Journal of bioinformatics最新文献

英文中文

Bioinformatics - The new home for protein sequence motifs 生物信息学-蛋白质序列基序的新家园

Journal of bioinformatics

Pub Date : 2006-01-01 DOI: 10.1093/bioinformatics/bti755

A. Bateman

Protein domains and sequence motifs have been very influential in the field of molecular biology. These units are the common currency of protein structure and function. The Protein Sequence Motifs series in Trends in Biochemical Sciences was an extremely popular forum to publish these results, but sadly the journal published the final one in 2004 (McEntyre and Gibson 2004). Bioinformatics is well placed to publish reports of novel protein domains and over the past year we have published reports of the MEDs and PocR domains (Anantharaman and Aravind, 2005), the G5 domain (Bateman et al., 2005), the Why domain (Ciccarelli and Bork 2005) and the OCRE domain (Callebaut and Mornon 2005). In this issue we publish the PilZ domain (pronounced ‘pills’) by Amikam and Galperin (2005). This manuscript strongly suggests that the PilZ domain mediates binding to c-di-GMP a universal bacterial second messenger. Because the PilZ is found in hundreds of bacterial proteins this work will have a large impact in understanding bacteria. I would like to invite you to submit your next novel domain finding as a Discovery Note to Bioinformatics. We will also consider papers that describe the unification of existing protein families and domains into a larger superfamily. Discovery notes are papers intended for the reporting of biologically interesting discoveries using computational techniques. Discovery notes can be up to 4 journal pages length. The instructions to authors can be found at the following URL: http://www.oxfordjournals.org/bioinformatics/ for_authors/general.html If you would like a quick assessment of your domain discovery please send me a pre-submission enquiry outlining the domain and the biological significance of the finding.

蛋白质结构域和序列基序在分子生物学领域有着重要的影响。这些单位是蛋白质结构和功能的通用货币。《生物化学科学趋势》中的蛋白质序列基序系列是发表这些结果的一个非常受欢迎的论坛，但遗憾的是，该杂志在2004年发表了最后一篇(McEntyre和Gibson 2004)。生物信息学很适合发表新的蛋白质结构域的报告，在过去的一年里，我们发表了med和PocR结构域(Anantharaman and Aravind, 2005)， G5结构域(Bateman et al.， 2005)， Why结构域(Ciccarelli and Bork 2005)和OCRE结构域(Callebaut and Mornon 2005)的报告。在这一期中，我们发表了Amikam和Galperin(2005)的PilZ域(发音为“药丸”)。这篇文章强烈表明PilZ结构域介导了与c-di-GMP的结合，这是一种普遍的细菌第二信使。由于PilZ存在于数百种细菌蛋白质中，这项工作将对理解细菌产生重大影响。我想邀请你提交你的下一个新领域发现作为《生物信息学》的发现笔记。我们还将考虑那些描述现有蛋白质家族和结构域统一成一个更大的超家族的论文。发现笔记是使用计算技术报告生物学上有趣的发现的论文。发现笔记的长度可达4页。对作者的指导可以在以下网址找到:http://www.oxfordjournals.org/bioinformatics/ for_authors/general.html如果您想快速评估您的域名发现，请在提交前向我发送一份咨询，概述该域名和该发现的生物学意义。

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引用次数: 6

An update from the Bioinformatics Editors 来自生物信息学编辑的更新

Journal of bioinformatics

Pub Date : 2005-12-15 DOI: 10.1093/bioinformatics/bti768

A. Bateman, A. Valencia

引用次数: 0

The Fifth Georgia Tech - Oak Ridge National Laboratory International Conference in Bioinformatics: in silico Biology, Computational Genomics and Evolutionary Biology 第五届佐治亚理工学院-橡树岭国家实验室生物信息学国际会议:硅生物学、计算基因组学和进化生物学

Journal of bioinformatics

Pub Date : 2005-02-01 DOI: 10.1093/bioinformatics/bti1207

M. Borodovsky, A. Rzhetsky, D. Frishman

引用次数: 0

Increasing the Impact of Bioinformatics 增加生物信息学的影响

Journal of bioinformatics

Pub Date : 2005-01-01 DOI: 10.1093/bioinformatics/bti185

A. Valencia, A. Bateman

引用次数: 6

New Leadership for Bioinformatics 生物信息学的新领导

Journal of bioinformatics

Pub Date : 2004-08-12 DOI: 10.1093/bioinformatics/bth403

A. Bateman, A. Valencia

引用次数: 2

Guest Editor Preface: Plant & Animal Genome (PAG) Meeting Bioinformatics Session Paper Competition 客座编辑序言:植物与动物基因组(PAG)会议生物信息学会议论文竞赛

