KR20040064763A - Client/server based workbench system and method for expressed sequence tag analysis - Google Patents

Abstract

PURPOSE: A system and a method for analyzing an EST(Expressed Sequence Tag) sequence based on a client/server are provided to efficiently integrate gene sequence databases and sequence analysis tools, and analogize a function of the EST sequence by extracting the similar candidate gene/protein domain information from a sequence search result and using the extracted data. CONSTITUTION: An I/O(Input/Output) manager(240) receives the EST sequence data calculated by an experiment of a user. A sequence input part(250) converts the EST sequence data into a predetermined format and stores it to the first database(220). Annotation analyzers(260,270) search the similarity/protein domain between the EST sequence data stored in the first database and the sequence data stored in the second database(230), which is stored the verified genes and the protein sequence data, and store at the result to the first database. An analysis result searcher(280) searches the data stored in the first database by responding to a search key inputted from the user.

Description

Client / server based workbench system and method for expressed sequence tag analysis}

The present invention relates to a genome analysis system, and more particularly, to a system and a method for storing, analyzing, and retrieving sequence and sequencing information obtained by an EST (Expressed Sequence Tag) sequencing method.

EST is an abbreviation of Expressed Sequence Tag, and refers to a fragment of a gene expressed as mRNA (messenger RNA) in the original genome sequence to function in life. In general, in the prokaryotic genome, introns and exons are not separated, and the genome sequence is directly transcribed into mRNA to form proteins. In contrast, each cell in a eukaryotes has the same genome and different patterns of proteome. That is, the eukaryote undergoes post-transcriptional modifications such as introns that are separated from RNA sequences in time and space, and then modified mRNAs are generated. Such mRNA can be experimentally extracted in large quantities in the form of a complementary DNA (cDNA) library using reverse transcription, and a fragment of the cDNA sequence is called EST. Thus, studying ESTs in eukaryotes is an effective technique for identifying genes that function compared to studying the entire genome.

ESTs produced in this way are stored and analyzed by the experimenter. At this time, since the amount of the object to be analyzed is very large, an effective search of the results of the EST study requires an integrated search between the database and the existing sequence data in addition to the database (DB) of the study results. However, existing sequence information is provided separately from each other by species and tissues of organisms, and tools for analyzing them are also separated and developed and maintained at different sites according to an analysis purpose. As such, since the storage, analysis, and retrieval functions of the EST data are operated separately under different environments, there is a difficulty in using them.

The technical problem to be achieved by the present invention is to provide a client / server-based EST analysis system that efficiently integrates the gene sequence database and sequencing tools that exist apart from each other.

Another technical task of the present invention is to extract candidate gene and protein domain information having similarity from sequence search result data obtained through sequence ID search, keyword search, and functional category keyword search, and use the extracted data. By providing a client / server based EST analysis system that can infer the function of the EST sequence.

Another technical problem to be achieved by the present invention is a system that facilitates mass data verification and checks the process of mass analysis through a hit list and a history map, which is an overall result viewing function for effectively viewing mass data analysis results. To provide.

Another technical problem to be achieved by the present invention is to provide a data management system consisting of project management, database management, user management, password management so that large-scale data management by user project and database, by user.

Another object of the present invention is to provide a computer-readable recording medium having recorded thereon a program for executing the method on a computer.

1 is a block diagram of a client / server based EST analysis system in accordance with a preferred embodiment of the present invention.

2 and 3 are block diagrams showing the information stored in the EST sequence and analysis result database shown in FIG. 1 and the relationships between the information.

FIG. 4 is a diagram illustrating a menu on a client interface for executing an EST sequence analysis program executed in the EST sequence analysis server illustrated in FIG. 1, and submenus thereof.

FIG. 5 is a diagram illustrating a database creation screen executed when the database creation menu illustrated in FIG. 4 is selected.

FIG. 6 is a data input screen executed when the data input menu shown in FIG. 4 is selected.

FIG. 7 is a diagram illustrating a BLAST search screen executed when the BLAST search menu illustrated in FIG. 4 is selected.

8 and 9 are diagrams showing the results of the BLAST search performed by FIG. 7 and the alignment results thereof.

FIG. 10 is a diagram illustrating a translation result performed when the translation menu illustrated in FIG. 4 is selected.

11 and 12 are diagrams showing the results of the PROSITE search performed when the PROSITE menu shown in FIG. 4 is selected and detailed information thereof.

