Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003最新文献

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Discovering compact and highly discriminative features or combinations of drug activities using support vector machines 使用支持向量机发现紧凑和高度判别的特征或药物活动组合
Hwanjo Yu, Jiong Yang, Wen Wang, Jiawei Han
{"title":"Discovering compact and highly discriminative features or combinations of drug activities using support vector machines","authors":"Hwanjo Yu, Jiong Yang, Wen Wang, Jiawei Han","doi":"10.1109/CSB.2003.1227321","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227321","url":null,"abstract":"Nowadays, high throughput experimental techniques make it feasible to examine and collect massive data at the molecular level. These data, typically mapped to a very high dimensional feature space, carry rich information about functionalities of certain chemical or biological entities and can be used to infer valuable knowledge for the purposes of classification and prediction. Typically, a small number of features or feature combinations may play determinant roles in functional discrimination. The identification of such features or feature combinations is of great importance. In this paper, we study the problem of discovering compact and highly discriminative features or feature combinations from a rich feature collection. We employ the support vector machine as the classification means and aim at finding compact feature combinations. Comparing to previous methods on feature selection, which identify features solely based on their individual roles in the classification, our method is able to identify minimal feature combinations that ultimately have determinant roles in a systematic fashion. Experimental study on drug activity data shows that our method can discover descriptors that are not necessarily significant individually but are most significant collectively.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"84 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":"134117664","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: 39
A semantic mediation approach for problems in computational molecular biology 计算分子生物学问题的语义调解方法
M. Chagoyen, M. E. Kurul, P. A. D. Alarcón, S. Santini, Bertram Ludäscher, J. Carazo, Amarnath Gupta
{"title":"A semantic mediation approach for problems in computational molecular biology","authors":"M. Chagoyen, M. E. Kurul, P. A. D. Alarcón, S. Santini, Bertram Ludäscher, J. Carazo, Amarnath Gupta","doi":"10.1109/CSB.2003.1227339","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227339","url":null,"abstract":"As great amount of data are being produced and accumulated in life sciences, information access and consequent integration in analytical and computational methods become critical issues in order to conduct research. In this work we describe how the synergic combination of a high-level programmable planner engine and formal semantics are suitable to resolve many information integration problems in molecular biology.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"9 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":"133561373","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
cWINNOWER algorithm for finding fuzzy DNA motifs cWINNOWER算法寻找模糊DNA基序
S. Liang
{"title":"cWINNOWER algorithm for finding fuzzy DNA motifs","authors":"S. Liang","doi":"10.1109/CSB.2003.1227326","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227326","url":null,"abstract":"The cWINNOWER algorithm detects fuzzy motifs in DNA sequences rich in protein-binding signals. A signal is defined as any short nucleotide pattern having up to d mutations differing from a motif of length l. The algorithm finds such motifs if multiple mutated copies of the motif (i.e., the signals) are present in the DNA sequence in sufficient abundance. The cWINNOWER algorithm substantially improves the sensitivity of the winnower method of Pevzner and Sze by imposing a consensus constraint, enabling it to detect much weaker signals. We studied the minimum number of detectable motifs q/sub c/ as a function of sequence length N for random sequences. We found that q/sub c/ increases linearly with N for a fast version of the algorithm based on counting three-member sub-cliques. Imposing consensus constraints reduces q/sub c/ by a factor of three in this case, which makes the algorithm dramatically more sensitive. Our most sensitive algorithm, which counts four-member sub-cliques, needs a minimum of only 13 signals to detect motifs in a sequence of length N=12000 for (l, d)=(15,4).","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"15 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":"115042701","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: 59
Pathway bioinformatics 途径生物信息学
P. Karp
{"title":"Pathway bioinformatics","authors":"P. Karp","doi":"10.1109/CSB.2003.1227294","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227294","url":null,"abstract":"Pathway bioinformatics is a subfield of bioinformatics that is concerned with pathway algorithms, ontologies, visualizations, and databases [4]. This talk will provide an overview of the pathway databases and software under development in the bioinformatics research group at SRI International, and will then discuss three pathway algorithms in detail.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"25 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":"132114265","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: 1
Automatic recognition of regions of intrinsically poor multiple alignment using machine learning 利用机器学习自动识别本质上较差的多重对齐区域
Yunfeng Shan, E. Milios, A. Roger, C. Blouin, E. Susko
{"title":"Automatic recognition of regions of intrinsically poor multiple alignment using machine learning","authors":"Yunfeng Shan, E. Milios, A. Roger, C. Blouin, E. Susko","doi":"10.1109/CSB.2003.1227381","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227381","url":null,"abstract":"Phylogenetic analysis requires alignment of gene or protein sequences. Some regions of genes evolve fast and suffer numerous insertion and deletion events and cannot be aligned reliably with automatic alignment algorithms. Such regions of intrinsically uncertain alignment are currently detected and deleted manually before performing phylogenetic analysis. We present the results of a machine learning approach to detect regions of poor alignment automatically. We compare the results obtained from Naive Bayes (NB), C4.5 decision tree (C4.5) and support vector machine (SVM) approaches.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"107 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":"133814096","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: 6
An exact algorithm for determining protein backbone structure from NH residual dipolar couplings 从NH残余偶极偶联中确定蛋白质主结构的精确算法
Lincong Wang, Ramgopal R. Mettu, R. Lilien, B. Donald
