Ebooks

BIOINFORMATICS IN AGRICULTURE: TOOLS AND APPLICATIONS

M. Balakrishnan
EISBN: 9789389907629 | Binding: Ebook | Pages: 294 | Language: English
Imprint: NIPA | DOI: 10.59317/9789389907629

135.58 USD 122.02 USD


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The book deals with various tools and applications of bioinformatics in the fields of: o agriculture, corals, structural bioinformatics, data-mining, text-mining; o medicinal plants, antibiotics, protein structure prediction, drug design; o gene expression, micro-arrays, proteomics, molecular phylogenic location of the Indian Liver Fluke, rough sets to predict protein structural class; o artificial neural networks for prediction of amino acids levels, plant systems biology, molecular modeling, homology modeling, bio-efficacy of indigenous bacillus through in-silico approach; o fresh aquaculture and fisheries, pesticides and insecticides, databases and tools development in the relevant area. The book would be of much use to the person working in the field of agricultural biotechnology, bioinformatics, computer science and applied statistics. This can act as a book for M.Sc, M.Tech and Ph.D students of and the faculty of Bioinformatics/Biotechnologists.

0 Start Pages

Preface Agriculture is knowledge intensive and horticulture is more so, since Agricultural crops are generally high value, technology intensive crops. Bioinformatics offers the potential to help in the process of technology development as well as its delivery. Use of Bioinformatics tools in agriculture is recent in India. It is only just more than a decade that ICAR went in for development of Bioinformatics infrastructure and also appointed computer application personnel in its Institutes. Since then many initiatives in the field of Bioinformatics have been taken in the different Institutes and some of them are indeed laudable. However, for effective utilization of the hardware and human resources, there needs to be synergy between the subject specialists and Bioinformatics personnel. The subject specialist needs to know how to structure his knowledge so that Bioinformatics specialist can use it to develop decision support tools. The Bioinformatics specialist on the other hand needs to know what type of knowledge is available in different disciplines in agriculture and the type of information required by the different user groups so that decision support tools are designed appropriately to deliver the required information. In this respect we can learn from the experience of the developed countries where Bioinformatics initiatives met with limited success initially which led to the requirement of good decision support tools to be formulated. Therefore, we need to evaluate the Bioinformatics initiatives being undertaken in the different institutes in the light of the experience of developed countries and take corrective steps wherever needed.

 
1 Application of Bioinformatics in Agriculture
D. Velmurugan

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.

1 - 12 (12 Pages)
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2 Statistical Data Mining-Concepts, Tools and Techniques for Bioinformatics
Ravi R. Saxena, Ritu R. Saxena, Akash Solanki and M.L. Lakhera

Today, when the collection of biological data has been increasing at explosive rate, the processing of these data is needed. It would be extremely valuable if the specialists who know what the data mean were also able to imagine ways to collect, process and exploit these data. Biological and agricultural scientists should note that concepts from computer science, discrete mathematics and statistics are being used increasingly to study and describe biological systems. The specialists, who know the subjects of mathematics, statistics and computer programming, are needed for solving the computational problems in biology. Statistical data mining approaches seem ideally suited for bioinformatics, since it is data rich, but lacks a comprehensive theory of life organization at molecular level, or in the words of I.E. Alcamo “ Keeping up with the directions and application of DNA is a never ending job.” Starting with possible definitions of statistical data mining and bioinformatics, this chapter will give a general side view of both the fields on the statistical data mining part and its technologies and discuss how statistical data mining may be used in bioinformatics.

13 - 26 (14 Pages)
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3 Prediction of 3D –Structure of Proteins Using Artificial Neural Networks
K. Meena

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].

27 - 40 (14 Pages)
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4 A Genomic Approach to Study the Insect Mitochondrial Evolution by Non coding LSU and SSU rRNA
S. Gifta Lorraine, Christy Jancy Joy P., Arul Samraj D. and Priyakumari Joyce C.

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.

41 - 46 (6 Pages)
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5 Analysis of Microarray Gene Expression Data
M. Balakrishnan, R.C. Srivastava and M. Ramachandran

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.

47 - 58 (12 Pages)
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6 A Novel Sequence Encoding Method for Searching Rareness Among Consensus DNA Sequences
K. Meena, K. Menaka, T.V. Sundar and K. R. Subramanian

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.

