KR20030019681A - Web-based workbench system and method for proteome analysis and management - Google Patents

Abstract

PURPOSE: A Web based proteome analysis and management system and a method for the same are provided to make a decision of protein identification on experiment data, and to store protein data and identification result data at a database if the experiment data is identified as an arbitrary protein. CONSTITUTION: The system comprises an interface(210), a proteome identifier(220), a proteome retrieval module(230), a proteome analyzer(240), a reference proteome database(250), an experiment proteome database(260), a data manager(270), a flat file converter(280), and an XML converter(290). If a user inputs experiment protein data, the proteome identifier(220) receives the experiment protein data via the data manager(270). If two dimensional gel image, peptide mass fingerprinting, a molecular weight, an isoelectric point and other detailed data are input by a research institute, the proteome identifier(220) makes a decision of a protein identification process. In a case that the protein is identified as arbitrary reference proteome data stored at the database(250), the data manager(270) stores the protein data and an entry number of the reference proteome at the experiment proteome database(260). So the reference proteome database(250) is linked to the experiment proteome database(260). If the experiment proteome database(260) is constructed, the data stored at the database(260) can be retrieved or analyzed by the proteome retrieval module(230) or the proteome analyzer(240).

Description

Web-based workbench system and method for proteome analysis and management

The present invention relates to a proteome analysis system, and more particularly, to a system and method for storing, retrieving and analyzing proteome related information obtained by two-dimensional electrophoresis, which is one of biological research methods.

Proteome is a compound word for protein (protein) and ome (total), and refers to the total of all proteins. In general, cells of a single cell organism have one aspect of the proteome, while each cell of the multicellular organism has the same genome and different aspects of the proteome. That is, in the case of multicellular organisms, the genome from which the proteome is derived is constant, but the appearance of the proteome under specific cells or under specific conditions is different. The study that identifies these proteins as a whole and comprehensively identifies the level of expression of these proteins, their modifications and locations within cells, and the interactions between these proteins is called proteomics. By proteomics, the total proteins expressed in cells are identified, and the networks between these proteins are identified, and the overall life phenomena from the genome to the proteins that make up real life are identified.

Currently, proteomics research can be divided into two technologies. The first technique is to separate the total protein groups obtained from one cell into a plurality of constituent proteins, and the second technique is to analyze the separated proteins. Currently, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has been developed as a technique for separating protein groups. The 2D-PAGE technique simply processes the steps of staining, cutting and proteolytic cleavage of individual proteins through automated devices and computers. Scientists further analyze each protein with Mass Spectrometry (MS) to more accurately identify proteins isolated by 2D-PAGE technology.

The vast amount of proteome research results from this process are stored and analyzed by the experimenter. In order to analyze the results of an effective proteome study, a database (DB) of the proteome study results is required, and an integrated search between the database and the existing database is required. However, since the experimental proteome data, the existing database for proteome analysis, and various proteome analysis programs are provided separately from each other, the data storage, retrieval, and analysis functions are operated separately under different environments, and thus used by users. There was a difficulty.

The technical problem to be achieved by the present invention is to perform a protein identification decision on the experimental data, and if the experimental data is identified in any protein, web-based proteome analysis that comprises the protein data and the identification results as an experimental database And to provide a management system.

The technical problem to be achieved by the present invention is to provide a web-based proteome analysis and management system that efficiently integrates the storage, retrieval and analysis function of the database and the existing database for the proteome research results that exist apart from each other.

Another technical object of the present invention is to search for desired data using keywords, two-dimensional gel images, protein expression profiles, isoelectric points, molecular weight, peptide mass fingerprinting (PMF) and protein sequence information. In addition, the present invention provides a web-based proteome analysis and management system that can characterize proteins based on retrieved data.

Another technical object of the present invention is to provide a web-based proteome analysis and management system in which proteome data stored in an experimental database and a reference database can be exchanged and integrated with data stored in another system.

1 is a block diagram of a web-based proteome analysis and management system according to a preferred embodiment of the present invention.

FIG. 2 is a block diagram schematically illustrating functions performed in the proteome analysis and management system shown in FIG. 1.

FIG. 3 is a block diagram illustrating information stored in a reference proteome database and an experimental proteome database shown in FIG. 1 and relationships among the information.

4 is a flowchart illustrating a data storage / modification / deletion method performed by the data manager shown in FIG. 1.

5 is a flowchart illustrating a protein identification decision method performed by the proteome identification shown in FIG. 1.

6 is a diagram illustrating an example of a search initial screen for proteome search according to a preferred embodiment of the present invention.

FIG. 7 is a flowchart illustrating a proteome search method performed by the proteome search unit shown in FIG. 1.

