Literature DB >> 26559752

Six-layer structure for genomics and its applications.

Naoyuki Kamatani1.   

Abstract

The term 'genetics' was coined before an understanding of DNA sequence data was achieved, and it is now insufficient to describe the broad areas in which DNA data have important roles. The term genomics is more broadly descriptive, but it does not provide a satisfactory conceptual framework that scientists can share. Here I propose a six-layer structure that describes the entire scientific field for 'genomics'. The proposed layers are 'life' as the uppermost layer, followed by 'species', 'population', 'family', 'individual' and finally 'cell' as the bottommost layer. In each pair of adjacent layers, each member of the upper layer comprises a set of members of the lower layer. In each layer, we can define consistent partial orders of members based on genomic data in the forms of phylogenic and pedigree trees. Although total orders such as those defined for time and space in physics cannot be defined in biology, defining consistent partial orders allows mathematical analysis to be performed. I will show that mathematical genetics studies can be understood as attempts to bridge gaps between layers of the proposed six-layer structure, while genetic tests can be understood as procedures to differentiate among members of each layer by using genomic data.

Mesh:

Year:  2015        PMID: 26559752     DOI: 10.1038/jhg.2015.137

Source DB:  PubMed          Journal:  J Hum Genet        ISSN: 1434-5161            Impact factor:   3.172


  8 in total

1.  Principal components analysis corrects for stratification in genome-wide association studies.

Authors:  Alkes L Price; Nick J Patterson; Robert M Plenge; Michael E Weinblatt; Nancy A Shadick; David Reich
Journal:  Nat Genet       Date:  2006-07-23       Impact factor: 38.330

2.  Selective killing of human malignant cell lines deficient in methylthioadenosine phosphorylase, a purine metabolic enzyme.

Authors:  N Kamatani; W A Nelson-Rees; D A Carson
Journal:  Proc Natl Acad Sci U S A       Date:  1981-02       Impact factor: 11.205

3.  Tumour evolution inferred by single-cell sequencing.

Authors:  Nicholas Navin; Jude Kendall; Jennifer Troge; Peter Andrews; Linda Rodgers; Jeanne McIndoo; Kerry Cook; Asya Stepansky; Dan Levy; Diane Esposito; Lakshmi Muthuswamy; Alex Krasnitz; W Richard McCombie; James Hicks; Michael Wigler
Journal:  Nature       Date:  2011-03-13       Impact factor: 49.962

4.  Pharmacokinetics and pharmacodynamics of febuxostat (TMX-67), a non-purine selective inhibitor of xanthine oxidase/xanthine dehydrogenase (NPSIXO) in patients with gout and/or hyperuricemia.

Authors:  K Komoriya; S Hoshide; K Takeda; H Kobayashi; J Kubo; M Tsuchimoto; T Nakachi; H Yamanaka; N Kamatani
Journal:  Nucleosides Nucleotides Nucleic Acids       Date:  2004-10       Impact factor: 1.381

5.  PTC124 targets genetic disorders caused by nonsense mutations.

Authors:  Ellen M Welch; Elisabeth R Barton; Jin Zhuo; Yuki Tomizawa; Westley J Friesen; Panayiota Trifillis; Sergey Paushkin; Meenal Patel; Christopher R Trotta; Seongwoo Hwang; Richard G Wilde; Gary Karp; James Takasugi; Guangming Chen; Stephen Jones; Hongyu Ren; Young-Choon Moon; Donald Corson; Anthony A Turpoff; Jeffrey A Campbell; M Morgan Conn; Atiyya Khan; Neil G Almstead; Jean Hedrick; Anna Mollin; Nicole Risher; Marla Weetall; Shirley Yeh; Arthur A Branstrom; Joseph M Colacino; John Babiak; William D Ju; Samit Hirawat; Valerie J Northcutt; Langdon L Miller; Phyllis Spatrick; Feng He; Masataka Kawana; Huisheng Feng; Allan Jacobson; Stuart W Peltz; H Lee Sweeney
Journal:  Nature       Date:  2007-04-22       Impact factor: 49.962

6.  Antileukemic and immunosuppressive activity of 2-chloro-2'-deoxyadenosine.

Authors:  D A Carson; D B Wasson; E Beutler
Journal:  Proc Natl Acad Sci U S A       Date:  1984-04       Impact factor: 11.205

7.  Deficiency of methylthioadenosine phosphorylase in human leukemic cells in vivo.

Authors:  N Kamatani; A L Yu; D A Carson
Journal:  Blood       Date:  1982-12       Impact factor: 22.113

8.  Possible metabolic basis for the different immunodeficient states associated with genetic deficiencies of adenosine deaminase and purine nucleoside phosphorylase.

Authors:  D A Carson; D B Wasson; E Lakow; N Kamatani
Journal:  Proc Natl Acad Sci U S A       Date:  1982-06       Impact factor: 11.205

  8 in total

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