2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops最新文献

Detecting constituent sequences by means of HP pattern-based grammars to synthesize proteins: Inferring sequence-structure-function relationship 基于HP模式语法的蛋白质合成成分序列检测:序列-结构-功能关系推断

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425400

G. Nicosia, E. Sciacca, L. Zammataro

{"title":"Detecting constituent sequences by means of HP pattern-based grammars to synthesize proteins: Inferring sequence-structure-function relationship","authors":"G. Nicosia, E. Sciacca, L. Zammataro","doi":"10.1109/BIBMW.2007.4425400","DOIUrl":"https://doi.org/10.1109/BIBMW.2007.4425400","url":null,"abstract":"The detection of protein characters that could reveal how protein chains are constituted, is an important step to understand the main functions of specific classes of proteins. We made use of the concept of \"HP pattern-based\" grammars to study the connection between protein chains and protein functions. In order to consider the structure of the proteins the HP models were used. Amino acid sequences were treated as a formal language, and it was built a set of HP pattern-based grammars to describe this language by means the Teiresiaspattern discovery tool. First, this methodology was tested on the class of antimicrobial peptides (AmPs). The deduced derivation rules of HP pattern-based grammars were validated by the regular grammar designed by [Loose, C., et al., 2006] which was used to create new, unnatural, AmPs sequences. Then, our approach was applied to characterize a function of the Pleckstrin homology domain (PH Domain) which represents an important three dimensional domain which bind to phosphoinositides. Nowadays, interactions among PH domain amino acids and inositol phosphate are not well characterized. For the first time, by means of an HP pattern-based grammar, we highlight that this binding function can be described in terms of hydrophocity patterns. Our approach points out some fundamental aspects regarding the relationship between sequence, structure and function of proteins.","PeriodicalId":260286,"journal":{"name":"2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123249966","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

An approximate robotics algorithm to assemble a loop between two helices 一种近似的机器人算法来组装两个螺旋之间的环

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425403

Jing He, K. Al Nasr

引用次数: 3

Protein folding simulation by all-atom CSAW method 全原子CSAW方法模拟蛋白质折叠

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425399

Weitao Sun

引用次数: 3

Rapid computation of large numbers of LOD scores in linkage analysis through polynomial expression of genetic likelihoods 利用遗传似然的多项式表达式快速计算连锁分析中的大量LOD分数

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425419

Hongling Wang, Yungui Huang, V. Vieland, Alberto Maria Segre, J. O’Connell

{"title":"Rapid computation of large numbers of LOD scores in linkage analysis through polynomial expression of genetic likelihoods","authors":"Hongling Wang, Yungui Huang, V. Vieland, Alberto Maria Segre, J. O’Connell","doi":"10.1109/BIBMW.2007.4425419","DOIUrl":"https://doi.org/10.1109/BIBMW.2007.4425419","url":null,"abstract":"This paper introduces a new method for computing large numbers of LOD scores in linkage analysis. The LOD score method is commonly used in genetic linkage analysis to associate functionality of genes to their locations on chromosomes. A LOD score is a log 10 likelihood ratio of linkage to no linkage. Instead of calculating values of likelihoods of linkage and no linkage under given values of genetic parameters directly from pedigree data, we construct expressions for likelihoods of linkage and no linkage as polynomials of genetic parameters. These likelihood polynomials of pedigrees don't change for different parameter values. After the likelihood polynomials are constructed, the values of likelihoods of linkage and no linkage can be computed by evaluating the likelihood polynomials with specific parameter values. The likelihood polynomials are optimized during construction so that repeated terms within the expressions are shared. Moreover, we find that the likelihood polynomials of different pedigrees also often share terms. This term-sharing feature leads us to an evaluation strategy where shared terms are evaluated only once and reused by all the polynomials that share them. The reuse of shared terms in polynomial evaluation greatly decreases the re- computation in calculation of large numbers of LOD scores and improves the computing efficiency. Our results show that this approach can speed up the traditional genetic linkage computation by 10~1200 times. This approached has been applied to the computation of the posterior probability of linkage (PPL) where calculation of large numbers of LOD scores is required.","PeriodicalId":260286,"journal":{"name":"2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114872985","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: 5

