当前位置:文档之家› # These authors contributed equally to this work.

# These authors contributed equally to this work.

# These authors contributed equally to this work.
# These authors contributed equally to this work.

SPINE 2: A System for Collaborative Structural Proteomics within a Federated

Database Framework

Chern-Sing Goh1#, Ning Lan1#, Nathaniel Echols1#, Shawn Douglas1,

Duncan Milburn1, Paul Bertone2, Tom Acton3, Deyou Zheng3, Zeba Wunderlich3, Gaetano T. Montelione3, and Mark Gerstein1,4*

The current Spine (1.5) can be found at https://www.doczj.com/doc/eb4837664.html,/spine/ and the new Spine (2.0) is at https://www.doczj.com/doc/eb4837664.html,/spine/.

The older spine https://www.doczj.com/doc/eb4837664.html,/nesgc/summary.cgi (1.0).

1 Molecular Biophysics and Biochemistry

2 Molecular, Cellular, and Developmental Biology

4 Computer Science

Yale University

266 Whitney Ave

New Haven, CT 06520

3 Center for Advanced Biotechnology and Medicine

Rutgers University

Piscataway, NJ 08854

#These authors contributed equally to this work.

02-15-03

*corresponding author: mark.gerstein@https://www.doczj.com/doc/eb4837664.html,

Abstract

We present version 2 of the SPINE system for structural proteomics. SPINE is available over the web at https://www.doczj.com/doc/eb4837664.html,. It serves as central hub for the Northeast Structural Genomics Consortium, allowing collaborative experimentation to be carried out in a distributed fashion. The core of SPINE is a laboratory information management system (LIMS) for information related the progress of the consortium in cloning, expressing and purifying proteins and then solving their structures by NMR or X-ray crystallography. Originally, SPINE focused on tracking constructs, but, in its current form, it is able to track target sample tubes and store detailed sample histories. The central database comprises a set of standard relational tables and data dictionary that form a preliminary ontology for proteomic properties and provide a framework for large-scale data mining. Moreover, SPINE functions within a federation of interoperable information resources. These can be divided into (i) local resources closely coupled with SPINE that enable it to handle less standardized information (e.g. integrated mailing and publication lists), (ii) other information resources in the NESG consortium that are inter-linked with SPINE (e.g. crystallization LIMS local to particular laboratories), and (iii) international archival resources that SPINE shares links and information with (e.g. TargetDB at the PDB). Introduction

The structural genomics effort is generating a vast amount of data, underscoring the need for database systems and servers that can organize this information (1-4). Structural genomics consortia have been formed to consolidate these efforts. These consortia, including the Northeast Structural Genomics Consortium (NESG), are composed of numerous researchers in disparate locations working cooperatively at each step of the structural determination process, from selection of targets through to analysis of the results. The SPINE (Structural Proteomics In the NorthEast) database (5) was designed to coordinate the efforts of these researchers in the NESG as an information management and data analysis resource.

SPINE was created in 1999 as a data repository with associated data-mining tools. Through many revisions, its tracking functionality has expanded to accommodate detailed histories for individual samples, thereby presenting a more complete framework for transmitting information through all stages in high-throughput protein production and structure determination. In the original publication, Bertone et al.described the system architecture and how it was interlinked with specific tools to enable data-mining. There have been previous discussions regarding a role of proteomics ontologies in structural genomics (6) and at this stage, SPINE can be described as the beginning of an ontology of standardized protein properties. Here we present version 2 of SPINE and describe its overall development over the last three years.

Our system encompasses several aspects. Firstly, the core of the SPINE system (core

SPINE) is a centralized information management system, which tracks protein targets through the structure determination process, from the cloning of expression constructs to final structural characterization and submission of PDB coordinate sets, providing histories for particular samples. Secondly, SPINE sits at the center of a federation of computational resources; there are a number of SPINE-integrated web tools, both local and remote, that allow members of the consortium to post further information related to protein targets. Finally, the database can be analyzed retrospectively to identify factors that contribute to the ease with which individual proteins may be studied. Although the system is tailored to the needs and goals of the NESG, we expect that many of its features could be readily adapted to similar projects.

