there is a great need to analyze and exploit the huge amount of biological data information generated through high throughput modern technologies like phenotyping, allelic variation, gene expression, chromatography, DArT, molecular marker etc. Principal component analysis (PCA) has stronghold on modern data analysis - A black box that is widely used but poorly understood. The goal of this article is to dispel the magic behind this black box and to focus on building a solid intuition for how and why principal component analysis works in huge numbers of high throughput biological data set. It is a versatile and easy-to-use multivariate mathematical statistical method (Jolliffe et al, 2003) developed to extract maximal information from large data matrices containing numerous columns and rows. It also makes possible the elucidation of the relationship between the columns and rows of any data matrix without being one of the dependent variable. So the PCA is a projection method representing the original data in smaller dimensions.

Data mining is becoming an increasingly important tool to transform the data into information. In recent years, data mining has been widely used in area of Bioinformatics for better understanding of gene expression, drug design, and other emerging problems in genomics and proteomics. Data mining is used to understand gene expression analysis, searching and understanding of protein mass spectroscopy data, 3D structural and functional analysis and mining of DNA and protein sequences for structural and functional motifs. For the first several hundred years of research in biology, the main bottleneck to scientific progress was data collection. Our new found data-richness, however, has shifted this bottleneck from collection to analysis. Biomedical literatures have been increased at the exponential rate. To find the useful and needed information from such a huge data set is a daunting task for users. Text mining is a powerful tool to solve this problem and it is used for biological knowledge discovery.

Algae refer to an assemblage of polyphyletic organism that conducts oxygen evolving photosynthesis other than land plants. They are distributed widely throughout India in the sea, in fresh water and in moist situations on land. Algae also form an important component of biodiversity of Andaman and Nicobar Group of Islands. Database for Algae resources of Andaman and Nicobar Islands are created with an aim of providing an information pool to the researchers working in fields related to fresh water and marine water algae in Andaman and Nicobar Group of Islands. About 313 fresh water algal species belonging to 15 families and 57 marine algal species belonging to 18 families has included in this database among which 40 species has been found to be first time reported in India. Algae have a wide application in a variety of Industries such as Food, Fodder, and Fertilizer etc. They are also important sources of Protein, Iodine, Vitamins, Minerals and Substances of Antibiotic Nature.

Biodiversity conservation and sustainable use has, for many people, become associated mainly with issues related to plants and wild animals. Although much less discussed, the loss of farm animal genetic resources may well be much more serious than in crops because the gene pool is smaller and very few wild relatives remain. The fact that 32% of livestock breeds worldwide are at risk of becoming extinct and that the rate of extinction continues to accelerate (FAO, 2000) is thus a serious cause for concern. Animals of different characteristics and hence outputs suit differing local community needs.

The union territory of A & N Islands constitutes the farthest and the remotest part of Indian union. The islands are situated in the Bay of Bengal surrounded by sea. The neighboring countries are Burma in north east and Singapore, Malaysia and Indonesia in south east. The Union territory of A & N Islands is situated between 60 and 140 north latitude and 920 and 940 east longitude forming a broken row of continuous islands from. North to South direction. They can be divided into two groups namely Andaman and Nicobar groups. The dreaded 100 channel which is about 145 Kms wide and 400 fathoms deep, separates the two groups

Introduction

The recent revolution in genomics and bioinformatics has caught the world by storm. The issues surrounding the human genome, including the analysis of genetic variation, access to genetic information and the privacy of the individual have fuelled public debate and extended way beyond the scientific and technical literature. During the past few years, bioinformatics, defined as the computational handling and processing of genetic information, has become one of the most highly visible fields of modern science. A flood of data means that many of the challenges in biology are now challenges in computing. Bioinformatics, the application of computational techniques to analyse the information associated with bio-molecules on a large-scale, has now firmly established itself as a discipline in molecular biology, and encompasses a wide range of subject areas from structural biology, genomics to gene expression studies. In this chapter we provide an introduction and overview of the current state of the field.

