NDLI: Identification of a Breast Cancer Associated Regulatory Network

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2009 Ohio Collaborative Conference on Bioinformatics

Cover Art

Modeling Genetic and Environmental Factors in Biological Systems Using Structural Equation Modeling: An Application to Energy Balance

Visualization and Functional Analysis of Genome-Wide Association Results

Comparison of Label Free and 18 O Labeling Mass Spectrometry in Relative Protein Quantification

A New Method for Mapping Short DNA Sequencing Reads by Using Quality Scores

xIP-seq Platform: An Integrative Framework for High-Throughput Sequencing Data Analysis

Computational Challenges and Solutions to the Analysis of Micro RNA Profiles in Virally-Infected Cells Derived by Massively Parallel Sequencing

TIGERA: A New Tool for Illumina Gene Expression Reads Analysis

Understanding Sequence Variability of RNA Motifs Using Geometric Search and IsoDiscrepancy Matrices

Beyond Identity- When Classical Homology Searching Fails, Why, and What you Can do About It

RNA Secondary Structure Prediction in the Presence of Single-Stranded Binding Proteins

Computation of Putative Targets for Human and Mouse snoRNAs, Responsible for Prader-Willi Syndrome

Discovery of Regulatory Networks in Plants by Linking Promoter and Transcription Factor Databases

Construction of Genomic Regulatory Encyclopedias: Strategies and Case Studies

Identification of a Breast Cancer Associated Regulatory Network

Comparative Assessment of DNA Assemblers for Assembling Expressed Sequence Tags

A Comparision of Codon Usage Trends in Prokaryotes

Parallel Approaches for SWAMP Sequence Alignment

The Evolution of Multidrug Resistance in a Hospital Pathogen

HIV Evolution: Fast or Slow?

Uncovering Androgen Responsive Regulatory Networks in Prostate Cancer

Comparative Analysis of Modularity in Biological Systems

Improving Functional Module Detection

Perceived Cost of Auxotrophic Amino Acids in Two Bacterial Species

SNP-SNP Interactions between dNTP Supply Enzymes and Mismatch DNA Repair in Breast Cancer

Binary Classification Based on Potentials

Quantile Scores for Combining Results from Different Microarray Platforms

Comparison of Binary Classification Based on Signed Distance Functions with Support Vector Machines

Author index

Publisher's Information

Identification of a Breast Cancer Associated Regulatory Network

Content Provider	IEEE Xplore Digital Library
Author	Parvin, J.D. Kais, Z. Arora, M. Kotian, S. Zha, A. Ransburgh, D. Bozdag, D. Catalyurek, U. Kun Huang
Copyright Year	2009
Abstract	We are developing a new framework for discovery of genes involved in the breast carcinogenesis process. Among families that have a predisposition to breast cancer, approximately 25% have inherited mutations in either breast cancer associated (“BRCA”) genes BRCA1 or BRCA2, but the predisposing mutated genes in the majority of the families are unknown. BRCA1 and BRCA2 gene products both regulate cellular pathways that involve DNA repair and centrosome duplication, and their expression is correlated in microarray analyses in many cell types. We hypothesize that other unidentified BRCA genes may be involved in the same pathways that BRCA1 and BRCA2 regulate, and thus may be discovered by identifying genes whose expression also is correlated with that of BRCA1 and BRCA2. We interrogate public-domain gene expression databases using newly developed computational tools that include combinatorial and algebraic clustering methods to identify genes whose expression correlates with these tumor suppressors. Identified genes are then tested in the laboratory. RNA interference is used to disrupt the expression of the candidate BRCA gene products in two different cell-based assays that are dependent on BRCA1 and BRCA2 expression. The first assay models the regulation of homology-directed recombination repair of double-strand DNA breaks, and the second assay tests the control of duplication of the centrosome. We have selected nine genes that tightly cluster with BRCA1 and BRCA2 expression in multiple datasets, and these nine genes have never before been linked with the two reference genes. When tested in the lab using RNA interference to deplete the specific protein, six of these genes were found to affect homologous recombination and four affected the regulation of centrosome number. If the informatics analysis is considered a screening tool to find genes/proteins involved in breast carcinogenesis, then this approach has an extremely high success rate in finding proteins that impact phenotypes regulated by BRCA1 and BRCA2. In summary, we employ a novel experimental framework that develops new bioinformatic tools for identifying candidate genes whose regulation suggests the potential for involvement in breast carcinogenesis, and we validate the gene in the lab. This experimental framework may also be applicable to the identification of networks of genes involved in common pathways in other disease processes.
Starting Page	71
Ending Page	75
File Size	2467328
Page Count	5
File Format	PDF
ISBN	9780769536859
DOI	10.1109/OCCBIO.2009.37
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	RNA Clustering methods Genetic mutations Interference breast cancer Breast cancer BRCA1 Gene expression BRCA2 Proteins Databases DNA Testing
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Comparative study of multivariate classification methods using microarray gene expression data for BRCA1/BRCA2 cancer tumors

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The importance of BRCA1 and BRCA2 genes mutations in breast cancer development.

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Identification of a Breast Cancer Associated Regulatory Network

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