Biotechnology Reseacrh Paper Essay Example

including the measurement of the distance between them.

The term genome refers to an organism's genetic material contained in its chromosome(s), typically measured by base pair count. The Human Genome Project (HGP) began in 1990 through the efforts of the United States Department of Energy and the National Institutes of Health. Its objective was to identify roughly 80,000 genes within human DNA, determine the sequences of the 3 billion chemical bases that make up human DNA, store this data in databases, and create tools for data analysis. Informatics involves utilizing computers and statistical methods to handle data. In genomics, informatics encompasses techniques for efficient database querying, analysis of DNA sequence data, and deriving protein sequences and structures from DNA sequences. Sequencing is the process of determining the order of nucleotides in DNA.

Biotechnology – Past, Present, and Future

During the 5th APEC R;D Leaders’ Forum held on November 3rd, 2004 in New Zealand, Alan G.

MacDiarmid, a professor from the University of Texas and recipient of the 2000 Chemistry Nobel Prize, delivered a speech titled "The World Is Becoming Smaller" where he disclosed that in 2003, the global population was recorded at 6.3 billion people. He also projected that by 2050, this figure will skyrocket to an astonishing 10 billion individuals. However, catering to the energy requirements of this rapidly growing populace will necessitate an incredible quantity of approximately 150 million barrels of oil per day sourced from new clean energy alternatives. This raises the question: from where will this ample supply originate? Furthermore, attaining universal harmony and prosperity is contingent upon affordability for this energy resource. Regrettably, with current technological advancements alone, humanity lacks the capability to accomplish

such an objective.

According to the text, energy is just one of several challenges that humanity will encounter in the future. MacDiarmid identified ten challenges for mankind to confront in the next 50 years, including energy, terrorism and war, food, environment, poverty, water, disease, education and democracy, and population. Biotechnology offers potential solutions to these challenges. In recent years, biotechnology has made significant progress as seen in academic publications, reliable papers, and even popular magazines.

The misconception that biotechnology is a relatively new field can arise when people fail to connect the use of microbes in fermenting food by ancient civilizations with biotechnology. However, in modern times, this "old biotechnology" has been vital in developing and implementing processes for producing various products such as antibiotics, drugs, alcohols, sugars, amino acids, organic acids, and specialty items. These processes utilize microbiology, enzymes, fermentation, and separation technology. Collaborations between engineers, industrialists, attorneys, and life scientists have allowed for rapid scaling up to industrial production. Consequently,the pharmaceutical industry along with food processing sector , agriculture sector and specialty product sectors experienced significant growth generating over $100 billion annually in the United States alone by the early 1990s. The emergence of the "new biotechnology" occurred during the 1970s through recombinant DNA procedures which involved direct manipulation of genetic material.

Since 1976, the use of biotechnology on an industrial level has significantly broadened the capabilities of biological systems, allowing scientists and engineers to bestow new characteristics upon microbes, plants, and animals through genetic manipulation. In a parallel manner to non-organic substances, it is now feasible to produce diverse biological molecules using biological methods. This emerging form of biotechnology, when combined with the pre-existing infrastructure

in the industrial, governmental, and academic sectors along with the pervasive role of biological materials in everyday life, has facilitated notable progress in products, markets, and future prospects.

The pharmaceuticals field is experiencing a significant impact from the new biotechnology, and its influence is continuously growing. Computers play a crucial role in advancing biotechnology and revolutionizing science. They enable the extraction of valuable information from extensive data sets and the creation of intricate models across various fields, including space science and quantum physics. However, computer modeling is currently benefiting biology the most.

Michael Levitt, a professor of structural biology at Stanford University, states that biological systems contain valuable information and believes that combining precise molecules with powerful computers is ideal (Iyengar, 1997). Levitt, who was awarded the 2013 Nobel Prize for Chemistry along with his group, envisions a future where computers have a significant impact on biology. In recent years, biologists have shifted from conducting hands-on experiments to utilizing advanced computer models and simulations. This shift enables them to unravel the mysteries of the human genome and discover previously unknown side effects of pharmaceutical drugs (Greengard, 2014). Currently, researchers are leveraging this knowledge to develop artificial organs and revolutionize fields like medicine and nutrition science. It is evident that computational biology and bioinformatics are driving transformative changes in our world.

