We provide hands-on experience with all the instruments. We provide practical exposure to all protocols in Microbiology, Biotechnology, Genetic Engineering, Molecular Biology, Biochemistry, Bioinformatics and Cheminformatics projects methodologies. We also provide training sessions for project methodologies, support for applying biostatistics in your projects and complete assistance in Thesis / project report completion. Students are also given complete guidance and reviews in the middle of project works.
Microbiology is the study of microscopic organisms, those being unicellular (single cell), multicellular (cell colony), or acellular (lacking cells). Microbiology encompasses numerous sub-disciplines including virology, mycology, parasitology, and bacteriology. While some fear microbes due to the association of some microbes with various human illnesses, many microbes are also responsible for numerous beneficial processes such as industrial fermentation (e.g. the production of alcohol, vinegar and dairy products), antibiotic production and as vehicles for cloning in more complex organisms such as plants. Scientists have also exploited their knowledge of microbes to produce biotechnologically important enzymes such as Taq polymerase, reporter genes for use in other.
Microorganisms are beneficial for microbial biodegradation or bioremediation of domestic, agricultural and industrial wastes and subsurfa0ce pollution in soils, sediments and marine environments. The ability of each microorganism to degrade toxic waste depends on the nature of each contaminant. Since sites typically have multiple pollutant types, the most effective approach to microbial biodegradation is to use a mixture of bacterial and fungal species and strains, each specific to the biodegradation of one or more types of contaminants.
Some benefit may be conferred by consuming fermented foods, probiotics (bacteria potentially beneficial to the digestive system) and/or prebiotics. The ways the microbiome influences human and animal health, as well as methods to influence the microbiome are active areas of research.
Immunoinformatics applies informatics techniques to the study of molecules of the immune system. One principal goal of this study is the efficient and effective prediction of immunogenicity. This may be done at the level of epitopes, subunit vaccines, or weakened or inactive pathogens.
Immunology is that the study of the system and could be a important branch of the medical and biological sciences. The system protects USA from infection through varied lines of defence. If the system isn't functioning because it ought to, it may end up in unwellness, like pathology, hypersensitivity reaction and cancer. It is also now becoming clear that immune responses contribute to the development of many common disorders not traditionally viewed as immunologic, including metabolic, cardiovascular, and neurodegenerative conditions such as Alzheimer’s.
The system could be a complicated system of structures and processes that has evolved to shield U.S.A. from unwellness. Molecular and cellular parts form up the system. The operate of those parts is split up into nonspecific mechanisms, those that area unit innate to Associate in Nursing organism, and responsive responses, which are adaptive to specific pathogens. Fundamental or classical medical specialty involves learning the parts that form up the innate and adaptive system.
Innate immunity is that the 1st line of defence and is non-specific. That is, the responses area unit an equivalent for all potential pathogens, in spite of however completely different they will be. Innate immunity includes physical barriers (e.g. skin, saliva etc) and cells (e.g. macrophages, neutrophils, basophils, mast cells etc). These parts ‘are able to go’ Associate in Nursing defend an organism for the primary few days of infection. In some cases, this is often enough to clear the infectious agent, but in other instances the first defence becomes overwhelmed and a second line of defence kicks in.
Adaptive immunity is that the second line of defence that involves increase memory of encountered infections thus wills mount Associate in Nursing increased response specific to the infectious agent or foreign substance. Adaptive immunity involves antibodies, which usually target foreign pathogens roaming free within the blood. Also concerned area unit T cells, that area unit directed particularly towards pathogens that have colonized cells and may directly kill infected cells or facilitate management the protein response.
Immunogenicity is the ability of a pathogen or a part or molecule of a pathogen to induce a specific immune response when first exposed to surveillance by the immune system. Antigenicity is the capacity for recognition by the adaptive immune response molecular machinery in a recall response
In Silico experiments, using a computer or computer simulation to enable more effective biological experiments, historically also refering to virtual experimentation in a humans brain, therotical biology, or "Gedanken experiments = Thought experiments", can be used to help predicting immunogenicity
In Silico Immunogenicity Predictions involve
Agricultural biological science could be a branch of biological science managing plant-associated microbes and plant and animal diseases. It conjointly deals with the biological science of soil fertility, like microbic degradation of organic matter and soil nutrient transformations. Again from varied naturally-occurring microorganisms like microorganism and fungi, these solutions will defend crops from pests and diseases and enhance plant productivity and fertility. Microbial solutions structure around 2 thirds of the agricultural biological business.
On the microscopic landscape of a root surface, totally different symbionts use distinctive strategies to infect. Once anchored, some microorganism categorical genes that convert soil and part molecules into compounds valuable to the plant, like element and element containing compounds. Others like mycorrhizal fungi turn out huge networks of hyphae that primarily perform as further root extent to mine soil for nutrients; they conjointly give some infectious agent protection to the host roots. At the plant-fungi interface, fungi give plants with compounds—ammonium, nitrate, amino acids, inorganic phosphate, and organic compounds like urea—in exchange for plant carbohydrates acquired through photosynthesis. The sloughed off cells from plant roots area unit necessary sources of carbon for organisms living accommodations within the rhizosphere. These dependent relationships not solely increase the bioavailability of crucial parts to plants, however conjointly improve soil fertility by increasing labile carbon and element levels. Crop rotation, particularly involving legumes and their Rhizobia symbionts, is practiced exactly for this reason
A majority of the fertilizers stay unabsorbed and travel into different components of adjacent ecosystems, wherever they're used by organisms like protectant. This ultimately results in a series of events that off-set the preexisting balance of the ecosystem. Applications of biological science in agriculture aim to reduce the utilization of plant food, however at identical time, provide another mode for environmental disruption. We should be aware of the fragility of nature, and cautiously monitor the conditions of microorganisms made in laboratories and inoculated into farmland.
