Evidence map›Paper›PMID 25705560›Full record

ArticleNatural science2014

Information Dynamics of Whole Genome Adaptation.

William Hercules, James Lindesay, Tshela E Mason, Georgia M Dunston

Open access · hybridAbstract read
In one paragraph

Article in Natural science, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 89% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

William HerculesComputational Physics Laboratory, Howard University, Washington DC, USA.
James LindesayComputational Physics Laboratory, Howard University, Washington DC, USA.
Tshela E MasonNational Human Genome Center, Howard University, Washington DC, USA.
Georgia M DunstonNational Human Genome Center, Howard University, Washington DC, USA ; Department of Microbiology, Howard University, Washington DC, USA.
Howard University · USComputational Physics (United States) · US

Funding

STRUCTURAL/FUNCTIONAL CHARACTERIZATION OF AMINOGLYCOSIDEG12RR003048 · NCRR · HOWARD UNIVERSITY · PI WANG, PAUL P · 1985 to 2011
$19.0M
PROTEOMICS CORE FACILITYG12MD007597 · NIMHD · HOWARD UNIVERSITY · PI SOUTHERLAND, WILLIAM M. · 2012 to 2018
$14.8M
NCRR NIH HHS G12 RR003048NIMHD NIH HHS G12 MD007597
6 · The paper itself

Abstract

The human genome is a complex, dynamic information system that encodes principles of life and living systems. These principles are incorporated in the structure of human genome sequence variation and are foundational for the continuity of life and human survival. Using first principles of thermodynamics and statistical physics, we have developed analogous "genodynamic tools" for population genomic studies. Characterizing genomic information through the lens of physics has allowed us to develop energy measures for modeling genome-environment interactions. In developing biophysical parameters for genome-environment homeostasis, we found that stable genomic free energy trades off low genomic energy (genomic conservation and increased order) and high genomic entropy (genomic variation) with an environmental potential that drives the variation. In our approach, we assert that common variants are dynamic sites in the genome of a population and that the stability of whole genome adaptation is reflected in the frequencies of maintained diversity in common variants for the population in its environment. In this paper, we address the relativity of whole genome adaptation towards homeostasis. By this we mean that adaptive forces are directly reflected in the frequency distribution of alleles and/or haplotypes of the population relative to its environment, with adaptive forces driving the genome towards homeostasis. The use of genomic energy units as a biophysical metric in DNA sequence variation analyses provides new insights into the foundations of population biology and diversity. Using our biophysical tools, population differences directly reflect the adaptive influences of the environment on populations.

Indexed as

Genome-Environment InteractionsGenomic HomeostasisGenomic InformationPopulation Adaptation

Identifiers

PMID25705560
PMCPMC4332707
OpenAlexW2084845219

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.