Biological Sciences
Bioinformatics
Bioinformatics is a field that combines biology and computer science to analyze and interpret biological data. It involves the use of computational tools and techniques to understand biological processes, such as DNA sequences, protein structures, and gene expression patterns. Bioinformatics plays a crucial role in areas like genomics, evolutionary biology, and drug discovery.
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10 Key excerpts on "Bioinformatics"
- Zheng Rong Yang(Author)
- 2010(Publication Date)
- World Scientific(Publisher)
2 Machine Learning Approaches to Bioinformatics modelling”. Finally, one of the important concepts in biological research (relationship) has been used in Eidhammer, Jonassen and Taylor’s definition [7], that Bioinformatics is “the study of biological information and biological systems – such as the relationship between the sequence, structure and function of genes and proteins”. We then examine the definitions according to dictionaries and organisations. The Oxford English Dictionary defines Bioinformatics as “the science of collecting and analysing complex biological data such as genetic codes”. According to NIH, Bioinformatics is defined as “research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data”. The National Center for Biotechnology Information, defines Bioinformatics as “the field of science in which biology, computer science, and information technology merge into a single discipline.” NCBI also notes three important sub-disciplines within Bioinformatics. The first is the development of new algorithms and statistics for accessing relationships among molecules of large data sets. The second is to analyse and interpret various data types. The outcome of these two is the integration of molecules into systems. This is also the basis of systems biology. The third is to develop and implement tools for efficient access and management of different types of information. This covers various web services and tools for public use. Both NIH and NCBI definitions cover a wide range of activities in Bioinformatics. I have no intention of giving a unique definition of Bioinformatics. First, this is unfair for a huge diversity of research interests and points of views in Bioinformatics. Second, the field of Bioinformatics is still progressing rapidly.
No longer available |Learn more- (Author)
- 2014(Publication Date)
- Learning Press(Publisher)
The primary goal of Bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques (e.g., pattern recognition, data mining, machine learning algorithms, and visualization) to achieve this goal. Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, genome-wide association studies and the modeling of evolution. Introduction Bioinformatics was applied in the creation and maintenance of a database to store biological information at the beginning of the genomic revolution, such as nucleotide and amino acid sequences. Development of this type of database involved not only design issues but the development of complex interfaces whereby researchers could both access existing data as well as submit new or revised data. In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of Bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within Bioinformatics and computational biology include: • the development and implementation of tools that enable efficient access to, and use and management of, various types of information. • the development of new algorithms (mathematical formulas) and statistics with which to assess relationships among members of large data sets, such as methods
eBook - PDFBioinformatics
Updated Features and Applications
- Ibrokhim Y. Abdurakhmonov(Author)
- 2016(Publication Date)
- IntechOpen(Publisher)
Presently, although still core for genomics and genetics field, Bioinformatics became an umbrella for wider range of biological studies analyzing variety types of biological data, structuring, systemizing, annotating, querying, mining, and visualizing available biological information and a variety of biomedical text records [1–3]. Although drawing a fine line between Bioinformatics and some other related fields is difficult because of increased appli‐ cations of computers, statistics, and mathematics to scientific problem solving and experiments of life sciences, there should not be a misperception about Bioinformatics description and objectives. Bioinformatics should not be mixed with, for example, biometry and biostatistics, development of DNA computers, or computerized generation and filing of data from imaging. Bioinformatics also should be differentiated from related scientific fields such as biological computation and computational biology [1, 2]. Biological computation aims to develop biological computers using advances of bioengineering, cybernetics, robotics, and molecular cell biology. In contrast, Bioinformatics develops and utilizes computational algorithms to understand and interpret biological processes based on genome-derived molecular sequences and their interactions [2 ]. Therefore, in many aspects, Bioinformatics seems similar to compu‐ tational biology objectives. A computational biology is concentrated on building and/or developing theoretical models for biological analyses [1, 2], whereas Bioinformatics focuses on providing practical tools to organize and analyze basic genomic, proteomic and other “omics” data, including sequence analysis and its visualization [1, 2]. Admittedly, computational biology and Bioinformatics both target to use genome data, for example, multiple sequence alignments and/or genome assembly tools.
