scholarly journals FGX: a frequentist gene expression index for Affymetrix arrays

Biostatistics ◽  
2006 ◽  
Vol 8 (2) ◽  
pp. 433-437 ◽  
Author(s):  
V. Purutcuoglu ◽  
E. Wit
Keyword(s):  
Gene Expression ◽  
Expression Index

Quantitative neurogenetics: applications in understanding disease

2021 ◽  
Author(s):  
Ali Afrasiabi ◽  
Jeremy T. Keane ◽  
Julian Ik-Tsen Heng ◽  
Elizabeth E. Palmer ◽  
Nigel H. Lovell ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Risk ◽  
Tissue Specificity ◽  
High Throughput Sequencing ◽  
Molecular Genetic ◽  
Brain Dysfunction ◽  
Neural Cells ◽  
Expression Index ◽  
The Central Nervous System ◽  
The Brain

Neurodevelopmental and neurodegenerative disorders (NNDs) are a group of conditions with a broad range of core and co-morbidities, associated with dysfunction of the central nervous system. Improvements in high throughput sequencing have led to the detection of putative risk genetic loci for NNDs, however, quantitative neurogenetic approaches need to be further developed in order to establish causality and underlying molecular genetic mechanisms of pathogenesis. Here, we discuss an approach for prioritizing the contribution of genetic risk loci to complex-NND pathogenesis by estimating the possible impacts of these loci on gene regulation. Furthermore, we highlight the use of a tissue-specificity gene expression index and the application of artificial intelligence (AI) to improve the interpretation of the role of genetic risk elements in NND pathogenesis. Given that NND symptoms are associated with brain dysfunction, risk loci with direct, causative actions would comprise genes with essential functions in neural cells that are highly expressed in the brain. Indeed, NND risk genes implicated in brain dysfunction are disproportionately enriched in the brain compared with other tissues, which we refer to as brain-specific expressed genes. In addition, the tissue-specificity gene expression index can be used as a handle to identify non-brain contexts that are involved in NND pathogenesis. Lastly, we discuss how using an AI approach provides the opportunity to integrate the biological impacts of risk loci to identify those putative combinations of causative relationships through which genetic factors contribute to NND pathogenesis.

scholarly journals Robust Gene Expression Index

2012 ◽  
Vol 2012 ◽  
pp. 1-12
Author(s):  
Vilda Purutçuoǧlu
Keyword(s):  
Gene Expression ◽  
Fisher Information Matrix ◽  
Maximum Likelihood Method ◽  
Information Matrix ◽  
Simulated Data ◽  
Likelihood Method ◽  
Bench Mark ◽  
Dna Arrays ◽  
Expression Index ◽  
Modified Maximum Likelihood

The frequentist gene expression index (FGX) was recently developed to measure expression on Affymetrix oligonucleotide DNA arrays. In this study, we extend FGX to cover nonnormal log expressions, specifically long-tailed symmetric densities and call our new index as robust gene expression index (RGX). In estimation, we implement the modified maximum likelihood method to unravel the elusive solutions of likelihood equations and utilize the Fisher information matrix for covariance terms. From the analysis via the bench-mark datasets and simulated data, it is shown that RGX has promising results and mostly outperforms FGX in terms of relative efficiency of the estimated signals, in particular, when the data are nonnormal.

scholarly journals Implementation of a gene expression index calculation method based on the PDNN model

2004 ◽  
Vol 21 (5) ◽  
pp. 687-688 ◽  
Author(s):  
H. B. r. Nielsen ◽  
L. Gautier ◽  
S. Knudsen
Keyword(s):  
Gene Expression ◽  
Calculation Method ◽  
Expression Index ◽  
Index Calculation

scholarly journals A compendium of gene expression in normal human tissues

2001 ◽  
Vol 7 (2) ◽  
pp. 97-104 ◽  
Author(s):  
LI-LI HSIAO ◽  
FERNANDO DANGOND ◽  
TAKUMI YOSHIDA ◽  
ROBERT HONG ◽  
RODERICK V. JENSEN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Housekeeping Genes ◽  
Human Tissues ◽  
Biological Processes ◽  
Expression Index ◽  
Specific Expression ◽  
Future Studies ◽  
Biochemical Processes ◽  
Organ Systems ◽  
Normal Human

