Computational systems bioinformatics. Computational Systems Bioinformatics Conference最新文献_第9页

A grammar based methodology for structural motif finding in ncRNA database search. 基于语法的ncRNA数据库结构基序查找方法。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0024

Daniel J. Quest, W. Tapprich, H. Ali

引用次数: 3

Composite motifs integrating multiple protein structures increase sensitivity for function prediction. 整合多种蛋白质结构的复合基序增加了功能预测的敏感性。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0035

B. Chen, D. Bryant, Amanda E. Cruess, Joseph H Bylund, V. Fofanov, D. Kristensen, M. Kimmel, O. Lichtarge, L. Kavraki

{"title":"Composite motifs integrating multiple protein structures increase sensitivity for function prediction.","authors":"B. Chen, D. Bryant, Amanda E. Cruess, Joseph H Bylund, V. Fofanov, D. Kristensen, M. Kimmel, O. Lichtarge, L. Kavraki","doi":"10.1142/9781860948732_0035","DOIUrl":"https://doi.org/10.1142/9781860948732_0035","url":null,"abstract":"The study of disease often hinges on the biological function of proteins, but determining protein function is a difficult experimental process. To minimize duplicated effort, algorithms for function prediction seek characteristics indicative of possible protein function. One approach is to identify substructural matches of geometric and chemical similarity between motifs representing known active sites and target protein structures with unknown function. In earlier work, statistically significant matches of certain effective motifs have identified functionally related active sites. Effective motifs must be carefully designed to maintain similarity to functionally related sites (sensitivity) and avoid incidental similarities to functionally unrelated protein geometry (specificity). Existing motif design techniques use the geometry of a single protein structure. Poor selection of this structure can limit motif effectiveness if the selected functional site lacks similarity to functionally related sites. To address this problem, this paper presents composite motifs, which combine structures of functionally related active sites to potentially increase sensitivity. Our experimentation compares the effectiveness of composite motifs with simple motifs designed from single protein structures. On six distinct families of functionally related proteins, leave-one-out testing showed that composite motifs had sensitivity comparable to the most sensitive of all simple motifs and specificity comparable to the average simple motif. On our data set, we observed that composite motifs simultaneously capture variations in active site conformation, diminish the problem of selecting motif structures, and enable the fusion of protein structures from diverse data sources.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"6 1","pages":"343-55"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64007752","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: 7

Using directed information to build biologically relevant influence networks. 利用定向信息建立生物学相关的影响网络。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Arvind Rao, Alfred O Hero, David J States, James Douglas Engel

{"title":"Using directed information to build biologically relevant influence networks.","authors":"Arvind Rao, Alfred O Hero, David J States, James Douglas Engel","doi":"","DOIUrl":"","url":null,"abstract":"The systematic inference of biologically relevant influence networks remains a challenging problem in computational biology. Even though the availability of high-throughput data has enabled the use of probabilistic models to infer the plausible structure of such networks, their true interpretation of the biology of the process is questionable. In this work, we propose a network inference methodology, based on the directed information (DTI) criterion, which incorporates the biology of transcription within the framework, so as to enable experimentally verifiable inference. We use publicly available embryonic kidney and T-cell microarray datasets to demonstrate our results. We present two variants of network inference via DTI (supervised and unsupervised) and the inferred networks relevant to mammalian nephrogenesis as well as T-cell activation. We demonstrate the conformity of the obtained interactions with literature as well as comparison with the coefficient of determination (CoD) method. Apart from network inference, the proposed framework enables the exploration of specific interactions, not just those revealed by data.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":" ","pages":"145-56"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27061634","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

Deconvoluting the BAC-gene relationships using a physical map. 使用物理图谱解卷积bac -基因关系。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Yonghui Wu, Lan Liu, Timothy J Close, Stefano Lonardi

{"title":"Deconvoluting the BAC-gene relationships using a physical map.","authors":"Yonghui Wu, Lan Liu, Timothy J Close, Stefano Lonardi","doi":"","DOIUrl":"","url":null,"abstract":"Motivation: The deconvolution of the relationships between BAC clones and genes is a crucial step in the selective sequencing of the regions of interest in a genome. It usually requires combinatorial pooling of unique probes obtained from the genes (unigenes), and the screening of the BAC library using the pools in a hybridization experiment. Since several probes can hybridize to the same BAC, in order for the deconvolution to be achievable the pooling design has to be able to handle a large number of positives. As a consequence, smaller pools need to be designed which in turn increases the number of hybridization experiments possibly making the entire protocol unfeasible.Results: We propose a new algorithm that is capable of producing high accuracy deconvolution even in the presence of a weak pooling design, i.e., when pools are rather large. The algorithm compensates for the decrease of information in the hybridization data by taking advantage of a physical map of the BAC clones. We show that the right combination of combinatorial pooling and our algorithm not only dramatically reduces the number of pools required, but also successfully deconvolutes the BAC-gene relationships with almost perfect accuracy.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":" ","pages":"203-14"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27061639","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 grammar based methodology for structural motif finding in ncRNA database search. 基于语法的ncRNA数据库结构基序查找方法。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Daniel Quest, William Tapprich, Hesham Ali

引用次数: 0

An algorithmic approach to automated high-throughput identification of disulfide connectivity in proteins using tandem mass spectrometry. 使用串联质谱法自动高通量鉴定蛋白质中二硫连通性的算法方法。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0009

