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Site Map annotation: Bioinformatics glossary behavior genetics, behavior genomics: Clinical genomics glossary Beyond Genome, June 20-22, 2007, San Francisco, California biochemical genomics: Chemistry & biology glossary biocomplexity: is concerned with the complex behavioral, biological, social, chemical, and physical interactions of living organisms with their environment. Both the term and the research field are relatively new and encompass other domains like biodiversity, ecology etc.. The aim of biocomplexity research is to discover, access, interpret, integrate and analyze complex ecological data. Wikipedia http://en.wikipedia.org/wiki/Biocomplexity Broader terms: complex, complexity cancer genomics: Cancer genomics glossary chemical genomics, chemogenomics: Chemistry & biology glossary comparative genome mapping: Maps glossary comparative genomics: Functional genomics glossary. completed genomes: This depends to an extent on how you define "complete". Portions of the human genome are unsequenceable with today's technology. Related term: Human Genome Project HGP- completion Completed genomes links
Related term: Sequences, DNA & beyond finished sequence complex: It has become common to use complicated and complex interchangeably … The essence of ‘complicated’ is hard to figure out. ..Complex, on the other hand is a term reserved for systems that display properties that are not predictable from a complete description of their components, and that are generally considered to be qualitatively different from the sum of their parts. [Editorial, "Complicated is not complex" Nature Biotechnology 17: 511 June 1999] Would it be fair to say that Mendelian genetics is linear, while genomics and polygenic diseases/traits are nonlinear? According to the Oxford English Dictionary one of the meanings of complicated is complex, though it also means not easy to unravel or separate. Both complex and complicated are contrasted with simple. Whatever the original senses of these two words, the above distinction seems a useful one now. Related term: complexity; Narrower terms: biocomplexity, complex diseases, complex genomes; complex phenotypes, complex traits complex diseases: Diseases characterized by risk to relatives of an affected individual which is greater than the incidence of the disorder in the population. [NHLBI] Are complex diseases essentially the same as polygenic diseases? Genome scans for other complex diseases have met with limited success, in part because of the difficulty in detecting the small individual contribution to phenotype made by many different genes. Recent theoretical work suggests that this problem may be circumvented by performing association tests with a large number of markers (on the order of 30,000) spread across the genome. To make such a large number of tests feasible, one needs markers that can be scored without resorting to gel- based techniques, and this has led to intense interest in developing methods to identify and detect single- nucleotide polymorphism markers or SNPs. SNPs are typically biallelic markers that differ from each other by one nucleotide (this difference can be a transition, transversion or even a deletion). There are several techniques available to score SNPs, and we are exploring the use of the 5' nuclease- detection system or TaqMan to score SNPs. ["Human genetics" David Botstein Lab, Stanford Univ.] http://genome-www.stanford.edu/group/botlab/humans.html Related terms: Genetic variations glossary; Omes & omics phenome, phenomics complex genomes: Is there a specific definition of complex genomes? Or is it a more general category (beyond viral, bacterial, microbial?) complex phenotypes: Those that exhibit familial clustering, which may mean that there is some genetic component, but that do not occur in Mendelian proportions in pedigrees. Complex phenotypes may be continuous in distribution, like height or blood pressure, or they may be dichotomous, like affected and not affected. The complexity arises from the fact one cannot accurately predict the expression of the phenotype from knowledge of the individual effects of individual factors considered alone, no matter how well understood each separate component may be. Genetic Architecture, Biological Variation and Complex Phenotypes, PA-02-110, May 29, 2002- June 5, 2005 http://grants1.nih.gov/grants/guide/pa-files/PA-02-110.html complex trait: Has a genetic component that is not strictly Mendelian (dominant, recessive, or sex linked) and may involve the interaction of two or more genes to produce a phenotype, or may involve gene environment interactions." [NHLBI] Related term: genetic architecture complexity:: Currently there are more than 30 different mathematical descriptions of complexity. However we have yet to understand the mathematical dependency relating the number of genes with organism complexity. [J. Craig Venter et. al. "The sequence of the Human Genome" Science 291 (5507): 1347, Feb. 16, 2001] Complexity Science comprises a toolset that examines large scale behaviors of complex systems by looking at how individual components of those systems interact with each other and their environment. From these interactions novel behaviors emerge. Stuart Kauffman http://www.santafe.edu/sfi/People/kauffman/ An ill- defined term that means many things to many people. Complex things are neither random nor regular, but hover somewhere in between. Intuitively, complexity is a measure of how interesting something is. Other types of complexity may be well defined. [Gary William Flake, Computational Beauty of Nature: Computer Explorations of Fractals, Chaos, Complex Systems, and Adaptation, MIT Press, 1998] http://mitpress.mit.edu/books/FLAOH/cbnhtml/glossary-C.html#complexity Complexity resources http://www.comdig.org/ Related term: complex Narrower terms: biocomplexity, biological complexity computational