Biologists are increasingly using computational methods alongside experimentation to advance their research. According to David Shaw, a principal scientist at D.E. Shaw Research and a high-ranking research fellow at the Center for Computational Biology and Bioinformatics at Columbia University, computation is becoming a valuable tool in the scientific enterprise. It not only generates hypotheses but also offers

independent evidence. Both experimentation and computation have their unique contributions in understanding biological and biochemical phenomena, leading to important scientific breakthroughs that would not have been possible with only one approach (Greengard, 2014).

Computational Biology

The field of bioinformatics emerged as early as the 1970s.

During that period, Paulien Hogeweg and Ben Hesper, theoretical biologists from Denmark, discovered that sophisticated mathematical patterns exist in the field of biology and it is possible to develop algorithms to identify them in a more comprehensive manner (Greengard, 2014). In the following years, there have been significant advancements in computer processing power, storage, software, and mathematical algorithms, leading to substantial progress in computational biology and bioinformatics. These fields are now extensively utilized to solve problems that were previously unimaginable. Hogeweg refers to this process as "a practical approach to modeling the complexities of biological organisms" (Greengard, 2014). Pavel Pevzner, a professor at the University of California (San Diego), states that computational technology has revolutionized biology, transforming it into a digital science. The use of computational tools and expertise across various disciplines has become essential in modern biology (Greengard, 2014). Pevzner also highlights that computers have not only accelerated modeling processes from years or months to hours but have also provided qualitatively superior data and helped researchers uncover intricate and hidden connections in the data.

The focus currently primarily revolves around well-known biology projects, such as the Human Genome Project and Foldit, a multiplayer game that has contributed to AIDS research discoveries (Khatib et al., 2011). Informatics and Computational biology have played important roles in studying DNA and protein structures, designing pharmaceutical drugs, and creating models for artificial tissues. Researchers are also exploring new

areas, like the European researchers who developed GENOBOX, an informatics platform that helps predict how food bacteria and probiotics affect a person's individual genome.

According to Ron Shamir, a computer science and bioinformatics professor at Tel Aviv University and an ACM Fellow, the rise of biotechnology in recent years heavily relies on next-generation sequencing. This technology allows for fast and affordable DNA sequencing (Greengard, 2014). Next-generation sequencing not only enables sequencing of genomes but also serves as a valuable tool for measuring various biological entities. Professor Shamir highlights that the decreasing cost of sequencing has made previously unimaginable capabilities now within reach (Greengard, 2014). Initially costing around $3 billion, the price of human genome sequencing is expected to decrease to about $1,000 and potentially drop even further to a few hundred dollars in the near future. However, these advancements also present computational challenges concerning data storage, transfer, and analysis.

The field of biology is being transformed by the progress in computational power and cost effectiveness. Professor Michael Levitt from Stanford University uses computers to study proteins, DNA, and RNA, which are vital for life. The comprehension of these molecules' structure is crucial for comprehending their function and creating medications. At the same time, Shamir is devising algorithms to analyze the connection between chromosomes, cancer, and biological control systems.

In order to understand the regulation of genes and proteins by other genes, which is important in medicine, agriculture, and basic biology (Greengard, 2014), David Shaw and his team are employing innovative techniques to investigate biological puzzles. Their focus lies particularly at the intersection of medicine and the human genome. They have developed a high-performance computer capable of simulating rapid

alterations in a protein's three-dimensional configuration within milliseconds.