59 - 64 (6 Pages)
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7 Statistical Methods for Genomic Sequence and Microarray Analysis
A.K. Roy and S.R. Martha

ANALYSIS OF CODON USAGE VARIATION Multivariate analysis methods such as Correspondence Analysis and Principle Component Analysis have often been used to identify major trends of variation in synonymous codon usage among inter or intra specific genes. Genetic codes are degenerate meaning most of amino acids can be encoded by more than one codon (triplet of nucleotides); such codons are synonymous and usually differ by one nucleotide in the third position. The alternative synonymous codons are not used with similar frequency and their usage varies among different genes. Hence there is the presence of Relative Synonymous Codon Usage values.  SEQUENCE DATA The gene sequences downloaded from Genbank of National Center for Biotechnology Information that is the nucleotide sequence repository known worldwide, serves as the secondary data used for analysis. Relative synonymous codon usage value of each gene is extracted separately using the Codon Usage software of Sequence Manipulation Suite. These are the raw data which needs to be normalized to be used before application of various multivariate analysis.

65 - 78 (14 Pages)
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8 Significance of Insect Genomics in Agro Ecosystems
R.W. Alexander Jesudasan

A genome is an organism’s complete genetic signature and the collection of information that an organism can pass on to its offspring. Genomics, the study of the structure, function, and evolution of entire genomes is principally dealing with genetic information which helps us to understand how organisms and ecosystems work, how theymalfunction, or how they might be melded to human needs. The model organisms used in genomics have, in general, small genomes and short generation times. To meaningfully analyze the gene-to-phenotype relationships, a large amount of sequencing information is necessary. Progress in DNA sequencing technologies leads to accumulate Information about structures of genomes (Mohan Kumar, 2007). HISTORY OF INSECT GENOMICS Commencing from the publication of the entire nucleotide sequence of the genome of Haemophilus influenzae in 1995, a complete genome sequence of many organisms, including lower and higher eukaryotes, have been reported. The cost-effective way to get sufficient sequence information to address the questions is to sequence a high-quality reference genome and then map sequences from other genomes onto the reference sequence. Insects constitute the vast majority of known species with their importance including biodiversity, agricultural, and human health concerns. Hence, a study of Insect genomics is imperative to elucidate information to other organisms.

79 - 86 (8 Pages)
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9 Bioinformatics Tools in Fish Molecular Modeling
Grinson George, K.Sarma, S. Dam Roy and Mukunda Goswamy

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.

87 - 102 (16 Pages)
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10 Structural Bioinformatics Goals and Challenges
Mayank Pokhriyal and M. Balakrishnan

Bioinformatics can be defined as “the collection, archiving, organization and interpretation of biological data” (Orengo et al., 2003). By extension, structural bioinformatics deals with the collection, archiving, organization and interpretation of 3-D structural data of bio macromolecules. Structural bioinformatics emerged with the first crystal structures of haemoglobin and myoglobin. These structures were analyzed and contributed significantly to our understanding of the principles of life at a molecular level. A repository of all publicly accessible protein crystal structures, the Protein Data Bank (PDB) was established by Walter Hamilton et al., at Brookhaven National Laboratory in 1971. Until the late 1980s, structural biologists often knew all the available structures of bio macromolecules and much of the analysis, such as structure comparison and hydrogen-bonding analysis was done manually without much computer intervention. As the number of available structures increased, so did the need for software tools for structure analysis. Structural bioinformatics encompasses a wide variety of applications, including structure visualization, validation, classification, structure-based function prediction, identification of targets for structural genomics projects and prediction of the structures of individual bio macromolecules and complexes as well the binding modes of small molecules inside proteins of pharmaceutical or biotechnological interestStructural and theoretical analyses of proteins are central to the understanding of complex molecular mechanisms and are fundamental to the drug discovery process.

103 - 106 (4 Pages)
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11 Database for Animal Genetic Resources of A & N Islands
M. Balakrishnan, S. Jeyakumar, R.C. Srivastava, Mayank Pokhriyal and Soma Mondal

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

107 - 110 (4 Pages)
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12 A Database for Medicinal Plants used in Treatment of Asthma
K. Balaji, M. Rajadurai, G. Vidhya, A. Krithika, E. Hudson, Vidya Murali, M. Ramya, Anusha Bhaskar and V. Stanley

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.