The role of bioinformatics in genomics and molecular biology research can be likened to the role of intelligence gathering in battlefield. Intelligence is clearly very important in leading to a victory in the battlefield. Computational algorithms are the heart of bioinformatics as they enable predictions, understanding and interpretation of the data generated from laboratory experimental research carried by biologist. This article discusses one such approach called Decision tree induction and its application for generating rules from a dataset extracted from biological databases.

Decision Tree (DT) is one of the most popular choices for learning from feature based examples. They are especially attractive in data mining environment for several reasons. First due to their intuitive representation, the resulting classification model is easy to assimilate by humans. Second, DT does not require any parameter setting from the user and thus are especially suited for exploratory knowledge discovery. Third DT can be constructed relatively fast and accuracy of DT is comparable or superior to other classification models.

Keeping pace with latest technologies Central Institute of Freshwater Aquaculture (CIFA) has attempted to develop the following three databases on the following aspects for quick retrieval of information resources. The brief description of the databases is presented below for easy comprehension.

CD-ROM Database on Socio-Economic Aspects of Carp Culture in Kolleru Lake (Pictorial)

In the era of 21st century world is progressing fast towards the electronic media of communication and the real revolution has been brought about in the information technology. It has revolutionized the collection, storage and retrieval of information very speedily and accurately. One of the IT tools like CD-ROM (Compact Disc Read Only Memory) plays an important role in storing the huge data and can be easily carried to remote places. Since it is lightweight, pocket sized and can hold about 660 megabytes of data which is equivalent to 3 lakh pages. CD-ROM is a high capacity optical disc. It is 12 cm diameter, made of durable plastic with a reflective metal coating and lacquered surface. Considering all these advantages an attempt has been made to develop a database on socio-economic aspects of carp culture in Kolleru Lake which is immensely helpful to all scientific and farming community (Roy et al., 2004).

A DNA microarray is a multiplex technology used in molecular biology. It consists of an arrayed series of thousands of microscopic spots of DNA oligonucleotides, called features, each containing picomoles (10-12 moles) of a specific DNA sequence, known as probes (or reporters).

The coral reef ecosystem is one of the most diverse ecosystems, which is housing for an amazing diversity of organisms and estimation of species richness ranges from 650 000 to over 9 million. For this reason, coral reefs often are referred to as the “rainforests of the ocean”1.Prokaryotes represent overriding life form on the planet and are almost certainly the most diverse component of coral reef communities2. Corals have been known to harbour many different species of bacteria.

The rise in the number of drug-resistant pathogens and the limited success of strategies in providing new agents indicate an uncertain forecast for future antimicrobial therapy. So it is critical that new groups of microbes from unexplored habitats be pursued as sources of novel antibiotics. Marine actinomycetes serve as a logical target given the historical significance of their terrestrial counterparts in antibiotic production. Isolation strategies directed towards new marine-derived actinomycetes have been lacking, but it is clear that such procedures will increase the understanding of marine bacterial diversity and yield many novel marine natural products. Though recent literatures report the isolation of novel class of actinomycetes from marine sediments and sponges, reports on actinomycetes associated with corals are very scanty. Therefore in this study we attempted to characterize the actiomycetes diversity associated with the coral Acropora digitifera from the Gulf of Mannar, Southern coast of India. The antibacterial potential of the isolated actinomycetes was also investigated.

Introduction
DNA barcoding is a molecular technique that uses a short section of DNA (genetic marker) extracted from a standardized region of tissue to identify it as belonging to a particular species. A desirable locus for DNA barcoding should be standardized and that should present in most of the taxa of interest and sequencable without species-specific PCR primers. A large database of sequences for the desirable locus needs to be developed. The desirable locus should be short enough to be easily sequenced with current technology, and provide a large variation between species yet a relatively small amount of variation within a species. Although several loci have been suggested, but the mitochondrial Cox1 became a gene of choice for animals and many other eukaryotes. However, the DNA regions that are being used are chosen to optimize the resolution for their specific experimental purposes.

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.

