Matrix methods for gene expression analysis

Pattern Recognition Methods for Gene Expression Analysis

Computer pattern recognition is a very important field of the human knowledge with applications in complex and diversified areas. Particularly in bioinformatics, pattern recognition is applied to address a miriad of problems such as identification of important regions in DNA sequences, biological classification (diagnostic) of a tissue based on mRNA expression of thousands of genes, functional ...

islanding detection methods for microgrids

امروزه استفاده از منابع انرژی پراکنده کاربرد وسیعی یافته است . اگر چه این منابع بسیاری از مشکلات شبکه را حل می کنند اما زیاد شدن آنها مسائل فراوانی برای سیستم قدرت به همراه دارد . استفاده از میکروشبکه راه حلی است که علاوه بر استفاده از مزایای منابع انرژی پراکنده برخی از مشکلات ایجاد شده توسط آنها را نیز منتفی می کند . همچنین میکروشبکه ها کیفیت برق و قابلیت اطمینان تامین انرژی مشترکان را افزایش ...

Geometric optimization methods for the analysis of gene expression data

DNA microarrays provide such a huge amount of data that unsupervised methods are required to reduce the dimension of the data set and to extract meaningful biological information. This work shows that Independent Component Analysis (ICA) is a promising approach for the analysis of genome-wide transcriptomic data. The paper first presents an overview of the most popular algorithms to perform ICA...

Algorithmic Methods for the Analysis of Gene Expression Data

The traditional approach to molecular biology consists of studying a small number of genes or proteins that are related to a single biochemical process or pathway. A major paradigm shift recently occurred with the introduction of gene expression microarrays that measure the expression levels of thousands of genes at once. These comprehensive snapshots of gene activity can be used to investigate...

HYPOTHESIS SETTINGS AND METHODS FOR GENE EXPRESSION META-ANALYSIS by