Results 11 to 20 of about 2,170,661 (326)

TGMI: an efficient algorithm for identifying pathway regulators through evaluation of triple-gene mutual interaction [PDF]

Nucleic Acids Research, 2018
Despite their important roles, the regulators for most metabolic pathways and biological processes remain elusive. Presently, the methods for identifying metabolic pathway and biological process regulators are intensively sought after. We developed a novel algorithm called triple-gene mutual interaction (TGMI) for identifying these regulators using ...
Chathura Gunasekara, Kui Zhang, Wenping Deng, Laura Brown, Hairong Wei   +4 more
openaire   +3 more sources

Evaluation of Machine Learning Algorithm Utilization for Lung Cancer Classification Based on Gene Expression Levels [PDF]

Asian Pacific Journal of Cancer Prevention, 2016
Lung cancer remains one of the most common cancers in the world, both in terms of new cases (about 13% of total per year) and deaths (nearly one cancer death in five), because of the high case fatality. Errors in lung cancer type or malignant growth determination lead to degraded treatment efficacy, because anticancer strategy depends on tumor ...
Maxim D, Podolsky, Anton A, Barchuk, Vladimir I, Kuznetcov, Natalia F, Gusarova, Vadim S, Gaidukov, Segrey A, Tarakanov   +5 more
openaire   +3 more sources

Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification

Genomics Data, 2015
Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using ...
D. Ramyachitra, M. Sofia, P. Manikandan
doaj   +2 more sources

Evolutionary Fuzzy Clustering Algorithm with Knowledge-Based Evaluation and Applications for Gene Expression Profiling

Journal of Computational and Theoretical Nanoscience, 2005
In microarray data analysis, clustering is a method that groups thousands of genes by their similarities of expression levels, helping to analyze gene expression profiles. This method has been used for identifying unknown functions of genes. The fuzzy clustering method assigns one sample to multiple groups according to their degrees of membership. This
Han-Saem Park, Si-Ho Yoo, Sung-Bae Cho
openaire   +2 more sources

Benchmarker: An Unbiased, Association-Data-Driven Strategy to Evaluate Gene Prioritization Algorithms [PDF]

The American Journal of Human Genetics, 2018
Genome-wide association studies (GWAS) are valuable for understanding human biology, but associated loci typically contain multiple associated variants and genes. Thus, algorithms that prioritize likely causal genes and variants for a given phenotype can provide biological interpretations of association data.
Fine, Rebecca S., Pers, Tune H., Amariuta, Tiffany, Raychaudhuri, Soumya, Hirschhorn, Joel N.   +4 more
openaire   +3 more sources

A Coherent Pattern Mining Algorithm Based on All Contiguous Column Bicluster

Journal of Artificial Intelligence and Technology, 2022
Microarray contains a large matrix of information and has been widely used by biologists and bio data scientist for monitoring combinations of genes in different organisms. The coherent patterns in all continuous columns are mined in gene microarray data
Xiaohui Hu, Qiuhua Kuang, Qianhua Cai, Yun Xue, Weixing Zhou, Ying Li   +5 more
semanticscholar   +1 more source

From knockouts to networks: establishing direct cause-effect relationships through graph analysis. [PDF]

PLoS ONE, 2010
BACKGROUND: Reverse-engineering gene networks from expression profiles is a difficult problem for which a multitude of techniques have been developed over the last decade.
Andrea Pinna, Nicola Soranzo, Nicola Soranzo, Alberto de la Fuente   +3 more
doaj   +1 more source

Parameterless Gene-Pool Optimal Mixing Evolutionary Algorithms [PDF]

Evolutionary Computation, 2021
When it comes to solving optimization problems with evolutionary algorithms (EAs) in a reliable and scalable manner, detecting and exploiting linkage information, that is, dependencies between variables, can be key.
A. Dushatskiy, M. Virgolin, A. Bouter, D. Thierens, P. Bosman   +4 more
semanticscholar   +1 more source

A comparison and evaluation of five biclustering algorithms by quantifying goodness of biclusters for gene expression data [PDF]

BioData Mining, 2012
Abstract Background Several biclustering algorithms have been proposed to identify biclusters, in which genes share similar expression patterns across a number of conditions. However, different algorithms would yield different biclusters and further lead to distinct conclusions. Therefore, some testing and comparisons
Li Li, Yang Guo, Wenwu Wu, Youyi Shi, Jian Cheng, Shiheng Tao   +5 more
openaire   +3 more sources

A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms

Frontiers in Neuroscience, 2022
An IA is an abnormal swelling of cerebral vessels, and a subset of these IAs can rupture causing aneurysmal subarachnoid hemorrhage (aSAH), often resulting in death or severe disability.
Qingqing Li, Qingqing Li, Peipei Wang, Peipei Wang, Jinlong Yuan, Yunfeng Zhou, Yaxin Mei, Yaxin Mei, Mingquan Ye, Mingquan Ye   +9 more
doaj   +1 more source