eBook - PDFOMICS
Biomedical Perspectives and Applications
- Debmalya Barh, Kenneth Blum, Margaret A. Madigan, Debmalya Barh, Kenneth Blum, Margaret A. Madigan(Authors)
- 2016(Publication Date)
- CRC Press(Publisher)
36 25 Bioinformatics databases for efficient and successful running of a biological project. Good examples are devel-opments in the field of omics involving handling, processing, and analyzing large-scale genomic data arising from various genome-sequencing projects. Bioinformatics precision extends beyond the study of genes and pathways to include the study of drug targets and therapeutic drugs. The strength of Bioinformatics resides in its ability to link diverse research and academic fields such as molecular biology, genetics, biochemistry, clinical genetics, molecular diagnostics, phar-macogenomics, biomedical informatics, mathematics, statistics, informatics, artificial intelligence, physics, chemistry, medicine, and biology, making it an interdisciplinary field (Figure 2.1). Hence, the field of Bioinformatics can be seen as a fine amalgamation of various disciplines. Bioinformatics is a dynamic and rapidly developing branch of modern science that has the capability to change the rule of thumb of biology: predictions are not based on general principles (Lake and Moore, 1998; Howard, 2000; Rashidi and Buehler, 2000). Bioinformatics tools are widely used by the scientific community for a variety of tasks includ-ing comparison of biological sequences, establishing ancestral relationship, structure prediction of a biomolecule, primer designing, genome-map construction, restriction-map construction, high-throughput data analysis, pathway analysis, and in silico drug designing. 2.2 UNIQUENESS OF Bioinformatics Successful running of an in silico analysis (Bioinformatics-based analysis) to decode the language of biomolecules requires modest hardware, and most Bioinformatics tools and biological reposito-ries are freely accessible. The results obtained through the in silico analysis unarguable cut down in laboratory time and cost. The efficiency of the Bioinformatics analysis is increased several-fold when linked to different repositories.
- Abhirup Khanna, May El Barachi, Sapna Jain, Manoj Kumar, Anand Nayyar(Authors)
- 2024(Publication Date)
- Wiley-Scrivener(Publisher)
In the field of Bioinformatics, genetic sequences, protein samples, cell populations, and even photographs of biomedical conditions can all be analyzed. The objective of Bioinformatics is to analyze and make sense of the information struc- tures underlying biological processes. The fields of genomics and genetics make substantial use of Bioinformatics. Using the information obtained through sequencing, Bioinformatics allows for the assembly, alignment, and annotation of genomes as well as the discovery of genes and regulatory elements and the construction of phylogenies. The fields of functional genomics, structural genomics, proteomics, biotechnology, and medicines all benefit greatly from the application of Bioinformatics. It is helpful in the formulation of pharmaceuticals, the production of vaccines, the investigation of metabolic pathways, the interpretation of genetic variations, and the forecasting of protein structures. Therefore, the field of Bioinformatics is an expanding one that plays an essential role in biological research. Both basic biological research and medical treatment are increasingly dependent on the data and computations provided by Bioinformatics. The field of bioinfor- matics may lead to the discovery of new living systems, which would aid in the treatment of sickness and contribute to an overall improvement in the quality of life in the future. This chapter provides an introduction to Bioinformatics, which is the intersection of biology and computation. The exponential growth of biological data that has been created over the past few decades by technology and our increased understanding of biological systems has necessitated the development of novel methods for its storage, management, and analysis. Because of this desire, the field of Bioinformatics developed. The chapter dis- cusses the storing, distributing, and analyzing of data in the field of Bioinformatics.