Developing an annotated corpus of patient histories from the primary care health record 从初级保健健康记录中开发带注释的患者病史语料库

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425415

O. Huseth, T. Brox Rost

引用次数: 3

Mediated taxonomy system for bioinformatics data integration 生物信息学数据整合的中介分类系统

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425410

Feng Ji, Jack Fu, R. Elmasri, N. Stojanovic, Geoffrey Grant

引用次数: 3

Comparison of experimental and computed protein anisotropic temperature factors 实验与计算蛋白质各向异性温度因子的比较

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1002/prot.22328

Lei Yang, Guang Song, R. Jernigan

引用次数: 43

SHA: A secure voice activated smart home for quadriplegia patients SHA:为四肢瘫痪患者设计的安全语音激活智能家居

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425413

Y. Uzunay, K. Bicakci

引用次数: 10

Flagellar proteins prediction after sequence-structure alignments of coronin and Arp2/3 complex in Leishmania spp. 利什曼原虫冠蛋白和Arp2/3复合体序列结构比对后鞭毛蛋白预测。

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425404

M. P. Costa, H. Ribeiro, A. Pacheco, D. Pinheiro, M. Kamimura, R. Araujo-Filho, D. M. de Oliveira

{"title":"Flagellar proteins prediction after sequence-structure alignments of coronin and Arp2/3 complex in Leishmania spp.","authors":"M. P. Costa, H. Ribeiro, A. Pacheco, D. Pinheiro, M. Kamimura, R. Araujo-Filho, D. M. de Oliveira","doi":"10.1109/BIBMW.2007.4425404","DOIUrl":"https://doi.org/10.1109/BIBMW.2007.4425404","url":null,"abstract":"Leishmania are uniflagellate protozoa, whose flagellum plays a key role in motility, being essential for parasite migration, invasion and persistence on host tissues. Actin is the major cytoskeleton protein, while polymerization and depolymerization of parasite actin and actin motor-associated proteins during both processes of motility and host cell entry might be key events for successful infection. In search for genomic and/or proteomic evidences of actin-interacting proteins (AIPs) involved in flagellar activities of Leishmania spp., we have applied computational tools (hidden Markov models, Viterbi algorithm and comparative modeling) to infer biological meaning through detailed sequence-structural-functional analyses on Leishmania AIPs, such as coronin and Arp2/3 complex proteins, two important elements on phagosome formation after parasite phagocytosis by macrophages. Results presented here provide the first integrated bioinformatics analyses of Leishmania coronin and Arp2/3 genes and their gene products, a direct contribution to genome annotation of these important actin-regulating proteins yet to be properly in vitro characterized in flagellate trypanosomatids towards their putative virulence.","PeriodicalId":260286,"journal":{"name":"2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116758463","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

Using fuzzy memberships to core patterns to interpret connectedness in gene expression clusters 利用模糊隶属度对核心模式进行解释基因表达簇中的连通性

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425409

N. A. Yousri, M. Kamel, M. Ismail

{"title":"Using fuzzy memberships to core patterns to interpret connectedness in gene expression clusters","authors":"N. A. Yousri, M. Kamel, M. Ismail","doi":"10.1109/BIBMW.2007.4425409","DOIUrl":"https://doi.org/10.1109/BIBMW.2007.4425409","url":null,"abstract":"Connectivity based clustering can reveal the continuity of gene expression patterns, and thus can discover interrelations between tumor types, as well as regulatory relations between genes that can lead to discovering gene pathways. Pattern cores are a subset of expression patterns that are representatives of the whole set of patterns and can be used to reveal the structure of the data as well as that of the clusters, especially in the presence of huge data sets. This work presents a fuzzy approach that starts by finding the density-based expression pattern cores. Those cores are then clustered into core clusters and fuzzy memberships to those cores are calculated for all patterns in the data set. The whole data set is then clustered into pattern clusters using a connectivity-based algorithm, where a pattern cluster might contain one or more core clusters. The fuzzy memberships to core clusters in each pattern cluster are used to interpret the connectedness of the pattern cluster using the structure of core clusters, as well as to identify how each pattern is related to one or more tumor types.","PeriodicalId":260286,"journal":{"name":"2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114848340","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: 2