Implementation of Core SPINE System

The core database is implemented in MySQL on a Unix platform, with its user interface written entirely in the Perl programming language and integrated with the Apache web server. (Previous versions of the database used PHP extensively;the current implementation provides a more consistent platform.) This approach offers a considerable speed advantage and allows sharing of libraries with offline programs used in the development of future releases and associated tools. Perl's suitability for systems programming also allows a wide variety of other modules to be used in the server with minimal setup and administrative overhead, such as the BLAST package (7), Java, and Lisp code for data analysis. The core data elements are stored in a number of tables that record the experimental progress of individual targets (Figure 1). Auxiliary tables control access to the database and record a history of individual changes.

Initially, the basic unit tracked by SPINE was the expression construct. However, with the evolution by the NESG consortium of a systematic protein target selection process (8), these protein targets, each of which may have multiple associated constructs, have been made the focus of the database. All derivative records from the target onwards comprise one-to-many relationships. At the level of protein purification, we have introduced parent-child relationships for individual protein samples, broadening the data structure instead of compressing multiple purification records into a single instance. Most records include some form of unstructured data, often in the form of analytical images that have been uploaded to the server. This has even been extended to encompass email (see below) related to specific targets.

A key feature of the database is the ability of any registered member of the consortium to add and modify entries via an intuitive web interface. This is regulated by journaling all changes to data (and the user responsible), and by restricting access to certain entries. More flexible and customized methods of data entry are also possible. The use of direct SQL and the Open Database Connectivity (ODBC) protocols enable a variety of remote interfaces to the server (such as Excel spreadsheets or Java programs), and data interchange uses standard XML or table formats. These features enable bulk uploading of local datasets into SPINE. In the future, development will focus mainly on the

schema, the SPINE data dictionary, and display functions, leaving data entry at the prerogative of individual users

Integration of Core SPINE with a Federation of other Resources

The core SPINE database system sits at the center of a federation of information resources diagrammed in Figure 2.The core of SPINE is a relational database handling highly standardized information that interoperates with a set of local resources designed to handle more heterogeneous data that is not readily stored in tables. Some of these features include the incorporation of free text fields, the ability to upload data files, and the utility of its data mining tools and servers.

SPINE is also associated with external resources that are coupled together in a loose federation associated with the NESG. These resources can be categorized into three tiers.

1. Local Integrated Resources

SPINE is integrated with a number of "local" resources, resident on the same machine and tightly coupled to it. These include:

a.The NESG website. This is built around a wiki platform, allowing for easy remote

editing of such things as links to related projects.

b. A Structure Gallery. This is used for displaying completed 3D structures of protein

targets.

c.Publication page. This is built on elaborating the NCBI PubMed XML dump to

incorporate such things as targets and websites. It allows the direct cross-referencing of targets, URLs, and medline identifiers.

d.The Target Info Bulletin Board. The idea behind this is there is a lot of information

that people would like to track about a particular target that does not fit into

standardized tables. This can be easily sent in the form of simple email messages that are cc'ed to this bulletin board. These messages are automatically parsed for specific target identifiers, and each instance of a target identifier in the archive is linked to its corresponding record in SPINE and vice versa.

2. Other NESG Resources

There are a number of other computational resources that are part of the NESG project which are connected to SPINE. In particular, the diverse needs of experimentalists have led to the creation of several specialized databases within the consortium, dedicated to aspects of the project such as NMR data collection or crystal screening that are not well-

served by a single central resource. SPINE is currently being extended to facilitate storage of summary information from these satellite databases and even perform remote queries. Some of the resources that SPINE interoperates with are the PEP (9) cluster viewer at Columbia University and ZebaView target list at Rutgers University where new target entries are automatically downloaded nightly and inserted into SPINE. Other web resources SPINE is linked with include the SPINS database at Rutgers (17), the PartsList and Gene Census databases at Yale University (18), the Proteus crystallization database at Columbia University, and a LIMS system at the University of Toronto.

