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» A DIAMOND Method for Classifying Biological Data
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KDD
2001
ACM
163views Data Mining» more  KDD 2001»
15 years 10 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...
BMCBI
2007
131views more  BMCBI 2007»
14 years 9 months ago
Prediction of peptides observable by mass spectrometry applied at the experimental set level
Background: When proteins are subjected to proteolytic digestion and analyzed by mass spectrometry using a method such as 2D LC MS/MS, only a portion of the proteotypic peptides a...
William S. Sanders, Susan M. Bridges, Fiona M. McC...
FUIN
2010
268views more  FUIN 2010»
14 years 4 months ago
Boruta - A System for Feature Selection
Machine learning methods are often used to classify objects described by hundreds of attributes; in many applications of this kind a great fraction of attributes may be totally irr...
Miron B. Kursa, Aleksander Jankowski, Witold R. Ru...
BMCBI
2008
208views more  BMCBI 2008»
14 years 9 months ago
GraphFind: enhancing graph searching by low support data mining techniques
Background: Biomedical and chemical databases are large and rapidly growing in size. Graphs naturally model such kinds of data. To fully exploit the wealth of information in these...
Alfredo Ferro, Rosalba Giugno, Misael Mongiov&igra...
BMCBI
2007
157views more  BMCBI 2007»
14 years 9 months ago
Impact of image segmentation on high-content screening data quality for SK-BR-3 cells
Background: High content screening (HCS) is a powerful method for the exploration of cellular signalling and morphology that is rapidly being adopted in cancer research. HCS uses ...
Andrew A. Hill, Peter LaPan, Yizheng Li, Steve Han...