Bioinformatics - the machine learning approach (2. ed.)

By Pierre Baldi, Søren Brunak. 2000

440 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/6383011826c14af5d63700b4a3dd6e33391c55d0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Niko Beerenwinkel
2. Thomas Lengauer
3. Oliver Sander
4. Tobias Sing
5. Chin-Teng Lin
6. Vasant G Honavar
7. Adrian Silvescu
8. Yangyang Shen

Citations in the corpus

• Recognition of Structure Classification of Protein Folding by NN and SVM Hierarchical Learning Architecture (2003, methodology): “Besides, these methods may cause the problem called ‘False Positive,’ resulting in poor classification accuracy [2].”
• Discriminatively trained Markov model for sequence classification (2005, background): “Hence it is useful to consider multiple performance criteria in evaluating learning algorithms [3].”
• ROCR: visualizing classifier performance in R (2005, background): “Pattern classification has become a central tool in bioinformatics, offering rapid insights into large data sets (Baldi and Brunak, 2001).”