Genomics in the context of Biological database

A genome is all the genetic information of an organism or cell. It consists of nucleotide sequences of DNA (or RNA in RNA viruses). The nuclear genome includes protein-coding genes and non-coding genes, other functional regions of the genome such as regulatory sequences (see non-coding DNA), and often a substantial fraction of junk DNA with no evident function. Almost all eukaryotes have mitochondria and a small mitochondrial genome. Algae and plants also contain chloroplasts with a chloroplast genome.

The study of the genome is called genomics. The genomes of many organisms have been sequenced and various regions have been annotated. The first genome to be sequenced was that of the virus φX174 in 1977; the first genome sequence of a prokaryote (Haemophilus influenzae) was published in 1995; the yeast (Saccharomyces cerevisiae) genome was the first eukaryotic genome to be sequenced in 1996. The Human Genome Project was started in October 1990, and the first draft sequences of the human genome were reported in February 2001.

Bioinformatics (/ˌbaɪ.oʊˌɪnfərˈmætɪks/ ) is an interdisciplinary field of science that develops computational methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, data science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. This process can sometimes be referred to as computational biology, however the distinction between the two terms is often disputed. To some, the term computational biology refers to building and using models of biological systems.

Computational, statistical, and computer programming techniques have been used for computer simulation analyses of biological queries. They include reused specific analysis "pipelines", particularly in the field of genomics, such as by the identification of genes and single nucleotide polymorphisms (SNPs). These pipelines are used to better understand the genetic basis of disease, unique adaptations, desirable properties (especially in agricultural species), or differences between populations. Bioinformatics also includes proteomics, which aims to understand the organizational principles within nucleic acid and protein sequences.

Human genetics is the study of inheritance as it occurs in human beings. Human genetics encompasses a variety of overlapping fields including: classical genetics, cytogenetics, molecular genetics, biochemical genetics, genomics, population genetics, developmental genetics, clinical genetics, and genetic counseling.

Genes are the common factor of the qualities of most human-inherited traits. Study of human genetics can answer questions about human nature, can help understand diseases and the development of effective treatment and help us to understand the genetics of human life. This article describes only basic features of human genetics; for the genetics of disorders please see: medical genetics. For information on the genetics of DNA repair defects related to accelerated aging and/or increased risk of cancer please see: DNA repair-deficiency disorder.

Personalized medicine, also referred to as precision medicine or systems medicine, is a medical model that separates people 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 organizations differentiate between these expressions based on particular nuances. P4 is short for "predictive, preventive, personalized and participatory".

While the tailoring of treatment to patients dates back at least to the time of Hippocrates, the usage of the term has risen in recent years thanks to the development of new diagnostic and informatics approaches that provide an understanding of the molecular basis of disease, particularly genomics. This provides a clear biomarker on which to stratify related patients.

Predictive medicine is a field of medicine that entails predicting the probability of disease and instituting preventive measures in order to either prevent the disease altogether or significantly decrease its impact upon the patient (such as by preventing mortality or limiting morbidity).

While different prediction methodologies exist, such as genomics, proteomics, and cytomics, the most fundamental way to predict future disease is based on genetics. Although proteomics and cytomics allow for the early detection of disease, much of the time those detect biological markers that exist because a disease process has already started. However, comprehensive genetic testing (such as through the use of DNA arrays or full genome sequencing) allows for the estimation of disease risk years to decades before any disease even exists, or even whether a healthy fetus is at higher risk for developing a disease in adolescence or adulthood. Individuals who are more susceptible to disease in the future can be offered lifestyle advice or medication with the aim of preventing the predicted illness.

A bacteriologist is a microbiologist, or similarly trained professional, in bacteriology— a subdivision of microbiology that studies bacteria, typically pathogenic ones. Bacteriologists are interested in studying and learning about bacteria, as well as using their skills in clinical settings. This includes investigating properties of bacteria such as morphology, ecology, genetics and biochemistry, phylogenetics, genomics and many other areas related to bacteria like disease diagnostic testing. Alongside human and animal healthcare providers, they may carry out various functions as medical scientists, veterinary scientists, pathologists, or diagnostic technicians in locations like clinics, blood banks, hospitals, laboratories and animal hospitals. Bacteriologists working in public health or biomedical research help develop vaccines for public use as well as public health guidelines for restaurants and businesses.

A biobank is a type of biorepository that stores biological samples (usually human) for use in research. Biobanks have become an important resource in medical research, supporting many types of contemporary research like genomics and personalized medicine.

Biobanks can give researchers access to data representing a large number of people. Samples in biobanks and the data derived from those samples can often be used by multiple researchers for cross purpose research studies. For example, many diseases are associated with single-nucleotide polymorphisms. Genome-wide association studies using data from tens or hundreds of thousands of individuals can identify these genetic associations as potential disease biomarkers. Many researchers struggled to acquire sufficient samples prior to the advent of biobanks.