Food biology is that the study of the microorganisms that inhibit, create, or contaminate food, as well as the study of microorganisms inflicting food spoilage, pathogens that will cause illness particularly if food is improperly stewed or keep, those wont to manufacture hard foods like cheese, yogurt, bread, beer, and wine, and people with alternative helpful roles like manufacturing probiotics.
Food safety may be a major focus of food biology. Numerous agents of illness, pathogens, are readily transmitted via food, including bacteria, and viruses. Microbial toxins are also possible contaminants of food. However, microorganisms and their product may be wont to combat these infective microbes. Probiotic bacterium, including those that produce bacteriocins, can kill and inhibit pathogens. Alternatively, purified bacteriocins such as nisin can be added directly to food products. Finally, bacteriophages, viruses that only infect bacteria, can be used to kill bacterial pathogens. Thorough preparation of food, including proper cooking, eliminates most bacteria and viruses.
However, toxins made by contaminants might not be vulnerable to modification to non-toxic forms by heating or change of state the contaminated food because of alternative safety conditions. To ensure safety of food product, microbiological tests such as testing for pathogens and spoilage organisms are required. This way the danger of contamination underneath traditional use conditions are often examined and sickness outbreaks are often prevented. Testing of food product and ingredients is very important on the complete offer chain as attainable flaws of product will occur at each stage of production, with the exception of sleuthing spoilage, microbiological tests may confirm germ content, determine yeasts and molds, and enterobacteria. For enterobacteria, scientists also are developing fast and moveable technologies capable of distinctive variants of enterobacteria.
The concepts that seeded nanotechnology were first discussed in 1959 by renowned physicist Richard Feynman in his talk There's Plenty of Room at the Bottom, in which he described the possibility of synthesis via direct manipulation of atoms. The term "nano-technology" was first used by Norio Taniguchi in 1974, okyo Science University to describe semiconductor processes such as thin-film deposition that deal with control on the order of nanometers. His definition still stands as the basic statement today: "Nano-technology mainly consists of the processing of separation, consolidation, and deformation of materials by one atom or one molecule."
What exactly is nano-technology? One of the problems facing this technology is the confusion about how to define nanotechnology. Most revolve around the study and control of phenomena and materials at length scales below 100 nm and quite often they make a comparison with a human hair, which is about 80,000 nm wide. This is the scale at which the basic functions of the biological world operate and materials of this size display unusual physical and chemical properties. These profoundly different properties are due to an increase in surface area compared to volume as particles get smaller and also the grip of weird quantum effects at the atomic scale. People have made use of some unusual properties of materials at the nanoscale for centuries. Tiny particles of gold for example, can appear red or green a property that has been used to colour stained glass windows for over 1000 years.
Green nanotechnology integrates the principles of green chemistry and green engineering to produce eco-friendly, safe, nanostructures that do not use toxic chemicals in the synthesis protocol. The parallel development of nanotechnology with green chemistry and potential synergism between the two fields can lead to sustainable methods with reduced environmental impacts, protection of resources and human health. Thus the concept of “green nanotechnology” comes to rescue. The main goal of green nanotechnology is to produce nanostructures without affecting the environment or human health. This can be a viable substitute to the conventional physical and chemical methods of synthesizing nanostructures.
On the scale of natural sciences, nanotechnology is a young field, which emerged in the second half of the 20th century and has been developing with superfast pace ever since. The discovery of the fullerenes, carbon-based structures with a 3-D hollow shape, and the invention of high-resolution microscopes (atomic force microscope and the scanning tunnel microscope) are often considered the cornerstones of the field. Looking back at the history of human civilization with our current understanding of science, one can find empirical examples of practical applications that are technically nanotechnologies, such as metal-based stained glass, which in fact employs metal nanoparticles, or the so-called Damascus saber blades owning their high quality to the properties of what would be described today as nanotubes and nanowires.
Nanotechnology is found elsewhere today in products ranging from nanometre-thick films on “self-cleaning” windows to pigments in sunscreens and lipsticks.More recently, scientists working on the nanoscale have created a multitude of other nanoscale components and devices, including: Tiny transistors, superconducting quantum dots, nanodiodes, nanosensors, molecular pistons, supercapacitors, “biomolecular” motors, chemical motors, a nano train set, nanoscale elevators, a DNA nanowalking robot, nanothermometers, nano containers, the beginnings of a miniature chemistry set, nano-Velcro, nanotweezers, nano weighing scales, a nano abacus, a nano guitar, a nanoscale fountain pen, and even a nanosized soldering iron.