8A to 8C are diagrams showing a keyword search screen executed by the method shown in FIG. 7 and a search result thereof when the keyword search menu shown in FIG. 6 is selected.

9A and 9B are diagrams illustrating an image search screen executed by the method shown in FIG. 7 when the image search menu shown in FIG. 6 is selected.

10A and 10B are diagrams showing a protein expression pattern search screen executed by the method shown in FIG. 7 and a search result thereof when the protein expression pattern search menu shown in FIG. 6 is selected.

11A to 11C are views showing an advanced search screen executed by the method shown in FIG. 7 and the search results thereof when the advanced search menu shown in FIG. 6 is selected.

<Description of Symbols for Main Parts of Drawings>

10: internet 100a-100z: client server

200: proteome analysis and management server 210: interface

220: Proteome East Government 230: Proteome Search Department

240: proteome analysis unit 250: reference proteome DB

260: experimental proteome DB270: data management

280: flat file conversion unit 290: XML configuration unit

In order to achieve the above object, a web-based proteome analysis and management system according to the present invention includes a first database in which a plurality of verified reference proteome data are stored; A second database in which experimental proteome data calculated by the experiment is stored; An interface that accepts one of experimental proteome data and a search clue from a user; Data management means for controlling an input / output function of data for the first and second databases; Proteome identification for performing protein identification decisions to identify which protein the experimental proteome data is; A proteome search unit for retrieving predetermined proteome data from the second database in response to any one of experimental proteome data and the search clue, and extracting detailed information of the retrieved proteome data from the first proteome database; And a proteome analyzer for analyzing the search results to extract the characteristics of the proteome.

In order to achieve the above object, an experimental proteome database construction method of a web-based proteome analysis and management system according to the present invention comprises the steps of: (a) inputting experimental proteome data; (b) retrieving similar proteome data of the proteome data with reference to peptide mass fingerprinting, isoelectric point, molecular weight and protein sequence information for the proteome data; (c) performing protein identification decisions on the proteome data in response to the search results; And (d) storing the experimental proteome data and the identification results in a second database in which the experimental proteome data is stored.

In order to achieve the above object, the experimental proteome data storage and modification method of the web-based proteome analysis and management system according to the present invention includes: (a) determining whether to newly store a two-dimensional gel image generated by electrophoresis in a database; step; (b) when the 2D gel image is newly stored, loading the 2D gel image and inputting an ID of the 2D gel image and an experimental condition for the 2D gel image; And (c) when modifying the existing 2D gel image without newly storing the 2D gel image, selecting the 2D gel image to be modified and modifying the corresponding data.

In order to achieve the above object, a web-based proteome analysis and management method according to the present invention includes: (a) selecting a search method; (b) inputting a keyword of proteome data to be searched if keyword search is selected as the search method; (c) responsive to the keyword, retrieving the proteome data from a first database in which experimental proteome data is stored and a second database in which a verified amount of reference proteome data is stored; (d) loading a two-dimensional gel image to be searched if image search is selected as the search method; (e) designating a location to be retrieved on the two-dimensional gel image; (f) retrieving proteome data corresponding to the designated location from the first and second databases; (g) when advanced search is selected as the search method, at least one of peptide mass fingerprinting, isoelectric point, molecular weight, and protein sequence information of the proteome data is taken as a search clue, and the proteome from the first and second databases is selected. Retrieving similar proteome data of the data; And (h) displaying the search results of steps (c), (f) and / or (g).

Hereinafter, with reference to the accompanying drawings will be described in detail a preferred embodiment of the present invention.

1 is a block diagram of a web-based proteome analysis and management system according to a preferred embodiment of the present invention. Referring to FIG. 1, the web-based proteome analysis and management system according to the present invention includes at least one client server 100a, 100b,..., 100z connected to the Internet 10, and the client server 100a, 100b on the web. , ..., 100z) is composed of a proteome analysis and management server 200 to provide a proteome analysis service. Proteome analysis and management server 200 interface 210, proteome identification 220, proteome search unit 230, proteome analysis unit 240, reference proteome database 250, experimental proteome database 260, data The management unit 270, the flat file conversion unit 280, and the XML configuration unit 290 are included. Prior to the description of the functions performed by each of these blocks, the functions performed by the proteome analysis and management system are schematically illustrated as follows.

FIG. 2 is a block diagram schematically illustrating functions performed in the proteome analysis and management system shown in FIG. 1. Referring to FIG. 2, the proteome analysis and management function 2000 performed by the proteome analysis and management system according to the present invention includes a proteome identification function 2200, a proteome search function 2300, a proteome analysis function 2400, And a data management function 2700.