FIG. 13 is a diagram illustrating a result of a PRINTS search performed when the PRINTS menu illustrated in FIG. 4 is selected.

FIG. 14 is a diagram illustrating an RPS-BLAST search screen performed when the RPS-BLAST menu shown in FIG. 4 is selected.

15 and 16 illustrate an RPS-BLAST search result and an alignment result thereof performed by FIG. 14.

17 is a flowchart showing a method for EST sequence analysis and annotation database construction according to a preferred embodiment of the present invention.

18 and 19 are views showing an annotation data search screen executed when the annotation data search menu, which is a submenu of ID search menu shown in FIG. 4, is selected and the search results thereof.

20 and 21 are diagrams illustrating a keyword search screen executed when the keyword search menu shown in FIG. 4 is selected, and a search result thereof.

22 and 23 are diagrams illustrating a function category keyword search screen executed when the function category keyword search menu shown in FIG. 4 is selected, and a search result thereof.

FIG. 24 illustrates a hit list screen executed when the hit list search menu illustrated in FIG. 4 is selected.

FIG. 25 is a diagram illustrating a Remarkable Hit search screen executed when the Remarkable Hit search menu shown in FIG. 4 is selected.

FIG. 26 illustrates a history map screen executed when the history map menu illustrated in FIG. 4 is selected.

27 is a flowchart showing a sequence retrieval method according to a preferred embodiment of the present invention.

In order to achieve the above object, the EST analysis system according to the present invention comprises: an input / output manager for receiving Expressed Sequence Tag (EST) sequence data calculated by an experiment from a user; A sequence input unit which converts the EST sequence data into a predetermined format and stores it in a first database; Perform similarity search and protein domain search between the EST sequence data stored in the first database and the sequence data stored in a second database in which verified large amounts of gene and protein sequence data are stored, and the search results are stored in the first database. An annotation analysis unit for storing; And an analysis result search unit configured to perform a search on data stored in the first database in response to a search clue input from a user.

In order to achieve the above object, the EST sequence analysis method according to the present invention includes the steps of: (a) receiving the EST (Expressed Sequence Tag) sequence data calculated by an experiment from a user; (b) converting the EST sequence data into a predetermined format and storing it in a first database; (c) perform a similarity search and a protein domain search between the EST sequence data stored in the first database and data stored in a second database in which verified large amounts of gene and protein sequence data are stored; Storing in a database; And (d) performing a search on the data stored in the first database in response to a search clue input from the user.

In order to achieve the above object, an EST sequence analysis and database construction method according to the present invention comprises: (a) receiving a EST (Expressed Sequence Tag) sequence data generated by an experiment from a user to construct a first database; (b) performing a similarity search between the EST sequence data stored in the first database and data stored in a second database in which verified large amounts of gene and protein sequence data are stored and a protein domain search for the EST sequence; (c) determining whether the EST sequence has been identified with any EST sequence stored in the second database based on the sequence similarity search result and the protein domain search result performed in step (b). ; (d) analyzing the necessary information in the gene contents of the second database corresponding to the EST sequence when the EST sequence is identified, and storing the analysis result in the first database; And (e) storing whether the steps (a) and (b) are performed in a history table of the first database.

In order to achieve the above object, the EST sequence retrieval method according to the present invention, in response to a search clue input from a user, performs one of an ID retrieval and a keyword-specific retrieval on a first database storing EST sequence analysis results. Extracting genetic information and protein domain information corresponding to the retrieved EST sequence data; (b) selecting one of a Remarkable Hit search and a function category keyword search by an advanced search method; (c) extracting and displaying a top result from the results extracted in step (a) when the remarkable hit search is selected as the advanced search method in step (b); And (d) when the function category keyword search is selected as the advanced search function in step (b), performing a function-specific search for the category to which the result extracted in step (a) belongs, and showing the search result. Characterized in that it comprises a step.

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 client / server based EST analysis system in accordance with a preferred embodiment of the present invention. Referring to FIG. 1, an EST analysis system according to the present invention includes at least one client 100 connected to a network 10 and an EST analysis server 200 that provides an EST analysis service. The EST analysis server 200 includes an EST analysis unit 210, an EST sequence and analysis result database 220, and a reference database 230.

First, the EST sequence and analysis result database 220 is a database for storing the EST sequence data generated by the experiment, the sequence similarity search result, and the protein domain search result, and stores the EST sequence data generated by the experiment. A sequence database 221, an annotation database 222 storing sequence similarity search results and protein domain search results for each EST sequence data, and a management database 223 storing information necessary for project management, user management, and database management It consists of

The reference database 230 is a gene sequence database in which a large amount of verified gene and protein sequences are stored. The reference database 230 is largely a database for searching a basic local alignment search tool (BLAST) 231 and a database for searching a domain ( 232).

