Microarray probes and probe sets

Liu, Hongfang

doi:10.2741/e93

Cited by 55 publications

(37 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The imperfect and variable correlation between mRNA and protein levels is in agreement with previous reports (4, 10–13) and can be explained by post-transcriptional and post-translational regulation and by misclassification due to measurement errors (14–17). The different levels of inaccuracy, noise, sensitivity and dynamic ranges of the methods used for transcript and protein analysis likely contribute to the lack of correlation observed for several of the markers examined (18–23). In addition, the measurement of levels of secreted cytokines instead of total intracellular levels may also have contributed in part for differences in between the two measures.…”

Section: Discussionmentioning

confidence: 99%

Comparison of mRNA and Protein Measures of Cytokines following Vaccination with Human Papillomavirus-16 L1 Virus-like Particles

Shebl

Pinto

Garcı́a-Piñeres

et al. 2010

Cancer Epidemiology, Biomarkers &Amp; Prevention

107

View full text Add to dashboard Cite

Background: mRNA expression signatures are frequently used as surrogate measures of cellular function and pathway changes. Few studies have directly compared results obtained using gene expression and multiplex protein assays for corresponding gene products.Methods: We used data available from a clinical trial of a human papillomavirus-16 vaccine that tracked gene expression and cytokine/chemokine production by peripheral blood mononuclear cells stimulated in culture with various antigens to evaluate the degree to which gene expression levels reflect observed levels of cytokines/chemokines. Twenty-six women enrolled in a phase II clinical trial of a human papillomavirus-16 vaccine were evaluated for gene expression (using the Affymetrix Human Genome Focus Array) and cytokine/chemokine levels (using a bead-based 22-plex cytokine assay developed by Linco Research, Inc.) before and after vaccination.Results: Our results suggest the presence of a wide range of correlations between mRNA expression and secreted protein levels. The strongest correlation was observed for IFN-γ (R = 0.90 overall levels; R = 0.69 when vaccine induced changes were evaluated). More modest overall correlations ranging from 0.40 to 0.80 were observed for MIP1A, IP10, TNF-α, MCP1, IL-2, GM-CSF, IL-5, RANTES, and IL-8. Weaker or no correlation was observed between gene expression and protein levels for the remaining cytokines/chemokines evaluated.Conclusion: The degree of correlation between gene expression and protein levels varied among different cytokines/chemokines. Impact: Researchers should be cautious when using mRNA expression array results as a proxy for protein levels using existing technologies. Cancer Epidemiol Biomarkers Prev; 19(4); 978-81. ©2010 AACR.

show abstract

Section: Discussionmentioning

confidence: 99%

Comparison of mRNA and Protein Measures of Cytokines following Vaccination with Human Papillomavirus-16 L1 Virus-like Particles

Shebl

Pinto

Garcı́a-Piñeres

et al. 2010

Cancer Epidemiology, Biomarkers &Amp; Prevention

107

View full text Add to dashboard Cite

show abstract

“…Moreover, up to 30,000 control probes are used to verify amplification and hybridization (spiked-in bacteria probes) making the microarray a reliable tool for holistic transcriptomic analysis. However, the need to clarify the identity of microarray probes and probe sets has been demanded elsewhere [5,6]. Holistic expression analyses require highly accurate annotation data to ensure the quality and reliability of a data set.…”

Section: Introductionmentioning

confidence: 99%

rePROBE: Workflow for Revised Probe Assignment and Updated Probe-Set Annotation in Microarrays

Hadlich

Reyer

Oster

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Elde edilen bu bilgiler sayesinde hastalıkların önlemesi yönünde tedbirler alınabilmektedir. Bu teknik sayesinde ayrıca gen üzerinde taşınan kalıtsal hastalıklar, alt türlerine kadar incelenebilmektedir [7].…”

Section: Gi̇ri̇ş (Introduction)unclassified

“…Elde edilen sonuçlar ise yüzlerce genin ifadesini barındırdığından dolayı sonuçları yorumlamanın bir hayli zor olduğu ve çok pahalı bir yöntem olduğundan dolayı çok fazla deneylerin tekrarlanamaması ise dezavantajlarını oluşturur [7].…”

Section: Gi̇ri̇ş (Introduction)unclassified

Karaciğer Mikroarray Kanser Verisinin Sınıflandırılması için Genetik Algoritma Kullanarak ANFIS’in eğitilmesi

Haznedar¹,

Arslan²,

Kalınlı³

2017

SAÜ Fen Bilimleri Enstitüsü Dergisi

View full text Add to dashboard Cite

ÖZSınıflandırma, verilerin analiz edilmesi için önemli bir veri madenciliği tekniği olup tıp, genetik ve biyomedikal mühendisliği başta olmak üzere birçok alanda kullanılmaktadır. Özellikle tıp alanında DNA mikrodizi gen ekspresyon verilerini sınıflandırmaya yönelik yapılan çalışmalarda artış görülmektedir. Ancak, mikrodizi gen ekspresyon (ifade) verilerinde bulunan gen sayılarının çokluğu ve bu veriler arasında doğrusal olmayan bağıntılar bulunması gibi problemlerden dolayı geleneksel sınıflandırma algoritmalarının başarımları sınırlı kalabilmektedir. Bu sebeplerden dolayı son yıllarda sınıflandırma probleminin çözümü için yapay zekâ tekniklerine dayalı sınıflandırma yöntemlerine olan ilgi giderek artmaya başlamıştır. Bu çalışmada, karaciğer mikrodizi kanser veri setinin sınıflandırılması için Uyarlamalı Ağ Tabanlı Bulanık Mantık Çıkarım Sistemi (ANFIS) ve Genetik Algoritmaya (GA) dayalı hibrid bir yaklaşım önerilmiştir. Simülasyon sonuçları, diğer bazı yöntemlere ait sonuçlarla karşılaştırılmıştır. Elde edilen sonuçlardan, önerilen yöntemin diğer yöntemlere göre daha başarılı olduğu görülmüştür.Anahtar Kelimeler: Neuro-fuzzy, ANFIS, genetik algoritma, sınıflandırma, mikrodizi gen ifade Training ANFIS structure using genetic algorithm for liver cancer classification based on microarray gene expression data ABSTRACT Classification is an important data mining technique, which is used in many fields mostly exemplified as medicine, genetics and biomedical engineering. The number of studies about classification of the datum on DNA microarray gene expression is specifically increased in recent years. However, because of the reasons as the abundance of gene numbers in the datum as microarray gene expressions and the nonlinear relations mostly across those datum, the success of conventional classification algorithms can be limited. Because of these reasons, the interest on classification methods which are based on artificial intelligence to solve the problem on classification has been gradually increased in recent times. In this study, a hybrid approach which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA) are suggested in order to classify liver microarray cancer data set. Simulation results are compared with the results of other methods. According to the results obtained, it is seen that the recommended method is better than the other methods.

show abstract

Microarray probes and probe sets

Cited by 55 publications

References 64 publications

Comparison of mRNA and Protein Measures of Cytokines following Vaccination with Human Papillomavirus-16 L1 Virus-like Particles

Comparison of mRNA and Protein Measures of Cytokines following Vaccination with Human Papillomavirus-16 L1 Virus-like Particles

rePROBE: Workflow for Revised Probe Assignment and Updated Probe-Set Annotation in Microarrays

Karaciğer Mikroarray Kanser Verisinin Sınıflandırılması için Genetik Algoritma Kullanarak ANFIS’in eğitilmesi

Contact Info

Product

Resources

About