3. External Archival Resources

SPINE is also connected to resources outside of the NESG through an evolving portal portal called SmartLink. This system handles much of the difficulty translating ORF and structure identifiers and dealing with missing or dangling links. Most of the information pertaining to 3D structure determinations is transferred to the PDB (13). Other resources that SPINE is connected to include are SwissProt (10), PIR (11), BMRB (12), TargetDB (13)- the RCSB’s registry for structural genomics projects - and Wormbase (14). Detailed sample tracking and history

The requirements of tracking a target’s progress across multiple institutions include the ability to maintain a list of individual samples and their locations. For example, a protein may be purified at one site, shipped to another for crystallization screening, and then sent to a third site for structural characterization. Protein production requires greater flexibility, since not only protein samples but construct stocks and fermentation batches must be stored and tracked. The current system handles all sample types via tube records, whose contents are determined from their “parent” record (construct, expression, or purification). Each “sample tube” generated in the pipeline of sample production is assigned a unique tube identifier, which eventually will be mapped into a bar coding system. Therefore, a collection of protein samples may be assigned for biophysical analysis without regard for their specific target, since the database automatically determines their history based on tube identifier. This concept has been extended to handle sample plates, which behave as an aggregation of tube records identified by their well number.With this approach, information pertaining to shipments as well as physical location can be easily associated with sample records. This provides accounting of material transfer between institutions, and a more accurate picture of the progress of individual targets.

Discussion

In this paper we’ve described the SPINE version 2, a relational database system that that serves as the LIMS for the NESG consortium. This new version serves as the center of a

federation of inter-operable resources to allow for distributed functionality across the entire consortium. The major goals of the database system include:

1. A distributed LIMS

Constructing a distributed LIMS enables information to be shared among all the members of the consortia. From a vast number of local and external resources, SPINE can incorporate and process data, which can then be made accessible through a simple user browser interface at any location.

2. Standardized proteomics ontology

An improved representation of protein properties that is standardized will allow for more efficient retrospective analysis of structural and functional information, which can be mined using an incorporated generalized data mining web tool.

3. Datamining

The schema for SPINE has been designed to facilitate analysis of the collected data to further optimize target selection criteria. Bertone et al (5)demonstrated the potential data-mining capabilities of the SPINE database by developing a decision tree algorithm that was used to infer whether a protein was soluble, and which biochemical properties contributed most to solubility, from a dataset of 562 M. thermoautotrophicum protein expression constructs. The decision tree analysis indicated that protein characteristics such as protein length, hydrophobicity, and percent composition of charged residues were the strongest determinants in inferring the solubility of a protein.At present, the number of targets in the NESG is 5388, roughly 10 times the size of the original dataset, and presents a wealth of new information for mining (Goh et al., in preparation).

Future Directions in interoperation

We envision enhancing the integration with other databases by establishing a tighter interoperation with external databases, particularly those in the second tier.

To this end, we are currently investigating automatic data integration tools to span our heterogeneous federation of databases into what appears as a single (but virtual) database. Such an approach seems like a logical progression since not only does it remove implementation dependencies for each site, but it also manages the interconnections between sites. Users at different project locations and people from the outside could then interface, query, and interact with the uniform interface at a single site, rather than considering the details of all the different lab databases. This will allows us to adopt a hub and spoke topology of database connections rather than a fully interconnected network, simplifying the interface as compared to an all-with-all federation. It also provides a graceful transition from a very loose federation to a single unified database.

A number of technologies that may be useful in this include the SDSC Storage Resource Broker (SRB, https://www.doczj.com/doc/eb4837664.html,/DICE/SRB, a piece of client-server middleware that

provides a uniform interface for connecting to heterogeneous data resources over a network and accessing replicated data sets), Bio-Kleisli (15), and the Object-Protocol Model (16).

Obtaining the software

The complete code for SPINE, including table creation commands, may be downloaded by arrangement with the authors.

Acknowledgements

We thank Michael Baran, Natalia Denissova, Chi Kent Ho, LiChung Ma, and Rong Xiao for helpful discussions.

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Figure 1

Schema of the SPINE database, showing evolution of tables and data flow. (A) The original version of SPINE, in which the construct was the primary object tracked, and table records typically had one-to-one relationships. (B) Current schema. Experimental records (outlined in blue) all have one-to-many relationships branching from target entries. The most recent additions to the database are highlighted in red.

Figure 2

Overview of the SPINE federation.