genomics: Computers & computing glossary DDBJ DNA DataBank of Japan: Shares information daily with EMBL and GenBank. http://www.ddbj.nig.ac.jp/ DNA forensics: DNA glossary DOE Department of Energy: Human Genome Initiative announced by DOE OHER [Office of Health and Environmental Research] in 1986. Congressionally chartered DOE advisory committee, HERAC [Health and Environmental Research Advisory Committee], recommended a 15 year multidisciplinary, scientific, and technological undertaking to map and sequence the human genome in 1987. DOE and NIH outlined plans for cooperation on genome research in 1988. [Oak Ridge National Laboratory (ORNL), Tennessee, US "Major events in the US Human Genome Project"] http://www.ornl.gov/hgmis/project/timeline.html Genome Project: Why the DOE?, Oak Ridge National Lab, US, 1997] http://www.ornl.gov/hgmis/publicat/tko/02_why.html deductive genomics: Functional Genomics glossary. druggable genome: Drug discovery & development glossary ecotoxicogenomics: Pharmacogenomics glossary EMBL (European Molecular Biology Laboratory: Main laboratory is in Heidelberg, Germany, with outstations in Hamburg, Grenoble, France (access to high powered instruments for structure studies) and Hinxton, UK (bioinformatics). Supported by 14 European countries and Israel, shares data daily with DDBJ and GenBank. http://www.embl-heidelberg.de/ evolutionary genomics: Functional Genomics glossary. expression genomics: Expression glossary extreme phenotype selection studies: http://www3.interscience.wiley.com/cgi-bin/abstract/98516956/ABSTRACT Broader term: phenotype forward genetics, forward genomics: Genetic manipulation & disruption glossary function, functional genomics: Functional Genomics glossary. funding of genomic research: Financial glossary GenBank: Located at NCBI, shares information daily with DDBJ and EMBL. NIH genetic sequence database, an annotated collection of all publicly available DNA sequences. Currently estimated (early 2000) that over 2 million bases are deposited here each day. This growth will only accelerate in the future. http://www.ncbi.nlm.nih.gov/Genbank/index.html Now accommodates > 10 10 nucleotides and more than doubles in size every year. [David Roos "Bioinformatics -- Trying to Swim in a Sea of Data" Science 291:1260-1261 Feb. 16, 2001] gene: Gene definitions genetic architecture: Refers to the full range of genetic effects on a trait; however, when studying variation on such a large [genomic] scale, it is especially important to consider the context or environments in which genetic variation arises, is selected, and is maintained. Genetic architecture is less a fixed property of the phenotype than a characteristic of a phenotype in a particular population. Genetic architecture is a moving target that changes according to gene and genotype frequencies, distributions of environmental factors, and such biological properties as age and sex. Genetic Architecture, Biological Variation and Complex Phenotypes, PA-02-110, May 29, 2002- June 5, 2005 http://grants1.nih.gov/grants/guide/pa-files/PA-02-110.html genetic privacy: Genetics Privacy and Legislation, HGMIS, DOE, US http://www.ornl.gov/TechResources/Human_Genome/elsi/legislat.html genetic variations, human: SNPs & Genetic variations glossary genetics: Clinical genomics and Molecular Medicine See also Basic genetics & genomics genome: The complete set of chromosomal and extrachromosomal genes of an organism, a cell, an organelle or a virus; the complete DNA component of an organism. [IUPAC Biotech] The fundamental concepts of genome, genotype and phenotype are not defined in a satisfactory manner within the biological literature. Not only are there inconsistencies in usage between various authors, but even individual authors do not use these concepts in a consistent manner within their own writings. We have found at least five different notions of genome, seven of genotype, and five of phenotype current in the literature. Our goal is to clarify this situation by (a) defining clearly and precisely the notions of genetic complement, genome, genotype, phenetic complement, and phenotype; (b) examining that of phenome; and (c) analysing the logical structure of this family of concepts. [M. Mahner, M. Kary "What exactly are genomes, genotypes and phenotypes? And what about phenomes?" Journal of Theoretical Biology 186 (1): 55- 63, May 1997] All the DNA contained in an organism or a cell, which includes both the chromosomes within the nucleus and the DNA in mitochondria. [NHGRI] Size expressed by the number of base pairs. [DOE]. First used by H. Winkler in 1920, was created by elision of the words GENes and chromosOMEs, and that is what the term signifies: the complete set of chromosomes and their genes. [V McKusick "Genomics: Structural and Functional studies of genomes" Genomics 45:244-249 Oct. 15 1997] Google = Sept. 8, 2003 genome about 7,479,000, genomes about 619,000
Genome databases:
Databases & software
directory Narrower terms: Gene Definitions chromosomal genome, mitochondrial genome, nuclear genome genome browser: As vertebrate genome sequences near completion and research re- focuses on their analysis, the issue of effective sequence display becomes critical: it is not helpful to have 3 billion letters of genomic DNA shown as plain text. As an alternative, the UCSC Genome Browser provides a rapid and reliable display of any requested portion of genomes at any scale, together with dozens of aligned annotation tracks (known genes, predicted genes, ESTs, mRNAs, CpG islands, assembly gaps and coverage, chromosomal bands, mouse homologies, and more). ...The Genome Browser stacks annotation tracks beneath genome coordinate positions, allowing rapid visual correlation of different types of information. The user can look at a whole chromosome to get a feel for gene density, open a specific cytogenetic band to see a positionally mapped disease gene candidate, or zoom in to a particular gene to view its spliced ESTs and possible alternative splicing. The Genome Browser itself does not draw conclusions; rather, it collates all relevant information in one location, leaving the exploration and interpretation to the user. [What does the Genome Browser do? UCSC Genome Browser, Univ. of California - Santa Cruz, US] http://genome.cse.ucsc.edu/goldenPath/help/hgTracksHelp.html#What Ensembl
