Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003最新文献_第5页

Group testing with DNA chips: generating designs and decoding experiments DNA芯片组测:生成设计和解码实验

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227307

Alexander Schliep, D. Torney, S. Rahmann

{"title":"Group testing with DNA chips: generating designs and decoding experiments","authors":"Alexander Schliep, D. Torney, S. Rahmann","doi":"10.1109/CSB.2003.1227307","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227307","url":null,"abstract":"DNA microarrays are a valuable tool for massively parallel DNA-DNA hybridization experiments. Currently, most applications rely on the existence of sequence-specific oligonucleotide probes. In large families of closely related target sequences, such as different virus subtypes, the high degree of similarity often makes it impossible to find a unique probe for every target. Fortunately, this is unnecessary. We propose a microarray design methodology based on a group testing approach. While probes might bind to multiple targets simultaneously, a properly chosen probe set can still unambiguously distinguish the presence of one target set from the presence of a different target set. Our method is the first one that explicitly takes cross-hybridization and experimental errors into account while accommodating several targets. The approach consists of three steps: (1) Pre-selection of probe candidates, (2) Generation of a suitable group testing design, and (3) Decoding of hybridization results to infer presence or absence of individual targets. Our results show that this approach is very promising, even for challenging data sets and experimental error rates of up to 5%. On a data set of 28S rDNA sequences we were able to identify 660 sequences, a substantial improvement over a prior approach using unique probes which only identified 408 sequences.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128328474","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: 69

Development and assessment of bioinformatics tools for species conservation and habitat management 物种保护和生境管理生物信息学工具的开发与评估

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227435

M. Sutton, Lori Deneke, J. Eme, W. Bennett, F. Wray

引用次数: 0

The SCP and compressed domain analysis of biological sequences 生物序列的SCP和压缩域分析

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227416

D. Adjeroh, Jianan Feng

引用次数: 9

Implementing parallel hmm-pfam on the EARTH multithreaded architecture 在EARTH多线程架构上实现并行hmm-pfam

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227404

Weirong Zhu, Yanwei Niu, Jizhu Lu, G. Gao

引用次数: 14

Accelerating the drug design process through parallel inductive logic programming data mining 通过并行归纳逻辑编程数据挖掘加速药物设计过程

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227345

J. Graham, David Page, A. H. Kamal

引用次数: 21

Application of singular value decomposition and functional clustering to analyzing gene expression profiles of renal cell carcinoma 应用奇异值分解和功能聚类分析肾细胞癌基因表达谱

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227341

Z. Duan, L. Liou, T. Shi, J. DiDonato

引用次数: 4

What makes IgG binding domain of protein L fold up to native state: a simulation study with physical oriented energy functions coupled to topology induced terms 是什么使蛋白质L的IgG结合域折叠到天然状态:与物理定向能量函数耦合到拓扑诱导项的模拟研究

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227370

Seung Yup Lee, Y. Fujitsuka, S. Takada, Do Hyun Kim

{"title":"What makes IgG binding domain of protein L fold up to native state: a simulation study with physical oriented energy functions coupled to topology induced terms","authors":"Seung Yup Lee, Y. Fujitsuka, S. Takada, Do Hyun Kim","doi":"10.1109/CSB.2003.1227370","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227370","url":null,"abstract":"The folding pathways and mechanisms of IgG binding domain of protein L composed of 62 residues are simulated by an over-damped Langevin dynamics with a coarse-grained chain representation. Physical oriented effective energy functions (EEFs) are employed for sequence-specific interactions as well as topology induced energies to bias overall energies to native basin. We observed the preferential formation of N terminal hairpin and the break of structural symmetry during folding. In the free energy profile calculated from equilibrium sampling and histogram method, it clearly shows two state folding scenario with transition state (TS). In the TS regime, N terminal hairpin already forms whereas C terminal hairpin and alpha helix are not structured yet. The predicted results are fully consistent with experimental data. Moreover, we found that hydrophobicity and secondary local propensity among many physical interactions determine the overall folding routes significantly by reduced model studies.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124484057","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

Identifying regulatory signals in DNA-sequences with a nonstatistical approximation approach 用非统计近似方法识别dna序列中的调控信号

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227417

Cun-Quan Zhang, Yunkai Liu, Elaine M. Eschen, Keqiang Wu

引用次数: 0

Prokaryote phylogeny without sequence alignment: from avoidance signature to composition distance 无序列比对的原核生物系统发育:从回避特征到组成距离

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227338

Bailin Hao, J. Qi

引用次数: 12

Can we identify cellular pathways implicated in cancer using gene expression data? 我们能否利用基因表达数据识别与癌症相关的细胞通路?

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI: 10.1109/CSB.2003.1227308

N. Shah, J. Lepre, Y. Tu, G. Stolovitzky

引用次数: 4