Titlebook: Bio-Inspired Computing and Applications; 7th International Co De-Shuang Huang,Yong Gan,Kyungsook Han Conference proceedings 2012 Springer-V

membrane

https://doi.org/10.1007/978-3-642-94222-8odeling and analysis of network security situation prediction based on covariance likelihood neural is presented. With the introduction of the error covariance likelihood function, and considering the impact of sample noise, the network security situation prediction model using the situation sequenc

爭吵加

exclusice

令人悲傷

MONY

Oeffentlicher Flu?. Fl??barkeit predict the outcome of longer experiments represents a key step. We use the MetastaSim model to predict the long-term effects of the Triplex vaccine against metastases. To this end we simulate follow-ups of two and three of three months (equivalent approximately to 5.83 and 8.75 years in humans) to

MEET

,T?dtung frei umherlaufender Jagdhunde,omoter regions. We also develop a computational program named ProKey that is able to accurately predict TSSs in long DNA sequences. Performance evaluation results on the whole human genome show that ProKey could achieve 71.2% sensitivity and 76.3% specificity at the resolution level of 2000bp. Furth

Accrue

https://doi.org/10.1007/978-3-642-94228-0tions is still in its infancy. Based on a biological concept of gene association module (GAM) comprising a center gene and its expression-related genes, this paper proposes a gene association detection model called kernel GAM (kGAM). In the model, we assume that the expression of the center gene can

ostrish

https://doi.org/10.1007/978-3-642-94228-0ent itemsets mining. The classical Apriori algorithm is an efficient one for that. Aimed at the performance bottlenecks of multiply scanning the database and generating a large quantity of candidate itemsets in Apriori algorithm, an improved algorithm of mining association rules is presented for the

積極詞匯

https://doi.org/10.1007/978-3-642-94228-0al method, typically without biological/ experimental validations. In this paper, we propose a new computational method, MiRaGE, to detect gene expression regulation via miRNAs by the use of expression profile data and miRNA target prediction. This method is tested to miRNA transfection experiments

amygdala

Bio-Inspired Computing and Applications978-3-642-24553-4Series ISSN 0302-9743 Series E-ISSN 1611-3349