Epigenetics is the study of reversible heritable changes in gene function that occur without a change in the sequence of nuclear DNA and Gene-regulatory information that is not expressed in DNA sequences is transmitted from one generation (of cells or organisms) to the next. Epigenetics has become an integral part of the study of evolution and development during the past 50 years. It was originally defined by Conrad Hal Waddington in 1942 (Waddington, 1942), but it is currently referred to any mechanism that affects genes without changing the nucleotide sequence. These mechanisms are involved in deploying the genetic program for the many processes operating during the lifespan of a cell: development, differentiation, stress response, and pathological conditions, and by the environment to adapt to those situations (Rakyan and Beck, 2006). Epigenetic mechanisms include covalent chemical modification of DNA (methylation) and chromatin (covalent histone modifications), non-coding RNAs, and polycomb group (PcG) genes, and are ultimately related to the regulation of gene expression and chromatin structure.

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).

Significant advancement in high throughput technologies (microarrays, automated sequencing and mass spectrometry), transcriptomics, the global study of transcription, together with genomics and proteomics, has undoubtedly contributed to a systems biology approach. These technologies have generated vast amount of sequence data from plants, animals and microorganisms. Fortunately, efficient computational tools (intelligent data networks, query, retrieval, analysis and visualization tools) have now optimized data mining, accelerating the process of discovery. The analysis of sequence variation is of major importance in genetic studies. In this context, molecular markers represent one of the most powerful tools for the analysis of variations in the genome and the association of heritable traits with underlying genetic variation. The development of high-throughput methods for the detection of simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs) has led to a revolution in their use as molecular markers. The availability of large sequence data sets permits mining for these molecular markers, which may then be used for numerous applications such as genetic mapping, association mapping, evolutionary and phylogenic studies.

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.

Introduction

Functional genomics is a field of molecular biology that attempts to make use of the vast wealth of data produced by genomic projects (such as genome sequencing projects) to describe gene (and protein) functions and interactions. Unlike genomics and proteomics, functional genomics focuses on the dynamic aspects such as gene transcription, translation, and protein-protein interactions, as opposed to the static aspects of the genomic information such as DNA sequence or structures. Functional genomics includes function-related aspects of the genome itself such as mutation and polymorphism (such as SNP) analysis, as well as measurement of molecular activities. The latter comprise a number of “-omics” such as transcriptomics (gene expression), proteomics (protein expression), phosphoproteomics and metabolomics. Together these measurement modalities quantifies the various biological processes and powers the understanding of gene and protein functions and interactions. Functional genomics uses mostly high-throughput techniques to characterize the abundance gene products such as mRNA and proteins.

Gene silencing is the suppression of gene expression through nucleotide sequence-specific interactions that are mediated by RNA. Many manifestations of RNA silencing-RNA interference (RNAi) in animals, quelling in fungi and post-transcriptional gene silencing (PTGS) in plants, appear to be related. RNA silencing is experimentally activated by double-stranded RNA (ds RNA) and is used as a powerful technique for specific inhibition of gene expression in a variety of organisms. In a natural context, ds RNA may be produced from rearranged loci by transcription from converging promoters or by host-or viral-encoded RNA-dependent RNA polymerases (RdRP). A key component of RNA silencing is 21-23 nt RNA known as short interfering RNA (Si RNA). In Drosophila, the siRNA is derived from ds RNA by the action of an RNase-III like enzyme named DICER. The siRNA guides a multi-subunit endnuclease, referred to as the RNA-induced silencing complex (RISC) and it specifically degrades RNA that share sequence similarly with the ds RNA.

Introduction
Genetic research has been transformed by technological developments, and has by necessity become extremely quantitative, as massive quantities of varying complex data types can now be generated very rapidly. High-throughput data are being used in a variety of basic science investigations that have implications in the diagnosis and treatment of human disease: identification and characterization of genetic variants associated with a particular disease within and across populations; discovery of gene expression signatures associated with disease phenotypes; identification and testing of potential disease biomarkers. Methodological advances in the statistical treatment and interpretation of these data are needed in order to meet the pressing need for powerful, efficient and robust analysis.

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.

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.