Genome browser http://www.ensembl.org/index.html genome components: The parts of a GENOME sequence that carry out the different functions of genomes. MeSH, 2003 genome database mining: The identification of the protein- encoding regions of a genome and the assignment of functions to these genes on the basis of sequence similarity homologies against other genes of known function. [John L. Houle et. al., White Paper: Database Mining in the Human Genome Initiative, AMITA Corp. 2000] http://www.biodatabases.com/whitepaper01.html Related terms: Expression, genes & beyond: gene expression database mining; Proteomics glossary: proteome database mining genome display: Related term: genome visualization genome informatics: The Twelfth International Conference on Genome Informatics (GIW 2001) focuses on Genome Informatics, including, but not limited to, the following areas: genomic database, knowledge extraction from literature, knowledge discovery and data mining from databases, structural genomics, protein structure and function prediction, proteome analysis, pathway analysis, functional genomics, gene expression analysis, gene network analysis, gene structure and function prediction, sequence analysis, motif extraction and search, multiple alignment, phylogenetic tree, linkage analysis program, systems for supporting experimental works (mapping, sequencing, primer design, etc.), high performance computing, simulation of biological system, DNA computing, artificial life, etc. [GIW 2001 homepage, Dec. 17-19, 2001, Tokyo, Japan] http://giw.ims.u-tokyo.ac.jp/giw2001/ Genome informatics can be divided into a few large categories: data acquisition and sequence assembly, database management, and genome analysis tools. ...Managing such a diverse informatics effort is a considerable challenge [JASON Program Office, Human Genome Project report "Genome Informatics" 1997] http://www.ornl.gov/hgmis/publicat/miscpubs/jason/informat.html genome map: Maps & mapping glossary genome properties: An emerging area of research focuses on how properties of genomes arise in evolutionary history. Such research has important consequences for understanding genome organization and for interpreting data on genetic and phenotypic variation. Such research could include the evolution of haplotypes, selection for genetic interactions, and the evolution of recombination and methylation patterns. Genetic Architecture, Biological Variation and Complex Phenotypes, PA-02-110, May 29, 2002- June 5, 2005 http://grants1.nih.gov/grants/guide/pa-files/PA-02-110.html genome sequencing proposals - prioritization: Status of Organisms in the Prioritization Process for Genome Sequencing and their ‘White Paper’ Proposals. Links to proposals. NHGRI, National Human Genome Research Institute, US http://www.genome.gov/page.cfm?pageID=10002154 Genome Technology Program: Supports research to develop new methods, technologies and instruments that enable rapid, low-cost determination of DNA sequence, SNP genotyping, and functional genomics (broadly defined). http://www.genome.gov/page.cfm?pageID=10000368 genome visualization: New visualization techniques developed by scientists at Pacific Northwest National Laboratory (PNNL) allow researchers to compare and analyze genomes using a powerful tool that computers cannot replace — the human brain. By presenting a color-coded graphic representation of genomes, people can easily identify similarities and differences. This approach may help identify individual genes responsible for certain properties and characteristics. Computational Science and Engineering, Pacific Northwest National Lab, http://www.pnl.gov/cse/computersci/genome.htm A significant challenge for genome centers is to make the data being generated available to biologists in a succinct and meaningful way. We are addressing this problem by creating extensible, reusable graphical components specifically designed for developing genome visualization applications. With careful planning and design this toolkit enhances the ability for others and ourselves to rapidly develop genome visualization applications for the Internet and as editing applications. Data Visualization for Distributed Bioinformatics, Gregg Helt, Suzanna Lewis, Nomi Harris, Gerald M. Rubin, DOE Human Genome Program Contractor- Grantee Workshop VII, Jan. 12-16, 1999 Oakland, CA http://www.ornl.gov/TechResources/Human_Genome/publicat/99santa/92.html Related term: genome display genomic DNA: DNA glossary genomic data: The strength of genomic studies lies in the global comparisons between biological systems rather than detailed examination of single genes or proteins. Genomic information is often misused when applied exclusively to individual genes. If one is interested only in one particular genes, there are many more conclusive experiments that should be consulted before using the results from genomic datasets. Therefore, genomic data should not be used in lieu of traditional biochemistry, but as an initial guidelines to identify areas for deeper investigation and to see how those results fit in with the rest of the genome. Moreover, most genomics datasets give relative rather than absolute information, which means that information about a single gene has little meaning in isolation. [Dov Greenbaum, Mark Gerstein et. al. "Interrelating Different Types of Genomic Data" Dept. of Biochemistry and Molecular Biology, Yale Univ., 2001] http://bioinfo.mbb.yale.edu/e-print/omes-genomeres/text.pdf Related terms: Expression glossary; Omes & Omics glossary interactome; Proteomics glossary genomic instability: An increased tendency of the GENOME to acquire MUTATIONS when various processes involved in maintaining and replicating the genome are dysfunctional. MeSH, 2004 genomic - research: The definition of genomics is not precise. Tom Roderick coined the term, and Victor McKusick and Frank Ruddle used it to launch Genomics the journal in 1987. We follow their definition here, but leave interpretation to your discretion. We intend to include research that addresses all or a substantial portion of an organism’s genome (including a chromosome or chromosome segment, but not a localized gene or gene family). This definition includes positional cloning if it starts from genome- wide (or chromosome- specific) marker scans. We include physical mapping and sequencing of all or a large part of a genome or chromosome. We also include array technologies that monitor expression of very large numbers of genes (hundreds or thousands), and informatic tools primarily intended to interpret DNA sequence or map information on a genomic or chromosomal scale. Software for melding high- throughput sequencing information into contigs would be included, for example, but not software for pedigree construction alone, or translation to protein sequence or simple homology comparison. We include techniques for high- throughput sequencing or genome- scale mapping, but not research directed at one or a few alleles (e.g., a single- locus diagnostic test would be excluded, even if based on DNA sequencing). We acknowledge broad gray zones, and accept therefore that genomics research is what you say it is. [Robert Cooke- Deegan et. al., World Survey of Funding for Genomics Research: Final Report to the Global Forum for Health Research and the World Health Organization, September 2000] http://www.stanford.edu/class/siw198q/websites/genomics/finalrpt.htm Related term: funding of genomic research: Financial glossary genomic technologies: Include DNA synthesis, sequencing, genotyping, and expression profiling, proteomics (peptide synthesis, protein sequencing, and mass spectrometry), and imaging. Innovative technologies might include applications of nanobiotechnology, isolation, imaging, and characterization of single molecules. [Cornell Genomics Initiative, Enabling Group, Genomic Technologies, 2001- 2002] http://www.genomics.cornell.edu/focus_areas/technology/ One of the primary reasons for the success of the Human Genome Project has been the development and use of high- throughput strategies for data generation, and the placement of the data immediately in the public domain. Most of the sequence data, the underlying maps and the sequence assemblies were generated through the use of large- scale automated processes. Now, methods such as sequence analysis of whole genomes, DNA microarray technology and mass spectrometry have been or are being developed as high- throughput approaches for additional types of genomic analyses, such as determining the parameters of gene expression or the location of gene products by the thousands at a time instead of individually. High- throughput methods to determine the location of cis- regulatory elements and, to a lesser extent, other sequence elements, are also beginning to be developed. However, at present, there is no single approach or compilation of approaches that can accurately and efficiently identify every sequence feature in genomic DNA. DETERMINATION OF ALL FUNCTIONAL ELEMENTS IN HUMAN DNA RELEASE DATE, NHGRI, February 21, 2003 RFA: HG-03-003 http://grants1.nih.gov/grants/guide/rfa-files/RFA-HG-03-003.html See also chromatography & electrophoresis, Gene Amplification & PCR, Microarrays, Sequencing genomics: Large-scale, high - throughput molecular analyses of multiple genes, gene products, or regions of genetic material. Originally, genomics meant analysis of the whole genome, but the term now commonly refers to large-scale technology molecular applications to DNA and RNA, whether or not the studies encompass the whole genome. CHA Cambridge Healthtech Advisors, Clinical Genomics: The Impact of Genomics on Clinical Trials and Medical Practice report, 2004 The border between genomics and the rest of molecular biology has been stretched thin and has become porous. The term remains useful, but interpreting findings from this and other surveys needs to take definition creep and the changing meaning of genomics in capital markets into account. . [Robert Cooke- Deegan et. al., World Survey of Funding for Genomics Research: Final Report to the Global Forum for Health Research and the World Health Organization, September 2000] http://www.stanford.edu/class/siw198q/websites/genomics/finalrpt.htm Generation of information about living things by systematic approaches that can be performed on an industrial scale. [Roger Brent "Genomic biology" Cell 100: 169-183 Jan 2, 2000] The systematic study of the complete DNA sequences (GENOME) of organisms. [MeSH, 2001] Basic genetics & genomics (tries to) answer the question of what the difference between genetics and genomics is. Coined by Thomas H. Roderick [of the Jackson Laboratory, Maine, US] in 1986 in Bethesda, MD during a discussion of a name for a planned new journal (Genomics) that was to include sequencing data, discovery of new genes, gene mapping, and new genetic technologies. According to Roderick, the term genomics "also had the comparative aspect of genomes of various species, their evolution, and how they related to each other. Although we didn’t come up with the term ‘functional genomics’ we thought of the genome as a functioning whole beyond just single genes of sequences spread around a chromosome." [B Kuska "Beer, Bethesda, and Biology" JNCI 90(2): 93 Jan 21, 1998] Although I haven't found any references to "genomics" prior to 1987, "genomic" is easily found in Medline from 1966 on, and probably could be located in journals earlier