In evolutionary biology, conserved sequences are identical or similar sequences in nucleic acids (DNA and RNA) or proteins across species (orthologous sequences), or within a genome (paralogous sequences), or between donor and receptor taxa (xenologous sequences). Conservation indicates that a sequence has been maintained by natural selection.

A highly conserved sequence is one that has remained relatively unchanged far back up the phylogenetic tree, and hence far back in geological time. Examples of highly conserved sequences include the RNA components of ribosomes present in all domains of life, the homeobox sequences widespread amongst eukaryotes, and the tmRNA in bacteria. The study of sequence conservation overlaps with the fields of genomics, proteomics, evolutionary biology, phylogenetics, bioinformatics and mathematics.

Genetic testing, also known as DNA testing, is used to identify changes in DNA sequence or chromosome structure. Genetic testing can also include measuring the results of genetic changes, such as RNA analysis as an output of gene expression, or through biochemical analysis to measure specific protein output. In a medical setting, genetic testing can be used to diagnose or rule out suspected genetic disorders, predict risks for specific conditions, or gain information that can be used to customize medical treatments based on an individual's genetic makeup. Genetic testing can also be used to determine biological relatives, such as a child's biological parentage (genetic mother and father) through DNA paternity testing, or be used to broadly predict an individual's ancestry. Genetic testing of plants and animals can be used for similar reasons as in humans (e.g. to assess relatedness/ancestry or predict/diagnose genetic disorders), to gain information used for selective breeding, or for efforts to boost genetic diversity in endangered populations.

The variety of genetic tests has expanded throughout the years. Early forms of genetic testing which began in the 1950s involved counting the number of chromosomes per cell. Deviations from the expected number of chromosomes (46 in humans) could lead to a diagnosis of certain genetic conditions such as trisomy 21 (Down syndrome) or monosomy X (Turner syndrome). In the 1970s, a method to stain specific regions of chromosomes, called chromosome banding, was developed that allowed more detailed analysis of chromosome structure and diagnosis of genetic disorders that involved large structural rearrangements. In addition to analyzing whole chromosomes (cytogenetics), genetic testing has expanded to include the fields of molecular genetics and genomics which can identify changes at the level of individual genes, parts of genes, or even single nucleotide "letters" of DNA sequence. According to the National Institutes of Health, there are tests available for more than 2,000 genetic conditions, and one study estimated that as of 2018 there were more than 68,000 genetic tests on the market.

The human microbiome is the aggregate of all microbiota that reside on or within human tissues and biofluids along with the corresponding anatomical sites in which they reside, including the gastrointestinal tract, skin, mammary glands, seminal fluid, uterus, ovarian follicles, lung, saliva, oral mucosa, ocular surface, and the biliary tract. Types of human microbiota include bacteria, archaea, fungi, protists, and viruses. Though micro-animals can also live on the human body, they are typically excluded from this definition. In the context of genomics, the term human microbiome is sometimes used to refer to the collective genomes of resident microorganisms; however, the term human metagenome has the same meaning.

The human body hosts many microorganisms, with approximately the same order of magnitude of non-human cells as human cells. Some microorganisms that humans host are commensal, meaning they co-exist without harming humans; others have a mutualistic relationship with their human hosts. Conversely, some non-pathogenic microorganisms can harm human hosts via the metabolites they produce, like trimethylamine, which the human body converts to trimethylamine N-oxide via FMO3-mediated oxidation. Certain microorganisms perform tasks that are known to be useful to the human host, but the role of most of them is not well understood. Those that are expected to be present, and that under normal circumstances do not cause disease, are sometimes deemed normal flora or normal microbiota.

The United States Department of Energy (DOE) is an executive department of the U.S. federal government that oversees U.S. national energy policy and energy production, the research and development of nuclear power, the military's nuclear weapons program, nuclear reactor production for the United States Navy, energy-related research, and energy conservation.

The DOE was created in 1977 in the aftermath of the 1973 oil crisis. It sponsors more physical science research than any other U.S. federal agency, the majority of which is conducted through its system of National Laboratories. The DOE also directs research in genomics, with the Human Genome Project originating from a DOE initiative.

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Sanford Burnham Prebys is an American nonprofit biomedical research institute located in La Jolla, California, conducting biomedical and translational research, including stem cell and drug discovery studies. It operates a National Cancer Institute-designated Cancer Center and conducts genomics research.

Omics is the collective characterization and quantification of entire sets of biological molecules and the investigation of how they translate into the structure, function, and dynamics of an organism or group of organisms. The branches of science known informally as omics are various disciplines in biology whose names end in the suffix -omics, such as genomics, proteomics, metabolomics, metagenomics, phenomics and transcriptomics.

The related suffix -ome is used to address the objects of study of such fields, such as the genome, proteome or metabolome respectively. The suffix -ome as used in molecular biology refers to a totality of some sort; it is an example of a "neo-suffix" formed by abstraction from various Greek terms in -ωμα, a sequence that does not form an identifiable suffix in Greek.