The proteome search function 2300 performed by the proteome search unit 230 is divided into a keyword search function 3100, an image search function 3200, and an advanced search function 3400, and the advanced search function 3400 is again pI. / MW similarity search function 3420, peptide mass fingerprinting similarity search function 3440, and sequence similarity search function 3460. The proteome analysis function 2400 performed by the proteome analyzer 240 includes a protein expression profile analysis function 2410, an image comparison analysis function 2420, an advanced search result analysis function 2430, and a post-translational modification analysis function 2440. ) And protein interaction analysis function 2450. The data management function 2700 performed by the data manager 270 includes a data storage / modification / deletion function 2710, a flat file conversion function 2800, and an XML configuration function 2900.

Referring to Figures 1 and 2, look at the function of each block constituting the web-based proteome analysis and management system according to the present invention.

First, the interface 210 receives any one of experimental proteome data and a search clue from the client servers 100a, 100b,..., And 100z, and transmits a proteome analysis result and a proteome search result to the client server via the Internet 10. 100a, 100b, ..., 100z).

The data management unit 270 connected to the interface 210 includes a data storage / modification / deletion function 2710 that receives data from a user, stores it, modifies, or deletes it, a flat file converter 280, and XML configuration. The flat file conversion function 2800 and the XML configuration function 2900 which control the operation of the unit 290 are performed.

The flat file converter 280 converts the flat file of the reference proteome database 250 so that the reference proteome data stored in an unprocessed form is input in accordance with the database structure under the control of the data manager 270. . The XML configuration unit 290 configures the proteome data as an XML file so that the proteome data stored in the two databases 250 and 260 can be exchanged and integrated with data stored in other systems in response to the control of the data management unit 270. do. All database contents are managed through the operation of the data manager 270 as described above.

Here, the reference proteome database 250 is a protein sequence database in which a large amount of verified proteome related data is stored. Although there are various specialized databases that can be used as the reference proteome database 250, in the present invention, in addition to the protein sequence information, the function and structure of the protein, information on each domain, and post-translational modification of the protein Use a SWISS-PROT database that stores most of the information related to proteins, including information.

The experimental proteome database 260 is a database in which experimental proteome data calculated by experiments is stored, and examples thereof include rat liver aging proteome database. The process of constructing the experimental proteome database 260 is as follows.

When the experimental protein data is input by the user, it is input to the proteome identification part 220 through the data manager 270. The proteome identification unit 220, when a two-dimensional gel image, peptide mass fingerprinting, molecular weight, isoelectric point, and protein detailed information calculated in a laboratory are input, a protein identification decision is made to identify what the proteome is based on the information. Do this. If the protein is identified as any reference proteome data stored in the reference proteome database 250 by the proteome identification unit 220, the data manager 270 stores the protein data in the experimental proteome database 260. The entry number of the reference proteome database 250 corresponding thereto is stored. Thus, the experimental proteome database 260 is configured, and the experimental proteome database 260 and the reference proteome database 250 are connected to each other. When the experimental proteome database 260 is configured as described above, the proteome search unit 230 and the proteome analyzer 240 may search and analyze data stored in the experimental proteome database 260.

The proteome search unit 230 receives a keyword, two-dimensional gel image, peptide mass fingerprinting (PMF), isoelectric point (pI), molecular weight (MW), protein sequence information, and the like as a search clue from the user, and uses a keyword search function (3100). ), The image search function 3200 and the advanced search function 3400 are performed, and the specific data stored in the databases 250 and 260 is searched and retrieved. For example, when a predetermined search clue is input from the user, the proteome search unit 230 retrieves predetermined proteome data from the experimental proteome database 260 in response to the search clue, and stores detailed information of the retrieved proteome data. The detailed information of the proteome data retrieved from the reference proteome database 250 is extracted with reference to the entry number.

Proteome analysis unit 240, protein expression profile analysis function 2410, image comparison analysis function 2420, advanced search result analysis function (2430), post-translational modification analysis function (2440) and protein interaction analysis function (2450) Perform a proteome analysis function 2400 including a). The protein expression profile analysis function 2410 is a function of analyzing the expression pattern and similar expression pattern according to the experimental conditions of the protein obtained by two-dimensional electrophoresis. The image comparison analysis function 2420 is a function of comparing at least two or more two-dimensional gel images and analyzing differences therebetween. The advanced search result analysis function 2430 is a function of analyzing the protein by the advanced search results. The post-translational modification analysis function 2440 analyzes the difference between the protein data obtained by the experiment and the theoretical data of homologous proteins stored in the reference proteome database 250, thereby providing a basic information on the post-translational modification of the protein. It is a function to provide information. In addition, the protein interaction analysis function 2450 is a function of analyzing a characteristic exhibited by interacting with at least two proteins. By such various analysis functions, the total protein expressed in the cell is identified.

As described above, when the database is constructed, the data itself stored in the reference proteome database 250 is not stored in the experimental proteome database 260, and the entry number of the reference proteome database 250 in which the corresponding data is stored is stored. do. The data models of the experimental proteome database 260 and the reference proteome database 250 configured as described above are as follows.

FIG. 3 is a block diagram illustrating the information stored in the reference proteome database 250 and the experimental proteome database 260 shown in FIG. 1 and the relationship between the information. Referring to FIG. 3, the reference proteome database 250 includes reference database management information 251, bibliographic management information REFERENCE 252, Swiss-Plot management information SWISS_INFO 253, and comment management information COMMENTS 254. , Proteome sequence management information (SEQ_VALUE; 255), and proteome characteristic management information (FEATURE; 256). This information divides the basic data supported by specialized databases, such as Swiss-Plot, into categories, including Swiss-Plot Registration Number, Receipt Number, Protein Name, Gene Name, Species of Species, Classification of Individuals, and Organelles. , Keyword information, protein sequence number, and the like, a detailed description thereof will be omitted below.

Information stored in the experimental proteome database 260 includes gel image management information (L_IMAGE; 261) for managing a two-dimensional gel image generated by electrophoresis, and for each spot constituting the two-dimensional gel image. Spot management information (L_SPOT_INFO; 262) for managing information, protein management information (PROTEIN_INFO; 265) for managing detailed information on proteins corresponding to each spot, and expression management information (SPOT_INTENSITY) for managing expression data for spots 267), quantitative management information (SPOT_QUANTITY) 268 that manages the expression level graph and information showing the change process for the spot, and modification management information (MOD_INFO; 269) that manages information on whether or not the proteome is modified.

Among the information stored in the experimental proteome database 260, gel image management information L_IMAGE 261 is configured as shown in Table 1 below.

TABLE 1

Column name Type overview Type name Length Scale Nulls GEL_ID SYSIBM VARCHAR 10 0 No FILE_NAME SYSIBM VARCHAR 100 0 No EXP_CON1 SYSIBM VARCHAR 20 0 No EXP_CON2 SYSIBM BIGINT 8 0 No REF_MAP SYSIBM VARCHAR 5 0 No

Referring to [Table 1], gel image management information (L_IMAGE; 261) includes a gel number (GEL_ID), a gel image file name (FILE_NAME), a first experimental condition (EXP_CON1), a second experimental condition (EXP_CON2), and a corresponding image. Information indicating whether or not is a reference map is included.

[Table 2] below shows spot management information (L_SPOT_INFO; 262) for managing information on each spot constituting the 2D gel image.

TABLE 2

Column name Type overview Type name Length Scale Nulls RLP_ID SYSIBM VARCHAR 10 0 No GEL_ID SYSIBM VARCHAR 10 0 No SPOT_LOCA_X SYSIBM INTEGER 4 0 No SPOT_LOCA_Y SYSIBM INTEGER 4 0 No

Referring to [Table 2], the spot management information (L_SPOT_INFO; 262) includes a protein number (RLP_ID), a gel number (GEL_ID), a spot X coordinate (SPOT_LOCA_X), and a spot Y coordinate (SPOT_LOCA_X) information for the spot. do. Here, the protein number (RLP_ID) for the spot is an ID set arbitrarily for the spot, and can be freely made and used for each use without overlapping. As will be described in detail below, image search is enabled by setting the spot X coordinate (SPOT_LOCA_X) and the spot Y coordinate (SPOT_LOCA_X).

Table 3 shows protein management information (PROTEIN_INFO; 265) for managing experimental proteome data corresponding to each spot.

TABLE 3

Column name Type overview Type name Length Scale Nulls RLP_ID SYSIBM VARCHAR 10 0 No SWISS_ID SYSIBM VARCHAR 10 0 No MW_EXP SYSIBM DECIMAL 10 5 Yes PI_EXP SYSIBM DECIMAL 10 5 Yes PMF_EXP SYSIBM VARCHAR 500 0 Yes AGE_REPORT SYSIBM VARCHAR 500 0 Yes

Referring to [Table 3], the protein management information (PROTEIN_INFO; 265) is a protein number (RLP_ID), Swiss-prote entry number (SWISS_ID), experimental molecular weight (MW_EXP), experimental isoelectric point (PI_EXP), experimental peptide mass fingerprinting ( PMF_EXP) and report information about aging (AGE_REPORT). Here, the Swiss-Plot entry number (SWISS_ID) is information indicating where detailed data on the protein (RLP_ID) obtained by the experiment is stored in the reference proteome database (eg, Swiss-Plot) 250. By the configuration of the protein management information PROTEIN_INFO 265, the experimental proteome database 260 and the reference proteome database 250 constructed by the experiment are connected to each other.

