Results 31 to 40 of about 11,201,470 (335)
RFCell: A Gene Selection Approach for scRNA-seq Clustering Based on Permutation and Random Forest
Frontiers in Genetics, 2021 In recent years, the application of single cell RNA-seq (scRNA-seq) has become more and more popular in fields such as biology and medical research. Analyzing scRNA-seq data can discover complex cell populations and infer single-cell trajectories in cell
Yuan Zhao +5 more
doaj +1 more source
Journal of Applied Science and Technology Trends, 2021 Microarray data plays a major role in diagnosing and treating cancer. In several microarray data sets, many gene fragments are not associated with the target diseases.
A. Jahwar, N. S. Ahmed
semanticscholar +1 more source
Translational selection on SHH genes [PDF]
Genetics and Molecular Biology, 2010 Codon usage bias has been observed in various organisms. In this study, the correlation between SHH genes expression in some tissues and codon usage features was analyzed by bioinformatics. We found that translational selection may act on compositional features of this set of genes.
Hajjari, Mohammadreza +2 more
openaire +5 more sources
The Roles of Gene Duplication, Gene Conversion and Positive Selection in Rodent \u3ci\u3eEsp\u3c/i\u3e and \u3ci\u3eMup\u3c/i\u3e Pheromone Gene Families with Comparison to the \u3ci\u3eAbp\u3c/i\u3e Family [PDF]
, 2012 Three proteinaceous pheromone families, the androgen-binding proteins (ABPs), the exocrine-gland secreting peptides (ESPs) and the major urinary proteins (MUPs) are encoded by large gene families in the genomes of Mus musculus and Rattus norvegicus.
Karn, Robert C., Laukaitis, Christina M.
core +10 more sources
CRIA: An Interactive Gene Selection Algorithm for Cancers Prediction Based on Copy Number Variations
Frontiers in Plant Science, 2022 Genomic copy number variations (CNVs) are among the most important structural variations of genes found to be related to the risk of individual cancer and therefore they can be utilized to provide a clue to the research on the formation and progression ...
Qiang Wu, Dongxi Li
doaj +1 more source
Comparative gene marker selection suite [PDF]
Bioinformatics, 2006 AbstractMotivation: An important step in analyzing expression profiles from microarray data is to identify genes that can discriminate between distinct classes of samples. Many statistical approaches for assigning significance values to genes have been developed. The Comparative Marker Selection suite consists of three modules that allow users to apply
Joshua, Gould +4 more
openaire +2 more sources
Template-driven gene selection procedure [PDF]
IEE Proceedings - Systems Biology, 2006 The hierarchical clustering and statistical techniques usually used to analyse microarray data do not inherently represent the underlying biology. Herein, a hybrid approach involving characteristics of both supervised and unsupervised learning is presented.
N, Knowlton +6 more
openaire +2 more sources
Selecting Genes by Test Statistics [PDF]
BioMed Research International, 2005 Gene selection is an important issue in analyzing multiclass microarray data. Among many proposed selection methods, the traditional ANOVA F test statistic has been employed to identify informative genes for both class prediction (classification) and discovery problems. However, the F test statistic assumes an equal variance. This assumption may not be
Chen, Dechang +3 more
openaire +2 more sources
Robustness of Random Forest-based gene selection methods [PDF]
, 2013 Gene selection is an important part of microarray data analysis because it provides information that can lead to a better mechanistic understanding of an investigated phenomenon.
Kursa, Miron B.
core +2 more sources
Positive selection underlies Faster-Z evolution of gene expression in birds. [PDF]
, 2015 The elevated rate of evolution for genes on sex chromosomes compared to autosomes (Fast-X or Fast-Z evolution) can result either from positive selection in the heterogametic sex, or from non-adaptive consequences of reduced relative effective population ...
Dean, R +4 more
core +1 more source