Computer modeling and simulations have been crucial in revealing the molecular mechanisms of biological processes and diseases. It is widely believed that these advancements can greatly transform the drug development process for pharmaceutical companies in the future as it has become progressively more challenging, expensive, and time-consuming. Moreover, computer modeling offers a way to decrease reliance on animal testing (Lipinski et al., 2012). Through the use of computer models, scientists are able to investigate intricate scenarios and simulate human responses to various medications and doses. With increased inclusion of comprehensive data such as correlations and relationships, the accuracy of these models improves over time.

This modeling technique is a valuable addition to traditional biological research methods as it has the potential to lower costs, expedite development, and enhance the effectiveness of medications. Furthermore, it opens up new opportunities. For instance, scientists from eight prominent institutions are currently collaborating on the Artificial Pancreas Project. They are working on developing and testing advanced software that can automatically regulate glucose levels for individuals with type 1 diabetes (Sparacino et al., 2012).

Beyond the Medical Field

Not only in medicine, but crowdsourcing, nanotechnology, gaming, and plugged-in devices are also emerging as important components in the vast field of bioinformatics.

Two games, Dizeez and Cut it Out, have been developed by The Scripps Research Institute and New England Biolabs respectively. Dizeez focuses on genetic medicine and has resulted in unique gene-disease observations, while Cut it Out involves players building and manipulating DNA sequences. These advancements in technology are leading scientists towards new possibilities (Schrope, 2013).

By utilizing sensors and incorporating data input

from mobile devices, biologists are able to not only capture a more comprehensive view of the immediate environment but also explore vast amounts of data across different disciplines and areas. According to Levitt, biological systems offer remarkable insights into various environmental phenomena, with almost limitless possibilities. Biological data can be used by scientists to gain a deeper understanding of pollution patterns in water and air, as well as their impact on health. Additionally, they can study the dispersal and interaction of harmful chemicals with their surroundings and examine the reactions between soil organisms and different substances under unique conditions.

New pollution management strategies, improved HAZMAT monitoring with protective gear, and advancements in food science and farming techniques can be guided by these developments. Moreover, biotechnology research can lead to the creation of better and upgraded fuels, transforming various aspects including batteries and manufacturing industry. Enhanced algorithms and computer models require fresh perspectives and interdisciplinary collaboration. According to David Shaw, interdisciplinary study, involving computer scientists along with biologists, chemists, and other experts, contributes significantly in computational biology fields. Such collaborations often result in innovative problem-solving approaches that are challenging to achieve within a single discipline (Greengard, 2014). Shamir also agrees that filtering algorithms play a crucial role in extracting relevant biomedical data accurately. It is equally important to enhance storage capacity and efficiency by utilizing cloud computing more effectively in order to have access to a larger pool of data.

According to Shamir, there is a need for improved bioinformatics algorithms capable of effectively integrating diverse data. He emphasizes that decrypting the data is the main challenge rather than obtaining it, with analysis being the current obstacle. Michael

Levitt predicts that bioinformatics will bring about significant changes in science in the future, stating that there is a model for all existing data worldwide at a certain stage.

"Currently, the majority of data examination techniques are generic; scientists search for relationships, dependencies, and connections." However, as scientists delve deeper into a more detailed level and gain a greater understanding of substances, frameworks, and correlations, significant improvements will be evident. From a molecular perspective, "Both a bridge and a serving dish are made of steel; it is the nature and functionality of the object that determines its role in real-world situations." As we develop a proper understanding to identify and differentiate complex biological structures, Levitt suggests that we will begin to comprehend the shapes and forms of biological objects beyond ordinary structures. "There is a possibility of achieving a level of understanding that will revolutionize several aspects of our world (Greengard, 2014)."

Computers in Biotechnology and the 6th Kondratieff Cycle

There is a business theory that suggests the movement of the economy occurs in long cycles driven by technological innovations. This theory is credited to Russian economist Nicolai Kondratiev (or Kondratieff), who identified a series of technological booms. In the late 1990s, the global economy entered a new long cycle – the sixth Kondratieff cycle (Figure.1).

