Cuckoo search optimisation for feature selection in cancer classification: a new approach [0.03%]
用于癌症分类的特征选择的 cuckoo 搜索优化：一种新方法
C Gunavathi,K Premalatha
C Gunavathi
Cuckoo Search (CS) optimisation algorithm is used for feature selection in cancer classification using microarray gene expression data. Since the gene expression data has thousands of genes and a small number of samples, feature selection m...
PMCR-Miner: parallel maximal confident association rules miner algorithm for microarray data set [0.03%]
基于微阵列数据集的并行可信赖度最大规则挖掘算法PMCR-Miner研究
Wael Zakaria,Yasser Kotb,Fayed F M Ghaleb
Wael Zakaria
The MCR-Miner algorithm is aimed to mine all maximal high confident association rules form the microarray up/down-expressed genes data set. This paper introduces two new algorithms: IMCR-Miner and PMCR-Miner. The IMCR-Miner algorithm is an ...
Sequence based human leukocyte antigen gene prediction using informative physicochemical properties [0.03%]
基于有信息量的理化特性的序列人类白细胞抗原基因预测
Watshara Shoombuatong,Panuwat Mekha,Jeerayut Chaijaruwanich
Watshara Shoombuatong
Prediction of different classes within the human leukocyte antigen (HLA) gene family can provide insight into the human immune system and its response to viral pathogens. Therefore, it is desirable to develop an efficient and easily interpr...
Wavelet-based gene selection method for survival prediction in diffuse large B-cell lymphomas patients [0.03%]
基于小波的基因选择方法在弥漫性大B细胞淋巴瘤患者生存预测中的应用
Maryam Farhadian,Hossein Mahjub,Abbas Moghimbeigi et al.
Maryam Farhadian et al.
Microarray technology allows simultaneous measurements of expression levels for thousands of genes. An important aspect of microarray studies includes the prediction of patient survival based on their gene expression profile. This naturally...
Orthogonal projection correction for confounders in biological data classification [0.03%]
用于生物数据分析分类的正交投影干扰因素校正方法
Limin Li,Shuqin Zhang
Limin Li
The existence of confounders such as population structure in genome-wide association study makes it difficult to apply machine learning methods directly to solve biological problems. It is still unclear how to effectively correct confounder...
Ali Katanforoush,Ehsan Mahdavi
Ali Katanforoush
MicroRNAs (miRNAs) are a class of short RNA molecules that regulate gene expression by binding directly to messenger RNAs. Conventional approaches to miRNA target prediction estimate the accessibility of target sites and the strength of the...
Analysing large biological data sets with an improved algorithm for MIC [0.03%]
一种改进的MIC算法及其在大规模生物数据挖掘中的应用分析
Shuliang Wang,Yiping Zhao
Shuliang Wang
The computational framework used the traditional similarity measures to find out the significant relationships in biological annotations. But its prerequisites that the biological annotations do not cooccur with each other is particular. To...
Tom Johnsten,Laura Fain,Leanna Fain et al.
Tom Johnsten et al.
Analysing and classifying sequences based on similarities and differences is a mathematical problem of escalating relevance and importance in many scientific disciplines. One of the primary challenges in applying machine learning algorithms...
A graph-based integrative method of detecting consistent protein functional modules from multiple data sources [0.03%]
一种基于图的综合方法：从多个数据源检测一致的蛋白质功能模块
Yuan Zhang,Yue Cheng,Liang Ge et al.
Yuan Zhang et al.
Many clustering methods have been developed to identify functional modules in Protein-Protein Interaction (PPI) networks but the results are far from satisfaction. To overcome the noise and incomplete problems of PPI networks and find more ...
An effective hybrid approach of gene selection and classification for microarray data based on clustering and particle swarm optimization [0.03%]
基于聚类和粒子群优化的微阵列数据基因选择与分类的有效混合方法
Fei Han,Shanxiu Yang,Jian Guan
Fei Han
In this paper, a hybrid approach based on clustering and Particle Swarm Optimisation (PSO) is proposed to perform gene selection and classification for microarray data. In the new method, firstly, genes are partitioned into a predetermined ...