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» The Combining Classifier: To Train or Not to Train
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RECOMB
2010
Springer
13 years 10 months ago
Leveraging Sequence Classification by Taxonomy-Based Multitask Learning
In this work we consider an inference task that biologists are very good at: deciphering biological processes by bringing together knowledge that has been obtained by experiments u...
Christian Widmer, Jose Leiva, Yasemin Altun, Gunna...
BMCBI
2007
149views more  BMCBI 2007»
13 years 8 months ago
A unified framework for finding differentially expressed genes from microarray experiments
Background: This paper presents a unified framework for finding differentially expressed genes (DEGs) from the microarray data. The proposed framework has three interrelated modul...
Jahangheer S. Shaik, Mohammed Yeasin
GECCO
2009
Springer
173views Optimization» more  GECCO 2009»
14 years 3 months ago
Creating regular expressions as mRNA motifs with GP to predict human exon splitting
Low correlation between mRNA concentrations measured at different locations for the same exon show many current Ensembl exon definitions are incomplete. Automatically created pa...
William B. Langdon, Joanna Rowsell, Andrew P. Harr...
BMCBI
2010
99views more  BMCBI 2010»
13 years 8 months ago
Prediction of novel precursor miRNAs using a context-sensitive hidden Markov model (CSHMM)
Background: It has been apparent in the last few years that small non coding RNAs (ncRNA) play a very significant role in biological regulation. Among these microRNAs (miRNAs), 22...
Sumeet Agarwal, Candida Vaz, Alok Bhattacharya, As...
CVPR
2008
IEEE
14 years 10 months ago
Automatic registration of aerial imagery with untextured 3D LiDAR models
A fast 3D model reconstruction methodology is desirable in many applications such as urban planning, training, and simulations. In this paper, we develop an automated algorithm fo...
Min Ding, Kristian Lyngbaek, Avideh Zakhor