The primary force behind the sixth Kondratieff wave is health care, with its main innovations being psychosocial health and biotechnology. This biotechnology relies on computers and allows for significant advancements in areas such as nutrition, medical treatments, technology, research, food production, ecology, energy generation, and data processing. Currently, there are no apparent limits to the growth of this technology (Nefiodow,

2014). In the context of the sixth Kondratieff cycle, computers play a crucial role in driving biotechnology. It is important to note that these long-term cycles involve a series of mutually beneficial technological and methodological inventions that are essential for complex systems. The key disciplines in modern biotechnology include biology, computer informatics, biochemistry, mathematics, and engineering. Each of these fields has seen significant progress in recent decades.

In general, molecular biology has greatly influenced the field of biological sciences. This influence is mainly due to the discovery of DNA's structure, gene replication, as well as advancements in bio-analytics such as genome sequencing using computers. The progress in molecular biology has been further accelerated by the rapid development of computer science. To cope with the vast amount of data, bioinformatics has implemented various techniques for archiving, retrieving, consolidating, and analyzing biological information. The availability of comprehensive data collections has shifted the focus from hypothesis-driven analysis to data-driven analysis utilizing statistical modeling. Additionally, these extensive and partially measurable datasets serve as the foundation for mathematical modeling and computer simulation of pathways and regulatory structures. The progress in computer science has also facilitated improved process management and automation.

The current extensive level of biotechnology is primarily the result of interdisciplinary collaboration among open-minded researchers from various fields. It is worth mentioning that previous biotechnology projects faced challenging economic circumstances. It is also important to acknowledge Prof. Mildner's significant contribution to research and education.

Biotechnology has undergone a transformation due to advancements in science and the use of computers. Previously, biotechnology involved using biological processes to produce technical products, but now it encompasses molecular biotechnology. This field includes various laboratory techniques such

as biochemistry, molecular biology, microbiology, immunology, and cell biology. These techniques are used to modify cellular organisms and produce healing molecules and biocatalysts for white biotechnology. Currently, the majority of biotechnological products are used in the healthcare industry. In addition to synthesizing specific molecules, modified cells are also used in cell-based therapies, which is a growing field in personalized medicine.

The human genome project (HUGO), which began in the 1990s, has significantly propelled molecular biotechnology in health applications. It has spurred advancements in analytical tools, such as computers, resulting in improved abilities and expanded roles. The knowledge gained from the human genome project offers new possibilities for diagnosis and therapy. It also paves the way for deeper insights into cellular structures, enabling targeted approaches to disease management. Notably, this enhanced understanding of cellular regulatory structures has led to a broader analysis of current medicinal chemistry methods. As a result, new medications are now being developed to specifically interact with particular pathological bodies.

These therapeutic ideas may lead to a significant reduction in product costs. In general, the combination of molecular biotechnology, biochemistry, molecular biology, cell biology, computers, and mathematical modeling has formed a new field in the life sciences (Buchholz; Collins, 2013).

Human Genetics and Computers

The progress in computer science and biotechnology is providing new opportunities in the field of human genetics and raising important questions on how to integrate these emerging technologies. The development of faster DNA sequencing methods through the Human Genome Project (HGP) and other initiatives has led to the creation of advanced computer software and hardware that enable scientists to analyze genetics with unprecedented speed, detail, and accuracy.

The future of medicine will be greatly

influenced by advancements in informatics equipment, chip technology, supercomputers, databases, imaging systems, and software and hardware. These tools are crucial for studying genetics and require interdisciplinary cooperation with fields such as engineering, physics, chemistry, and mathematics (Yashon & Cummings, 2012). Additionally, the increasing reliance on the Internet enables exciting global partnerships and enhanced data sharing worldwide.

The emergence of new technologies in genetic study brings with it various social, ethical, and legal issues. The speed at which genetic data is becoming accessible surpasses society's ability to address potential abuses. The impact of these capabilities on individuals and society as a whole has yet to be fully evaluated, as decision makers and lawmakers strive to keep pace with these developments. As more information becomes available about individuals' genetic makeup, it is certain that additional ethical questions will arise in the future. Computers can effectively be used to locate and analyze genes and their regulatory regions, as well as establish connections between different organisms. This process, known as "sequence annotation," involves exposing and explaining biologically relevant features in the genetic sequence.

