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ICMLA
2008
15 years 6 months ago
Tumor Targeting for Lung Cancer Radiotherapy Using Machine Learning Techniques
Accurate lung tumor targeting in real time plays a fundamental role in image-guide radiotherapy of lung cancers. Precise tumor targeting is required for both respiratory gating an...
Tong Lin, Laura Cervino, Xiaoli Tang, Nuno Vasconc...
BMCBI
2010
133views more  BMCBI 2010»
15 years 4 months ago
Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
Lance E. Palmer, Mathäus Dejori, Randall A. B...
BMCBI
2008
141views more  BMCBI 2008»
15 years 4 months ago
Functional discrimination of membrane proteins using machine learning techniques
Background: Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amin...
M. Michael Gromiha, Yukimitsu Yabuki
BMCBI
2006
216views more  BMCBI 2006»
15 years 4 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
JMLR
2006
132views more  JMLR 2006»
15 years 4 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof