Toward intelligent training of supervised image classifications: directing training data acquisition for SVM classification
GM Foody, A Mathur - Remote Sensing of Environment, 2004 - Elsevier
Conventional approaches to training a supervised image classification aim to fully describe
all of the classes spectrally. To achieve a complete description of each class in feature …
all of the classes spectrally. To achieve a complete description of each class in feature …
Parameterized algorithms in bioinformatics: an overview
Bioinformatics regularly poses new challenges to algorithm engineers and theoretical
computer scientists. This work surveys recent developments of parameterized algorithms …
computer scientists. This work surveys recent developments of parameterized algorithms …
[書籍][B] Handbook of computational molecular biology
S Aluru - 2005 - taylorfrancis.com
The enormous complexity of biological systems at the molecular level must be answered
with powerful computational methods. Computational biology is a young field, but has seen …
with powerful computational methods. Computational biology is a young field, but has seen …
Practical applications of boolean satisfiability
J Marques-Silva - 2008 9th International Workshop on Discrete …, 2008 - ieeexplore.ieee.org
Boolean satisfiability (SAT) solvers have been the subject of remarkable improvements
since the mid 90s. One of the main reasons for these improvements has been the wide …
since the mid 90s. One of the main reasons for these improvements has been the wide …
[書籍][B] ReCombinatorics: the algorithmics of ancestral recombination graphs and explicit phylogenetic networks
D Gusfield - 2014 - books.google.com
Combinatorial structure and algorithms for deducing genetic recombination history,
represented by ancestral recombination graphs and other networks, and their role in the …
represented by ancestral recombination graphs and other networks, and their role in the …
Models and algorithms for haploty** problem
One of the main topics in genomics is to determine the relevance of DNA variations with
some genetic disease. Single nucleotide polymorphism (SNP) is the most frequent and …
some genetic disease. Single nucleotide polymorphism (SNP) is the most frequent and …
[PDF][PDF] Efficient haplotype inference with Boolean satisfiability
One of the main topics of research in genomics is determining the relevance of mutations,
described in haplotype data, as causes of some genetic diseases. However, due to …
described in haplotype data, as causes of some genetic diseases. However, due to …
SAT in bioinformatics: Making the case with haplotype inference
Mutation in DNA is the principal cause for differences among human beings, and Single
Nucleotide Polymorphisms (SNPs) are the most common mutations. Hence, a fundamental …
Nucleotide Polymorphisms (SNPs) are the most common mutations. Hence, a fundamental …
Characterisation of single nucleotide polymorphisms in sugarcane ESTs
GM Cordeiro, F Eliott, CL McIntyre, RE Casu… - Theoretical and Applied …, 2006 - Springer
Commercial sugarcane cultivars (Saccharum spp. hybrids) are both polyploid and aneuploid
with chromosome numbers in excess of 100; these chromosomes can be assigned to 8 …
with chromosome numbers in excess of 100; these chromosomes can be assigned to 8 …
[書籍][B] Integer linear programming in computational and systems biology: an entry-level text and course
D Gusfield - 2019 - books.google.com
Integer linear programming (ILP) is a versatile modeling and optimization technique that is
increasingly used in non-traditional ways in biology, with the potential to transform biological …
increasingly used in non-traditional ways in biology, with the potential to transform biological …