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» Predicting Nucleolar Proteins Using Support-Vector Machines
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BMCBI
2008
74views more  BMCBI 2008»
13 years 7 months ago
Prediction of mucin-type O-glycosylation sites in mammalian proteins using the composition of k-spaced amino acid pairs
Background: As one of the most common protein post-translational modifications, glycosylation is involved in a variety of important biological processes. Computational identificat...
Yong-Zi Chen, Yu-Rong Tang, Zhi-Ya Sheng, Ziding Z...
PKDD
2010
Springer
152views Data Mining» more  PKDD 2010»
13 years 5 months ago
Online Knowledge-Based Support Vector Machines
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbee...
JCP
2008
166views more  JCP 2008»
13 years 7 months ago
Water Demand Prediction using Artificial Neural Networks and Support Vector Regression
Computational Intelligence techniques have been proposed as an efficient tool for modeling and forecasting in recent years and in various applications. Water is a basic need and as...
Ishmael S. Msiza, Fulufhelo Vincent Nelwamondo, Ts...
BMCBI
2007
153views more  BMCBI 2007»
13 years 7 months ago
A new pairwise kernel for biological network inference with support vector machines
Background: Much recent work in bioinformatics has focused on the inference of various types of biological networks, representing gene regulation, metabolic processes, protein-pro...
Jean-Philippe Vert, Jian Qiu, William Stafford Nob...
BMCBI
2005
120views more  BMCBI 2005»
13 years 7 months ago
pSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties
Background: Protein subcellular localization is an important determinant of protein function and hence, reliable methods for prediction of localization are needed. A number of pre...
Deepak Sarda, Gek Huey Chua, Kuo-Bin Li, Arun Kris...