Impact of Parallel Computing on Identifying Biomarkers of Hepatocellular Carcinoma

Hashem, Esraa M.; Mabrouk, Mai S.

doi:10.1166/jmihi.2014.1296

Cited by 2 publications

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After using Haar function, there is a need to remove noise from the signal by decomposing, the input signal into an approximation sub-bands and a set of detail sub-bands at different resolution scales using a set of high pass and low pass filters [25]. The number of samples contained by each sub-band at level N, so the number of input samples divided by 2 N [26].…”

Section: B Discrete Stationary Wavelet Transform (Dswt)mentioning

confidence: 99%

Novel Altered Region for Biomarker Discovery in Hepatocellular Carcinoma (HCC) Using Whole Genome SNP Array

Hashem¹,

Mabrouk²,

Eldeib³

2016

ijacsa

View full text Add to dashboard Cite

Abstract-cancer represents one of the greatest medical causes of mortality. The majority of Hepatocellular carcinoma arises from the accumulation of genetic abnormalities, and possibly induced by exterior etiological factors especially HCV and HBV infections. There is a need for new tools to analysis the large sum of data to present relevant genetic changes that may be critical for both understanding how cancers develop and determining how they could ultimately be treated. Gene expression profiling may lead to new biomarkers that may help develop diagnostic accuracy for detecting Hepatocellular carcinoma. In this work, statistical technique (discrete stationary wavelet transform) for detection of copy number alternations to analysis high-density single-nucleotide polymorphism array of 30 cell lines on specific chromosomes, which are frequently detected in Hepatocellular carcinoma have been proposed. The results demonstrate the feasibility of whole-genome fine mapping of copy number alternations via high-density single-nucleotide polymorphism genotyping, Results revealed that a novel altered chromosomal region is discovered; region amplification (4q22.1) have been detected in 22 out of 30-Hepatocellular carcinoma cell lines (73%). This region strike, AFF1 and DSPP, tumor suppressor genes. This finding has not previously reported to be involved in liver carcinogenesis; it can be used to discover a new HCC biomarker, which helps in a better understanding of hepatocellular carcinoma.

show abstract

Section: B Discrete Stationary Wavelet Transform (Dswt)mentioning

confidence: 99%

Novel Altered Region for Biomarker Discovery in Hepatocellular Carcinoma (HCC) Using Whole Genome SNP Array

Hashem¹,

Mabrouk²,

Eldeib³

2016

ijacsa

View full text Add to dashboard Cite

show abstract

Detecting and Analyzing Copy Number Alternations in Array-Based CGH Data

Sheha

Mabrouk

ElHefnawi

2016

Biomed. Eng. Appl. Basis Commun.

View full text Add to dashboard Cite

Copy number changes or alterations are a form of genetic variation in the human genome. Genomic DNA copy number alterations (CNAs) are associated with the development and progression of cancers. Array-based comparative genomic hybridization (a-CGH) is a technique used to identify copy number changes in genomic DNA. It yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of automated statistics algorithms for learning about the genomic alterations from array CGH data. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data. For this purpose the proposed study introduces three different approaches; Circular binary segmentation, Bayesian approach, relying on the hidden Markov model and effective Gaussian mixture (GM) clustering for the analysis of array CGH profiles. Publicly available data on pancreatic adenocarcinoma and Coriell cell line bacterial artificial chromosome (BAC) array were used for the analysis to illustrate the reliability and success of the techniques.

show abstract

Impact of Parallel Computing on Identifying Biomarkers of Hepatocellular Carcinoma

Cited by 2 publications

References 15 publications

Novel Altered Region for Biomarker Discovery in Hepatocellular Carcinoma (HCC) Using Whole Genome SNP Array

Novel Altered Region for Biomarker Discovery in Hepatocellular Carcinoma (HCC) Using Whole Genome SNP Array

Detecting and Analyzing Copy Number Alternations in Array-Based CGH Data

Contact Info

Product

Resources

About