Unsupervised Clustering Analysis of Gene Expression
نویسندگان
چکیده
The availability of whole genome sequence data has facilitated the development of high-throughput technologies for monitoring biological signals on a genomic scale. The revolutionary microarray technology, first introduced in 1995 (Schena et al., 1995), is now one of the most valuable techniques for global gene expression profiling. Other high-throughput genomic technologies, such as Serial Analysis of Gene Expression (SAGE) (Velculescu et al., 1995), mass spectrometry for protein identification (Henzel et al., 1993) and ChIP-chip for DNA binding (Ren et al., 2000), have also been widely used for different purposes in current biological and medical research.
منابع مشابه
Expression Profiling of Microarray Gene Signatures in Acute and Chronic Myeloid Leukaemia in Human Bone Marrow
Background Classification of cancer subtypes by means of microarray signatures is becoming increasingly difficult to ignore as a potential to transform pathological diagnosis nonetheless, measurement of Indicator genes in routine practice appears to be arduous. In a preceding published study, we utilized real-time PCR measurement of Indicator genes in acute lymphoid leukaemia (ALL) and acute m...
متن کاملبررسی اثرات تغییر بیان ریز آر ان ای های سلولی ناشی از ویروس پاپیلوم انسانی در سلول های سرطانی سنگفرشی سر و گردن در سطح پروفیل بیان ژنی
Background and aim: Human Papilloma Virus plays an important role in some of human malignancies and causes alterations in normal expression levels of cellular microRNAs. In this paper, we evaluated the effects of such changes on Head and Neck Squamous Cell Carcinoma tumor samples at gene expression profile level. Methods: in this descriptive-analytical study, gene expression profiles of 36 tum...
متن کاملModification of the Fast Global K-means Using a Fuzzy Relation with Application in Microarray Data Analysis
Recognizing genes with distinctive expression levels can help in prevention, diagnosis and treatment of the diseases at the genomic level. In this paper, fast Global k-means (fast GKM) is developed for clustering the gene expression datasets. Fast GKM is a significant improvement of the k-means clustering method. It is an incremental clustering method which starts with one cluster. Iteratively ...
متن کاملComparison Between Unsupervised and Supervise Fuzzy Clustering Method in Interactive Mode to Obtain the Best Result for Extract Subtle Patterns from Seismic Facies Maps
Pattern recognition on seismic data is a useful technique for generating seismic facies maps that capture changes in the geological depositional setting. Seismic facies analysis can be performed using the supervised and unsupervised pattern recognition methods. Each of these methods has its own advantages and disadvantages. In this paper, we compared and evaluated the capability of two unsuperv...
متن کاملHigh-Dimensional Unsupervised Active Learning Method
In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...
متن کاملInterrelated Two-way Clustering: An Unsupervised Approach for Gene Expression Data Analysis
DNA arrays can be used to measure the expression levels of thousands of genes simultaneously. Currently most research focuses on the interpretation of the meaning of the data. However, majority methods are supervised-based, less attention has been paid on unsupervised approaches which is important when domain knowledge is incomplete or hard to obtain. In this paper, we present a new framework f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006