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Cell biology also called cytology is a branch of biology that studies the structure and function of the cell, the basic unit of life. Cell biology is concerned with the physiological properties, metabolic processes, signaling pathways, life cycle, chemical composition and interactions of the cell with their environment. This is done both on a microscopic and molecular level as it encompasses prokaryotic cells and eukaryotic cells. Knowing the components of cells and how cells work is fundamental to all biological sciences; it is also essential for research in bio-medical fields such as cancer, and other diseases. Research in cell biology is related to genetics, biochemistry, molecular biology, immunology, and developmental biology.
Agricultural Biotechnology, also known as agritech is an area of agricultural science involving the use of scientific tools and techniques, including genetic engineering, molecular markers, molecular diagnostics, vaccines, and tissue culture, to modify living organisms: plants, animals, and microorganisms. Crop biotechnology is one aspect of agricultural biotechnology which has been greatly developed upon in recent times. Desired traits are exported from a particular species of crop to an entirely different species. These transgene crops possess desirable characteristics in terms of flavor, color of flowers, growth rate, size of harvested products and resistance to diseases and pests. In traditional practices, pollen from one plant is placed on the female part of another which leads to a hybrid that contains genetic information from both parent plants.
Plant biotechnology may be defined as the application of knowledge obtained from study of the life sciences to create technological improvements in plant species. The roots of plant biotechnology can be traced back to the time when humans started collecting seeds from their favorite wild plants and began cultivating them in tended fields. It appears that when the plants were harvested, the seeds of the most desirable plants were retained and replanted in the next growing season. While these primitive agriculturists did not have extensive knowledge of the life sciences, they evidently did understand the basic principles of collecting and replanting the seeds of any naturally occurring variant plants with improved qualities, such as those with the largest fruits or the highest yield, in a process that we call artificial selection. This domestication and controlled improvement of plant species was the beginning of plant biotechnology. Today, genetically modified plants can contribute desirable genes from outside traditional breeding boundaries. Even genes from outside the plant kingdom can now be brought into plants. For instance, animal genes, human genes were transferred into plants a feat not replicated in nature
Environmental biotechnology is the branch of biotechnology that addresses environmental problems such as the removal of pollution, renewable energy generation or biomass production, by exploiting biological processes. The application of biotechnology to solve the environmental problems in the environment and in the ecosystems is called environmental biotechnology. Environmental Biotechnology helps to develop, efficiently use and regulate the biological systems and prevent the environment from pollution or from contamination of land, air and water. The major benefits of environmental biotechnology are it helps to keep our environment safe and clean for the use of the future generations. It helps the organisms and the engineers to find useful ways of getting adapted to the changes in the environment and keep the environment clean and green. It helps to avoid the use of hazardous pollutants and wastes that affect the natural resources and the environment.
Animal biotechnology is a branch of biotechnology in which molecular biology techniques are used to genetically engineer to modify the genome of animals in order to improve their suitability for pharmaceutical, agricultural or industrial applications. It has been used to produce genetically modified animals that synthesize therapeutic proteins, have improved growth rates or are resistant to disease. Animal biotechnology supports research for development of affordable new generation vaccines and diagnostics against a plethora of animal diseases. A thrust in this direction is given through multi-faceted approaches such as collaborative translational research, consolidation of existing projects with potential leads and generation of network programs around major animal diseases of national importance.
Applied Biotechnology is concerned with studies to explore the advanced and latest research developments in the use of living organisms and bioprocesses in engineering, technology, medicine, agricultural, animal, environmental, industrial, medical, and microbial biotechnology, bioinformatics, and socio-legal and ethical aspects in biotechnology. It covers from molecular biology and the chemistry of biological process to earth environmental aspects as well as computational applications, policy and ethical issues directly related to applied biotechnology. Biotechnology in the developed and developing world, management and economics of biotechnology political and social issues are some of the main issues to be considered.
Pharmaceutical biotechnology is a new and growing field in which the principles of biotechnology are applied to the development of drugs. A majority of therapeutic drugs in the current market are bioformulations such as antibodies, nucleic acid products and vaccines. Such bioformulations are developed through several stages that include understanding the principles underlying health and disease; the fundamental molecular mechanisms governing the function of related biomolecules; synthesis and purification of the molecules; determining the product shelf life, stability, toxicity and immunogenicity; drug delivery systems; patenting; and clinical trials. The pharmaceutical companies that have marketed bioformulations use biotechnology principles such as recombinant DNA technology to design more effective protein-based drugs, such as erythropoietin and fast-acting insulin.