The BLAST search database 231 is a database composed of a certain type (for example, formatDB type), and a UniGene, StackDB, RefSeq, TIGR database, etc. having gene sequence information and information on a gene's function may be used. In addition, it is possible to add a database for BLAST search that matches the species of the input sequence.

In addition, the domain search database 232 is a database storing information about each domain of the protein, and includes a database of protein families and domains (PROSITE) database 233, a protein motif fingerprint (PRINTS) database 234, and protein (PFAM). family (Simple Modular Architecture Research Tool) database (235). Here, the PROSITE database 233 is a protein database provided by the ExPASy WWW server of the Swiss Institute of Bioinformatics (SIB). It is a database of biologically meaningful patterns from the protein sequences in the existing Swiss-Prot database, collected by patterns, and used to predict the function of new protein sequences. The PRINTS database (234) is a database for 'fingerprint' multiple alignments (ordered blocks) from the OWL protein database, and the PFAM / SMART database (235) is based on a Swiss-Prot / TrEMBL protein database. A module database is used to align new protein sequences and verify their function using HMM (hidden Markov model) PSSMs obtained from seed alignment. The difference between these databases 233, 234, 235 is that the format in which the data is represented, i.e. a general text pattern, multiple alignment, profile, or hidden Markov models (HMM). ) And so on.

The EST analyzer 210 includes an input / output manager 240, a sequence input unit 250, a sequence annotation analyzer 260, a protein annotation analyzer 270, and an analysis result search unit 280. The EST analyzer 210 performs a similarity search (ie, a BLAST search) and a protein domain search on the EST sequence data input from the input / output manager 240 and from the input / output manager 240 based on the search result. It is determined whether the input EST sequence data has been identified. As a result of the determination, when the corresponding EST sequence data is identified, the information of the similar gene obtained by the search is parsed and stored in the EST sequence and analysis result database 220. Then, the data stored in the EST sequence and analysis result database 220 is searched through the analysis result search unit 280. Detailed configuration and operation of the EST analysis unit 210 for performing such an operation is as follows.

First, the input / output manager 240 receives the EST sequence data from the client 100 so that the EST analysis unit 210 can perform the EST analysis operation, and the EST sequence analysis result process performed by the EST analysis unit 210 is described above. Output to the client 100. Then, the search clue necessary for the search for the EST sequence analysis result is accepted, and the result of the EST sequence analysis according to the search clue is output to the client 100.

The format of the EST sequence data input through the input / output manager 240 supports the ABI (Application Binary Interface) file format and the FASTA file format. The FASTA file format is the most commonly used file format of bioinformatics programs. It is used to indicate the name (or description) of a particular sequence and the contents of the sequence itself.

The sequence input unit 250 reads the ABI file 251 inputted through the input / output manager 240 and converts the sequence into a sequence, converts the converted sequence or FASTA sequence 252 into a predetermined data format, and converts the EST sequence database 221. ). Then, the redundancy of the EST sequences is confirmed, and linkable EST sequences are clustered using the PHRAP program. In addition, the sequence input unit 250 stores project management information and user management information input through the input / output manager 240 in the management database.

The sequence annotation analyzer 260 accepts the sequence information Seq stored in the EST sequence database 221 and performs a similarity search on the EST sequence such as BLASTn and BLASTx.

Here, the BLASTn search is a BLAST search function that performs a comparison between the base sequences, and the BLASTx search is a BLAST search function that converts the input base sequence into six frames and compares it with the reference database 230. The sequence annotation analysis unit 260 performs the similarity search as described above, and identifies which gene sequence of the reference database 230 is known that the corresponding EST sequence is similar, and the result (gene) of the annotation database (222) Store in

The protein annotation analyzer 270 accepts the sequence information Seq stored in the EST sequence database 221 and uses the domain search database 232 included in the reference database 230 for the protein domain of the EST sequence. Regular expression search (PROSITE), protein domain fingerprint pattern search (PRINTS), and protein profile search (PFAN / SMART). The domain search result (domain) for the corresponding EST sequence is stored in the annotation database 222.