than that. Narrower terms include: Genomics categories: agricultural genomics, applied genomics, Beowulf Genomics, combinatorial genomics, crop genomics, environmental genomics, high throughput genomics, industrial genomics, intergenomics, inverse genomics, microbial genomics, network genomics, plant genomics, translational genomics; Clinical genomics glossary behavioral genomics, cancer genomics, clinical genomics, oncogenomics, predictive genomics; Computers & computing: computational genomics, post- genomic, post- genomics; Drug discovery & development chemical genomics, chemogenomics; Functional genomics glossary: biochemical genomics, comparative genomics, deductive genomics, forward genomics, functional genomics, lateral genomics, phylogenomics, physiological genomics, reverse genomics; SNPs & other Genetic variations: population genomics; Nanoscience & Miniaturization: nanogenomics, Pharmacogenomics: ecotoxicogenomics, toxicogenomics genomics firms: Business of biopharmaceuticals genomics - legal aspects: Intellectual property and legal glossary genomics technologies - integrated: The grand challenge of fully characterizing the genomics/ proteomics of the intact living cell … The information coming from these projects [Human Genome Project, variety of plant genome sequencing initiatives, and the completion of an extensive array of microorganism genomes], massive and complex as it will be, provides only the starting point for understanding how the cell, the basic unit of life, interprets the blueprint contained in its genome … What is not understood is how the cell creates and orchestrates its own physiology using the information contained in its DNA …. it is unlikely that a useful understanding of the cell will be possible until a quantitative appreciation of both rates and equilibria of molecular processes in the living cell is achieved. [National Center for Research Resources "Integrated Genomics Technologies Workshop Report" Jan 1999] http://grants.nih.gov/grants/guide/rfa-files/RFA-RR-99-003.html Related terms: Functional genomics glossary, Informatics Overview genotype: Sequencing glossary genotyping, genotyping technologies: Sequencing glossary HUGO: Human Genome Organization, an international organization of scientists involved in the Human Genome Project, the global initiative to map and sequence the human genome. Established 1989 http://www.hugo-international.org/ haplotype: Sequencing glossary Human Genome Project HGP: Horace Freeland Judson writes in "Talking about the genome" (Nature 409:769, 15 Feb. 2001) "The language we use about genetics and the genome project at times limits and distorts our own understanding, and the public understanding. Look at the phrase - or marketing slogan - 'the human-genome project'. In reality, of course we have not just one human genome but billions. ... Then, too, the entire phrase - the human- genome project: singular, definite, with a fixed end- point, completed by 2000, packaged so it could be sold to legislative bodies, to the people, to venture capitalists. But we knew from the start the genome project would never be complete. A coordinated effort of researchers to map (CHROMOSOME MAPPING) and sequence (SEQUENCE ANALYSIS, DNA) the human genome. MeSH, 1990 Related terms: DDBJ, DOE, EMBL, GenBank, NCBI, NHGRI, RIKEN, Sanger Centre; Maps genetic & genomic glossary Sequencing glossary resequencing Human Genome Project HGP- completion: The completion of the draft human genome sequence has both symbolic and real implications for this next stage. The symbolic nature of the accomplishment is primarily the fact that people have been claiming for the past 15 or 16 years that the Human Genome Project is biology’s moon shot. The fact that it has been accomplished during the past year or so is very important since it connects with the policy makers and decision makers who control and govern the future of public funding for biological and other research in this country. The real accomplishment for the life sciences has been the transition to big science, as illustrated by the dramatic decrease in the range of cost per sequence (Figure 2.1). In a way, the real transition to big- time science is evidenced by the large- scale sequencing centers that have cropped up over the last few years and accomplished sequencing the human genome in so timely a manner in both the public and private sector. The public has a conservatively estimated sequencing capacity of eight to ten million lanes per month (75- 80% pass rate, 450- 500 Phred20 bases). The private sector effort is much more difficult to estimate, but the capacity is roughly in ten to twenty million lanes per month. For reference, seven million lanes represent approximately one mammalian genome. These figures demonstrate that this country has a very powerful engine in place to deal with the genomes that will need to be sequenced in the months and years ahead. Ari Patrinos, US DOE CHI's GenomeLink 9.2 An international effort formally begun in October 1990. The project was planned to last 15 years, but rapid technological advances have accelerated the expected completion date to 2003. Project goals are to discover all the approximate 30,000 human genes (the human genome) and make them accessible for further biological study .. Another project goal is to determine the complete sequence of the 3 billion DNA bases in the human genome. As part of the HGP, parallel studies are being carried out on selected model organisms such as the bacterium E. coli to help develop the technology and interpret human gene function. The Department of Energy's Human Genome Program and the National Institutes of Health's National Human Genome Research Institute (NHGRI) together make up the U.S. Human Genome Project. [Oak Ridge National Lab, HGP "FAQ" About the Human Genome Project 2002] http://www.ornl.gov/hgmis/faq/faqs1.html What
happens when the Human Genome sequence is complete?