Public health genomics is the use of genomics information to benefit public health. This is visualized as more effective preventive care and disease treatments with better specificity, tailored to the genetic makeup of each patient. According to the Centers for Disease Control and Prevention (U.S.), Public Health genomics is an emerging field of study that assesses the impact of genes and their interaction with behavior, diet and the environment on the population's health.

This field of public health genomics is less than a decade old. A number of think tanks, universities, and governments (including the U.S., UK, and Australia) have started public health genomics projects. Research on the human genome is generating new knowledge that is changing public health programs and policies. Advances in genomic sciences are increasingly being used to improve health, prevent disease, educate and train the public health workforce, other healthcare providers, and citizens.

Phylogenomics is the intersection of the fields of evolution and genomics. The term has been used in multiple ways to refer to analysis that involves genome data and evolutionary reconstructions. It is a group of techniques within the larger fields of phylogenetics and genomics. Phylogenomics draws information by comparing entire genomes, or at least large portions of genomes. Phylogenetics compares and analyzes the sequences of single genes, or a small number of genes, as well as many other types of data. Four major areas fall under phylogenomics:

• Prediction of gene function
• Establishment and clarification of evolutionary relationships
• Gene family evolution
• Prediction and retracing lateral gene transfer.

The ultimate goal of phylogenomics is to reconstruct the evolutionary history of species through their genomes. This history is usually inferred from a series of genomes by using a genome evolution model and standard statistical inference methods (e.g. Bayesian inference or maximum likelihood estimation).

Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Messenger RNA (mRNA), gene expression data, and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism. There are indeed quantifiable correlations between the metabolome and the other cellular ensembles (genome, transcriptome, proteome, and lipidome), which can be used to predict metabolite abundances in biological samples from, for example mRNA abundances. One of the ultimate challenges of systems biology is to integrate metabolomics with all other -omics information to provide a better understanding of cellular biology.

Riken (Japanese: 理研; English: /ˈrɪkɛn/; stylized in all caps as RIKEN) is a national scientific research institute in Japan. Founded in 1917, it now has about 3,000 scientists on seven campuses across Japan, including the main site at Wakō, Saitama Prefecture, on the outskirts of Tokyo. Riken is a Designated National Research and Development Institute, and was formerly an Independent Administrative Institution.

Riken conducts research in various fields of science, including physics, chemistry, biology, genomics, medical science, engineering, high-performance computing and computational science, and ranging from basic research to practical applications with 485 partners worldwide. It is almost entirely funded by the Japanese government, with an annual budget of ¥100 billion (US$750 million) in FY2023.

Shiladitya DasSarma (born November 11, 1957) is an Indian-American molecular biologist well-known for contributions to the biology of halophilic and extremophilic microorganisms. He is a Professor in the University of Maryland Baltimore. He earned a PhD degree in biochemistry from the Massachusetts Institute of Technology and a BS degree in chemistry from Indiana University Bloomington. Prior to taking a faculty position, he conducted research at the Massachusetts General Hospital, Harvard Medical School, and Pasteur Institute, Paris.

DasSarma has served on the faculty of the University of Massachusetts Amherst (1986-2001), University of Maryland Biotechnology Institute (2001-2010), and University of Maryland School of Medicine, Institute of Marine and Environmental Technology (2010–present). He is a researcher and teacher of molecular genetics, genomics, and bioinformatics and mentor of undergraduate, graduate and postdoctoral students, and junior faculty. He is widely known to have been instrumental in the foundation of the fields of halophile and extremophile research.

Pharmacogenomics, often abbreviated "PGx", is the study of the role of the genome in drug response. Its name (pharmaco- + genomics) reflects its combining of pharmacology and genomics. Pharmacogenomics analyzes how the genetic makeup of a patient affects their response to drugs. It deals with the influence of acquired and inherited genetic variation on drug response, by correlating DNA mutations (including point mutations, copy number variations, and structural variations) with pharmacokinetic (drug absorption, distribution, metabolism, and elimination), pharmacodynamic (effects mediated through a drug's biological targets), and immunogenic endpoints.

Pharmacogenomics aims to develop rational means to optimize drug therapy, with regard to the patients' genotype, to achieve maximum efficiency with minimal adverse effects. It is hoped that by using pharmacogenomics, pharmaceutical drug treatments can deviate from what is dubbed as the "one-dose-fits-all" approach. Pharmacogenomics also attempts to eliminate trial-and-error in prescribing, allowing physicians to take into consideration their patient's genes, the functionality of these genes, and how this may affect the effectiveness of the patient's current or future treatments (and where applicable, provide an explanation for the failure of past treatments). Such approaches promise the advent of precision medicine and even personalized medicine, in which drugs and drug combinations are optimized for narrow subsets of patients or even for each individual's unique genetic makeup.