At this time, the EST sequence and analysis result database 220 does not take and store the data itself stored in the reference database 230 at the time of constructing the database, and analyzes the search result to provide only necessary information (for example, entry number, Gene title, E-value (Expect value), score (score, etc.) is extracted and stored. Therefore, data storage and retrieval are efficiently performed. The data model of the EST sequence and analysis result database 220 configured as described above will be described in detail with reference to FIGS. 2 and 3.

The analysis result search unit 280 retrieves the EST data corresponding to the search clue from the EST sequence and the analysis result database 220 in response to the search clue input from the input / output manager 240, and retrieves the retrieved data from the input / output manager ( Through the 240 to the client 100 side.

As such, the EST analysis unit 210 of the EST analysis server 200 performs processing on the EST analysis and search query, and the client 100 monitors the progress of the EST analysis performed by the EST analysis server 200. At the same time, the entire and detailed parts of the search result can be provided through the network 10. At this time, the user can input a large amount of EST sequences into the system and perform the necessary search conveniently and simply through the GUI (Graphic User Interface). Can be.

As described above, the EST analysis system according to the present invention has a GUI for placing the necessary search target database (ie, EST sequence and analysis result database 220) and analysis tool (ie, reference database 230) on the server 200. Through the client 100 selectively performs a search for the required database. The search results are stored in a server by forming a relational database (RDB) and used for analysis. In addition, all relevant data is localized to enhance the security of the research results. In this case, since the database and search tool necessary for the EST analysis are installed only in one server 200, all the analysis is performed in the server 200, thereby reducing the burden on the client 100.

2 and 3 are block diagrams showing the information stored in the EST sequence and analysis result database 220 shown in FIG. 1 and the relationship between the information. 2 shows a detailed configuration of the EST sequence database 221 and the annotation database 222, and a detailed configuration of the management database 223 is shown in FIG.

First, referring to FIG. 2, the EST sequence database 221 in which the EST sequence information generated by the experiment is stored may include an ABI sequence management information table 2211 (hereinafter referred to as an ABI table) and a sequence clone management information table 2212 (hereinafter referred to as an ABI table). The CLONE table). The ABI table 2211 stores the ABI sequence related information that manages the original EST sequence generated by the sequencing experiment, and the CLONE table 2212 assembles the sequences and then contigs and contigs. The reads and the singlet constituting the read are separated and stored. Contigs are the post-assembly sequence consisting of EST reads linkable with overlapping ESTs. Information stored in the ABI table 2211 is shown in Table 1 below.

Column name Type name Length Nulls ABI_ID VARCHAR 40 NO SEQ_LEN INT 10 YES SEQ TEXT YES CONTIG_NO VARCHAR 20 YES START_POS INT 10 YES END_POS INT 10 YES TRIM ENUM YES TRIMPOS VARCHAR 12 YES

Referring to Table 1, the ABI table 2211 includes an ABI clone number (ABI_ID), a sequence length (SEQ_LEN), a sequence (SEQ), a contig number (CONTIG_NO), and a start position of reads constituting a contig. (START_POS), the end position of the Reads constituting the contig (END_POS), whether or not the region having low sequence quality (TRIM) was cut out, and the TRIM position (TRIMPOS) information on the sequence. Table 2 below shows information stored in the CLONE table 2212.

Column name Type name Length Nulls NAME VARCHAR 20 YES LIBRARY VARCHAR 50 YES DB_LINK VARCHAR 10 YES ORGANISM VARCHAR 50 YES SEQ_LEN INT 10 YES SEQ TEXT YES ID VARCHAR 40 NO KNOWN SET YES REF_ID VARCHAR 20 YES PATTERN ENUM YES PRINTS ENUM YES TRIMPOS VARCHAR 12 YES CONTIG ENUM YES TRANS1 TEXT YES TRANS2 TEXT YES TRANS3 TEXT YES TRANS4 TEXT YES TRANS5 TEXT YES TRANS6 TEXT YES ESTSCAN TEXT YES ABI_ID VARCHAR 40 YES RPSBLAST ENUM YES

