Proceedings. International Conference on Intelligent Systems for Molecular Biology最新文献_第8页

Reconstructing the duplication history of a tandem repeat. 重建串联重复序列的复制历史。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1999-01-01

G Benson, L Dong

{"title":"Reconstructing the duplication history of a tandem repeat.","authors":"G Benson, L Dong","doi":"","DOIUrl":"","url":null,"abstract":"One of the less well understood mutational transformations that act upon DNA is tandem duplication. In this process, a stretch of DNA is duplicated to produce two or more adjacent copies, resulting in a tandem repeat. Over time, the copies undergo additional mutations so that typically, multiple approximate tandem copies are present. An interesting feature of tandem repeats is that the duplicated copies are preserved together, making it possible to do \"phylogenetic analysis\" on a single sequence. This involves using the pattern of mutations among the copies to determine a minimal or a most likely history for the repeat. A history tries to describe the interwoven pattern of substitutions, indels, and duplication events in such a way as to minimize the number of identical mutations that arise independently. Because the copies are adjacent and ordered, the history problem can not be solved by standard phylogeny algorithms. In this paper, we introduce several versions of the tandem repeat history problem, develop algorithmic solutions and evaluate their performance. We also develop ways to visualize important features of a history with the goal of discovering properties of the duplication mechanism.","PeriodicalId":79420,"journal":{"name":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1999-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21633638","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

Seamless integration of biological applications within a database framework. 在数据库框架内无缝集成生物应用程序。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1999-01-01

T Topaloglou, A Kosky, V Markowitz

引用次数: 0

Pharmaceutical target discovery using Guilt-by-Association: schizophrenia and Parkinson's disease genes. 利用联想内疚发现药物靶点:精神分裂症和帕金森病基因。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1999-01-01

M G Walker, W Volkmuth, T M Klingler

引用次数: 0

Multiple structural alignment and core detection by geometric hashing. 基于几何哈希的多结构对齐和岩心检测。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1999-01-01

N Leibowitz, Z Y Fligelman, R Nussinov, H J Wolfson

引用次数: 0

TEXTAL: a pattern recognition system for interpreting electron density maps. 用于解释电子密度图的模式识别系统。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1999-01-01

T R Ioerger, T Holton, J A Christopher, J C Sacchettini

{"title":"TEXTAL: a pattern recognition system for interpreting electron density maps.","authors":"T R Ioerger, T Holton, J A Christopher, J C Sacchettini","doi":"","DOIUrl":"","url":null,"abstract":"X-ray crystallography is the most widely used method for determining the three-dimensional structures of proteins and other macromolecules. One of the most difficult steps in crystallography is interpreting the electron density map to build the final model. This is often done manually by crystallographers and is very time-consuming and error-prone. In this paper, we introduce a new automated system called TEXTAL for interpreting electron density maps using pattern recognition. Given a map to be modeled, TEXTAL divides the map into small regions and then finds regions with a similar pattern of density in a database of maps for proteins whose structures have already been solved. When a match is found, the coordinates of atoms in the region are inferred by analogy. The key to making the database lookup efficient is to extract numeric features that represent the patterns in each region and to compare feature values using a weighted Euclidean distance metric. It is crucial that the features be rotation-invariant, since regions with similar patterns of density can be oriented in any arbitrary way. This pattern-recognition approach can take advantage of data accumulated in large crystallographic databases to effectively learn the association between electron density and molecular structure by example.","PeriodicalId":79420,"journal":{"name":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1999-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21634900","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

Database search based on Bayesian alignment. 基于贝叶斯对齐的数据库搜索。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1999-01-01

J Zhu, R Lüthy, C E Lawrence

{"title":"Database search based on Bayesian alignment.","authors":"J Zhu, R Lüthy, C E Lawrence","doi":"","DOIUrl":"","url":null,"abstract":"The size of protein sequence database is getting larger each day. One common challenge is to predict protein structures or functions of the sequences in databases. It is easy when a sequence shares direct similarity to a well-characterized protein. If there is no direct similarity, we have to rely on a third sequence or a model as intermediate to link two proteins together. We developed a new model based method, called Bayesian search, as a means to connect two distantly related proteins. We compared this Bayesian search model with pairwise and multiple sequence comparison methods on structural databases using structural similarity as the criteria for relationship. The results show that the Bayesian search can link more distantly related sequence pairs than other methods, collectively and consistently over large protein families. If each query made one error on average against SCOP database PDB40D-B, Bayesian search found 36.5% of related pairs, PSI-Blast found 32.6%, and Smith-Waterman method found 25%. Examples are presented to show that the alignments predicted by the Bayesian search agree well with structural alignments. Also false positives found by Bayesian search at low cutoff values are analyzed.","PeriodicalId":79420,"journal":{"name":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1999-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21633994","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

Metrics and similarity measures for hidden Markov models. 隐马尔可夫模型的度量和相似性度量。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1999-01-01

R B Lyngsø, C N Pedersen, H Nielsen

引用次数: 0

INTERACT: an object oriented protein-protein interaction database. 一个面向对象的蛋白质-蛋白质相互作用数据库。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1999-01-01

K Eilbeck, A Brass, N Paton, C Hodgman

引用次数: 0

Proceedings of the 6th International Conference on Intelligent Systems for Molecular Biology. Montreal, Quebec, Canada. June 28-July 1, 1998. 第六届分子生物学智能系统国际会议论文集。蒙特利尔，魁北克，加拿大。1998年6月28日至7月1日。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1998-01-01

引用次数: 0

Genetic algorithms for protein threading. 蛋白质穿线的遗传算法。

Proceedings. International Conference on Intelligent Systems for Molecular Biology Pub Date : 1998-01-01

J Yadgari, A Amir, R Unger

{"title":"Genetic algorithms for protein threading.","authors":"J Yadgari, A Amir, R Unger","doi":"","DOIUrl":"","url":null,"abstract":"Despite many years of efforts, a direct prediction of protein structure from sequence is still not possible. As a result, in the last few years researchers have started to address the \"inverse folding problem\": Identifying and aligning a sequence to the fold with which it is most compatible, a process known as \"threading\". In two meetings in which protein folding predictions were objectively evaluated, it became clear that threading as a concept promises a real breakthrough, but that much improvement is still needed in the technique itself. Threading is a NP-hard problem, and thus no general polynomial solution can be expected. Still a practical approach with demonstrated ability to find optimal solutions in many cases, and acceptable solutions in other cases, is needed. We applied the technique of Genetic Algorithms in order to significantly improve the ability of threading algorithms to find the optimal alignment of a sequence to a structure, i.e. the alignment with the minimum free energy. A major progress reported here is the design of a representation of the threading alignment as a string of fixed length. With this representation validation of alignments and genetic operators are effectively implemented. Appropriate data structure and parameters have been selected. It is shown that Genetic Algorithm threading is effective and is able to find the optimal alignment in a few test cases. Furthermore, the described algorithm is shown to perform well even without pre-definition of core elements. Existing threading methods are dependent on such constraints to make their calculations feasible. But the concept of core elements is inherently arbitrary and should be avoided if possible. While a rigorous proof is hard to submit yet an, we present indications that indeed Genetic Algorithm threading is capable of finding consistently good solutions of full alignments in search spaces of size up to 10(70).","PeriodicalId":79420,"journal":{"name":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1998-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"20695284","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