Results 41 to 50 of about 11,201,470 (335)

Selection, Gene Interaction, and Flexible Gene Networks [PDF]

open access: yesCold Spring Harbor Symposia on Quantitative Biology, 2009
Recent results from a variety of different kinds of experiments, mainly using behavior as an assay, and ranging from laboratory selection experiments to gene interaction studies, show that a much wider range of genes can affect phenotype than those identified as "core genes" in classical mutant screens.
openaire   +2 more sources

Genetic Variation in Human Gene Regulatory Factors Uncovers Regulatory Roles in Local Adaptation and Disease [PDF]

open access: yes, 2019
Differences in gene regulation have been suggested to play essential roles in the evolution of phenotypic changes. Although DNA changes in cis-regulatory elements affect only the regulation of its corresponding gene, variations in gene regulatory factors
Nowick, Katja, Perdomo-Sabogal, Álvaro
core   +1 more source

Gene Selection in Disease: Review

open access: yesJournal of Pharmaceutical Research International, 2022
In utilizing AI algorithms to investigate expression patterns, genetic factors are a significant problem for objective aggregates. Numerous genetic characteristics exist, but just a few have substantial relationships with a specific aggregate.
M. Rashmi, Manish Varshney
semanticscholar   +1 more source

Natural selection and gene substitution

open access: yesGenetical Research, 1969
Using models which describe the change, by natural selection, of the actual numbers of genes rather than their relative frequencies, it is demonstrated that the equation familiar to geneticists, i.e.dp/dt=sp(1 −p), is appropriate under a wide range of circumstances.
M, Kimura, J F, Crow
openaire   +2 more sources

Species versus gene selection [PDF]

open access: yesGenetics Selection Evolution, 1989
Author(s): Tsakas, S. C. | Abstract: Species selection has been recently promoted (Gould a Eldredge, 1988a, 1988b) as the driving force in macroevolution, and viewed as an explanation for the variability in rates observed, both temporally and spatially, at the phenotypic level. This has rekindled the contention between microevolutionists (Maynard Smith,
openaire   +5 more sources

Improving the Classification of Alzheimer’s Disease Using Hybrid Gene Selection Pipeline and Deep Learning

open access: yesFrontiers in Genetics, 2021
Alzheimer’s is a progressive, irreversible, neurodegenerative brain disease. Even with prominent symptoms, it takes years to notice, decode, and reveal Alzheimer’s.
Nivedhitha Mahendran   +3 more
doaj   +1 more source

Genetic Evolution and Molecular Selection of the HE Gene of Influenza C Virus [PDF]

open access: yes, 2019
Influenza C virus (ICV) was first identified in humans and swine, but recently also in cattle, indicating a wider host range and potential threat to both the livestock industry and public health than was originally anticipated.
He, Wanting   +10 more
core   +1 more source

Genes, individuals, and kin selection [PDF]

open access: yesProceedings of the National Academy of Sciences, 1981
The altruistic-gene theory of kin selection requires conditions so improbable that its reality is doubtful. The gene-quantity theory, including the theory of inclusive fitness, assumes that selection acts on sums of kins' genes, but no effective mechanism is apparent.
openaire   +2 more sources

Gene selection and classification for cancer microarray data based on machine learning and similarity measures

open access: yesBMC Genomics, 2011
Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the ...
Liu Qingzhong   +8 more
doaj   +1 more source

Gene Correlation Guided Gene Selection for Microarray Data Classification [PDF]

open access: yesBioMed Research International, 2021
The microarray cancer data obtained by DNA microarray technology play an important role for cancer prevention, diagnosis, and treatment. However, predicting the different types of tumors is a challenging task since the sample size in microarray data is often small but the dimensionality is very high.
Dong Yang, Xuchang Zhu
openaire   +2 more sources

Home - About - Disclaimer - Privacy