eBook - PDFBioinformatics Basics
Applications in Biological Science and Medicine
- Lukas K. Buehler, Hooman H. Rashidi, Lukas K. Buehler, Hooman H. Rashidi(Authors)
- 2005(Publication Date)
- CRC Press(Publisher)
1 1 Biology and Information 1.1 Bioinformatics—A Rapidly Maturing Science Bioinformatics is a rapidly growing field within the biological sciences. It dates back to the 1960s following the discovery of the DNA double helix, when cracking the genetic code allowed for the ability to treat genes as strings of information that guide the building of cellular components, the faithful reproduction of an organism’s form and function, and its ability to evolve. Today, Bioinformatics is driven by the challenge of integrating the large amount of genetic and structural data emanating from biomed-ical research. Using computational power bioinformaticians catalog and FIGURE 1.1 Chapter overview. Biology and Information Bioinformatics: a Rapidly Maturing Science Computers in Biology and Medicine Biological Macromolecules as Information Carriers From Genes to Proteins Bioinformatics in the Public Domain Computational Tools The Virtual Doctor Proteins: From Sequence to Structure to Function DNA and RNA Structure DNA Cloning and Sequencing Genes, Taxonomy, and Evolution 2 Bioinformatics Basics: Applications in Biological Science and Medicine compare genetic and structural information with biochemical, physiolog-ical, and medical data furthering our understanding of the cellular orga-nization of life, its diversity, and the fact that all modern organisms are the children of a common ancestral cell. 1.1.1 From Genes to Proteins Reflecting upon the complexity of living organisms and the many different ways man studies life, the term “Bioinformatics” refers to the task of orga-nizing, analyzing, and predicting increasingly complex data arising from mod-ern molecular and biochemical techniques. For some the meaning extends to the concept of information flow within biological systems alluding to the transmission of genetically encoded information transmitted from genes to proteins, from the blueprint to the machinery of life.
eBook - PDF- Jewell, C K(Authors)
- 2018(Publication Date)
- Agri Horti Press(Publisher)
In the case of the eyeless and aniridia genes, scientists hope that studying the role of the eyeless gene in Drosophila eye development will help us understand how aniridia works in human eye development. Bioinformatics ABOUT BUILDING DATABASES Much of what we currently think of as part of Bioinformatics--sequence comparison, sequence database searching, sequence analysis--is more complicated than just designing and populating databases. Bioinformaticians (or computational biologists) go beyond just capturing, managing, and presenting data, drawing inspiration from a wide variety of quantitative fields, including statistics, physics, computer science, and engineering. Shows how quantitative science intersects with biology at every level, from analysis of sequence data and protein structure, to metabolic modeling, to quantitative analysis of populations and ecology. This ebook is exclusively for this university only. Cannot be resold/distributed. 48 Handbook of Bioinformatics Fig . How Technology Intersects with Biology Bioinformatics is first and foremost a component of the biological sciences. The main goal of Bioinformatics isn't developing the most elegant algorithms or the most arcane analyses; the goal is finding out how living things work. Like the molecular biology methods that greatly expanded what biologists were capable of studying, Bioinformatics is a tool and not an end in itself. Bioinformaticians are the tool-builders, and it's critical that they understand biological problems as well as computational solutions in order to produce useful tools. Research in Bioinformatics and computational biology can encompass anything from abstraction of the properties of a biological system into a mathematical or physical model, to implementation of new algorithms for data analysis, to the development of databases and web tools to access them.
eBook - PDF- Enrico Coiera(Author)
- 2015(Publication Date)
- CRC Press(Publisher)
Bioinformatics Molecular biology produces vast quantities of data about the genetic and functional state of organisms. Advancements in genetic sequencing methods quickly moved from the study of individual genes to the whole genomes of organisms, with decoding of their structure and function. The small genome of the pathogenic bacterium Haemophilus influenzae was the first whole genome of a living organism to be completely sequenced. Only small viral genomes and parts of other genomes had been sequenced before that point. Inspired by this success, scientists embarked on the task of sequencing and analyzing much larger and the more complex genomes of multicellular organisms such as the fruit fly Drosophila melano-gaster, the round worm and, subsequently, the human genome. Bioinformatics (or computational biology) was born out of such genome sequencing pro-jects. It was originally limited to developing algorithms that automated the analysis of gene sequences, but it has expanded to supporting the analysis of many other elements of cell biol-ogy (Box 30.1). Indeed, Bioinformatics is now an essential part of the biomedical ‘workbench’, providing computational tools for the storage of biological data and for data integration, visualization and analysis. Biology and Bioinformatics now advance in synergy with each other, and together they have dramatically increased our ability to observe and analyze the living world at the molecular level. We now recognize just how different each human, each cancer and each infectious pathogen are and can exploit these individual molecular signa-tures to treat disease more effectively. Initially, Bioinformatics and health informatics were seen as separate disciplines because their research subjects and communities did not overlap. However, they use very similar methodologies, and both require access to phenotypic data stored in the patient record.