Neisseria meningitidis, also simply known as meningococcus, is a gram-negative bacterium best known for its role in meningitis. It only infects humans; there is no animal reservoir. It is the only form of bacterial meningitis known to cause epidemics. The carbohydrate capsule of N. meningitidis determines its virulence and is targeted by the immune system. Approximately 12 strains of N. meningitidis exist and are characterized by the polysaccharide expressed on its capsule: A, B, C, 29-E, H, I, K, L, W-135, X, Y and Z. Inhibition of Pencillin Binding proteins (PBPs) leads to irregularities in cell wall structure such as elongation, lesions, loss of selective permeability and eventual cell death and lysis. 3-D structure of PBP was studied using Bioinformatics tool. Using Homology modelling, converted protein sequence of penicillin binding protein, extracted from NCBI server, in FASTA format and performed PDB-BLAST to search a desired template. Selection of template was based on lower E-value, bit score and identity. Using MSA with the help of CLUSTAL W software conserved region was found between the target and template sequence, 1K25. The 3-D structure of penicillin binding protein was found with the help of Modeller 9v2 and molecular dynamics was performed using GROMACS software. The docking was performed (Autodock 3.0 software) using 3 ligands viz. Cefuroxime, Chloramphenicol, Cefalotoxime with standard Bioinformatics tools.

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.

1.1    General Introduction, History, Ownership of Tangible and Intellectual Property
    
1.2    Patentable Subject Matter
    
1.3    Basic Requirements of Patentability
    
1.4    Novelty, Public Domain, Obviousness and Non Obviousness
    
1.5    Inventive Step (Non-Obviousness) and Industrial Application

3.1    Competitive and Collaborative Research
    
3.2    The Strategy to Protecting Plants : Plant Variety Protection Act
    
3.3    IPR Issues in Biotechnological Patents Haldi, Neem and Basmati Rice
    
3.4    Patent Litigation

Introduction
Machine learning is a branch of artificial intelligence which is concerned with the development of algorithms and techniques that allow computers to learn. These techniques are tolerant of imprecision, uncertainty, partial truth, and approximation. There have emerged many methods based on machine learning techniques, such as Artificial Neural Networks (NNs), Support Vector Machines (SVMs), Decision Tree (DT), Bayesian Networks (BNs), Hidden Markov Models (HMMs), etc. These techniques attempt to study, model, and analyze very complex phenomena  for which more conventional methods have not yielded low cost, analytic, and complete solutions.

Bioinformatics is the application of information technology to the area of molecular biology. The increase in the number and complexity of biological databases has raised the need for powerful data analysis tools and techniques. To fulfill these requirements, the machine learning discipline has become an everyday tool in bio-laboratories (Inza et al., 2010). Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in approximation.

The Madrid System for the International Registration of Marks is governed by two treaties. The first one is he Madrid Agreement, which was concluded in 1891 and revised at Brussels (1900), Washington (1911), The Hague (1925), London (1934), Nice (1957) and Stockholm (1967), and amended in 1979. The other one is the Protocol related to this agreement which was concluded in 1989. The aims of this protocol are to make the Madrid system more flexible and more compatible with the domestic legislation of certain countries or intergovernmental organizations that had not been able to accede to the Agreement. 

A microarray, as the name suggests, is a two dimensional array of microscopic probes which captures certain molecules in an environment by a process known as hybridization, and are used to detect quantities of these molecules in the environment. The probes can vary according to requirement of experiment, and so can the environment, which in technical terms is an extract of tissue under study.

Abstract
This chapter describes how modern quantum mechanical methods can be applied in a systematic manner to understand pharmacophore and mechanistic aspects of drugs. This chapter also explains why accurate computation of drug-receptor interactions is important for in silico drug designing and testing.

WHY in silico DESIGNING?
Drug designing is the inventive art of finding a new lead compound based on knowledge of its biological target and then its slow conversion to a compound of therapeutic benefit to patient termed as “drug”. This whole process comprises of long sequels of synthesizing compounds followed by their testing and activity evaluation procedures; often a seemingly endless task until desired potency level is achieved.