{"title":"An exact algorithm for determining protein backbone structure from NH residual dipolar couplings","authors":"Lincong Wang, Ramgopal R. Mettu, R. Lilien, B. Donald","doi":"10.1109/CSB.2003.1227422","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227422","url":null,"abstract":"We have developed a novel algorithm for protein backbone structure determination using global orientational restraints on internuclear bond vectors derived from residual dipolar couplings (RDCs) measured in solution NMR. The algorithm is a depth-first search (DPS) strategy that is built upon two low-degree polynomial equations for computing the backbone (/spl phi/, /spl psi/) angles, exactly and in constant time, from two bond vectors in consecutive peptide planes.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"12 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":"133437961","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: 3
Motifs and modules in cellular signal processing: applications to microbial stress response pathways 细胞信号处理中的基序和模块:在微生物应激反应途径中的应用
A. Arkin
{"title":"Motifs and modules in cellular signal processing: applications to microbial stress response pathways","authors":"A. Arkin","doi":"10.1109/CSB.2003.1227299","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227299","url":null,"abstract":"Bacterial and animal cells are dynamic machines whose internal chemical networks perform hundreds of complex control and signal processing tasks to govern cellular development over time and in response to deterministic and stochastic signals from the environment. A central challenge in post-genomic biology is to discover the complete physical nature of these networks and to determine if there are principles of control and signal processing by which these cell operate and evolve. If such principles exist then they are handles by which cellular engineers can determine the best placement of external signals (such as Pharmaceuticals) to cause a cell to move from an undesired state to a desired state. Here, initial attempts at determining the principles of control, the possible modular structure and the nature of signal flow in cellular networks are briefly introduced. We use examples from bacterial stress response pathways and yeast deletion viability studies to illustrate the principles and approaches.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"37 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":"130275184","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
Microbial functional genomics: pulling together a variety of approaches and concepts 微生物功能基因组学:汇集各种方法和概念
J. Claverie
{"title":"Microbial functional genomics: pulling together a variety of approaches and concepts","authors":"J. Claverie","doi":"10.1109/CSB.2003.1227291","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227291","url":null,"abstract":"With the human and mouse genome sequences behind us, whole microbial genome sequencing has become the most active area in genomics today. As easy targets have been worked on first, the microbes under scrutiny today are frequently uncharacterized and difficult to grow and isolate. In those cases, genome sequences often constitute the first and only reliable information about the microorganism to which they belong. It also becoming the rule that no experiments (genetics, transformation, mutagenesis) are directly possible on the microorganism. For better characterized microbes, the competition in the field pushes us to get interested in \"anonymous genes\" for which no functional clues have be gained from routine sequence analysis.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"63 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":"129097639","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
A parallel genetic algorithm for physical mapping of chromosomes 染色体物理映射的并行遗传算法
S. Bhandarkar, Jinling Huang, J. Arnold
{"title":"A parallel genetic algorithm for physical mapping of chromosomes","authors":"S. Bhandarkar, Jinling Huang, J. Arnold","doi":"10.1109/CSB.2003.1227410","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227410","url":null,"abstract":"Physical map reconstruction in the presence of errors is a central problem in genetics of high computational complexity. A parallel genetic algorithm for a maximum likelihood estimation-based approach to physical map reconstruction is presented. The estimation procedure entails gradient descent search for determining the optimal spacings between probes for a given probe ordering. The optimal probe ordering is determined using a genetic algorithm. A two-tier parallelization strategy is proposed wherein the gradient descent search is parallelized at the lower level and the genetic algorithm is simultaneously parallelized at the higher level. Implementation and experimental results on a network of shared-memory symmetric multiprocessors (SMPs) are presented. The genetic algorithm is seen to result in physical maps with fewer contig breaks when compared to simulated Monte Carlo algorithms such as simulated annealing and the large-step Markov chain algorithm.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"9 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":"128066708","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: 3
Mapping discontinuous antibody epitopes to reveal protein structure and changes in structure related to function 定位不连续抗体表位,揭示蛋白质结构和与功能相关的结构变化
B. Mumey, T. Angel, Bonnie Kirkpatrick, B. W. Bailey, P. Hargrave, A. J. Jesaitis, E. Dratz
{"title":"Mapping discontinuous antibody epitopes to reveal protein structure and changes in structure related to function","authors":"B. Mumey, T. Angel, Bonnie Kirkpatrick, B. W. Bailey, P. Hargrave, A. J. Jesaitis, E. Dratz","doi":"10.1109/CSB.2003.1227415","DOIUrl":"https://doi.org/10.1109/CSB.2003.1227415","url":null,"abstract":"We are developing a new method for protein structure determination that overcomes limitations in traditional methods, such as x-ray crystallography or nuclear magnetic resonance, and requires about a thousandfold less protein. The method, called antibody imprinting, uses antibodies against target proteins and random peptide probe libraries to map the epitopes of antibody binding sites on target proteins. Virtually all known antibody epitopes are highly discontinuous and are \"assembled\" by folding together regions of the protein that are far apart in the primary sequence. The antibody imprinting method seeks to rapidly and efficiently \"mine\" the antibody epitope information to reveal the structure of the target proteins.","PeriodicalId":147883,"journal":{"name":"Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003","volume":"32 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":"117305673","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: 3
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