[Table 4] shows the expression management information (SPOT_INTENSITY; 267) for managing the expression data for the spot.

TABLE 4

Column name Type overview Type name Length Scale Nulls INTENSITY_ID SYSIBM BIGINT 8 0 No RLP_ID SYSIBM VARCHAR 10 0 No GEL_ID SYSIBM VARCHAR 10 0 No QUAN_DATA SYSIBM VARCHAR 100 0 Yes

Referring to [Table 4], the expression management information (SPOT_INTENSITY; 267) includes an expression number (INTENSITY_ID), a protein number (RLP_ID), a gel number (GEL_ID), and expression quantitative numerical information (QUAN_DATA).

[Table 5] shows quantitative management information (SPOT_QUANTITY; 268) for managing information showing the expression level graph and the change process for the spot.

TABLE 5

Column name Type overview Type name Length Scale Nulls RLP_ID SYSIBM VARCHAR 10 0 No GRAPH_IMG SYSIBM VARCHAR 100 0 Yes GEL_IMG SYSIBM VARCHAR 100 0 Yes

Referring to [Table 5], the quantitative management information (SPOT_QUANTITY; 268) includes a protein number (RLP_ID), expression level graph (GRAPH_IMG) and expressed gel image information (GEL_IMG).

Table 6 shows modification management information (MOD_INFO) 269 that manages information on whether a proteome is modified.

TABLE 6

Column name Type overview Type name Length Scale Nulls MOD_ID SYSIBM BIGINT 8 0 No RLP_ID SYSIBM VARCHAR 10 0 No MOD_KIND SYSIBM VARCHAR 50 0 Yes DESCRIPTION SYSIBM VARCHAR 500 0 Yes

Referring to [Table 6], the modification management information (MOD_INFO) 269 includes a modification number (MOD_ID), a protein number (RLP_ID), a modification type (MOD_KIND), and modification description information (DESCRIPTION). Here, the deformation description information (DESCRIPTION) is information that allows the experimenter to freely write his or her view. Referring to FIGS. 4 and 5, the construction method of the experimental proteome database 260 having the above configuration will be described as follows.

4 is a flowchart illustrating a data storage / modification / deletion method performed by the data management unit 270 shown in FIG. 1, a method of storing data to be stored in the experimental proteome database 260, and an experimental proteome database 260. It shows how to modify existing protein data stored in.

Referring to FIG. 4, it is first determined whether to newly store the 2D gel image (step 2711). If it is determined that the 2D gel image is to be newly stored, the 2D gel image is loaded (step 2712), the ID of the 2D gel image is input (step 2713), and the experimental conditions for the 2D gel image are input. (Step 2714). In addition, when it is determined that the existing two-dimensional gel image stored in the experimental proteome database 260 is modified without newly storing the two-dimensional gel image, first, a plurality of two stored in the experimental proteome database 260 may be used. The 2D gel image is displayed (step 2716) to select a 2D gel image to be modified (step 2725), and then the data of the selected 2D gel image or the corresponding gel image is modified (step 2718). If such storage or modification has been performed on the two-dimensional gel image, any spot constituting the two-dimensional gel image is selected (step 2721). Here, any spot designated on the two-dimensional gel image corresponds to any protein constituting the two-dimensional gel image.

If any spot constituting the two-dimensional gel image is selected, it is determined whether proteomic data corresponding to the selected spot is newly stored (step 2722). If it is determined that the proteome data corresponding to the selected spot is to be newly stored, the experimental data for the selected spot is input (step 2723). If it is determined that the existing spot data stored in the experimental proteome database 260 is modified without newly storing proteome data corresponding to the selected spot, the spot data is corrected (step 2725). By this method data for the two-dimensional gel image and any spots constituting it are stored or modified.

The new experimental protein data to be stored in the experimental proteome database 260 input to the data management unit 270 by the method shown in FIG. 4 is input to the proteome identification unit 220. The proteome identification unit 220 performs the protein identification decision by the method shown in FIG. 5, and stores the experimental protein data and the protein identification decision result in the experimental proteome database 260 according to the protein identification decision result. Detailed method for this is as follows.