Nanotechnology provides an important new set of tools for the diagnosis and treatment of ocular diseases. Miniaturization of devices, chip-based technologies, and novel nanosized materials and chemical assemblies already provide novel tools that are contributing to improved healthcare in the 21st century Applications of nanotechnology to ophthalmology, including drug, peptide, and gene delivery; imaging; minimally invasive physiological monitoring; prosthetics; regenerative medicine; and surgical technology. Nanotechnology has been used for dental applications in several forms, including the field of prosthodontics with the development of nanobiomaterials as a useful tool. To date, there has been an exponential increase in studies using nanotechnology for other dental applications. It is not too early to consider, evaluate, and attempt to shape potential effects of nanodentistry. Nanodentistry will lead to efficient and highly effective personalized dental treatments.
The future of the field is often discussed in the context of two major trajectories: new materials and complex nanodevices, many of which are geared toward biomedical applications. Vaccines, drug and gene delivery, and biomedical imaging are among the areas of virus-related research that are expected to be most influenced by nanotechnology. Nanotechnology seems to be where the world is headed if technology keeps advancing and competition practically guarantees that advance will continue. It will open a huge range of opportunities of benefit for both the clinicians and the patient.
Virology is the study of viruses – submicroscopic, parasitic particles of genetic material contained in a protein coat – and virus-like agents. It focuses on the following aspects of viruses: their structure, classification and evolution, their ways to infect and exploit host cells for reproduction, their interaction with host organism physiology and immunity, the diseases they cause, the techniques to isolate and culture them, and their use in research and therapy. Virology is considered to be a subfield of microbiology or of medicine.
One main motivation for the study of viruses is the fact that they cause many important infectious diseases, among them the common cold, influenza, rabies, measles, many forms of diarrhea, hepatitis, Dengue fever, yellow fever, polio, smallpox and AIDS. Herpes simplex causes cold sores and genital herpes and is under investigation as a possible factor in Alzheimer's.
Some viruses, known as oncoviruses, contribute to the development of certain forms of cancer. The best studied example is the association between Human papillomavirus and cervical cancer: almost all cases of cervical cancer are caused by certain strains of this sexually transmitted virus. Another example is the association of infection with hepatitis B and hepatitis C viruses and liver cancer.
The word virus appeared in 1599 and originally meant "venom". A very early form of vaccination known as variolation was developed several thousand years ago in China. It involved the application of materials from smallpox sufferers in order to immunize others. In 1717 Lady Mary Wortley Montagu observed the practice in Istanbul and attempted to popularize it in Britain, but encountered considerable resistance. In 1796 Edward Jenner developed a much safer method, using cowpox to successfully immunize a young boy against smallpox, and this practice was widely adopted. Vaccinations against other viral diseases followed, including the successful rabies vaccination by Louis Pasteur in 1886. The nature of viruses however was not clear to these researchers.
Clinical Microbiology is the study of microscopic organisms, those being unicellular (single cell), multicellular (cell colony), or acellular (lacking cells). Microbiology encompasses numerous sub-disciplines including virology, mycology, parasitology, and bacteriology. While some fear microbes due to the association of some microbes with various human illnesses, many microbes are also responsible for numerous beneficial processes such as industrial fermentation (e.g. the production of alcohol, vinegar and dairy products), antibiotic production and as vehicles for cloning in more complex organisms such as plants. Scientists have also exploited their knowledge of microbes to produce biotechnologically important enzymes such as Taq polymerase, reporter genes for use in other.
Microorganisms are beneficial for microbial biodegradation or bioremediation of domestic, agricultural and industrial wastes and subsurfa0ce pollution in soils, sediments and marine environments. The ability of each microorganism to degrade toxic waste depends on the nature of each contaminant. Since sites typically have multiple pollutant types, the most effective approach to microbial biodegradation is to use a mixture of bacterial and fungal species and strains, each specific to the biodegradation of one or more types of contaminants.
Some benefit may be conferred by consuming fermented foods, probiotics (bacteria potentially beneficial to the digestive system) and/or prebiotics. The ways the microbiome influences human and animal health, as well as methods to influence the microbiome are active areas of research.
Medical Microbiology is the study of microscopic organisms, those being unicellular (single cell), multicellular (cell colony), or acellular (lacking cells). Microbiology encompasses numerous sub-disciplines including virology, mycology, parasitology, and bacteriology. While some fear microbes due to the association of some microbes with various human illnesses, many microbes are also responsible for numerous beneficial processes such as industrial fermentation (e.g. the production of alcohol, vinegar and dairy products), antibiotic production and as vehicles for cloning in more complex organisms such as plants. Scientists have also exploited their knowledge of microbes to produce biotechnologically important enzymes such as Taq polymerase, reporter genes for use in other.
Microorganisms are beneficial for microbial biodegradation or bioremediation of domestic, agricultural and industrial wastes and subsurfa0ce pollution in soils, sediments and marine environments. The ability of each microorganism to degrade toxic waste depends on the nature of each contaminant. Since sites typically have multiple pollutant types, the most effective approach to microbial biodegradation is to use a mixture of bacterial and fungal species and strains, each specific to the biodegradation of one or more types of contaminants.
Some benefit may be conferred by consuming fermented foods, probiotics (bacteria potentially beneficial to the digestive system) and/or prebiotics. The ways the microbiome influences human and animal health, as well as methods to influence the microbiome are active areas of research.