Evolution is a self-occurring natural phenomenon by which new organisms develop gradually as a result of change in genetic pool of a population. It is a very widely and historically studied phenomenon which still surprises scientists due to its underlying complexity. The three processes which contribute most to evolution are genetic drift (also known as random drift or allelic drift), natural selection and mutations. Genetic drift and natural selection act at a population level, whereas mutations act at individual level. For evolution to occur, the changes these processes bring about must be heritable, which they are.
 
Genes are present on chromosomes inside nucleus of the cell and the collection of all the genes in a cell is known as the genome of that cell. Genome size and complexity varies from species to species. Simple organisms, such as bacteria and protozoans have a very simple genome, with very few genes, whereas complex higher organisms such as humans have a large genome, with thousands of genes. The position of a gene on a chromosome is known as a locus. Organisms may have more than one copy of a chromosome in the cell.

Abstract

The species of liver flukes of the genus Fasciola (Platyhelminthes: Digenea: Fasciolidae)are obligate parasitic trematodes residing in the large biliary ducts of the herbivorous mammalian hosts causing fascioliasis worldwide. While Fasciola hepatica has a cosmopolitan distribution, the other major species, i.e., F. gigantica is reportedly prevalent in the tropical and subtropical regions of Africa and Asia. To determine the phylogenic location of Fasciola sp. of Assam (India) origin based on rDNA molecular data,ribosomal ITS regions were sequenced (Accession numbers- EF027103 and EF027104) and compared with other species of trematodes in the family Fasciolidae that includes, Fasciolopsis buski and Fascioloides magna besides the species of Fasciola. NCBI databases were used for sequence homology analysis using BLAST; multiple sequence alignments were performed using ClustalW program.The phylogenetic trees constructed based upon the ITS (I & II) sequences by multiple tree building methods in MEGA revealed a close relationship with isolates of F. gigantica from China, Indonesia , Japan, Egypt and Zambia, the isolate from China with significant bootstrap values being the closest. Using the novel approach of molecular morphometrics that is based on ITS2 secondary structure homologies, phylogenetic relationships 

Introduction

Since the onset of human civilization molluscs have a tremendous impact on Indian tradition and economy. In India, molluscs have been in great demand as ornaments, currency, as popular panacea for illnesses and as mascot for ward off evil spirits in olden days. Now, molluscs have assumedgreater significance in our industrial, technological and aesthetic aspects of life, in addition to edible utility. Several species of gastropods and bivalves are traditionally fished for food and shell from time immemorial. About 80,000 - 1, 00,000 species of molluscs are recorded from the world over and a total of 3271 species are recorded from India. They are represented in 220 families and 591 general and the spectrum comprise of 1900 gastropods,1100 bivalves,210 cephalopods,41 polyplacophores and 20 scaphopods (edible and ornamental) and 14 species of cephalopods are exploited on commercial basis in India(Appukkuttan et al.,1989). It is difficult to categories shells satisfactorily according to their uses as many are collected for several purposes. The main categories are shown in the Table-1.

ABSTRACT

Gene expression profiling holds tremendous promise for dissecting the regulatory mechanisms and transcriptional networks that underlie biological processes. Microarray expression analysis has become one of the most widely used functional genomics tools. Typical approaches to gene identification and functional characterization have and continue to involve protein characterization, peptide sequence determination, and identification of the corresponding DNA sequence. More recently, expressed sequence tags (ESTs), microarrays, large-scale gene expression (transcriptome) profiling, and associated informatics technologies are rapidly becoming commonplace in the sciences. These ‘genomic’ approaches typically take advantage of technologies for characterizing large numbers of nucleic acid sequences, bioinformatics, and the expanding collection of nucleic acid sequence data.

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.

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.

1.1. INTRODUCTION

In this chapter, we will know how to classify raw data. The purpose of classifying raw data is to bring order in them so that they can be statistically analysed easily. Classification of objects or things saves our valuable time and effort. It is done in a logical manner and similar things are arranged into a group or class.

