2009 Fourth International on Conference on Bio-Inspired Computing最新文献_第7页

Overview and study focuses of microfluidic-based cell culture systems 基于微流体的细胞培养系统综述及研究重点

2009 Fourth International on Conference on Bio-Inspired Computing Pub Date : 2009-11-17 DOI: 10.1109/BICTA.2009.5338136

Manguo Huang, S. Fan, Weiwei Xing

引用次数: 2

Combining genetic algorithms with optimality criteria method for topology optimization 结合遗传算法和最优准则的拓扑优化方法

2009 Fourth International on Conference on Bio-Inspired Computing Pub Date : 2009-11-17 DOI: 10.1109/BICTA.2009.5338131

Zhimin Chen, Liang Gao, H. Qiu, X. Shao

引用次数: 16

DNA algorithm on optimal path selection for bus travel network 公交网络最优路径选择的DNA算法

2009 Fourth International on Conference on Bio-Inspired Computing Pub Date : 2009-11-17 DOI: 10.1109/BICTA.2009.5338116

Qian Zhang, Enqi Xu, Zhenye Wang, Yafei Dong

引用次数: 5

A position-slots model for nucleosome assembly in the yeast genome based on integrated multi-platform positioning dataseis 基于集成多平台定位数据的酵母基因组核小体组装位置槽模型

2009 Fourth International on Conference on Bio-Inspired Computing Pub Date : 2009-11-17 DOI: 10.1109/BICTA.2009.5338121

Jihua Feng, X. Dai, Qian Xiang, Zhiming Dai, Jiang-Hai Wang, Yangyang Deng, Caisheng He

{"title":"A position-slots model for nucleosome assembly in the yeast genome based on integrated multi-platform positioning dataseis","authors":"Jihua Feng, X. Dai, Qian Xiang, Zhiming Dai, Jiang-Hai Wang, Yangyang Deng, Caisheng He","doi":"10.1109/BICTA.2009.5338121","DOIUrl":"https://doi.org/10.1109/BICTA.2009.5338121","url":null,"abstract":"In-depth analysis of the recent five experimental nucleosome datasets reveals the broad disagreements between the final nucleosome positions detected by the previous studies. Using signal processing methods, we found two distinct nucleosome distribution domains which evidently emerge from promoter and coding regions. We calculated and confirmed that the fuzzy nucleosomes fall into the dynamic domain, and well-positioned nucleosomes fall into the stable one. By combining the domains information with gene properties, transcription factors binding sites (TFBs) and DNA bendability, we revealed the relationship between the two domains with TATA and TATA_less genes. Then, investigating the link between the two domains and the histone H3 modifications, we observed that the extremely rapid-replacing histone H3 occurs at the immediate downstream of transcription start sites (TSS) rather than +1 nucleosome position. Finally, we presented a slots model for nucleosome assembly in the yeast genome to explain the mechanism of nucleosome forming in the genes promoter regions.","PeriodicalId":161787,"journal":{"name":"2009 Fourth International on Conference on Bio-Inspired Computing","volume":"85 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113996303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of protein-protein interaction types using the decision templates 使用决策模板预测蛋白质-蛋白质相互作用类型

2009 Fourth International on Conference on Bio-Inspired Computing Pub Date : 2009-10-01 DOI: 10.1109/BICTA.2009.5338145

Wei Chen, Shaowu Zhang, Yong-mei Cheng

{"title":"Prediction of protein-protein interaction types using the decision templates","authors":"Wei Chen, Shaowu Zhang, Yong-mei Cheng","doi":"10.1109/BICTA.2009.5338145","DOIUrl":"https://doi.org/10.1109/BICTA.2009.5338145","url":null,"abstract":"Protein-protein interactions (PPIs) play a key role in many cellular processes. Knowing about the multitude of PPIs can help the biological scientist understand the molecular mechanism of the cell. Unfortunately, it is both time-consuming and expensive to do so solely based on experiments. Therefore, developing computational approaches for predicting PPIs, PPI binding sites and PPI types would be of significant value. Here, we propose a novel method for predicting the PPI types based on decision templates. First, we introduce the concept of tensor product to construct three kinds of feature vectors which are the amino acid composition tensor product, the residue multi-scale conservation energy tensor product and the secondary structure content tensor product. Then, the correlation-based feature selection method was also used to reduce the dimensionality of these feature vectors. So, the protein pair can be represented by our three new kinds of feature vectors and Zhu's six kinds of feature vectors. The nine kinds of feature vectors are further taken as the inputs of individual support vector machine classifier respectively, and the outputs of these classifiers are aggregated with decision templates in decision level. The overall success rate obtained by jackknife cross-validation was 90.95%, indicating our method is very promising for predicting PPI types.","PeriodicalId":161787,"journal":{"name":"2009 Fourth International on Conference on Bio-Inspired Computing","volume":"83 302 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125967198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0