eChapters

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.