Referring to FIG. 5, the proteome identification unit 220 first receives experimental data from the data management unit 270 (step 2210), and performs an advanced search for the data to obtain data necessary for making protein identification decisions. (Step 2220). Then, the protein identification decision process is performed based on the advanced search results. At this time, if it is determined that protein identification has been performed on the input experimental data (step 2230), the data management unit 2670 stores the experimental protein data and its identification result in the experimental proteome database 260 (step 2240). ). This establishes an experimental proteome database 260.

The experimental proteome database 260 constructed by the above method can be used for keyword search, image search, protein expression pattern search, and advanced search using these search results. In particular, the experimental proteome database 260 has a feature that is searched in association with the reference proteome database 250 when retrieving proteome data. Proteome search method according to the present invention is as follows.

6 is a diagram illustrating an example of a search initial screen 300 for proteome analysis according to an exemplary embodiment of the present invention. Referring to FIG. 6, a search initial screen 300 for proteome analysis according to the present invention includes a keyword search 310, an image search 320, and an advanced search 340 as a graphic user interface for data search. ) A menu is provided. Here, the advanced search menu 340 is divided into an isoelectric point / molecular weight similarity search menu 342, a peptide mass fingerprinting similarity search menu 344, and a protein sequence similarity search menu 346.

FIG. 7 is a flowchart illustrating a proteome search method 2300 performed by the proteome search unit 230 shown in FIG. 1. Referring to FIG. 7, one of a keyword search method, an image search, and an advanced search is selected in operation 3010.

In this case, when the keyword search is selected, a keyword to be searched is input from the user (step 3110), the protein information based on the input keyword is searched (3120), and the search result is displayed (step 3500). If the image search is selected in step 3010, the image to be searched is selected from the reference images stored in the database, and then the 2D gel image to be searched is loaded (3210), and the position of the protein to be searched is determined by the user. It is designated on a two-dimensional gel image (step 3220). In this case, the present invention provides an image magnification function in which a predetermined area is enlarged and displayed based on the position specified in step 3220 to designate a more accurate position. This feature allows the user to perform more accurate positioning.

Subsequently, after the protein information corresponding to the designated location is searched (3230), the search result is displayed (step 3500). If the advanced search is selected in step 3110, the procedure proceeds to step 3410, and the detailed search method for the advanced search is selected. In this case, when the isoelectric point / molecular weight (pI / MW) similarity search is selected as the detailed search method, the isoelectric point / molecular weight (pI / MW) data is input from the user (step 3421), and the pseudo isoelectric point / molecular weight (pI / MW) is obtained. After searching for the proteins having (step 3342), the search results are displayed (step 3500). When the peptide mass fingerprinting similarity search is selected as a detailed search method in step 3410, the user receives peptide mass fingerprinting (PMF) data from the user (3441), and then searches for proteins having similar peptide mass fingerprinting (step 3344). In operation 3500, the search result is displayed. When sequence similarity search is selected as a detailed search method in step 3410, the user receives protein sequence information from the user (step 3651), searches for proteins having similar sequences (step 3346), and displays the search result (3500). step).

By this method, the proteome analysis and management system according to the present invention can obtain detailed data of proteins through keyword and image search, and analyze isoelectric point, molecular weight, peptide mass fingerprinting, or protein sequence information through advanced search. Thus, proteins having similar characteristics can be extracted.

8A to 8C are diagrams illustrating a keyword search screen executed by the method shown in FIG. 7 and the search results thereof when the keyword search menu 310 shown in FIG. 6 is selected. When a user inputs proteome related central words such as protein isoelectric point, molecular weight, protein name, and aging report data in the keyword search screen as shown in FIG. 8A, the experimental proteome database 260 as shown in FIG. The search results and the search results in the reference proteome database 250 are displayed in a table form, respectively. In this case, when a user clicks on an arbitrary protein number displayed on the screen, proteome related information such as more detailed property information, sequence, comments, references, species information, etc., including a two-dimensional gel image is displayed. ) Is displayed as shown in FIG. 8C.

9A and 9B illustrate an image search screen executed by the method shown in FIG. 7 when the image search menu 320 shown in FIG. 6 is selected. When the user selects an image to be searched as shown in FIG. 9A and designates an arbitrary position included in the image, a proteome search corresponding to the x-axis and y-axis coordinates of the corresponding position is performed. If there is no spot information assigned to the corresponding location, an image enlarged around the corresponding location is displayed as shown in FIG. 9B, so that the user can accurately specify the location to be searched. When the x-axis and y-axis positions of the corresponding spots are determined by designating the search position as described above, a search for a proteome corresponding to the x- and y-axis coordinates of the spot is performed, and the search result is output as shown in FIG. 8B. . Although not shown in the drawing, when the user clicks on any result data, as shown in FIG. 8C, more detailed proteome related information, including a two-dimensional gel image, is displayed in the reference proteome database (not shown). 250 is retrieved and displayed.

