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AAAI
2007
14 years 1 months ago
Biomind ArrayGenius and GeneGenius: Web Services Offering Microarray and SNP Data Analysis via Novel Machine Learning Methods
Analysis of postgenomic biological data (such as microarray and SNP data) is a subtle art and science, and the statistical methods most commonly utilized sometimes prove inadequat...
Ben Goertzel, Cassio Pennachin, Lúcio de So...
APBC
2003
116views Bioinformatics» more  APBC 2003»
14 years 7 days ago
An Empirical Comparison of Supervised Machine Learning Techniques in Bioinformatics
Research in bioinformatics is driven by the experimental data. Current biological databases are populated by vast amounts of experimental data. Machine learning has been widely ap...
Aik Choon Tan, David Gilbert
IJON
2008
186views more  IJON 2008»
13 years 11 months ago
Computational analysis and learning for a biologically motivated model of boundary detection
In this work we address the problem of boundary detection by combining ideas and approaches from biological and computational vision. Initially, we propose a simple and efficient ...
Iasonas Kokkinos, Rachid Deriche, Olivier D. Fauge...
BMCBI
2008
134views more  BMCBI 2008»
13 years 11 months ago
Identification of transcription factor contexts in literature using machine learning approaches
Background: Availability of information about transcription factors (TFs) is crucial for genome biology, as TFs play a central role in the regulation of gene expression. While man...
Hui Yang, Goran Nenadic, John A. Keane
AUSAI
2008
Springer
14 years 26 days ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan