9 Result(s)
within
Saman K Halgamuge
Computational Biology/Bioinformatics
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Article
Open AccessENVirT: inference of ecological characteristics of viruses from metagenomic data
Estimating the parameters that describe the ecology of viruses,particularly those that are novel, can be made possible using metagenomic approaches. However, the best-performing existing methods require databa...
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Article
Open AccessAccurate reconstruction of viral quasispecies spectra through improved estimation of strain richness
Estimating the number of different species (richness) in a mixed microbial population has been a main focus in metagenomic research. Existing methods of species richness estimation ride on the assumption that the...
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Article
Open AccessErratum to: CoNVEX: copy number variation estimation in exome sequencing data using HMM
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Article
Open AccessCoNVEX: copy number variation estimation in exome sequencing data using HMM
One of the main types of genetic variations in cancer is Copy Number Variations (CNV). Whole exome sequenicng (WES) is a popular alternative to whole genome sequencing (WGS) to study disease specific genomic v...
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Chapter and Conference Paper
A Meta-learning Prediction Model of Algorithm Performance for Continuous Optimization Problems
Algorithm selection and configuration is a challenging problem in the continuous optimization domain. An approach to tackle this problem is to develop a model that links landscape analysis measures and algorit...
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Article
Structure adaptation of hierarchical knowledge-based classifiers
This paper introduces a new method to identify the qualified rule-relevant nodes to construct hierarchical neuro-fuzzy systems (HNFSs). After learning, the proposed method analyzes the entire history of activi...
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Article
Open AccessBinning sequences using very sparse labels within a metagenome
In metagenomic studies, a process called binning is necessary to assign contigs that belong to multiple species to their respective phylogenetic groups. Most of the current methods of binning, such as BLAST, k-me...
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Article
Polynomial kernel adaptation and extensions to the SVM classifier learning
Three extensions to the Kernel-AdaTron training algorithm for Support Vector Machine classifier learning are presented. These extensions allow the trained classifier to adhere more closely to the constraints i...
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Article
Open AccessGene function prediction based on genomic context clustering and discriminative learning: an application to bacteriophages
Existing methods for whole-genome comparisons require prior knowledge of related species and provide little automation in the function prediction process. Bacteriophage genomes are an example that cannot be ea...