10A and 10B are diagrams illustrating a protein expression pattern search screen executed by the method shown in FIG. 7 and a search result thereof when the protein expression pattern search menu 330 shown in FIG. 6 is selected. Referring to FIG. 10A, when inputting experimental conditions such as a time zone and a dietary time of a protein expression change pattern to be searched on the initial screen displayed at the bottom of the figure, the time-dependent protein expression change pattern and dietary status are shown in FIG. 10B. The resulting protein expression change pattern is displayed in tabular form. Although not shown in the drawing, the search results shown in FIG. 10B also include more detailed proteome-related information, including a two-dimensional gel image, as shown in FIG. 8C when the user clicks on arbitrary result data. It is retrieved from the reference proteome database 250 and displayed.

11A to 11C are diagrams showing an advanced search screen executed by the method shown in FIG. 7 and the search results thereof when the advanced search menu 340 shown in FIG. 6 is selected. Advanced searches are divided into isoelectric point / molecular weight (pI / MW) similarity searches (342), peptide mass fingerprinting similarity searches (344) and sequence similarity searches (346), depending on input values. As shown in FIGS. 11A to 11C, when each variable required for an advanced search is input, an advanced search 342, 244, or 346 corresponding to each variable is performed. And, although not shown in the drawing, the advanced search results according to FIGS. 11A-11C are also related to more detailed proteome, including two-dimensional gel images, as shown in FIG. 8C when the user clicks on any result data. The information is retrieved from the reference proteome database 250 and displayed.

In the above, as an embodiment of the present invention, an experimental proteome database was constructed using a Swiss-prot database as a reference proteome database, and a web-based proteome analysis and management system integrating search and analysis functions of two databases was specifically illustrated. In addition, various protein sequence databases may be applied to the present invention, and the present invention may be applied to a local environment rather than a web environment.

The invention can also be embodied as computer readable code on a computer readable recording medium. The computer-readable recording medium includes all kinds of recording devices in which data that can be read by a computer system is stored. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, and the like, and may also be implemented in the form of a carrier wave (for example, transmission over the Internet). Include. The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.

As described above, according to the web-based proteome analysis and management system according to the present invention, the storage, retrieval and analysis functions of the database and the existing database for the proteome research results which are separated from each other can be efficiently integrated. Thus, database of experimental data and protein search and analysis can be easily performed.

Claims (20)