Facts about genome
sequencing, HGMIS, Oak Ridge National Laboratory, 2002 http://www.ornl.gov/hgmis/faq/seqfacts.html#post Google = "human genome project" completion about 14,500 Jan. 6, 2003 human phenotype: A human Phenotype is the total physical appearance and constitution of a person, often determined by multiple genes and influenced by environmental interactions. Initiatives in this area would encourage the development of resources to systematically catalog human phenotypes in an effort to characterize complex diseases and disorders. New Roadmap Emphasis areas for 2008, NIH Roadmap, http://nihroadmap.nih.gov/2008initiatives.asp immunophenotyping: Pharmacogenomics glossary International Human Genome Sequencing Consortium: Published the draft human genome sequence in Nature 15 Feb. 2001 See also Human Genome Project. International Nucleotide Database: Composed of DDBJ, EMBL and GenBank. Joint Genome Initiative: Collaboration between Los Alamos National Lab, Lawrence Livermore National Lab and Oak Ridge National Lab. Organized in 1997. http://www.jgi.doe.gov/ Mendelian genetics: Classical genetics, focuses on monogenic genes with high penetrance, the tip of the iceberg of genetics. It is useful to remember that Mendelian genetics itself was a true paradigm shift, and not at all intuitively obvious. This is poignantly described in Robin Henig's artfully crafted biography of Gregor Mendel The Monk in the Garden. Mendel was not recognized by scientists until 1900 -- 35 years after his initial publication and 16 years after his death. Those who heard his talks did not seem to understand them. Some of the reprints he sent out have vanished. Others were found (years later) with leaves uncut and unread. It is also instructive to remember that Mendelian genetics were quite applicable to the breeding of plants and animals (including racehorses) with serious economic implications. This may well have encouraged Mendel's superiors to let him pursue his work with peas. metabolic phenotypes: Metabolic engineering glossary Minorities, race and Genetics: Human Genome Project Information, DOE, US http://www.ornl.gov/TechResources/Human_Genome/elsi/minorities.html molecular phenotyping: Pharmacogenomics glossary monogenic: Diseases caused by alterations in single genes. Single -gene disorders are also sometimes called Mendelian disorders since they are usually transmitted in a manner such as that described by Mendel as simple recessive or dominant traits. CHA Cambridge Healthtech Advisors, Clinical Genomics: The Impact of Genomics on Clinical Trials and Medical Practice report, 2004 Compare multifactorial, polygenic. multifactorial diseases: SNPs & other genetic variations glossary NCBI National Center for Biotechnology Information Bioinformatics glossary NHGRI National Human Genome Research Institute: http://www.nhgri.nih.gov The National Center for Human Genome Research (NCHGR) became a NIH Institute in 1997 Original NIH funding of genome projects was through NIGMS (National Institute of General Medical Sciences) in 1985. [Oak Ridge National Laboratory (ORNL), Tennessee, US "Major events in the US Human Genome Project"] http://www.ornl.gov/hgmis/project/timeline.html nanogenomics: Nanoscience & Miniaturization glossary network genomics: Functional genomics glossary nonlinear: Advances in genomic technologies are a mix of incremental improvements to existing technologies (linear) and occasionally, a truly new paradigm or breakthrough. Related terms complex; Business of biotechnology disruptive technologies, emerging technologies, oncogenomics: Cancer genomics glossary organelle genomes: Eukaryotic genomes are multicomponent. The majority of genetic information is located in the nucleus and inherited according to Mendel's laws. However, there are small but essential genomes located in the cellular organelles - the plastids and mitochondria. Plant cells, therefore, have three separate genetic systems. Organelle genomes differ from nuclear genomes in a number of important ways. They are small relative to the nuclear genome. There are multiple organelles per cell and each organelle contains from 20 to 20,000 organelle genomes depending upon the cell type. Organelle genomes are organized into structures called nucleoids. Organelles are easily purified from other cell contents by differential centrifugation. The abundance of these organelles and organelle genomes makes it easy to study their biochemistry and molecular biology. Organelle genomes are inherited in a non- Mendelian fashion. Inheritance can be studied using RFLP markers. While inheritance is usually through the maternal parent only, there are a number of interesting exceptions in the higher plants. [Christine Chase, PCB 6528, Institute of Food and Agricultural Sciences, Univ. of Florida, 2001] http://www.hos.ufl.edu/ctdcweb/pcb6528I.htm Related term: organelles Cell biology glossary Narrower term: mitochondrial genes Compare nuclear genes "parts list": Now that the sequencing of the human genome is approaching completion, an important next step is to extract as much of the information contained in the genome as possible. All of the genes encoded in the genome should be enumerated, a task that is not as simple as once thought. Other data sets of high interest include all of the regulatory elements, all forms of structural RNA, recombination and replication signals, and all encoded proteins and their modified forms. In contrast to genomic sequence, which can in principle be determined completely, there are questions about whether any of these other data sets can be compiled with the same degree of completeness. It is not obvious that completeness is even conceivable in the case of some data sets, such as transcripts (given alternative splicing), regulatory elements, proteins (given isoforms), protein- protein and protein- nucleic acid interactions, and protein modifications. The desire for completeness will need to be balanced by cost-benefit considerations. Beyond the beginning: The Future of Genomics, NHGRI, Dec. 12-14, 2001, Warrenton, VA http://www.genome.gov/10001650 penetrance: The probability of expressing a phenotype given a genotype. Penetrance is described as either "complete" or "incomplete" … .Penetrance may also be dependent on a susceptible individual’s current age… incomplete penetrance is usually a matter of chance or modifiers in the genetic background. [NHLBI] Mendelian genetics focuses on genes with