Tissue Science and Engineering employs physical, chemical, and biological factors to replace and or improve biological functions of the cell. The interdisciplinary field of tissue engineering has been one of the most active and quickly expanding disciplines during the past two decades. Researchers are on to develop various novel tissue engineering approaches. Genetic engineering, also called genetic modification or genetic manipulation is the direct manipulation of an organism's genes using biotechnology. It is a set of technologies used to change the genetic makeup of cells including the transfer of genes within and across species boundaries to produce improved or novel organisms. New DNA is obtained by either isolating or copying the genetic material of interest using recombinant DNA methods or by artificially synthesizing the DNA.
Biomedical engineering is the application of the principles and problem solving techniques of engineering in biology and medicine. This is evident throughout healthcare from diagnosis and analysis to treatment and recovery and has entered the public conscience though the proliferation of implantable medical devices such as pacemakers and artificial hips to more futuristic technologies such as stem cell engineering and the 3-D printing of biological organs. Biomedical engineering focuses on the advances that improve human health and health care at all levels. Biomedical engineering has profound influence on human health in that biomedical engineering use and applies modern biological principles in their engineering design process; be it in advanced prosthetic limb or a breakthrough in identifying proteins within cells
Industrial biotechnology includes modern application of biotechnology for sustainable processing and production of chemical products, materials and fuels. Biotechnological processing uses enzymes and microorganisms to produce products that are useful to a broad range of industrial sectors, including chemical and pharmaceutical, human and animal nutrition, pulp and paper, textiles, energy, materials, polymers, using renewable raw materials. The basics of industrial biotechnology applying to the design of fermentation processes for the production of fuels, chemicals and foodstuffs is all about industrial biotechnology. Industrial Biotechnology deals with the studies on fossil-based fuels and raw materials which contribute to climate change, and the use of renewable materials as alternative energy. We can use the unique properties of microorganisms to convert organic waste streams into biomaterials, chemicals and biofuels.
Nanobiotechnology refers to the intersection of nanotechnology and biology. This discipline helps to indicate the merger of biological research with various fields of nanotechnology. Concepts that are enhanced through nanobiology include nanodevices such as biological machines, nanoparticles, and nanoscale phenomena that occurs within the discipline of nanotechnology. This technical approach to biology allows scientists to imagine and create systems that can be used for biological research. Biologically inspired nanotechnology uses biological systems as the inspirations for technologies not yet created. As with nanotechnology and biotechnology, bionanotechnology does have many potential ethical issues associated with it. Nanobiology involves applying nanotools to relevant medical/biological problems and refining these applications. Developing new tools, such as peptoid nanosheets for medical and biological purposes is another primary objective in nanotechnology.
Systems biology is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems using a holistic approach to biological research. The Human Genome Project is an example of applied systems thinking in biology which has led to new, collaborative ways of working on problems in the biological field of genetics. One of the aims of the systems biology is to model and discover emergent properties, properties of cells, tissues and organisms functioning as a system whose theoretical description is only possible using techniques of systems biology. These typically involve metabolic networks or cell signaling networks. Uses of bioinformatics include the identification of genes and single nucleotide polymorphisms (SNPs). Such identification is made with the aim of better understanding the genetic basis of disease, unique adaptations, desirable properties especially in agricultural species.
Computational biology involves the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. Computational biology is different from biological computing, which is a subfield of computer science and computer engineering using bioengineering and biology to build computers, but is similar to bioinformatics, which is an interdisciplinary science using computers to store and process biological data. Metabolomics is the systematic study of the unique chemical fingerprints that specific cellular processes leave behind, the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ or organism which are the end products of cellular processes.
The study of the function of proteomes is called proteomics. A proteome is the entire set of proteins produced by a cell type. Genomics led to proteomics via transcriptomics as a logical step. Proteomes can be studied using the knowledge of genomes because genes code for mRNAs and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins. Proteomics complements genomics and is useful when scientists want to test their hypotheses that were based on genes. Even though all cells of a multicellular organism have the same set of genes, the set of proteins produced in different tissues is different and dependent on gene expression. Thus the genome is constant, but the proteome varies and is dynamic within an organism.
Structural Bioinformatics is the study of Protein structure prediction, which is an important application of bioinformatics. The amino acid sequence of a protein, the so-called primary structure can be easily determined from the sequence on the gene that codes for it. In the vast majority of cases, this primary structure uniquely determines a structure in its native environment. Knowledge of this structure is vital in understanding the function of the protein. Structural information is usually classified as one of secondary, tertiary and quaternary structure. Evolutionary biology is the study of the origin and descent of species, as well as their change over time. Evolutionary Bioinformatics traces the evolution of a large number of organisms by measuring changes in their DNA rather than through physical taxonomy or physiological observations alone.
