Cuardaigh malartuithe:
davar algorithm » radar algorithm (Fairsingigh an Cuardach), 4dvar algorithm (Fairsingigh an Cuardach), david algorithms (Fairsingigh an Cuardach)
java algorithm » jaya algorithm (Fairsingigh an Cuardach), data algorithm (Fairsingigh an Cuardach), aaa algorithm (Fairsingigh an Cuardach)
dna algorithm » data algorithm (Fairsingigh an Cuardach), a algorithm (Fairsingigh an Cuardach), rsa algorithm (Fairsingigh an Cuardach)
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DNA computing and molecular programming 16th International Conference, DNA 16, Hong Kong, China, June 14-17, 2010 : revised selected papers /
DNA computing and molecular programming 19th International Conference, DNA 2013, Tempe, AZ, USA, September 22-27, 2013, proceedings /

DNA computing 11th international workshop on DNA computing, DNA11, London, on, Canada, june 6-9, 2005 ; revised selected papers /
DNA computing 14th International Meeting on DNA Computing, DNA 14, Prague, Czech Republic, June 2-9, 2008 : revised selected papers /

BLAMM: BLAS-based algorithm for finding position weight matrix occurrences in DNA sequences on CPUs and GPUs
BLAMM: BLAS-based algorithm for finding position weight matrix occurrences in DNA sequences on CPUs and GPUs

Intelligent algorithms in ambient and biomedical computing
Data structures and algorithms in java /

Data structures & algorithms in Java /
Strain-specific behavior of Mycobacterium tuberculosis in A549 lung cancer cell line

ALGORITHMS AND DATA STRUCTURE LIBRARIES FOR JAVA
Efficient Algorithms for Large-Scale Image Analysis

Refinement-Cut: User-Guided Segmentation Algorithm for Translational Science
Performance of Parallel K-Means Algorithms in Java

JavaScript Algorithm for Quantifier Elimination in Epidemiology
On Using Quasi-Newton Algorithms of the Broyden Class for Model-to-Test Correlation

A concise and practical introduction to programming algorithms in Java
Digital image processing an algorithmic introduction using Java /

Isula: A java framework for ant colony algorithms
Practical mathematical optimization an introduction to basic optimization theory and classical and new gradient-based algorithms /

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