6.1    Copyrights
    
6.2    Trademarks
    
6.3    Geographical Indications
    
6.4    Trade Secrets

Introduction
At the beginning of the 21^st century, with a population of 6.1 billion in 2000 and expected to be headed for 9.1 billion by 2050 (UN News Centre, 2005), the challenge of yet again increase food production by many folds only in 50 years has become a daunting task in itself. The situation is further worsen because now, we need to increase food production in sustainable way by 2050 on approximately the same area of arable land using less resources, particularly, fossil fuel, water and nitrogen, at a time when we must also mitigate some of the enormous challenges associated with climate change. Furthermore, there is the critical and urgent humanitarian need to alleviate poverty, hunger and malnutrition which is afflicting more than 1 billion people

4.1    Provisional and Complete Specifications
    
4.2    Publication
    
4.3    Request of Examination
    
4.4    PCT Application: Gateway to Foreign Patents

5.1    TRIPS
    
5.2    WTO
    
5.3    WIPO
    
5.4    Paris Convention
    
5.5    Berne Convention
    
5.6    Budapest Treaty
    
5.7    Madrid Agreement Marks (MAM)
    
5.8    The Patent Law Treaty (PLT)

2.1    Specification Drafting
    
2.2    Methods and Precautions in Drafting Patent Specification
    
2.3    Disclosure Requirements
    
2.4    Patent Claims
    
2.5    Filing of A Patent Application

Introduction

Microbes (bacteria, archea and eukarya) are single celled organisms that rule the planet. Microbes occupy every possible niche, from the high atmosphere to the deep ocean, from hot springs to artic ice, from hot deserts to deep forests including many regions that cannot yet be accessed for study. The biosphere contains between 1030 and 1031 microbial genomes, which is about 2-3 times more than the number of plant and animal cells combined (67). In fact, studies have shown that microbes associated with the human body are about ten times more than the number of human cells (5).  Microbes play a critical role in the life cycle of all living organism and environment in general.  Some microbes cause disease, but the most of them are either innocuous or play a role in physiology and cellular response including immune response, digestion and vitamin production of various organisms.

INTRODUCTION
 
Environment and ecological set up is maintained by the climatic conditions, presence and compositions of gases present in them, humidity level, temperature and the pollution. These conditions are responsible for the emerging of diseases in the environment. The diseases in plants, animals and human beings are due to the factors that affect the ecology. This also depends on the organism whether they are susceptible or resistant to the specific disease. This means the genetic level of the organism is an important factor.
Plant pathology or phytopathology is the study of diseases in plants. The disease evolution may be due to the climatic condition, humidity level, temperature and the genetic character of the plant and the pathogen. The parasitic adaptation of microorganisms to be plant pathogens includes acquisition of the following three abilities: 1) ability to enter into a plant, (2) ability to overcome the resistance of the host and (3) ability to evoke disease.

Abstract

DNA barcoding, an additional global standard taxonomic tool for identifying plant species helps the non-taxonomists also to identify the plant species in a more reliable way with the help of devices including nanotechnology. Researchers proposed various genes or gene portions as potential barcodes either singly or in combination, yet there is no standard/ universal barcode DNA region for plants. The more accurate plant DNA barcode region would have to be from highly variable markers in the nuclear genome preferably from multiple loci and in combination with variable DNA regions of chloroplast genome, to resolve the problems that arise due to hybridization, allopolyploidization and introgression. Nonetheless, the phylogenetically informative sites might not be the potential DNA barcode regions as the former requires synapomorphies unlike autapomorphies with high levels of informative characters in the latter DNA taxonomy, but could provide insights into genetic distances between species.

SYSTEMS BIOLOGY

The ultimate goal of any biological experiment is to understand biological systems in sufficient detail to enable accurate, quantitative predictions about the behavior of the systems, including predictions of the effects of modifications of the systems. To precisely simulate the behavior of the system using a computer model is one of the ways to achieve the above goal and in this venture we are nowhere close to the goal. Systems biology will help us to get closer to this goal and it is expected that biologists to adopt to take advantage of the power of systems biology approach. Systems biology is an emergent field that aims at system-level understanding of biological systems. Systems Biology is the study of the interactions between the components of biological systems, and how these interactions give rise to the function and behavior of that system. For example, theenzymes and metabolites in a metabolic pathway.With the progress of genome sequence projects and range of other molecular biology projects that accumulate in-depth knowledge of molecular nature of biological system, we are now at the stage to seriously look into possibility of system-level understanding of solidly grounded on molecular-level understanding.Unlike molecular biology which focus on molecules, such as sequence of nucleic acids and proteins, systems biology focus on systems that are composed of molecular components. Although systems are composed of matters, the essence of system lies in dynamics and it cannot be described merely by enumerating components of the system.

