In situ footprinting of chicken histone H5 gene in mature and immature erythrocytes reveals common factor-binding sites

Chromosoma ◽  
1996 ◽  
Vol 104 (7) ◽  
pp. 504-510 ◽  
Author(s):  
Jian-Min Sun ◽  
Rosa Ferraiuolo ◽  
James R. Davie
Keyword(s):  
Binding Sites ◽  
Common Factor ◽  
Factor Binding ◽  
Histone H5

In situ footprinting of chicken histone H5 gene in mature and immature erythrocytes reveals common factor-binding sites

Chromosoma ◽  
1996 ◽  
Vol 104 (7) ◽  
pp. 504-510
Author(s):  
Jian-Min Sun ◽  
Rosa Ferraiuolo ◽  
James R. Davie
Keyword(s):  
Binding Sites ◽  
Common Factor ◽  
Factor Binding ◽  
Histone H5

scholarly journals Upstream stimulatory factor (USF) and neurogenic differentiation/beta-cell E box transactivator 2 (NeuroD/BETA2) contribute to islet-specific glucose-6-phosphatase catalytic-subunit-related protein (IGRP) gene expression

2003 ◽  
Vol 371 (3) ◽  
pp. 675-686 ◽  
Author(s):  
Cyrus C. MARTIN ◽  
Christina A. SVITEK ◽  
James K. OESER ◽  
Eva HENDERSON ◽  
Roland STEIN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Binding Sites ◽  
Fusion Gene ◽  
Catalytic Subunit ◽  
Related Protein ◽  
Upstream Stimulatory Factor ◽  
Factor Binding ◽  
E Box ◽  
Stimulatory Factor

Islet-specific glucose-6-phosphatase (G6Pase) catalytic-subunit-related protein (IGRP) is a homologue of the catalytic subunit of G6Pase, the enzyme that catalyses the final step of the gluconeogenic pathway. The analysis of IGRP-chloramphenicol acetyltransferase (CAT) fusion-gene expression through transient transfection of islet-derived βTC-3 cells revealed that multiple promoter regions, located between −306 and −97, are required for maximal IGRP-CAT fusion-gene expression. These regions correlated with trans-acting factor-binding sites in the IGRP promoter that were identified in βTC-3 cells in situ using the ligation-mediated PCR (LMPCR) footprinting technique. However, the LMPCR data also revealed additional trans-acting factor-binding sites located between −97 and +1 that overlap two E-box motifs, even though this region by itself conferred minimal fusion-gene expression. The data presented here show that these E-box motifs are important for IGRP promoter activity, but that their action is only manifest in the presence of distal promoter elements. Thus mutation of either E-box motif in the context of the −306 to +3 IGRP promoter region reduces fusion-gene expression. These two E-box motifs have distinct sequences and preferentially bind NeuroD/BETA2 neurogenic differentiation/β-cell E box transactivator 2 and upstream stimulatory factor (USF) in vitro, consistent with the binding of both factors to the IGRP promoter in situ, as determined using the chromatin-immunoprecipitation (ChIP) assay. Based on experiments using mutated IGRP promoter constructs, we propose a model to explain how the ubiquitously expressed USF could contribute to islet-specific IGRP gene expression.

Electron Probe Analysis of Muscle

1982 ◽  
Vol 40 ◽  
pp. 398-401
Author(s):  
A. V. Somlyo ◽  
H. Shuman ◽  
A. P. Somlyo
Keyword(s):  
Skeletal Muscle ◽  
Smooth Muscle ◽  
Sarcoplasmic Reticulum ◽  
Resting State ◽  
Binding Sites ◽  
Electron Probe ◽  
Frog Skeletal Muscle ◽  
Electron Probe Analysis ◽  
Probe Analysis

Electron probe analysis of frozen dried cryosections of frog skeletal muscle, rabbit vascular smooth muscle and of isolated, hyperpermeab1 e rabbit cardiac myocytes has been used to determine the composition of the cytoplasm and organelles in the resting state as well as during contraction. The concentration of elements within the organelles reflects the permeabilities of the organelle membranes to the cytoplasmic ions as well as binding sites. The measurements of [Ca] in the sarcoplasmic reticulum (SR) and mitochondria at rest and during contraction, have direct bearing on their role as release and/or storage sites for Ca in situ.

scholarly journals Prediction of Transcription Factor Binding Sites of SP1 on Human Chromosome1

2021 ◽  
Vol 11 (11) ◽  
pp. 5123
Author(s):  
Maiada M. Mahmoud ◽  
Nahla A. Belal ◽  
Aliaa Youssif
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Messenger Rna ◽  
Area Under The Curve ◽  
Noisy Data ◽  
Transcription Factor Binding Sites ◽  
Classification Problem ◽  
Transcription Factor Binding ◽  
K Nearest Neighbors ◽  
Factor Binding

Transcription factors (TFs) are proteins that control the transcription of a gene from DNA to messenger RNA (mRNA). TFs bind to a specific DNA sequence called a binding site. Transcription factor binding sites have not yet been completely identified, and this is considered to be a challenge that could be approached computationally. This challenge is considered to be a classification problem in machine learning. In this paper, the prediction of transcription factor binding sites of SP1 on human chromosome1 is presented using different classification techniques, and a model using voting is proposed. The highest Area Under the Curve (AUC) achieved is 0.97 using K-Nearest Neighbors (KNN), and 0.95 using the proposed voting technique. However, the proposed voting technique is more efficient with noisy data. This study highlights the applicability of the voting technique for the prediction of binding sites, and highlights the outperformance of KNN on this type of data. The study also highlights the significance of using voting.

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