Figure 3

Assorted screenshots from the NESG/SPINE web server; (a) the

NESG home page, providing links to all the institutions involved and to

the gallery of structures produced by them; (b) the SPINE target summary

page showing the data recorded in SPINE at each stage of the protein

production and structure determination process (blue shading indicates

data is present) for every target in the project; (c) one of the new

additions in version 2 of SPINE is the ability to track in detail a given sample tube down to a well, plate and physical location and can be changed by clicking on the desired sample entry (blue circle).

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this, these, that, those 的用法

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?这是你的祖父母吗? ?是的,他们是。 由此可以看出,当指示代词所指的事物已确定时,后面的指示代词指人时用he、she 和they 来代替,指物时用it 和they 来代替。再如: ?Is that a bird or a plane? ?It's a plane. ?那是鸟还是飞机? ?是飞机。 ?Is this your friend Tony ?Yes, he is. ?这是你的朋友托尼吗? ?是的,他是。 上一个:Module1 动词be 说明身份、年龄、状态等 下一个:Module 3 there be 句型的用法

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不对。 Theway(that ,in which)you’re doingit is comple tely crazy.你这么个干法,简直发疯。 Weadmired him for theway inwhich he facesdifficulties. Wallace and Darwingreed on the way inwhi ch different forms of life had begun.华莱士和达尔文对不同类型的生物是如何起源的持相同的观点。 This is the way(that) hedid it. I likedthe way(that) sheorganized the meeting. 3.theway(that)有时可以与how(作“如何”解)通用。例如: That’s the way(that) shespoke. = That’s how shespoke.

小学this-that-these-those用法+练习(带答案)

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way 用法

表示“方式”、“方法”,注意以下用法: 1.表示用某种方法或按某种方式,通常用介词in(此介词有时可省略)。如: Do it (in) your own way. 按你自己的方法做吧。 Please do not talk (in) that way. 请不要那样说。 2.表示做某事的方式或方法,其后可接不定式或of doing sth。 如: It’s the best way of studying [to study] English. 这是学习英语的最好方法。 There are different ways to do [of doing] it. 做这事有不同的办法。 3.其后通常可直接跟一个定语从句(不用任何引导词),也可跟由that 或in which 引导的定语从句,但是其后的从句不能由how 来引导。如: 我不喜欢他说话的态度。 正:I don’t like the way he spoke. 正:I don’t like the way that he spoke. 正:I don’t like the way in which he spoke. 误:I don’t like the way how he spoke. 4.注意以下各句the way 的用法: That’s the way (=how) he spoke. 那就是他说话的方式。 Nobody else loves you the way(=as) I do. 没有人像我这样爱你。 The way (=According as) you are studying now, you won’tmake much progress. 根据你现在学习情况来看,你不会有多大的进步。 2007年陕西省高考英语中有这样一道单项填空题: ——I think he is taking an active part insocial work. ——I agree with you_____. A、in a way B、on the way C、by the way D、in the way 此题答案选A。要想弄清为什么选A,而不选其他几项,则要弄清选项中含way的四个短语的不同意义和用法,下面我们就对此作一归纳和小结。 一、in a way的用法 表示:在一定程度上,从某方面说。如: In a way he was right.在某种程度上他是对的。注:in a way也可说成in one way。 二、on the way的用法 1、表示:即将来(去),就要来(去)。如: Spring is on the way.春天快到了。 I'd better be on my way soon.我最好还是快点儿走。 Radio forecasts said a sixth-grade wind was on the way.无线电预报说将有六级大风。 2、表示:在路上,在行进中。如: He stopped for breakfast on the way.他中途停下吃早点。 We had some good laughs on the way.我们在路上好好笑了一阵子。 3、表示:(婴儿)尚未出生。如: She has two children with another one on the way.她有两个孩子,现在还怀着一个。 She's got five children,and another one is on the way.她已经有5个孩子了,另一个又快生了。 三、by the way的用法

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3

A: We are ( ).We can’t find our ( ). B: Are you in ( ) Four ? A: Yes , we ( ). B: What class are you ( ) A: We’re in ( ) Three . B: Class Three ? This ( ) , please . 教学内容: 1. Let’s learn . 2. Let’s sing . 3.Read for fun . 4. Listen and tick . 教学目标: 1.掌握主题句型. A: Are they in Grade Four ? Yes , they are ./No ,they aren’t . B: What grade are they in ? They are in Grade Four . 2、会唱歌曲. 教学重点: 4