high penetrance. These were the easiest genes to identify. Related terms: SNPs & Genetic variations glossary. personal genomics: Molecular Medicine glossary pharmacogenomics: Pharmacogenomics glossary phenotype: The observable structural and functional characteristics of an organism determined by its genotype and modulated by its environment. [IUPAC Biotech] The observed manifestation of a genotype, which may be expressed physically, biochemically or physiologically. [NHLBI] Refers to all biological consequences from the presence of the mutation in question. Phenotype is logically the subject of functional genomics. In its broadest definition, phenotype includes phenomena at all organizational levels of biology, and is defined as the consequence of mutations in one or more genes relative to an non- mutated or wild type genotype in a given organism. At the molecular level, for example, phenotype includes all temporal and spatial aspects of gene expression as well as related aspects of the expression, structure, function and spatial localization of proteins. The latter has acquired the name "proteomics" Univ. of California Davis, Genome Center "What is Genomics" http://www.genomecenter.ucdavis.edu/what.html Systematic collection and organization of data on phenotypes is still at an early stage. The International Mouse Mutagenesis Consortium (IMMC), writing in the Human Genome issue of Science notes that improved phenotyping technologies are needed, as are "more efficient and reliable methods for archiving, managing, analyzing, displaying and disseminating the complex phenotype data sets resulting from mutagenesis programs, and that there are no large- scale phenotype databases. Phenotype vocabularies seem to be in the works and a Mouse Phenome Project is based at Jackson Labs, US. [IMMC JH Nadeau et. al "Functional Annotation of Mouse Genome Sequences" Science 291: 1251-1255 Feb. 16, 2001] From a cellular point of view, the phenotype can be divided into two parts – the proteome and the metabolome, the observed phenotype being their summation. Both of these phenotypes are important, but in different ways. The changes observed in the metabolome directly indicate what system changes (i.e. genes or drugs) affect the function of which pathways. As well, the exact point(s) in the pathway affected can be determined. The proteins involved in these pathways may be useful drug or pesticide targets. See note on variant meanings for phenotype, genome and genotype under genome definition, Journal of Theoretical Biology 1997 article. Narrower term: human phenotypes Phenotype databases See Databases & software directory Mammalian
Phenotype Browser, MGI Mouse Genome Informatics,
Jackson Laboratory, Compare genotype. Related terms: genetic architecture; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Microarrays
glossary phenotype array; Omes & omics glossary
metabolomics, phenome, phenomics; Drug
discovery & development glossary phenotypic screening; Functional
genomics phenotypic profiling; Model
& other organisms glossary
Pharmacogenomics glossary genotype- to-
phenotype, phenotype standards, phenotype- to- genotype
phenotypic screening: Assays
& screening glossary
phenotyping:
A major challenge in phenotyping is weighing the need to gather sufficient
information on each mutation against the need to screen large numbers of animals
to gain broad coverage of the genome. Proper balance of these factors will
maximize the eventual recovery of interesting new mutations. Our approach is to
devise efficient screens for a series of phenotypic domains, favoring high-
throughput, simple tests (and multiple tests where possible), and then to rely
on more sophisticated confirmatory testing of suspect mice. [Scientific
Overview, Neuroscience Mutagenesis Facility, Jackson Laboratory, US, 2002]
http://www.jax.org/nmf/documents/overview.html
Narrower terms: Pharmacogenomics
glossary immunophenotyping, molecular phenotyping; : Microscopy
glossary image- based phenotyping phylogenomics, physiological genomics:
Phylogenomics glossary
polygenic: The next scientific frontier, however, will be those
polygenic disorders involving a combination of gene polymorphisms, each
of which contributes in some small way to pathology. Examples of such conditions
include a variety of mental and behavioral problems (alcoholism, schizophrenia,
depression), as well as physiological disorders that involve complex
interactions between genetics and environment (atherosclerosis, hypertension).
These problems will require the ability to look at patterns of gene expression
at multiple stages of disease/ disorder progression and under a variety of
physiological and environmental conditions. Array
technologies will provide just such capabilities.
Genetic disorder resulting from the combined action
of alleles of more than one gene (e.g. heart disease, diabetes
and some cancers). Although such disorders are inherited, they depend on
the simultaneous presence of several alleles; thus the hereditary patterns
are usually more complex than those of single gene disorders. [DOE]
[Axel Kahn] also suggests that the notion of interacting genetic factors
in polygenic conditions remains an uncertainty. "Thus far, when we have
looked at what we have thought of as multifactorial polygenic conditions,
we have only seen diseases with several monogenic causes. Thus for
each of a number of conditions we can identify several separate genes,
each of which on its own in different patients is associated with diseases
which we classify as diabetes or Alzheimer’s disease or obesity. We simply
have not really started looking at the additive or multiplicative contributions
of several factors to disease inheritance." John. Hodgson "Crystal gazing
the new Biotechnologies" Nature Biotechnology 18: 29- 31 Jan 2000]
Related terms: Clinical genomics:
behavior genomics; Genetic
variations glossary multigenic, oligogenic, Gene
definitions: pleiotropy.
population genetics, population genomics: SNPs
& Genetic variations glossary
post-genomic
era:
The genome era is generally regarded to have started
on 28 July 1995, with the publication of the genome of the bacterium Haemophilus
influenzae. ["A point of entry into genomics" Nature Genetics 23:273
Nov. 1999]
But the human
mitochondrial genome was sequenced in 1981 and published in Nature 290 (5806):
457- 465, Apr. 9, 1981. Sequence
and organization of the human mitochondrial genome by S. Anderson et.
al.