This study creates a compendium of gene expression in normal human tissues suitable as a reference for defining basic organ systems biology. Using oligonucleotide microarrays, we analyze 59 samples representing 19 distinct tissue types. Of ∼7,000 genes analyzed, 451 genes are expressed in all tissue types and designated as housekeeping genes. These genes display significant variation in expression levels among tissues and are sufficient for discerning tissue-specific expression signatures, indicative of fundamental differences in biochemical processes. In addition, subsets of tissue-selective genes are identified that define key biological processes characterizing each organ. This compendium highlights similarities and differences among organ systems and different individuals and also provides a publicly available resource (Human Gene Expression Index, the HuGE Index, http://www.hugeindex.org ) for future studies of pathophysiology.

The Gene Expression Index c-myc× E2F-1/p21 Is Highly Predictive of Malignant Phenotype in Human Bronchial Epithelial Cells

1998 ◽  
Vol 19 (1) ◽  
pp. 18-24 ◽  
Author(s):  
Jeffrey P. DeMuth ◽  
Clara M. Jackson ◽  
David A. Weaver ◽  
Erin L. Crawford ◽  
Dennis S. Durzinsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Epithelial Cells ◽  
Bronchial Epithelial Cells ◽  
Human Bronchial Epithelial Cells ◽  
Malignant Phenotype ◽  
Expression Index ◽  
Bronchial Epithelial

scholarly journals The c-myc x E2F-1/p21 Interactive Gene Expression Index Augments Cytomorphologic Diagnosis of Lung Cancer in Fine-Needle Aspirate Specimens

2003 ◽  
Vol 5 (3) ◽  
pp. 176-183 ◽  
Author(s):  
Kristy A. Warner ◽  
Erin L. Crawford ◽  
Aiman Zaher ◽  
Robert J. Coombs ◽  
Haitham Elsamaloty ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Fine Needle Aspirate ◽  
Expression Index ◽  
Fine Needle ◽  
Diagnosis Of Lung Cancer

A prognostic gene expression index in ovarian cancer-validation across different independent data sets

2009 ◽  
Vol 218 (2) ◽  
pp. 273-280 ◽  
Author(s):  
Carsten Denkert ◽  
Jan Budczies ◽  
Silvia Darb-Esfahani ◽  
Balazs Györffy ◽  
Jalid Sehouli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Data Sets ◽  
Independent Data ◽  
Expression Index ◽  
Prognostic Gene

scholarly journals Comparative evaluation of IL-17 and TGF-β expression in tissues of patients with chronic periodontitis and healthy individuals using real-time PCR

2018 ◽  
Vol 10 (1) ◽  
pp. 8-12
Author(s):  
Kazem Fatemi ◽  
Seyed Abdolrahim Rezaee ◽  
Amir Moeintaghavi ◽  
Farid Shiezadeh ◽  
Golnaz Dadpour ◽  
...  
Keyword(s):  
Gene Expression ◽  
Real Time ◽  
Chronic Periodontitis ◽  
Treg Cells ◽  
Control Group ◽  
Case Group ◽  
Expression Index ◽  
Tissue Samples ◽  
Crown Length ◽  
Periodontal Inflammation

Background. The present study aimed to determine the association between periodontal disease and the Th17/Treg balance by examining the genetic expression of IL-17 and TGF-β, which influence incidence and suppression of inflammation. Methods. In this case-control study, samples were collected in a randomized and task-oriented order. Thirty-seven patients referred to professional periodontology clinics in Mashhad and the Periodontology Department of the Mashhad Dentistry Faculty for periodontal (case) or crown-length (control) surgery was enrolled. IL-17 and TGF-β gene expression indices were measured in tissue samples by real-time polymerase chain reaction. Results. The IL-17 gene expression index was higher in the case group (2.68±0.91) than in the control group (1.68±0.41), but this difference was not significant. The TGF-β gene expression index was significantly higher in the case group (54.42±7.88) than in the control group (24.12±3.38). Conclusion. L-17 and TGF-β expression is increased in chronic periodontitis patients, but TGF-β plays a more important role in periodontal inflammation in patients with chronic periodontitis. Further studies of the roles of Th17 and Treg cells are warranted.

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