Bioinformatics Algorithms is concerned with algorithmic principles driving advances in bioinformatics. It strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. Bioinformatics has emerged into a discipline due to the availability of huge amount of data. The collection of biological information is very vast and as a result there are number of databases available. They include Protein Sequences Databases; Primary Protein Sequence Databases which currently hold over 300,000 non-redundant protein sequences. The most commonly-used are SWISS PROT and PIR. Next Composite Databases of protein sequences. These compile their sequence data from the primary sequence databases and filter them to retain only the non-redundant sequences. Secondary Sequence Databases contain information derived from the primary sequence databases like PROSITE, PRINTS and Pfam.
Protein moonlighting or gene sharing is a phenomenon by which a protein can perform more than one function. Ancestral moonlighting proteins originally possessed a single function but through evolution, acquired additional functions. Many proteins that moonlight are enzymes; others are receptors, ion channels or chaperones. The most common primary function of moonlighting proteins is enzymatic catalysis, but these enzymes have acquired secondary non-enzymatic roles. Some examples of functions of moonlighting proteins secondary to catalysis include signal transduction, transcriptional regulation, apoptosis, motility, and structural. Protein moonlighting through gene sharing differs from the use of a single gene to generate different proteins by alternative RNA splicing, DNA rearrangement, or post-translational processing. Protein moonlighting by gene sharing means that a gene may acquire and maintain a second function without gene duplication and without loss of the primary function. Such genes are under two or more entirely different selective constraints
Structural biology and bioinformatics have assisted in lead optimization and target identification where they have well established roles. They can now contribute to lead discovery, exploiting high-throughput methods of structure determination that provide powerful approaches to screening of fragment binding. Impressive progress in genome sequencing, protein expression and high-throughput crystallography and NMR has radically transformed the opportunities to use protein three-dimensional structures to accelerate drug discovery, but the quantity and complexity of the data have ensured a central place for informatics. Protein structure can influence drug discovery at every stage in the design process. Classically it has been exploited in lead optimization, a process that uses structure to guide the chemical modification of a lead molecule to give an optimized fit in terms of shape, hydrogen bonds and other non-covalent interactions with the target. Protein structure can also be used in target identification and selection and the assessment of tractability of a target
Health and Medical Informatics deal with the information on current research on clinical informatics, consumer health informatics, and other health care informatics of people. Health and Medical Informatics contain data relating to a person's physical and psychological wellness, demographic information, closest relative, GP points of interest, and a large portion of the accompanying restorative history; examinations; analyze; counting surgical methods and medication treatment; aftereffects of examinations labs such as organic chemistry, hematology, pathology, imaging like plain movies, sweeps; alarms and notices like anaphylaxes, blood bunch, compulsory medications, record of precaution measures like immunisations, screenings—bosom, cervical, fecal, mysterious blood; nursing records; clinical correspondence and referrals for treatment; assent shapes for surgical systems; theater reports; release letters; posthumous reports.
Pattern Recognition in bioinformatics is concerned with the development of systems that learn to solve a given problem using a set of example instances, each represented by a number of features. These problems include clustering, the grouping of similar instances; classification, the task of assigning a discrete label to a given instance; and dimensionality reduction, combining or selecting features to arrive at a more useful representation. The use of statistical pattern recognition algorithms in bioinformatics is pervasive. Classification and clustering are often applied to high-throughput measurement data arising from microarray, mass spectrometry and next-generation sequencing experiments for selecting markers, predicting phenotype and grouping objects or genes. Classification is at the core of a wide range of tools such as predictors of genes, protein function, functional or genetic interactions, etc., and used extensively in systems biology.
Biological data come from all fields of biology and in many formats. The amount of biological data is exploding, both in size and in complexity and to fully exploit the data increasingly sophisticated computational techniques, efficient means for storing, searching and retrieving data, and powerful algorithms and statistical tools are required. With the rapid advances of various high-throughput technologies, large amount of data has been generated using sequencing nucleic acid and protein, microarray technology and macromolecule structural determination approaches especially in efforts to understand and treat human diseases. Data Management is a complex task. It handles all sorts of data such as microarray, proteomics and next-generation sequencing data using appropriate data-management and data-analysis methods. Further it requires skills to transform raw data into biological knowledge.
The massively parallel sequencing technology known as next-generation sequencing has revolutionized the biological sciences. With its ultra-high throughput, scalability, and speed, next-generation sequencing enables researchers to perform a wide variety of applications and study biological systems at a level never before possible. Today's complex genomic research questions demand a depth of information beyond the capacity of traditional DNA sequencing technologies. Next-generation sequencing has filled that gap and become an everyday research tool to address these questions. Today's complex genomic research questions demand a depth of information beyond the capacity of traditional DNA sequencing technologies. Next-generation sequencing has filled that gap and become an everyday research tool to address these questions.