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Computational intelligence techniques in bioinformatics
Computational Biology and Chemistry, 2013Computational intelligence (CI) is a well-established paradigm with current systems having many of the characteristics of biological computers and capable of performing a variety of tasks that are difficult to do using conventional techniques. It is a methodology involving adaptive mechanisms and/or an ability to learn that facilitate intelligent ...
Aboul Ella Hassanien +2 more
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Advances in Computational Intelligence and Bioinformatics
Soft Computing, 2010Bioinformatics is the application of information technology and computer science to the field of molecular biology. The potential range of applications of bioinformatics techniques is quite large, including ontologies in biomedicine, biomolecular dynamics, comparative genomics, gene expression analysis, protein structure prediction, protein expression ...
Francesco Masulli, Roberto Tagliaferri
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Bioinformatics and computational methods for lipidomics
Journal of Chromatography B, 2009Large amounts of lipidomics data are rapidly becoming available. However, there is a lack of tools capable of taking the full advantage of the wealth of new information. Lipid bioinformatics is thus an emerging need as well as challenge for lipid research.
Perttu S, Niemelä +3 more
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Introduction to bioinformatics and computational biology
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation, 2012The field of biological sciences has been transformed in recent years to a domain of incredibly rich data ripe for computational exploration. High throughput technologies allow investigators to construct vast feature sets, including genetic variables, gene expression values, protein levels, biomarkers, and a multitude of other traits.
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Computational Intelligence in Bioinformatics
2005Computational intelligence poses several possibilities in Bioinformatics, particularly by generating low-cost, low-precision, good solutions. Rough sets promise to open up an important dimension in this direction. The present article surveys the role of artificial neural networks, fuzzy sets and genetic algorithms, with particular emphasis on rough ...
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Bioinformatics—an introduction for computer scientists
ACM Computing Surveys, 2004The article aims to introduce computer scientists to the new field of bioinformatics. This area has arisen from the needs of biologists to utilize and help interpret the vast amounts of data that are constantly being gathered in genomic research---and its more recent counterparts, proteomics and functional genomics.
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Computational intelligence in bioinformatics
Biosystems, 2003Combining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. Now, Computational Intelligence in Bioinformatics offers an introduction to the topic, covering the most relevant and popular CI methods, while also ...
Gary B. Fogel, David W. Corne
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Bioinformatics and computing curriculum
ACM SIGCSE Bulletin, 2006An interdisciplinary bioinformatics course has been taught at Wake Forest for three semesters. Undergraduate and graduate students from multiple academic specialties are brought together in a single classroom. In addition to focusing on traditional bioinformatics topics, this course concentrates on interdisciplinary collaboration in the in-class ...
Jacquelyn S. Fetrow, David J. John
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Computational and Statistical Methods in Bioinformatics
2005Many computational and statistical methods have been developed and applied in bioinformatics. Recently, new approaches based on support vector machines have been developed. Support vector machines provide a way of combining computational methods and statistical methods.
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Computational Intelligence in Bioinformatics
2008Bioinformatics involve the creation and advancement of algorithms using techniques including computational intelligence, applied mathematics and statistics, informatics, and biochemistry to solve biological problems usually on the molecular level. Major research efforts in the field include sequence analysis, gene finding, genome annotation, protein ...
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