The history of biochemistry can be said to have started with the ancient Greeks who were interested in the composition and processes of life, although biochemistry as a specific scientific discipline has its beginning around the early 19th century. The term “biochemistry” itself is derived from the combining form bio, meaning "life", and chemistry. The subject of study in biochemistry is the chemical processes in living organisms, and understanding of the complex components of life and the elucidation of pathways of biochemical processes.
Much of biochemistry deals with the structures and functions of cellular components such as proteins, carbohydrates, lipids, nucleic acids and other bio molecules; their metabolic pathways and flow of chemical energy through metabolism.
Over the last 40 years the field has had success in explaining living processes such that now almost all areas of the life sciences from botany to medicine are engaged in biochemical research. Biochemistry, sometimes called biological chemistry, is the study of chemical processes within and relating to living organisms. By controlling information flow through biochemical signalling and the flow of chemical energy through metabolism, biochemical processes give rise to the complexity of life. Over the last decades of the 20th century, biochemistry has become so successful at explaining living processes that now almost all areas of the life sciences from botany to medicine to genetics are engaged in biochemical research. Today, the main focus of pure biochemistry is on understanding how biological molecules give rise to the processes that occur within living cells, which in turn relates greatly to the study and understanding of tissues, organs, and whole organisms.
The history of biochemistry can be said to have started with the ancient Greeks who were interested in the composition and processes of life, although biochemistry as a specific scientific discipline has its beginning around the early 19th century. The term “biochemistry” itself is derived from the combining form bio, meaning "life", and chemistry. The subject of study in biochemistry is the chemical processes in living organisms, and understanding of the complex components of life and the elucidation of pathways of biochemical processes.
Much of biochemistry deals with the structures and functions of cellular components such as proteins, carbohydrates, lipids, nucleic acids and other bio molecules; their metabolic pathways and flow of chemical energy through metabolism.
Over the last 40 years the field has had success in explaining living processes such that now almost all areas of the life sciences from botany to medicine are engaged in biochemical research. Biochemistry, sometimes called biological chemistry, is the study of chemical processes within and relating to living organisms. By controlling information flow through biochemical signalling and the flow of chemical energy through metabolism, biochemical processes give rise to the complexity of life. Over the last decades of the 20th century, biochemistry has become so successful at explaining living processes that now almost all areas of the life sciences from botany to medicine to genetics are engaged in biochemical research. Today, the main focus of pure biochemistry is on understanding how biological molecules give rise to the processes that occur within living cells, which in turn relates greatly to the study and understanding of tissues, organs, and whole organisms.
Immunology is a branch of biology that covers the study of immune systems in all organisms. It was the Russian biologist Ilya Ilyich Mechnikov who boosted studies on immunology, and received the Nobel Prize in 1908 for his work. physiological functioning of the immune system in states of both health and diseases; malfunctions of the immune system in immunological disorders (such as autoimmune diseases, hypersensitivities, immune deficiency, and transplant rejection); the physical, chemical and physiological characteristics of the components of the immune system in vitro, in situ, and in vivo. Immunology has applications in numerous disciplines of medicine, particularly in the fields of organ transplantation, oncology, virology, bacteriology, parasitology, psychiatry, and dermatology.
Cancer is caused when cells within the body accumulate genetic mutations and start to grow in an uncontrolled manner. Understanding how cancer develops and progresses, including how gene mutations drive the growth and spread of cancer cells, and how tumours interact with their surrounding environment, is vital for the discovery of new targeted cancer treatments.
Now a day's Scientists working on the role of cancer’s and gene mutations, so they can identify promising new targets for cancer drugs. They are exploring how genetic mutations allow cancer cells to divide more frequently, avoid cell death and invade neighbouring tissues to spread locally and around the body.
Genetic approaches are central to the efforts of many laboratories studying aspects of tumor development, including the cloning of human oncogenes and tumor suppressor genes, the generation of mutant mouse strains to study these and other cancer-associated genes, and the use of classical genetics to elucidate the components of growth control pathways in model organisms, such as Drosophila and C. elegans. These genetic approaches are complemented in the Department by biochemical and cell biological studies aimed at understanding the function of cancer genes; the details of proliferation, cell cycle and cell death pathways; the nature of cell-cell and cell-matrix interactions; and mechanisms of DNA repair, replication, transcription and chromosome stability.
Cancer is caused when cells within the body accumulate genetic mutations and start to grow in an uncontrolled manner. Understanding how cancer develops and progresses, including how gene mutations drive the growth and spread of cancer cells, and how tumours interact with their surrounding environment, is vital for the discovery of new targeted cancer treatments.
Now a day's Scientists working on the role of cancer’s and gene mutations, so they can identify promising new targets for cancer drugs. They are exploring how genetic mutations allow cancer cells to divide more frequently, avoid cell death and invade neighbouring tissues to spread locally and around the body.
Genetic approaches are central to the efforts of many laboratories studying aspects of tumor development, including the cloning of human oncogenes and tumor suppressor genes, the generation of mutant mouse strains to study these and other cancer-associated genes, and the use of classical genetics to elucidate the components of growth control pathways in model organisms, such as Drosophila and C. elegans. These genetic approaches are complemented in the Department by biochemical and cell biological studies aimed at understanding the function of cancer genes; the details of proliferation, cell cycle and cell death pathways; the nature of cell-cell and cell-matrix interactions; and mechanisms of DNA repair, replication, transcription and chromosome stability.
Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines computer science, statistics, mathematics, and engineering to analyze and interpret biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques.