Journal of bioinformatics

Pub Date : 2004-01-22 DOI: 10.1093/bioinformatics/bth016

R. Bruskiewich

In the field of science, not all experiments take place in the laboratory. In some cases, experiments can be organizational to explore a new way of doing things. Scientific workshops at the annual Plant & Animal Genome (PAG) conference in San Diego have traditionally followed a format of coordinator-invited presentations. Based on feedback from PAG meeting attendees in 2003 concerning the meeting’s bioinformatics workshops and inspired by the paper-driven format of other international bioinformatics meetings, a different workshop format for bioinformatics was proposed for 2004: an invited keynote speaker presenting a review of specified methodology in the field, followed by presentation of selected papers from a first ever PAG bioinformatics paper competition. The theme of the competitive papers was requested to be ‘bioinformatics applied to answer specific plant and/or animal genome research questions’. As an added incentive for prospective authors, the workshop organizer negotiated with Bioinformatics, to publish the keynote review paper and the five selected papers chosen by a formal process of peer review. I am now pleased to introduce these keynote and five selected papers of the competition, published in this special section of Bioinformatics:

在科学领域，并非所有的实验都在实验室里进行。在某些情况下，实验可以有组织地探索一种新的做事方式。在圣地亚哥举行的一年一度的动植物基因组(PAG)会议上，科学研讨会传统上遵循协调员邀请演讲的形式。根据2003年PAG会议与会者对会议生物信息学研讨会的反馈，并受到其他国际生物信息学会议论文驱动形式的启发，2004年提出了一种不同的生物信息学研讨会形式:邀请一位主讲人介绍该领域特定方法的回顾，然后介绍首次PAG生物信息学论文竞赛中的精选论文。竞赛论文的主题要求是“应用生物信息学来回答特定的植物和/或动物基因组研究问题”。作为对潜在作者的额外激励，研讨会组织者与生物信息学进行了谈判，发表主题评论论文和通过正式同行评议过程选出的五篇论文。现在我很高兴地向大家介绍本次大赛的主题和五篇精选论文，这些论文发表在《生物信息学》的专刊上:

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引用次数: 0

Growth in Bioinformatics 生物信息学的发展

Journal of bioinformatics

Pub Date : 2003-01-01 DOI: 10.1093/bioinformatics/19.1.1

C. Sander

引用次数: 27

The Fourth Georgia Tech-University of Georgia International Conference in Bioinformatics: in silico Biology, Biological Networks, from Genomics to Epidemiology (November 13-16, 2003, Atlanta, Georgia, USA) 第四届佐治亚理工大学生物信息学国际会议:从基因组学到流行病学的硅生物学、生物网络(2003年11月13-16日，美国佐治亚州亚特兰大)

Journal of bioinformatics

Pub Date : 2003-01-01 DOI: 10.1093/bioinformatics/btg365

Three previous bioinformatics meetings organized by Georgia Tech were held in Atlanta in 1997, 1999 and 2001 have attracted outstanding researchers from 14 countries around the globe and established this conference as a major academic forum for intensive and open exchange of new ideas. This year we again have invited many rising junior scientists to deliver plenary lectures on their discoveries made in silico, with many of these accomplishments driven by the explosion of genomic and proteomic data. The focus of the 2003 conference, in comparison with the previous ones, has shifted even further to the most complicated aspects of genomics and proteomics manifested by the impressive advances in creating consistent models of networks of cellular processes (http://opal. biology.gatech.edu/GeneMark/conference/). Other changes include the University of Georgia joining Georgia Tech as a co-organizer of the meeting and a move of the conference site to the brand new Georgia Tech Conference Center & Hotel opened in the Midtown area extension of Georgia Tech campus near the Atlanta Arts Center and the city’s historic area. Several papers presented at the conference are included in this current Special Issue of Bioinformatics, with their publication serving a parallel avenue of presentation for conference participants. Seven papers out of seventeen submitted manuscripts successfully passed peer review and were accepted for publication. The paper by Rocco and Critchlow describes a method for scanning the internet to identify web sites with particular functionalities and developing wrappers for automatic queries of those sites. They tested it on sites that perform BLAST searches and showed reasonable success at automatic classification and query submission. An important aspect of the work is the ability of the system to learn the appropriate queries. This is an important and very challenging problem and this paper offers interesting algorithmic ideas. Qian, Lin, Luscombe, Yu and Gerstein address the important and challenging computational problem of defining relationships between transcription factors (TFs) and their target genes. They apply support vector machines to microarray expression data to generate novel predictions from known interactions. Interestingly, their approach does not use DNA sequence information. Existing databases of experimentally confirmed TF-target pairs only contain positive examples, so the authors are careful to construct a balanced set of both positive and negative training data. The resulting database ofin silico predictions of TF-target pairs is a valuable complement to the information that can be derived from chromatin-immunoprecipitation microarray (‘ChIP on a chip’) experiments. Lukashin, Lukashev and Fuchs attack the problems of inference of topology of gene regulation networks that manifests itself in capricious patterns of gene expression in microarray experiments. They verify that genetic networks have many properties, such

