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» Predicting Nucleolar Proteins Using Support-Vector Machines
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ICDM
2007
IEEE
157views Data Mining» more  ICDM 2007»
15 years 10 months ago
Failure Prediction in IBM BlueGene/L Event Logs
Frequent failures are becoming a serious concern to the community of high-end computing, especially when the applications and the underlying systems rapidly grow in size and compl...
Yinglung Liang, Yanyong Zhang, Hui Xiong, Ramendra...
139
Voted
CIBCB
2006
IEEE
15 years 9 months ago
A Model-Free Greedy Gene Selection for Microarray Sample Class Prediction
— Microarray data analysis is notoriously challenging as it involves a huge number of genes compared to only a limited number of samples. Gene selection, to detect the most signi...
Yi Shi, Zhipeng Cai, Lizhe Xu, Wei Ren, Randy Goeb...
140
Voted
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
16 years 4 months ago
Learning to recognize brain specific proteins based on low-level features from on-line prediction servers
During the last decade, the area of bioinformatics has produced an overwhelming amount of data, with the recently published draft of the human genome being the most prominent exam...
Henrik Boström, Joakim Cöster, Lars Aske...
111
Voted
CSB
2005
IEEE
125views Bioinformatics» more  CSB 2005»
15 years 9 months ago
Peptide Charge State Determination for Low-Resolution Tandem Mass Spectra
Mass spectrometry is a particularly useful technology for the rapid and robust identification of peptides and proteins in complex mixtures. Peptide sequences can be identified b...
Aaron A. Klammer, Christine C. Wu, Michael J. MacC...
126
Voted
ICML
2006
IEEE
16 years 4 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...