Bioinformatics is both an umbrella term for the body of biological studies that use computer programming as part of their methodology, as well as a reference to specific analysis "pipelines" that are repeatedly used, particularly in the field of genomics. Common uses of bioinformatics include the identification of candidate genes and nucleotides (SNPs). Often, such identification is made with the aim of better understanding the genetic basis of disease, unique adaptations, desirable properties (esp. in agricultural species), or differences between populations. In a less formal way, bioinformatics also tries to understand the organisational principles within nucleic acid and protein sequences, called proteomics.
Bioinformatics has become an important part of many areas of biology. In experimental molecular biology, bioinformatics techniques such as image and signal processing allow extraction of useful results from large amounts of raw data. In the field of genetics and genomics, it aids in sequencing and annotating genomes and their observed mutations. It plays a role in the text mining of biological literature and the development of biological and gene ontologies to organize and query biological data. It also plays a role in the analysis of gene and protein expression and regulation. Bioinformatics tools aid in the comparison of genetic and genomic data and more generally in the understanding of evolutionary aspects of molecular biology. At a more integrative level, it helps analyze and catalogue the biological pathways and networks that are an important part of systems biology. In structural biology, it aids in the simulation and modeling of DNA,, RNA, proteins as well as biomolecular interactions.
Historically, the term bioinformatics did not mean what it means today. Paulien Hogeweg and Ben Hesper coined it in 1970 to refer to the study of information processes in biotic systems. This definition placed bioinformatics as a field parallel to biophysics (the study of physical processes in biological systems) or biochemistry (the study of chemical processes in biological systems).
Chemiinformatics (also known as chemoinformatics, chemioinformatics and chemical informatics) is the use of computer and informational techniques applied to a range of problems in the field of chemistry. These in silico techniques are used, for example, in pharmaceutical companies in the process of drug discovery. These methods can also be used in chemical and allied industries in various other forms.
The term chemoinformatics was defined by F.K. Brown in 1998: Chemoinformatics is the mixing of those information resources to transform data into information and information into knowledge for the intended purpose of making better decisions faster in the area of drug lead identification and optimization.
The primary application of cheminformatics is in the storage, indexing and search of information relating to compounds. The efficient search of such stored information includes topics that are dealt with in computer science as data mining, information retrieval, information extraction and machine learning.
Virtual screening (VS) is a computational technique used in drug discovery to search libraries of small molecules in order to identify those structures which are most likely to bind to a drug target, typically a protein receptor or enzyme.
Virtual screening has been defined as the "automatically evaluating very large libraries of compounds" using computer programs. Although searching the entire chemical universe may be a theoretically interesting problem, more practical VS scenarios focus on designing and optimizing targeted combinatorial libraries and enriching libraries of available compounds from in-house compound repositories or vendor offerings. As the accuracy of the method has increased, virtual screening has become an integral part of the drug discovery process.
The aim of virtual screening is to identify molecules of novel chemical structure that bind to the macromolecular target of interest. Thus, success of a virtual screen is defined in terms of finding interesting new scaffolds rather than the total number of hits. Interpretations of virtual screening accuracy should therefore be considered with caution. Low hit rates of interesting scaffolds are clearly preferable over high hit rates of already known scaffolds.
This is the calculation of quantitative structure-activity relationship and quantitative structure property relationship values, used to predict the activity of compounds from their structures. In this context there is also a strong relationship to chemometrics. Chemical expert systems are also relevant, since they represent parts of chemical knowledge as an in silico representation. There is a relatively new concept of matched molecular pair analysis or prediction-driven MMPA which is coupled with QSAR model in order to identify activity cliff.
Chemical data can pertain to real or virtual molecules. Virtual libraries of compounds may be generated in various ways to explore chemical space and hypothesize novel compounds with desired properties.
Virtual libraries of classes of compounds (drugs, natural products, diversity-oriented synthetic products) were recently generated. This was done by using cheminformatic tools to train transition probabilities of a Markov chain on authentic classes of compounds, and then using the Markov chain to generate novel compounds that were similar to the training database.
In the field of molecular modeling, docking is a method which predicts the preferred orientation of one molecule to a second when bound to each other to form a stable complex. Knowledge of the preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules using, for example, scoring functions.
Molecular docking is one of the most frequently used methods in structure-based drug design, due to its ability to predict the binding-conformation of small molecule ligands to the appropriate target binding site. Characterisation of the binding behaviour plays an important role in rational design of drugs as well as to elucidate fundamental biochemical processes.
Biotechnology is the use of living systems and organisms to develop or make products, or "any technological application that uses biological systems, living organisms, or derivatives thereof, to make or modify products or processes for specific use".
For thousands of years, humankind has used biotechnology in agriculture, food production, and medicine. The term is largely believed to have been coined in 1919 by Hungarian engineer Károly Ereky. In the late 20th and early 21st centuries, biotechnology has expanded to include new and diverse sciences such as genomics, recombinant gene techniques, applied immunology, and development of pharmaceutical therapies and diagnostic tests.
At its simplest, biotechnology is technology based on biology - biotechnology harnesses cellular and biomolecular processes to develop technologies and products that help improve our lives and the health of our planet. We have used the biological processes of microorganisms for more than 6,000 years to make useful food products, such as bread and cheese, and to preserve dairy products.
Biomarker, or Biological marker, generally refers to a measurable indicator of some biological state or condition. The term is also occasionally used to refer to a substance the presence of which indicates the existence of a living organism. Further, life forms are known to shed unique chemicals, including DNA, into the environment as evidence of their presence in a particular location.
Biomarkers are often measured and evaluated to examine normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Biomarkers are used in many scientific fields.
The widespread use of the term "biomarker" dates back to as early as 1980. The term "biological marker" was introduced in 1950s. In 1998, the National Institutes of Health Biomarkers Definitions Working Group defined a biomarker as "a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.
In medicine, a biomarker can be a traceable substance that is introduced into an organism as a means to examine organ function or other aspects of health. More specifically, a biomarker indicates a change in expression or state of a protein that correlates with the risk or progression of a disease, or with the susceptibility of the disease to a given treatment.
Genetic engineering, also called genetic modification, is the direct manipulation of an organism's genome 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 may be inserted in the host genome by first isolating and copying the genetic material of interest using molecular cloning methods to generate a DNA sequence, or by synthesizing the DNA, and then inserting this construct into the host organism. Genes may be removed, or "knocked out", using a nuclease. Gene targeting is a different technique that uses homologous recombination to change an endogenous gene, and can be used to delete a gene, remove exons, add a gene, or introduce point mutations.
In 1972, Paul Berg created the first recombinant DNA molecules by combining DNA from the monkey virus SV40 with that of the lambda virus. In 1973 Herbert Boyer and Stanley Cohen created the first transgenic organism by inserting antibiotic resistance genes into the plasmid of an E. coli bacte.
Genetic engineering, also called genetic modification, is the direct manipulation of an organism's genome 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 may be inserted in the host genome by first isolating and copying the genetic material of interest using molecular cloning methods to generate a DNA sequence, or by synthesizing the DNA, and then inserting this construct into the host organism. Genes may be removed, or "knocked out", using a nuclease. Gene targeting is a different technique that uses homologous recombination to change an endogenous gene, and can be used to delete a gene, remove exons, add a gene, or introduce point mutations.
In 1972, Paul Berg created the first recombinant DNA molecules by combining DNA from the monkey virus SV40 with that of the lambda virus. In 1973 Herbert Boyer and Stanley Cohen created the first transgenic organism by inserting antibiotic resistance genes into the plasmid of an E. coli bacte.
Pharmacogenomics is the study of the role of the genome in drug response. Its name (pharmaco- + genomics) reflects its combining of pharmacology and genomics. Pharmacogenomics can be defined as the technology that analyzes how the genetic makeup of an individual affects his/her response to drugs. It deals with the influence of acquired and inherited genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with pharmacokinetics and pharmacodynamics (drug absorption, distribution, metabolism, and elimination), as well as drug receptor target effects. The term pharmacogenomics is often used interchangeably with pharmacogenetics. Although both terms relate to drug response based on genetic influences, pharmacogenetics focuses on single drug-gene interactions.
For patients who have lack of therapeutic response to a treatment, alternative therapies can be prescribed that would best suit their requirements. In order to provide pharmacogenomic recommendations for a given drug, two possible types of input can be used: genotyping or exome or whole genome sequencing.[11] Sequencing provides many more data points, including detection of mutations that prematurely terminate the synthesized protein (early stop codon).
Pharmacogenomics was first recognized by Pythagoras around 510 BC when he made a connection between the dangers of fava bean ingestion with hemolytic anemia and oxidative stress. Interestingly, this identification was later validated and attributed to deficiency of G6PD in the 1950s and called favism.[12][13]] The term pharmacogenetic was first coined in 1959 by Friedrich Vogel of Heidelberg, Germany (although some papers suggest it was 19570.
In cancer treatment, pharmacogenomics tests are used to identify which patients are most likely to respond to certain cancer drugs. In behavioral health, pharmacogenomic tests provide tools for physicians and care givers to better manage medication selection and side effect amelioration. Pharmacogenomics is also known as companion diagnostics, meaning tests being bundled with drugs. Examples include KRAS test with cetuximab and EGFR test with gefitinib. Beside efficacy, germline pharmacogenetics can help to identify patients likely to undergo severe toxicities when given cytotoxics showing impaired detoxification in relation with genetic polymorphism, such as canonical 5-FU.
Personalised medicine is a medical procedure that separates patients into different groups—with medical decisions, practices, interventions and/or products being tailored to the individual patient based on their predicted response or risk of disease. The terms personalized medicine, precision medicine, stratified medicine and P4 medicine are used interchangeably to describe this concept though some authors and organisations use these expressions separately to indicate particular nuances.
While the tailoring of treatment to patients dates back at least to the time of Hippocrates, the term has risen in usage in recent years given the growth of new diagnostic and informatics approaches that provide understanding of the molecular basis of disease, particularly genomics. This provides a clear evidence base on which to stratify (group) related patients.
Every person has a unique variation of the human genome. Although most of the variation between individuals has no effect on health, an individual's health stems from genetic variation with behaviours and influences from the environment.
