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10 results on '"Shustova, Valentina"'

3. ALLERGY TO ANOPHELES

Author

Ado, Andrey D., Bondareva, Galena P., and Shustova, Valentina I.

Published
1996

5. Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions

Author

Selaru, Florin M., primary, Xu, Yan, additional, Yin, Jing, additional, Zou, Tong, additional, Liu, Thomas C., additional, Mori, Yuriko, additional, Abraham, John M., additional, Sato, Fumiaki, additional, Wang, Suna, additional, Twigg, Charlie, additional, Olaru, Andreea, additional, Shustova, Valentina, additional, Leytin, Anatoly, additional, Hytiroglou, Prodromos, additional, Shibata, David, additional, Harpaz, Noam, additional, and Meltzer, Stephen J., additional

Published
2002
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7. Amplified RNA for Gene Array Hybridizations.

Author

Walker, John M., O'Connell, Joe, Shustova, Valentina I., and Meltzer, Stephen J.

Abstract

The human genome contains perhaps more than 50,000 genes. A typical cell in the human body is believed to express from 15,000 to 25,000 proteins. The majority of these proteins are expressed in all the cells, and are known as housekeeping genes. These are proteins involved in vital cell functions, including production of energy, oxidation, biosynthesis, regulation of cell cycle, and cell growth. The rest of the proteins are expressed differentially in various cell types. For example, some genes are expressed only in liver cells, muscle cells, or neurons, and not in any other cell types. These differentially expressed genes define the phenotype and function of a particular cell type. The identification of genes solely expressed in one cell type may shed light on mechanisms of cellular function and gene interaction. [ABSTRACT FROM AUTHOR]

Published
2002
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8. Application of cDNA microarrays to generate a molecular taxonomy capable of distinguishing between colon cancer and normal colon.

Author

Tong-Tong Zou, Selaru, Florin M., Yan Xu, Shustova, Valentina, Jing Yin, Mori, Yuriko, Shibata, David, Sato, Fumiaki, Suma Wang, Olaru, Andreea, Deacu, Elena, Liu, Thomas C., Abraham, John M., and Meltzer, Stephen J.

Subjects
COLON cancer, DNA microarrays, PRECANCEROUS conditions, EPITHELIAL tumors, COMPUTER software
Abstract

Presents a study where microarrays were hybridized to labeled RNA obtained from several colonic specimens in order to discover global gene expression patterns characterizing subgroups of colon cancer. Information on colorectal cancer; Importance of the early detection of colon cancer in the premalignant stages; Application of the software program Significant Analysis of Microarrays to identify genes whose expression were used to distinguish between normal and cancerous colonic epithelium.

Published
2002
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9. Artificial neural networks and gene filtering distinguish between global gene expression profiles of Barrett's esophagus and esophageal cancer.

Author

Xu Y, Selaru FM, Yin J, Zou TT, Shustova V, Mori Y, Sato F, Liu TC, Olaru A, Wang S, Kimos MC, Perry K, Desai K, Greenwald BD, Krasna MJ, Shibata D, Abraham JM, and Meltzer SJ

Subjects
Adenocarcinoma genetics, Adenocarcinoma metabolism, Barrett Esophagus metabolism, Carcinoma, Squamous Cell genetics, Carcinoma, Squamous Cell metabolism, Cluster Analysis, Computational Biology methods, Esophageal Neoplasms metabolism, Gene Expression Profiling, Humans, Multigene Family, Oligonucleotide Array Sequence Analysis, Barrett Esophagus genetics, Esophageal Neoplasms genetics, Neural Networks, Computer
Abstract

cDNAmicroarrays, combined with bioinformatics analyses, are becomingincreasingly used in current medical research. Existing analytic methods,particularly those that are unsupervised, often have difficulty recognizing subtle differences among predefined subgroups. In contrast, supervised methods, such as Artificial Neural Networks (ANNs), are able to recognize subtly different biological entities. We applied ANNs in a proof-of-principle study of cDNA microarray data in esophageal cancer (CA) and premalignancy. cDNA microarrays, each containing 8064 clones, were hybridized to RNAs from 22 esophageal lesions, including 14 Barrett's esophagus (BA) metaplasias and 8 esophageal carcinomas (3 squamous cell carcinomas and 5 adenocarcinomas). Scanned cDNA microarray data were analyzed using the bioinformatics software Cluster/TreeView, Significance Analysis of Microarrays (SAM), and ANNs. Cluster analysis based on all 8064 clones on the microarrays was unable to correctly distinguish BA specimens from CA specimens. SAM then selected 160 differentially expressed genes between Barrett's and cancer. Cluster analysis based on this reduced set still misclassified 2 Barrett's as cancers. The ANN was trained on 12 samples and tested against the remaining 10 samples. Using the 160 selected genes, the ANN correctly diagnosed all 10 samples in the test set. Finally, the 160 genes selected by SAM may merit further study as biomarkers of neoplastic progression in the esophagus, as well as in elucidating pathological mechanisms underlying BA and CA.

Published
2002

10. Amplified RNA for gene array hybridizations.

Author

Shustova VI and Meltzer SJ

Subjects
DNA-Directed RNA Polymerases metabolism, Oligonucleotide Array Sequence Analysis methods, Viral Proteins, RNA biosynthesis, Reverse Transcriptase Polymerase Chain Reaction methods
Published
2002
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