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BMCBI
2008
160views more  BMCBI 2008»
11 years 9 months ago
Predicting cancer involvement of genes from heterogeneous data
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...
Ramon Aragues, Chris Sander, Baldo Oliva
BMCBI
2007
94views more  BMCBI 2007»
11 years 9 months ago
A Hidden Markov Model to estimate population mixture and allelic copy-numbers in cancers using Affymetrix SNP arrays
Background: Affymetrix SNP arrays can interrogate thousands of SNPs at the same time. This allows us to look at the genomic content of cancer cells and to investigate the underlyi...
Philippe Lamy, Claus L. Andersen, Lars Dyrskjot, N...
BMCBI
2007
97views more  BMCBI 2007»
11 years 9 months ago
SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets
Background: Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, lea...
Carmen Lai, Hugo M. Horlings, Marc J. van de Vijve...
BMCBI
2007
207views more  BMCBI 2007»
11 years 9 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
BMCBI
2010
125views more  BMCBI 2010»
11 years 9 months ago
Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types
Background: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in stand...
Noor B. Dawany, Aydin Tozeren
BMCBI
2007
113views more  BMCBI 2007»
11 years 9 months ago
miRAS: a data processing system for miRNA expression profiling study
Background: The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even a...
Feng Tian, Huayue Zhang, Xinyu Zhang, Chi Song, Yo...
BMCBI
2010
122views more  BMCBI 2010»
11 years 9 months ago
Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data
Background: Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduc...
Kai-Lin Tang, Tong-Hua Li, Wen-Wei Xiong, Kai Chen
BMCBI
2010
131views more  BMCBI 2010»
11 years 9 months ago
JISTIC: Identification of Significant Targets in Cancer
Background: Cancer is caused through a multistep process, in which a succession of genetic changes, each conferring a competitive advantage for growth and proliferation, leads to ...
Felix Sanchez-Garcia, Uri David Akavia, Eyal Mozes...
BMCBI
2010
96views more  BMCBI 2010»
11 years 9 months ago
Incorporating gene co-expression network in identification of cancer prognosis markers
Background: Extensive biomedical studies have shown that clinical and environmental risk factors may not have sufficient predictive power for cancer prognosis. The development of ...
Shuangge Ma, Mingyu Shi, Yang Li, Danhui Yi, Ben-C...
APBC
2003
128views Bioinformatics» more  APBC 2003»
11 years 11 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
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