[Francis Collins] began
his presentation by taking issue with the term "post-genomics era." He
queries whether his means that from the beginning of the universe until 2001 we
were in the "pre-genome era," and then suddenly, "bang" we
moved into the past-genome era (leading one to wonder what happened to the
genome era). He suggested that it was presumptuous to say that the Human Genome
Project is already behind us. He pointed out that proteomics is a subset
of genomics, and genomics is more than sequencing genomes, which will be ongoing
for decades to come. Defining the Mandate of Proteomics in the Post- Genomics
Era, Board on International Scientific Organizations, National Academy of
Sciences, 2002 http://www.nap.edu/books/NI000479/html/R1.html The "post- genomic era" holds phenomenal promise for identifying the mechanistic
bases of organismal development, metabolic processes, and disease,
and we can confidently predict that bioinformatics research will have a
dramatic impact on improving our understanding of such diverse areas
as the regulation of gene expression, protein structure determination,
comparative evolution, and drug
discovery. The availability of virtually
complete data sets also makes negative data informative: by mapping entire pathways, for example, it becomes interesting to ask not only what is present,
but also what is absent. [David Roos "Bioinformatics -- Trying to Swim in a Sea of Data"
Science 291:1260-1261 Feb. 16, 2001] http://www.sciencemag.org/cgi/content/full/291/5507/1260
Post-genomic can also refer to the increasing emphasis on functional
genomics. With an increasing number of organisms for which we have
(more or less) complete genomes we are beginning to see glimpses of the
power of having fully mapped sequences. Still, in most contexts talk about
being "post- genomic" seems a little premature. "Post
Mendelian" seems more
accurate as we move from an era in which genetics has been rooted in monogenic
diseases with high penetrance to a greater awareness (but limited
understanding) of polygenic diseases (and traits) often with relatively
low penetrance. However with the publication of the draft human sequences
in Feb. 2001 we are beginning to be truly "post- genomic".
post-genomics:
The general rubric "post- genomics" encompasses an increasingly broad array of topic areas -- essentially, anything connected with teasing higher biological meaning and
function out of raw sequence data.
[Science Online "Functional genomics research] http://www.sciencemag.org/feature/plus/sfg/research/index.shtml
Related terms: -Omes &
-omics glossary
post-Mendelian: See under post- genomic
predictive genomics: Clinical
genomics glossary
Radio Free Genome: DNA
glossary
reaction
phenotypes: Metabolic profiling
glossary
RIKEN:
Rikagaku Kenkyusy Institute of Physical and Chemical Research,
Japan. http://www.riken.go.jp/
Sanger Centre, UK:
A genome research centre founded by the Wellcome
Trust and the Medical Research
Council. Our purpose is to further the knowledge of genomes, particularly
through large scale sequencing and analysis. http://www.sanger.ac.uk/
structural genomics: Structural
genomics glossary.
toxicogenomics: Pharmacogenomics glossary
virtual genomes: In
silico & Molecular modeling
glossary
whole genome:
There are several reasons for completely sequencing
a genome. The first and most simple reason is that it provides a
basis for the discovery of all the genes. Despite the power of cDNA analysis
and the enormous value in interpreting genome sequence, it is now generally
recognized that a direct look at the genome is needed to complete the inventory
of genes. Second, the sequence shows the long- range relationships between
genes and provides the structural and control elements that must lie among
them. Third, it provides a set of tools for future experimentation, where
any sequence may be valuable and completeness is the key. Fourth, sequencing
provides an index to draw in and organize all genetic information about
the organism. Fifth, and most important over time, is that the whole
is an archives for the future, containing all the genetic information required
to make the organism (the greater part of which is not yet understood).
[C. elegans Sequencing Consortium “Genome sequence of the nematode
C.
elegans; A platform for investigating biology” Science 282: 2013 Dec
11 1998]
Narrower term: whole genome index
whole genome index:
All the data related to genes, with the
information indexed and catalogued in a uniform manner ... [and with] access
[to] information about what tissues [those] genes are known to be expressed in,
and under what circumstances. The family that the protein encoded by the gene
belongs to would be quickly identified, as would valuable information about how
genetic variation, or other processes, alter the structure and
function of that protein. The active sites on the protein, and the types of compounds that are
most likely to interfere with its activity, would be available through a few
strokes on a keyboard. ... Without a complete gene index for humans (as well as
other medically important organisms), the data- integration problem will be
huge, and those researchers who have not adapted their systems to allow for the
constant and dramatic changes ahead will spend much of their time just making
sure their old data remain usable
Bibliography
How
to look for other unfamiliar terms
IUPAC definitions are
reprinted with the permission of the International Union of Pure and Applied
Chemistry.
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