Modern advances in personalized medicine rely on technology that confirms a patient's fundamental biology, DNA, RNA, or protein, which ultimately leads to confirming disease. For example, personalised techniques such as genome sequencing can reveal mutations in DNA that influence diseases ranging from cystic fibrosis to cancer. Another method, called RNA-seq, can show which RNA molecules are involved with specific diseases. Unlike DNA, levels of RNA can change in response to the environment. Therefore, sequencing RNA can provide a broader understanding of a person’s state of health. Recent studies have linked genetic differences between individuals to RNA expression, translation, and protein levels.
The concepts of personalised medicine can be applied to new and transformative approaches to health care. Personalised health care is based on the dynamics of systems biology and uses predictive tools to evaluate health risks and to design personalised health plans to help patients mitigate risks, prevent disease and to treat it with precision when it occurs. The concepts of personalised health care are receiving increasing acceptance with the Veterans Administration committing to personalised, proactive patient driven care for all veterans.
Perhaps the most critical issue with the commercialization of personalised medicine is the protection of patients. One of the largest issues is the fear and potential consequences for patients who are predisposed after genetic testing or found to be non-responsive towards certain treatments. This includes the psychological effects on patients due to genetic testing results. The right of family members who do not directly consent is another issue, considering that genetic predispositions and risks are inheritable. The implications for certain ethnic groups and presence of a common allele would also have to be considered. In 2008, the Genetic Information Nondiscrimination Act (GINA) was passed in an effort to minimize the fear of patients participating in genetic research by ensuring that their genetic information will not be misused by employers or insurers. On February 19, 2015 FDA issued a press release titled: "FDA permits marketing of first direct-to-consumer genetic carrier test for Bloom syndrome".
Enzymology is the study of enzymes, their kinetics, structure, and function, as well as their relation to each other.
Hexokinase is displayed as an opaque surface with a pronounced open binding cleft next to an unbound substrate and the same enzyme with more closed cleft that surrounds the bound substrate. The enzyme changes shape by induced fit upon substrate binding to form an enzyme-substrate complex. Hexokinase has a large induced fit motion that closes over the substrates adenosine triphosphate and xylose.
Molecular dynamics (MD) is a computer simulation method for studying the physical movements of atoms and molecules, and is thus a type of N-body simulation. The atoms and molecules are allowed to interact for a fixed period of time, giving a view of the dynamical evolution of the system. In the most common version, the trajectories of atoms and molecules are determined by numerically solving Newton's equations of motion for a system of interacting particles, where forces between the particles and their potential energies are calculated using interatomic potentials or molecular mechanics force fields. The method was originally developed within the field of theoretical physics in the late 1950s but is applied today mostly in chemical physics, materials science and the modelling of biomolecules.
Structural Bioinformatics studies the structure of biological molecules and compounds, such as the structure of proteins, RNA structure, even the structure of DNA. There are two main approaches – molecular dynamics, which simulated the movement of molecules under the action of physical fields and statistical, containing a variety of methods, allowing on the basis of comparing the sequences of amino acids or nucleotides represented in databases to predict the structure of the molecule under study. In addition to predicting the structure of a single molecule this section will address the problem of studying of mechanisms of small molecule interaction with protein, prediction by computational methods of interaction of transcription factors (proteins that control the expression of genes) with DNA and others.
Drug design, often referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target. The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient.
In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies on computer modeling techniques. This type of modeling is sometimes referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design.
In addition to small molecules, biopharmaceuticals and especially therapeutic antibodies are an increasingly important class of drugs and computational methods for improving the affinity, selectivity, and stability of these protein-based therapeutics have also been developed.
Molecular biology concerns the molecular basis of biological activity between biomolecules in the various systems of a cell, including the interactions between DNA, RNA, and proteins and their biosynthesis, as well as the regulation of these interactions. so much a technique as an approach, an approach from the viewpoint of the so-called basic sciences with the leading idea of searching below the large-scale manifestations of classical biology for the corresponding molecular plan. It is concerned particularly with the forms of biological molecules and [...] is predominantly three-dimensional and structural—which does not mean, however, that it is merely a refinement of morphology. It must at the same time inquire into genesis and function."
Molecular biology is the study of molecular underpinnings of the processes of replication, transcription, translation, and cell function. The central dogma of molecular biology where genetic material is transcribed into RNA and then translated into protein.
Much of molecular biology is quantitative, and recently much work has been done at its interface with computer science in bioinformatics and computational biology. In the early 2000s, the study of gene structure and function, molecular genetics, has been among the most prominent sub-fields of molecular biology. Increasingly many other areas of biology focus on molecules, either directly studying interactions in their own right such as in cell biology and developmental biology, or indirectly, where molecular techniques are used to infer historical attributes of populations or species, as in fields in evolutionary biology such as population genetics and phylogenetics. There is also a long tradition of studying biomolecules "from the ground up" in biophysics.
Various types of data related to sequence (DNA, RNA and protein), pathways, reaction parameters, gene expression, gene ontology are being generated through different high throughput technologies in the field of molecular biology. In general, these data are complex and are existing in different nature including structured, unstructured and semi structured. The amount of these data is huge and has led to the most discussed current trend Big Data in bioinformatics. Different people think of different things when they hear about Big Data. For statisticians, the challenge is to get various statistical parameters and thereby to draw inference on these data. The computer and information science people wish to extract usable information out of databases that are so huge and complex that many of the traditional or classical methods cannot handle. Thus, Big Data Analytics would be helpful to analyze huge, complex and heterogeneous data and provide the insight in timely manner. The most importantly Big Data analytics provides cost effective solutions to deliver information effectively.