Timothy Lee, Rahul Singh, T. Yen, B. Macher

{"title":"An algorithmic approach to automated high-throughput identification of disulfide connectivity in proteins using tandem mass spectrometry.","authors":"Timothy Lee, Rahul Singh, T. Yen, B. Macher","doi":"10.1142/9781860948732_0009","DOIUrl":"https://doi.org/10.1142/9781860948732_0009","url":null,"abstract":"Knowledge of the pattern of disulfide linkages in a protein leads to a better understanding of its tertiary structure and biological function. At the state-of-the-art, liquid chromatography/electrospray ionization-tandem mass spectrometry (LC/ESI-MS/MS) can produce spectra of the peptides in a protein that are putatively joined by a disulfide bond. In this setting, efficient algorithms are required for matching the theoretical mass spaces of all possible bonded peptide fragments to the experimentally derived spectra to determine the number and location of the disulfide bonds. The algorithmic solution must also account for issues associated with interpreting experimental data from mass spectrometry, such as noise, isotopic variation, neutral loss, and charge state uncertainty. In this paper, we propose a algorithmic approach to high-throughput disulfide bond identification using data from mass spectrometry, that addresses all the aforementioned issues in a unified framework. The complexity of the proposed solution is of the order of the input spectra. The efficacy and efficiency of the method was validated using experimental data derived from proteins with with diverse disulfide linkage patterns.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"6 1","pages":"41-51"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64007128","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: 10

Exact and heuristic algorithms for weighted cluster editing. 加权聚类编辑的精确启发式算法。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0040

S. Rahmann, T. Wittkop, J. Baumbach, Marcel Martin, A. Truß, Sebastian Böcker

{"title":"Exact and heuristic algorithms for weighted cluster editing.","authors":"S. Rahmann, T. Wittkop, J. Baumbach, Marcel Martin, A. Truß, Sebastian Böcker","doi":"10.1142/9781860948732_0040","DOIUrl":"https://doi.org/10.1142/9781860948732_0040","url":null,"abstract":"Clustering objects according to given similarity or distance values is a ubiquitous problem in computational biology with diverse applications, e.g., in defining families of orthologous genes, or in the analysis of microarray experiments. While there exists a plenitude of methods, many of them produce clusterings that can be further improved. \"Cleaning up\" initial clusterings can be formalized as projecting a graph on the space of transitive graphs; it is also known as the cluster editing or cluster partitioning problem in the literature. In contrast to previous work on cluster editing, we allow arbitrary weights on the similarity graph. To solve the so-defined weighted transitive graph projection problem, we present (1) the first exact fixed-parameter algorithm, (2) a polynomial-time greedy algorithm that returns the optimal result on a well-defined subset of \"close-to-transitive\" graphs and works heuristically on other graphs, and (3) a fast heuristic that uses ideas similar to those from the Fruchterman-Reingold graph layout algorithm. We compare quality and running times of these algorithms on both artificial graphs and protein similarity graphs derived from the 66 organisms of the COG dataset.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"6 1","pages":"391-401"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64007620","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

Modeling species-genes data for efficient phylogenetic inference. 为有效的系统发育推断建立物种-基因数据模型。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0043

Wenyuan Li, Y. Liu

{"title":"Modeling species-genes data for efficient phylogenetic inference.","authors":"Wenyuan Li, Y. Liu","doi":"10.1142/9781860948732_0043","DOIUrl":"https://doi.org/10.1142/9781860948732_0043","url":null,"abstract":"In recent years, biclique methods have been proposed to construct phylogenetic trees. One of the key steps of these methods is to find complete sub-matrices (without missing entries) from a species-genes data matrix. To enumerate all complete sub-matrices, (17) described an exact algorithm, whose running time is exponential. Furthermore, it generates a large number of complete sub-matrices, many of which may not be used for tree reconstruction. Further investigating and understanding the characteristics of species-genes data may be helpful for discovering complete sub-matrices. Therefore, in this paper, we focus on quantitatively studying and understanding the characteristics of species-genes data, which can be used to guide new algorithm design for efficient phylogenetic inference. In this paper, a mathematical model is constructed to simulate the real species-genes data. The results indicate that sequence-availability probability distributions follow power law, which leads to the skewness and sparseness of the real species-genes data. Moreover, a special structure, called \"ladder structure\", is discovered in the real species-genes data. This ladder structure is used to identify complete sub-matrices, and more importantly, to reveal overlapping relationships among complete sub-matrices. To discover the distinct ladder structure in real species-genes data, we propose an efficient evolutionary dynamical system, called \"generalized replicator dynamics\". Two species-genes data sets from green plants are used to illustrate the effectiveness of our model. Empirical study has shown that our model is effective and efficient in understanding species-genes data for phylogenetic inference.","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"6 1","pages":"429-40"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64007901","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

Rule-based human gene normalization in biomedical text with confidence estimation. 基于规则的生物医学文本人类基因归一化与置信度估计。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01 DOI: 10.1142/9781860948732_0037

W. Lau, Calvin A. Johnson, Kevin Becker

引用次数: 11

fRMSDPred: predicting local RMSD between structural fragments using sequence information. fRMSDPred:利用序列信息预测结构片段之间的局部RMSD。

Computational systems bioinformatics. Computational Systems Bioinformatics Conference Pub Date : 2007-01-01

Huzefa Rangwala, George Karypis

引用次数: 0