佐治亚理工学院于1997年、1999年和2001年在亚特兰大举办了三届生物信息学会议，吸引了来自全球14个国家的杰出研究人员，并将此会议建立为一个集中和开放交流新思想的重要学术论坛。今年，我们再次邀请了许多崭露头角的年轻科学家来做全体讲座，介绍他们在计算机上的发现，其中许多成就是由基因组和蛋白质组学数据的爆炸式增长推动的。与之前的会议相比，2003年会议的焦点已经进一步转移到基因组学和蛋白质组学最复杂的方面，这体现在创建细胞过程网络的一致模型方面取得了令人印象深刻的进展(http://opal)。biology.gatech.edu/GeneMark/conference/)。其他变化包括佐治亚大学加入佐治亚理工学院作为会议的共同组织者，并将会议地点转移到全新的佐治亚理工学院会议中心和酒店，该会议中心和酒店位于亚特兰大艺术中心和城市历史区域附近的佐治亚理工学院校园的中城扩展区。在会议上发表的几篇论文被包括在本期《生物信息学》特刊中，它们的出版为会议参与者提供了一个平行的展示途径。17篇投稿论文中有7篇成功通过同行评议，并被接受发表。Rocco和Critchlow的论文描述了一种方法，用于扫描互联网以识别具有特定功能的网站，并开发用于自动查询这些网站的包装器。他们在执行BLAST搜索的网站上进行了测试，并在自动分类和查询提交方面取得了一定的成功。这项工作的一个重要方面是系统学习适当查询的能力。这是一个非常重要且具有挑战性的问题，本文提供了有趣的算法思想。Qian, Lin, Luscombe, Yu和Gerstein解决了定义转录因子(tf)与其靶基因之间关系的重要且具有挑战性的计算问题。他们将支持向量机应用于微阵列表达数据，从已知的相互作用中产生新的预测。有趣的是，他们的方法不使用DNA序列信息。现有的实验证实的tf -目标对数据库只包含正例，因此作者谨慎地构建一个正负训练数据的平衡集。由此产生的tf靶对的计算机预测数据库是对染色质免疫沉淀微阵列(“芯片上的芯片”)实验所得信息的有价值的补充。Lukashin, Lukashev和Fuchs攻击了基因调控网络拓扑的推理问题，这些问题在微阵列实验中反复无常的基因表达模式中表现出来。他们验证了遗传网络具有许多特性，如连接度分布、容错和攻击以及网络冗余，这与几年前建立的蛋白质-蛋白质相互作用网络没有什么不同。Krause, von Mering和Bork描述了对酵母蛋白相互作用组的仔细的大规模计算分析，旨在识别尚未发现的蛋白质复合物并评估已知信息片段的可靠性。他们为分组蛋白质相互作用数据定义了一种新的相似性度量，并最终通过对原始实验数据的无监督聚类产生最小冗余的蛋白质复合物集合。Han和Ju的论文描述了一个快速显示具有数千条边和节点的图形的程序，这在蛋白质相互作用网络中很常见。该方法允许多种查看选项，例如关注特定子图和折叠图的部分以减小其大小。该算法是有效的，足以使它适用于整个蛋白质组分析所需的非常大的图形问题。它们还提供了比较两个或多个图形的工具，以突出它们的相似点和不同点。Joel Bader描述了一种高效的贪婪算法，该算法从选定的种子蛋白开始，从蛋白质相互作用数据中自动提取生物相关网络(因此该算法有了有趣的名字，SEEDY)。交互数据是出了名的嘈杂，Bader试图使用在他之前的工作中开发的置信度标准来提高生成的网络的可靠性。还有一个有趣的尝试是同时分析蛋白质-蛋白质和基因相互作用的数据。Gomez、Noble和Rzhetsky通过建立一个吸引-排斥学习模型，解决了在基因组尺度上预测蛋白质-蛋白质相互作用的棘手问题。简单地说，相互作用的蛋白质对的进化保守特征有助于吸引，而不相互作用的蛋白质对的特征有助于排斥。作者表明，该模型适用于已知的相互作用，包括排斥(不仅是吸引力)。

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引用次数: 0

The Journal Bioinformatics, key medium for computational biology 生物信息学杂志，计算生物学的关键媒介

Journal of bioinformatics

Pub Date : 2002-01-01 DOI: 10.1093/bioinformatics/18.1.1

C. Sander

引用次数: 22

Erratum: Evaluation of methods for the prediction of membrane spanning regions 勘误:评价预测膜跨越区域的方法

Journal of bioinformatics

Pub Date : 2002-01-01 DOI: 10.1093/bioinformatics/18.1.218

Steffen Möller, M. Croning, R. Apweiler

引用次数: 14

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