Results 81 to 90 of about 411,688 (293)

Boosting the concordance index for survival data--a unified framework to derive and evaluate biomarker combinations. [PDF]

PLoS ONE, 2014
The development of molecular signatures for the prediction of time-to-event outcomes is a methodologically challenging task in bioinformatics and biostatistics.
Andreas Mayr, Matthias Schmid
doaj   +1 more source

gdGSE: An algorithm to evaluate pathway enrichment by discretizing gene expression values

Computational and Structural Biotechnology Journal
We proposed gdGSE, a novel computational framework for gene set enrichment analysis. Unlike conventional methods that rely on continuous gene expression values, gdGSE employs discretized gene expression profiles to assess pathway activity. This approach effectively mitigates discrepancies caused by data distributions.
Jiangti Luo, Qiqi Lu, Mengjiao He, Xiaobo Zhang, Xiang Yang, Xiaosheng Wang   +5 more
openaire   +2 more sources

Evolutionary Clustering Algorithm with Knowledge-Based Evaluation for Fuzzy Cluster Analysis of Gene Expression Profiles [PDF]

, 2005
Clustering method, which groups thousands of genes by their similarities of expression levels, has been used for identifying unknown functions of genes. Fuzzy clustering method that is one category of clustering assigns one sample to multiple groups according to their membership degrees.
Han-Saem Park, Sung-Bae Cho
openaire   +1 more source

Mining Images in Biomedical Publications: Detection and Analysis of Gel Diagrams [PDF]

, 2014
Authors of biomedical publications use gel images to report experimental results such as protein-protein interactions or protein expressions under different conditions. Gel images offer a concise way to communicate such findings, not all of which need to
Krauthammer, Michael, Kuhn, Tobias, Luong, ThaiBinh, Nagy, Mate Levente   +3 more
core   +2 more sources

Plasma extrachromosomal circular DNA as a biomarker in EGFR‐targeted therapy of non‐small cell lung cancer

Molecular Oncology, EarlyView.
Detection of extrachromosomal circular DNA (eccDNA) in plasma samples from EGFR‐mutated non‐small cell lung cancer patients. Plasma was collected before and during treatment with the EGFR‐tyrosine kinase inhibitor osimertinib. Plasma eccDNA was detected in all cancer samples, and the presence of the EGFR gene on eccDNA serves as a potential biomarker ...
Simone Stensgaard, Sarmad Mehmood, Eva Boysen Fynboe Ebert, Peter Meldgaard, Anindya Dutta, Boe S. Sorensen   +5 more
wiley   +1 more source

Evaluation of clustering algorithms for gene expression data using gene ontology annotations.

Chinese medical journal, 2013
Clustering is a useful exploratory technique for interpreting gene expression data to reveal groups of genes sharing common functional attributes. Biologists frequently face the problem of choosing an appropriate algorithm. We aimed to provide a standalone, easily accessible and biologically oriented criterion for expression data clustering evaluation ...
Ning, Ma, Zheng-Guo, Zhang
openaire   +1 more source

PDGA: The primal-dual genetic algorithm [PDF]

, 2003
Copyright @ 2003 IOS PressGenetic algorithms (GAs) are a class of search algorithms based on principles of natural evolution. Hence, incorporating mechanisms used in nature may improve the performance of GAs.
Yang, S
core   +1 more source

Liquid biopsy epigenetics: establishing a molecular profile based on cell‐free DNA

Molecular Oncology, EarlyView.
Cell‐free DNA (cfDNA) fragments in plasma from cancer patients carry epigenetic signatures reflecting their cells of origin. These epigenetic features include DNA methylation, nucleosome modifications, and variations in fragmentation. This review describes the biological properties of each feature and explores optimal strategies for harnessing cfDNA ...
Christoffer Trier Maansson, Anders Lade Nielsen, Boe Sandahl Sorensen   +2 more
wiley   +1 more source

Integrating Feature Selection and Feature Extraction Methods With Deep Learning to Predict Clinical Outcome of Breast Cancer

IEEE Access, 2018
In many microarray studies, classifiers have been constructed based on gene signatures to predict clinical outcomes for various cancer sufferers. However, signatures originating from different studies often suffer from poor robustness when used in the ...
Dejun Zhang, Lu Zou, Xionghui Zhou, Fazhi He   +3 more
doaj   +1 more source

Performance evaluation of different machine learning algorithms in presence of outliers using gene expression data

Journal of Bio-Science, 2019
Classification of samples into one or more populations is one of the main objectives of gene expression data (GED) analysis. Many machine learning algorithms were employed in several studies to perform this task. However, these studies did not consider the outliers problem.
MNH Mollah, SMS Islam, H Akter, MI Asifuzzaman, MM Rashid, M Shahjaman   +5 more
openaire   +2 more sources