eBook - PDF- Emmanuel Barillot, Laurence Calzone, Philippe Hupe, Jean-Philippe Vert, Andrei Zinovyev(Authors)
- 2012(Publication Date)
- CRC Press(Publisher)
Chapter 4 Bioinformatics tools and standards for systems biology Systems biology relies heavily on a number of preliminary steps for prepar-ing high-throughput experiments and making the results readily available for biological analysis and modelling. Though these steps are not per se part of what we commonly define as systems biology, they are essential for enabling the systems biology approach (Ghosh et al., 2011). Therefore, this chapter presents an overview of Bioinformatics tools and standards used in a typi-cal analysis workflow Figure 4.1 which includes the following steps. Once the biological and/or clinical question is posed ( ˚ ), an experimental design is defined in order to efficiently answer the problem raised ( ¸ ). Then, the high-throughput experiments are performed ( ). A scanner generally analyses the microarray * , sequencing slides or phenotyping screening, and produces images which are processed using appropriate algorithms to quantify the raw signal ( ˝ ). This step is followed by normalisation which aims at correcting the systematic sources of variability in order to improve the signal-to-noise ratio ( ˛ ). The quality of data is checked at the level of both the image analysis and the normalisation steps ( ˇ ). At this stage, the information provided after normalisation is still rough. The meaningful biological information relevant for biologists must be extracted from the data ( — ). Once the relevant information is extracted, the data can be used in a transversal analysis to perform clinical biostatistics, classification or systems biology approaches ( ). Finally, the re-sults need to be validated, interpreted and can lead to new experiments ( ). The Bioinformatics workflow and computational systems biology approach are cyclical processes involving data acquisition and preprocessing, modelling and analysis.
eBook - PDFSystems and Computational Biology
Bioinformatics and Computational Modeling
- Ning-Sun Yang(Author)
- 2011(Publication Date)
- IntechOpen(Publisher)
Finally, the growing number of proteomic data repositories and emerging data standards developed for the field are highlighted. These tools and technologies point the way towards the next phase of experimental proteomic and informatics challenges that the proteomics community will face. The majority of the chapter is devoted to the description of Bioinformatics technologies (hardware and data management and applications) with particular emphasis on the Bioinformatics improvements that have made possible to obtain significant results in the study of proteomics. Particular attention is focused on the emerging statistic semantic, network learning technologies and data sharing that is the essential core of system biology data elaboration. Finally, many examples of Bioinformatics applied to biological systems are distributed along the different section of the chapter so to lead the reader to completely fill and understand the benefits of Bioinformatics applied to system biology. 2. Genomics versus proteomics There have been two major diversification paths appeared in the development of Bioinformatics in terms of project concepts and organization, the -omics and the bio-. These two historically reflect the general trend of modern biology. One is to go into molecular level resolution. As one of the -omics and bio- proponents, the -omics trend is one of the most important conceptual revolutions in science. Genetic, microbiology, mycology and agriculture became effectively molecular biology since 1970s. At the same time, these fields are now absorbing omics approach to understand their problems more as complex systems. Omics is a general term for a broad discipline of science and engineering for analyzing the interactions of biological information objects in various omes. These include genome, proteome, metabolome, expressome, and interactome.
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