Introduction

India is an agriculture based country with 60% of the manpower employed in agriculture (World Bank, 2010). Few of the main environmental issues are soil erosion, water pollution from raw sewage and runoff of agricultural pesticides. There is a need to maintain a sustainable environment and a sustainable agricultural system.  Sustainable Agricultural system is a self sustaining system, is dependent up the ability to bring together and manage simultaneously the soil, water, plant and animal resources with the limitation of climatic and environment in such a way that the agricultural production/profitability can be maintained in the future too. So initiatives need to be taken to achieve a sustainable agricultural system. Tools have been developed to aid agriculturist, extension personnel and policy makers. The World Wide Web has made the tools easy accessible.

The development of bio-informatics started with the working of computers and accumulation of data on genes and proteins. There are 100,000 proteins in the human body or 1 million. In the last decade the number of protein sequences gathered in databases increased tremendously, but the key to understand the function of a protein is not its sequence but its structure. Experimental determination of 3 dimensional native folded structure of a protein usually can be done via crystallography techniques. But such experiments are time consuming. Currently there are hundreds of different fully automated approaches to protein 3D structure prediction.

All proteins are polymers of Amino acids. The polymers also known as polypeptides consist of a sequence of 20 different L-m-amino acids also referred to as residues. For chains under 40 residues the term peptide is frequently used instead of protein. To be able to perform their biological function, proteins fold into one that is driven by a number of non covalent interactions such as hydrogen bonding, ionic interaction, Vander Waal’s forces and hydrophobic packing. In order to understand the functions of proteins at a molecular level, it is often necessary to determine the three dimensional structure of proteins. The modern Information Technology techniques like Artificial Intelligence have opened new pathways to researchers. Once ANN has been trained it is capable of producing accurate output for the unknown inputs. Many researchers have tried to analyze the large sequence sized gene to determine the protein, predict the secondary structure of the protein and model its three dimensional (3D) view [11].

Abstract

A Mathematical Method for Artificial Neural Networks offers an original, broad and integrated approach that explains each tool in a manner that is independent of specific ANN systems. Artificial Neural Networks are abstract mathematical models of brain structure and functions. They are nothing but a mathematical model that relies on varying the strength of connections between the internal processing elements to interpret data. They can be applied to many pattern classification problems. In this paper, it has been used to predict the level of amino acid in protein sequences. Amino acids are the building blocks of proteins. It is any molecule that contains both amine and carboxylic acid functional groups. Here, known protein sequences of ingredients are taken as input patterns. The network is trained using back propagation algorithm with sigmoid function as activation function by generating random weights. It is tested again with unknown protein sequence. Error is calculated by the difference between actual network output and desired output. If the training is successful the patterns are correctly classified. The network is trained until the error is minimum. The amino acid level is thus predicted in a particular protein sequence.

The dream of having genomes completely sequenced is now a reality. The complete sequence of many genomes including the human one is known. However, the understanding of probably half a million human proteins encoded by less than 30’000 genes is still a long way away and the hard work to unravel the complexity of biological systems is yet to come. A new fundamental concept called proteome (PROTEin complement to a genOME) has recently emerged that should drastically help to unravel biochemical and physiological mechanisms of complex multivariate diseases at the functional molecular level. Proteomics involves the systematic study of proteins in order to provide a comprehensive view of the structure, function and regulation of biological systems. Coupled with advances in bioinformatics, this approach to comprehensively describing biological systems will undoubtedly have a major impact on our understanding of the phenotypes of both normal and diseased cells. Initially, proteomics focused on the generation of protein maps using two-dimensional polyacrylamide gel electrophoresis.