An important requirement prior to the genome sequence information becoming useful is the quality of annotation. The value of annotation directly impacts the quality of the sequence. To effectively annotate DNA sequences, substantial computational difficulties and organizational issues need to be addressed. Implementing new computational approaches and a workable procedure is essential for successful and timely investigation and control of these data (Uberbacher, n.d.). When considering computing for large-scale sequence investigation and annotation process, it is advisable to review earlier developed models. High-throughput examination processes have been applied to various microorganisms such as Mycoplasma genitalium and Haemophilus influenzae

using simpler methods that allow for a single pass through the data. However, this model is inadequate for examining complex genomes like the human genome.

The investigation of genomic sequence areas should be consistently updated throughout the Genome Project, as it is an ongoing process. New data related to a sequenced gene can emerge in various databases at any given time, and researchers should establish and present new connections to this data. However, researchers' abilities to analyze the sequence may vary over time. The use of computers to examine DNA sequences is a relatively new science, and informatics professionals in this field are expected to successfully identify different features, like gene regulatory regions, in the future. Reanalyzing sequences and regularly updating knowledge of them will result in significant advancements as new sequences are discovered, techniques improve, and relevant data in computer databases expands. In this context, sequence annotation serves as a dynamic entity that will continue to grow in richness and quality in the years to come.

The "single pass-through pipeline" is not the recommended prototype for human genome examination because of the incredibly fast pace at which fresh and relevant information arises (Uberbacher, n.d.).

The Human Genome Figures and Development

According to the National Institutes of Health, the human genome is estimated to consist of three billion base pairs. In terms of paper, it could fill one thousand page books, equivalent to a telephone directory in size. The process of mapping, sequencing, and collecting this data presents a significant challenge that can only be overcome through complex computational methods.

Using computers to decrypt, manage, and consolidate this data could potentially shorten the time required to discover disease genes from

years to days. For instance, in the United States, the Human Genome Project is a large-scale research endeavor involving the Department of Energy, National Institutes of Health, and scientists from across the country. Furthermore, the Human Genome Management Information System has facilitated the establishment of human genome projects in over 20 states, with more than one thousand scientists affiliated with the Human Genome Organization (HUGO), an international partnership involved in the human genome project (Speaker et al., 1993). In early 1998, The Institute for Genome Research (TIGR) and Perkin-Elmer Corporation announced their collaboration to sequence the entire human genome by the end of 2001. This raised concerns about the impact of private corporations, driven by proprietary and financial interests, taking on a project that was originally intended to be publicly funded and managed by governments.

Those in favor of private research argue that competitive opportunities in the economy drive biomedical study and have significant positive effects on the general population. However, some caution that sequencing done by private corporations may not be as accurate and complete as that of the HGP. There is also concern that legal battles may arise over the private corporations' right to patent discovered genes and profit from them. These debates raise questions about the ownership of portions of the human genome. Both global and national efforts are being made to help society determine how to responsibly integrate these emerging technologies.

In 1997, the United Nations Educational, Scientific and Cultural Organization (UNESCO) approved a "Universal Declaration on the Human Genome and Human Rights." This declaration states that the human genome is "the heritage of humanity" and provides regulations that balance individual sovereignty and

scientific activity (In Have, In Jean; Unesco, 2009). In the United States, the National Human Genome Research Institute's Ethical, Legal and Social Implications (ELSI) program focuses on issues such as privacy, fairness, and the ethical use of genetic data. This program also addresses the incorporation of emerging genetic technologies into clinical practice, challenges in genetics research, and provides public and professional training (Sateesh, 2008). Various committees and task forces, including the United States National Bioethics Advisory Commission, are also involved in addressing ethical concerns in genetic research. The increasing availability of genetic data is a significant issue that needs attention.