The volume of data is growing fast in bioinformatics research. To cope up with its scale, diversity, and complexity Big Data requires new architecture, techniques and algorithms. It also requires analytics to manage it and extract value and hidden knowledge from it. In other words, big data are characterised by volume, variety (structured and unstructured data), velocity (high rate of changing), veracity (biases, noise and abnormality), validity (correctness and accuracy of data), volatility (how long data is valid and how long it should be stored), value (source of value to those who can deal with its scale and unlock the knowledge within) and visualization (transform the scale of it into something easily comprehended and actionable). The traditional definition of big data does not cover two most important characteristics which separate big data from traditional databases and data warehouses. First, big data are incremental, i.e., from time to time new data are dynamically added to the big data lake. Second, big data are geographically distributed. Big data sources are no longer limited to particle physics experiments or search engine logs and indexes. With digitization of various processes and availability of high throughput devices at lower costs, data volume is rising everywhere, including in bioinformatics research. Advances in next generation sequencing technologies has resulted in the generation of unprecedented levels of sequence data. Thus modern biology now presents new challenges in terms of data management, query and analysis. Human DNA comprises approximately 3 billion base pairs with a personal genome representing approximately 100 gigabytes (GB) of data.
Due to this high availability of information intensive data stream and the advances in high performance computing technologies, big data analytics have emerged to perform real time descriptive and predictive analyses on massive amount of biological data, in order to formulate intelligent informed decisions and make biology a predictive science.
Proteomics is the large-scale study of proteins. Proteins are vital parts of living organisms, with many functions. The term proteomics was coined in 1997 in analogy with genomics, the study of the genome. The word proteome is a portmanteau of protein and genome, and was coined by Marc Wilkins in 1994 while a PhD student at Macquarie University. Macquarie University also founded the first dedicated proteomics laboratory in 1995 (the Australian Proteome Analysis Facility – APAF).
As with other subsets of biology, an increased ability to generate large amounts of data from the use of high throughput methods has led to an increased reliance on computers for data acquisition, storage, and analysis. The internet has also enabled collaboration and sharing of data that would have previously not been possible, leading to the development of large public databases with contributors all over the world. Many databases exist for protein-related information, such as the Protein Data Bank (PDB) which handles structure and sequence information for proteins with a determined crystal structure. Expasy is a popular and well-curated resource for proteomics databases and tools, including resources such as the Prosite protein feature and domain database, protein BLAST (Basic Local Alignment and Search Tool, for similarity searching), and structure prediction. NCBI also provides many resources for many types of data, including proteins, which are all searchable and well integrated.
As with other bioinformatics resources, "in-silico" discovery is not meant as a replacement for lab techniques, but rather as a supplement to work done in a wet lab. For example, if a protein thought to be a transmembrane protein was analyzed with a sequence-based localization tool that agreed with the hypothesis, it would probably still be worth experimentally confirming before drawing a conclusion. However, bioinformatics tools can be extremely useful time savers, and can provide a possible place to start with experimentation, narrow down a problem domain, or provide potential solutions to problems which would be very difficult or impossible to determine experimentally, such as with protein folding
Protein folding has become a benchmark application for many supercomputers and distributed computing systems. Distributed computing makes use of many independent client nodes that connect to a master server to obtain data to process and send back results, making them well suited to use over LANs and the internet. Although folding for now is not a replacement for structure determination by crystallography, it can provide a reasonable estimate of structure which can be investigated until actual structure is elucidated
Genomic technologies are generating an extraordinary amount of information, unprecedented in the history of Biology. Thus, a new scientific discipline, Bioinformatics, at the intersection between Biology and Computation, has recently emerged. Bioinformatics addresses the specific needs in data acquisition, storage, analysis and integration that research in genomics generates.
Among the current research lines, we highlight 1) Gene Prediction and Modeling of Splicing, related to the research on Regulation of Alternative Splicing, and on Regulation of Protein Synthesis within the "Gene Regulation" program, and in general with the "Genes and Diseases" program, 2) Identification and characterization of genomic regions involved in Gene Regulation, related to the research on Chromatin and Gene Expression, and on RNA proteins Interactions within the "Gene Regulation" program, and 3) Molecular Evolution, which includes evolution of the exonic structure of the genes, and evolution of splicing.
Genomics and bioinformatics research often requires the development of new techniques, including both experimental protocols and data analysis algorithms, to enable a deeper understanding of complex biological systems. In this respect, the field is entering a new and exciting era; rapidly improving “next-generation” DNA sequencing technologies now allow for the routine sequencing of entire genomes and transcriptomes, or of virtually any targeted set of DNA or RNA molecules.
The exponential explosion of genomic data fueled by these technologies presents an unprecedented opportunity to elucidate the molecular underpinnings of natural variation and human disease, but the sheer abundance and complexity of these data also pose significant and unsolved bioinformatic challenges. The scope of these opportunities and challenges promises to revolutionize biology and medicine.
| S.No | Project duration | Fee structure (INR) |
|---|---|---|
| 1 | 30 days to 45 days | 8000 |
| 2 | >45 days to 3 months | 10,000 |
| 3 | 3 months to 5 months | 12,500 |
| 4 | 6 months | 15,000 |
| 5 | 1 year | 20,000 |
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