111 - 114 (4 Pages)
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13 In-silico Determination of Potential Drug Target for Curing Meningococcal Disease- Bioinformatics Study On Penicillin- Binding Proteins
Vijay Tripathi, Dwijendra Gupta and Navita Srivastava

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.

115 - 120 (6 Pages)
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14 Text Mining: Potential Applications in Bioinformatics
M. Balakrishnan, R.C. Srivastava, S.K. Zamir Ahmed and Subhash Chand

A fundamental problem facing researchers today is how to make effective use of available wealth of online background domain knowledge to improve their understanding of complex biological system. Effective use of such online background domain knowledge plays a crucial role in all stages of integrated biological studies. In the past years, research in molecular biology and molecular medicine has accumulated enormous amounts of data. This includes genomic sequences gathered by the Human Genome Project, gene expression data from micro array experiments, protein identification and quantification data from proteomics experiments, and SNP data from high-throughput SNP arrays. However, the understanding of the biological processes underlying these data lags behind. There is a strong interest in employing methods of knowledge discovery and data mining to generate models of biological systems. Mining biological databases put forward challenges which knowledge discovery and data mining have to address in the future. Important background knowledge in bioinformatics is often contained in documents, such as scientific publications or database annotations. Analyzing data from biological databases often requires the consideration of data from multiple relations rather than from one single table. Recently, approaches (such as propositionalization algorithms) are being studied that utilize multi-relational data and yet meet the efficiency requirements of large-scale data mining problems.

121 - 124 (4 Pages)
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15 Diversity and Antibacterial Activity of Coral Associated Actinomycetes
P. Nithyanand, S. Manju and S. Karutha Pandian

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.

125 - 130 (6 Pages)
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16 Decision Tree and its Application in Bioinformatics
Rajni Jain and Amarendra Kumar Mishra

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.

131 - 142 (12 Pages)
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17 Database for Algae Resources in Andaman and Nicobar Islands
M. Balakrishnan

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.

143 - 146 (4 Pages)
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18 Bioinformatics of Natural Antibiotics
S. Rajarajan, M. Yogambal, K. Sangeetha

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.

147 - 164 (18 Pages)
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19 PhytopathoSys v1.0 – A Phytopathology Information System
M. Balakrishnan, R.C. Srivastava, Michael Imanual Jesse and M. Ramachandran

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.

165 - 170 (6 Pages)
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20 Multiple Gene Expression Profiles of Chemically Induced Parkinson Disease: Implication in Neuroprotection Mechanism Offered by Nicotine and Caffeine
Kavita Singh, M.P. Singh and M. Balakrishnan

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.

171 - 186 (16 Pages)
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21 Development of Databases on Freshwater Aquaculture
A.K. Roy and Nibedita Jena

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).

187 - 198 (12 Pages)
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22 Proteomics and Bioinformatics
A. Subash Chandira Bose, R. Venkateshwaran and M. Balakrishnan

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.

199 - 204 (6 Pages)
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23 Data Mining and its Applications in Bioinformatics
Soma Mondal and M. Balakrishnan

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.

205 - 208 (4 Pages)
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24 Molecular Phylogenic Location of the Indian Liver Fluke, Fasciola (Trematoda: Fasciolidae) Based on The Ribosomal Internal Transcribed Spacer Regions
P. K. Prasad, V. Tandon, D.K. Biswal, L.M. Goswami and A. Chatterjee

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 

209 - 218 (10 Pages)
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25 Prediction of Amino Acid Levels in Protein Sequences Using Artificial Neural Networks
K. Meena and M. Manimekalai

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.

219 - 226 (8 Pages)
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26 Applying New Data Mining Method of Rough Sets to Predict Protein Structural Class
K. Meena and M. Durairaj

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.

227 - 238 (12 Pages)
USD34.99
 
27 Plant Systems Biology
G. Ramesh Kumar, CP Rajadurai and M. Ramachandran

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.

239 - 252 (14 Pages)
USD34.99
 
28 Bio-efficacy of Indigenous Bacillus thuringiensis LDC-9 Against Insect Pest and its Characterization through In-silico Approach
R. Shenbagarathai and A. Mahalakshmi

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). 

253 - 272 (20 Pages)
USD34.99
 
29 Molluscan Resources and Its Management Measures in Andaman & Nicobar Islands
S.N. Sethi, M. Balakrishnan, S. Chand and B.Varghese

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.

273 - 278 (6 Pages)
USD34.99
 
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