A personalized microRNA microarray normalization method using a logistic regression model

A personalized microRNA microarray normalization method using a logistic regression model

MOTIVATION MicroRNA (miRNA) is a set of newly discovered non-coding small RNA molecules. Its significant effects have contributed to a number of critical biological events including cell proliferation, apoptosis development, as well as tumorigenesis. High-dimensional genomic discovery platforms (e.g. microarray) have been employed to evaluate the important roles of miRNAs by analyzing their exp...

Distributed Search Using A Logistic Regression Model

This short paper presents some preliminary effectiveness results for a probabilistic approach to distributed information retrieval using a Logistic regression algorithm for estimation of collection relevance. The algorithm is compared to other methods for distributed search using test collections developed for distributed search evaluation.

cDNA Microarray Data Normalization

An Iterative Nonlinear Regression Method for Microarray Data Normalization

Normalization is a prerequisite for almost all follow-up steps in microarray data analysis. Accurate normalization across different experiments and phenotypes assures a common base for comparative yet quantitative studies using gene expression data. In this paper, we report a novel normalization approach, namely iterative nonlinear regression (INR) method, which exploits concurrent identificati...

Score Normalization Using Logistic Regression with Expected Parameters

State-of-the-art score normalization methods use generative models that rely on sometimes unrealistic assumptions. We propose a novel parameter estimation method for score normalization based on logistic regression, using the expected parameters from past queries. Experiments on the Gov2 and CluewebA collection indicate that our method is consistently more precise in predicting the number of re...