A first database in which verified quantities of reference proteome data are stored; A second database in which experimental proteome data calculated by the experiment is stored; An interface that accepts one of experimental proteome data and a search clue from a user; Data management means for controlling an input / output function of data for the first and second databases; Proteome identification for performing protein identification decisions to identify which protein the experimental proteome data is; A proteome search unit for retrieving predetermined proteome data from the second database in response to any one of experimental proteome data and the search clue, and extracting detailed information of the retrieved proteome data from the first proteome database; And Proteome analysis and management system characterized in that it comprises a proteome analyzer for extracting the characteristics of the proteome by analyzing the search results. The method of claim 1, The interface receives any one of the experimental proteome data and the search condition from at least one server connected through a communication network, and transfers the data to one of the data management means, the proteome search unit, and the proteome analyzer, and searches for the proteome search. Proteome analysis and management system characterized in that for transmitting the search results of the unit and the analysis results of the proteome analysis unit to the server through the communication network. The method of claim 1, wherein the data management means A data manager which receives the experimental proteome data from the interface and controls a storage / modification / deletion function of the proteome data stored in the second database; A flat file conversion unit converting the flat file of the first database so that the reference proteome data stored in the form of raw data in the first database is input in accordance with the second database structure; And And an XML constructing unit configured to construct the proteome data into an XML file so that the proteome data stored in the first and second databases can be exchanged and integrated with data stored in another system. The method of claim 1, And the first database includes management information, reference management information, comment management information, proteome sequence management information, and proteome characteristic management information for the reference proteome data. The method of claim 1, The second database includes two-dimensional gel image management information generated by electrophoresis, respective protein position management information constituting the two-dimensional gel image, enlarged image information of the image, and experimental proteome data corresponding to each of the positions. A proteome analysis and management system comprising management information, proteome expression management information, proteome quantitative management information, and proteome modification management information. The method of claim 5, And the management information of the experimental proteome data includes an entry number of the first database in which reference proteome data related to the experimental proteome is stored. The method of claim 1, The proteome search unit includes: a keyword search for searching for predetermined proteome data in response to a keyword input from the user, an image search for searching for predetermined proteome data in response to a two-dimensional gel image input from the user, and the user from the user. A proteome analysis and management system comprising performing an advanced search for retrieving similar proteome data in response to at least one of input peptide mass fingerprinting, isoelectric point, molecular weight and protein sequence information. The method of claim 7, wherein The proteome analysis unit, protein expression profile analysis for analyzing the expression pattern and similar expression pattern for each experimental condition of the proteome data, image comparison analysis for comparing at least two or more of the two-dimensional gel image and analyzing the difference between the images, the Advanced search result analysis to analyze the characteristics of the protein in response to the advanced search results, by analyzing the difference between the theoretical data of the homologous protein of the experimental proteome data and the experimental proteome data stored in the first database, A proteome analysis and management system comprising post-translational modification analysis for analyzing whether or not post-translational modification of the proteome and protein interaction analysis for analyzing the characteristics exhibited by interaction of at least two proteins. (a) inputting experimental proteome data; (b) retrieving similar proteome data of the proteome data with reference to peptide mass fingerprinting, isoelectric point, molecular weight and protein sequence information for the proteome data; (c) performing protein identification decisions on the proteome data in response to the search results; And and (d) storing the experimental proteome data and the identification results in a second database in which the experimental proteome data is stored. (a) determining whether to newly store a two-dimensional gel image generated by electrophoresis in a database; (b) when the 2D gel image is newly stored, loading the 2D gel image and inputting an ID of the 2D gel image and an experimental condition for the 2D gel image; And (c) when modifying the existing 2D gel image without newly storing the 2D gel image, selecting the 2D gel image to be modified and modifying the corresponding data How to store and modify experimental proteome data in analysis and management systems. The method of claim 10, wherein the experimental proteome data storage and modification method comprises: (d) determining whether to newly store experimental proteome data corresponding to an arbitrary position of the two-dimensional gel image; (e) inputting experimental proteome data for the selected location when newly storing experimental proteome data corresponding to the location; And (f) web-based proteome analysis and management system, further comprising modifying the experimental proteome data when modifying the existing experimental proteome data without newly storing the experimental proteome data corresponding to the location. Method for storing and modifying experimental proteome data. (a) selecting a search method; (b) inputting a keyword of proteome data to be searched if keyword search is selected as the search method; (c) responsive to the keyword, retrieving the proteome data from a first database in which experimental proteome data is stored and a second database in which a verified amount of reference proteome data is stored; (d) loading a two-dimensional gel image to be searched if image search is selected as the search method; (e) designating a location to be retrieved on the two-dimensional gel image; (f) retrieving proteome data corresponding to the designated location from the first and second databases; (g) when advanced search is selected as the search method, at least one of peptide mass fingerprinting, isoelectric point, molecular weight, and protein sequence information of the proteome data is taken as a search clue, and the proteome from the first and second databases is selected. Retrieving similar proteome data of the data; And (h) displaying the search results of steps (c), (f) and / or (g). The method of claim 12, wherein step (e) (e-1) expanding a predetermined area around the designated position; And (e-2) proteome analysis and management method further comprising the step of specifying a position to be searched on the enlarged two-dimensional gel image. The method of claim 12, wherein the proteome analysis and management method comprises: (i) protein expression profile analysis for analyzing expression patterns and similar expression patterns according to experimental conditions of the proteome data; image comparison analysis for comparing at least two or more two-dimensional gel images and analyzing differences between the images; Advanced search result analysis to characterize the protein in response to the results, analyzing the difference between the experimental proteome data and the theoretical data of the homologous proteins of the experimental proteome data stored in the first database, And a proteome analysis step of performing any one of post-translational modification analysis for analyzing post-translational modification, and protein interaction analysis for analyzing characteristics exhibited by interaction of at least two proteins. How to manage. The method of claim 12, And the keyword, the two-dimensional gel image, and the search clue are input through at least one server connected through a communication network, and the search result is provided to the server through the communication network. The method of claim 12, The advanced search method includes isoelectric point / molecular weight similarity search, peptide mass fingerprinting similarity search, and protein sequence similarity search. The method of claim 12, The first database includes two-dimensional gel image management information generated by electrophoresis, respective protein position management information constituting the two-dimensional gel image, enlarged image information of the image, and experimental proteome data corresponding to each of the positions. A proteome analysis and management method comprising management information, proteome expression management information, proteome quantitative management information, and proteome modification management information. The method of claim 17, And the experimental proteome data management information includes an entry location of the second database in which reference proteome data associated with the experimental proteome is stored. The method of claim 12, And the second database includes management information, reference management information, comment management information, proteome sequence management information, and proteome characteristic management information on the reference proteome data. A computer-readable recording medium having recorded thereon a program for executing the method of any one of claims 9 to 19 on a computer.