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2015六年级英语上册重点知识(新版科普 版) 六年级英语上册重点句型 Unit1Areyougoingtohaveabirthdayparty? 1.重点词汇 weather天气(可数或者不可数) sunny晴朗的(名词变形容词) will将要(情态动词+动词原形) begin开始(begintodosth.) 2.重点短语 aeacae做蛋糕 invitesoefriends邀请朋友 singanddance唱歌跳舞 eatnoodles吃面条 visityfriends拜访朋友 taeswiinglessons上游泳课 dosoewashing洗刷 bytheway顺便问一下 3.重点句型(考试必备) ybirthdayiscoing. Areyougoingtoaeacae?yes,Ia./No,Ianot. I’goingtohaveapartyathoenextSundayevening.

Wouldyoulietocoe? ThisisyplanforthisSunday. Whataboutyourplan? onay3rd,I’goingtohelpyudosoewashing. Theweatherisgood. Thepartywillbeginatfouro’cloc. I’asingyuncleandaunttocoetoyparty. couldIbringhitotheparty? 4.必考语法 一般将来时 时:toorrow、thedayaftertoorrow,next+时间,in+将来的时间等 态:主语+will+动词原形+其他. 主语+shall+动词原形+其他.(适合主语时第一人称)主语+begoingto+动词原形+其他. 句型: 否定句:主语+will+not+动词原形+其他. 主语+shall+not+动词原形+其他.(适合主语时第一人称) 主语+begoingto+not+动词原形+其他. 疑问句: 一般疑问句;will/shall+主语+动词原形+其他?

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科普版英语四年级下册教案(全册) 教学内容: 1.Let’s talk . 教学目标: 1.能听懂.会说.会认读way, they, behind, new, table.并能根据中文拼写出英文. 2.能听懂.会说交际用语,并能用来进行对话. 教学重难点: 1.词汇. 2.交际用语. 教学方法: 自问自答法. 教具准备: 录音机. 教学过程: 一. 学习单词: 教师把本课要求掌握的8个生词写在黑板上,教师领读几遍,让学生自己读,直到熟练为止. 二.学习 Let’s talk : 本课的对话可以用自问自答导入法导入,教师可同时充当Jill, Bill和Lulu 三个角色,先站在右边充当Jill 和Bill ,说”Excuse me , .please.”再转到左边充当Lulu ,说” Yes ?” ,再转回右边充当Jill和Bill 说” We are new . We can’t find our classroom.”一直到将全段对话表演完,表演两遍后放录音,先将全段放一遍,然后逐句放,让学生逐句跟说并翻译成中文. 三. 操练: 将对话分成三段, 各配一幅简笔画,教师写出关键词,然后逐段操练.操练的顺序是:先让学生听录音并跟说两遍,再让他们连起来说,并给他们半分钟时间让他们根据关键词复述,然后让全班复述. 在三段都操练完毕后,让同座间充当不同角色进行对话,一人充当Bill,另一人充当Lulu, 三段连起来练习,最后叫若干对同学站起来复述全段对话,然后将学生按三人一组分组,要求他们在下一堂课上进行表演. 四.作业:

让学生课下练习,准备下节课进行表演. 五. 效果测试: 根据Let’s talk.的内容填空 A: Excuse ( ) , please. B: Yes ? A: We are ( ).We can’t find our ( ). B: Are you in ( ) Four ? A: Yes , we ( ). B: What class are you ( ) A: We’re in ( ) Three . B: Class Three ? This ( ) , please . 教学内容: 1. Let’s learn . 2. Let’s sing . 3.Read for fun . 4. Listen and tick . 教学目标: 1.掌握主题句型. A: Are they in Grade Four ? Yes , they are ./No ,they aren’t . B: What grade are they in ? They are in Grade Four . 2.会唱歌曲. 教学重点: 能理解和掌握主语为复数的主系表结构,并能用替换词造句. 教学方法: 简笔画情景教学法. 教具准备: 简笔画. 教学过程: 一. 复习检查:

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