Referring to [Table 2], the CLONE table 2212 includes the name of the EST sequence (NAME), the source cDNA library information of the EST (LIBRARY), the external link database list (DB_LINK), the species of the EST sequence (ORGANISM), and the sequence. Length (SEQ_LEN), Sequence (SEQ), Sequence ID (ID), Name list (KNOWN) of the search database where the hit data (HIT) is present in the BLAST search, Sequence ID (REF_ID), PROSITE Search result (PATTERN), PRINTS search result (PRINTS), TRIM position (TRIMPOS), CONTIG (CONTIG), amino acid sequence (TRANS1) translated into the first frame (frame 1), second frame ( amino acid sequence (TRANS2) translated into frame 2), amino acid sequence (TRANS3) translated into third frame (frame 3), amino acid sequence translated into fourth frame (frame 4) (TRANS4), fifth frame (frame 5) ) Translated into amino acid sequence (TRANS5), amino acid sequence translated into frame 6 (TRANS6), EST Sca The amino acid sequence obtained by n (ESTSCAN), the ABI number (ABI_ID) of the corresponding EST CLONE providing linkage information with the ABI table 2211, and the presence or absence of a reversed position specific blast (RPS-BLAST) search result (RPS-BLAST) Contains information such as Here, RPS-BLAST is a type of BLAST search, and is a program for searching a protein domain part using protein profile information.

The BLAST management information table 2221 (hereinafter referred to as the HIT_BLAST table) and the sequence alignment management information table 2222 are included in the annotation database 222 that stores the sequence similarity search result and the protein domain search result for the EST sequence data. , Hereinafter referred to as ALIGN table), PROSITE management information table (2223, hereinafter referred to as PROSITE table), PRINTS management information table (2226, hereinafter referred to as PRINT table), and reference management information table (2227, hereinafter referred to as REFERENCE table). This includes.

The HIT_BLAST table 2221 stores BLAST search results (ie, similar EST sequence data) equal to or less than an E-value designated by the user. The ALIGN table 2222 stores individual high-scoring segment pair (HSP) information for each BLAST search result and sequence alignment result. Here, sequence alignment is a process in which two or more sequences are aligned in a straight line so as to create maximum identity in order to evaluate the degree of homology and the degree of similarity. Means.

The PROSITE table 2223 includes a pattern management information table 2224 (hereinafter referred to as a PATTERN table) and a MOTIF management information table 2225 (hereinafter referred to as a MOTIF table) to store protein domain regular expression search results. The PATTERN table 2224 stores the pattern information obtained as a result of the regular expression search, and the MOTIF table 2225 stores the motif site information obtained as a result of the regular expression search. The protein domain fingerprint result is stored in the PRINT table 2226. The REFERENCE table 2227 stores management information of a reference database in which data stored in the CLONE table 2212 is stored. Information stored in the HIT_BLAST table 2221 is shown in Table 3 below.

Column name Type name Length Nulls ACC_ID VARCHAR 50 NO DESCRIPTION TEXT YES ALIGN_NUM INT 10 YES DBNAME VARCHAR 20 YES PROGRAM VARCHAR 10 YES CLONE_ID VARCHAR 40 NO GI VARCHAR 250 YES GB VARCHAR 250 YES EMB VARCHAR 250 YES DBJ VARCHAR 250 YES PIR VARCHAR 250 YES PRF VARCHAR 250 YES SP VARCHAR 250 YES PDB VARCHAR 250 YES PAT VARCHAR 250 YES BBS VARCHAR 250 YES GNL VARCHAR 250 YES REF VARCHAR 250 YES LCL VARCHAR 250 YES TISSUE VARCHAR 15 YES ORGANISM VARCHAR 50 YES EVALUE DOUBLE YES HITRPS MEDIUMBLOB YES

Referring to [Table 3], the HIT_BLAST table 2221 includes a unique number (ACC_ID) of a BLAST HIT, a title (DESCRIPTION) of a BLAST HIT, a number of HSPs (ALIGN_NUM), a name of a database used for a BLAST search (DBNAME), Type of BLAST search program (PROGRAM), EST sequence ID (CLONE_ID), sequence unique number (GI) of the GenBank associated with BLAST HIT (GI; GenBank Identifier), GB sequence access number (GB; GenBank accession number), European sequence Unique number (EMB) of database (European Molecular Biology Laboratory (EMBL)), unique number (DBJ) of DNA Data Bank of Japan (DDBJ), unique number (PIR) of Protein Information Resource (PIR), PRF ( Protein Research Foundation's name, SWISS-PROT's unique number (SP), PDB (Brookhaven Protein Data Bank) unique number (PDB), sequence PAT (Patent) number (PAT), BBS (GenInfo Backbone) unique number (BBS), GNL (General database) unique number (GNL), document unique number (REF), LCL (Local Sequence) unique number (LCL ), Tissue name (TISSUE), species name (ORGANISM), E-value value (EVALUE) of BLAST HIT, and sorted information (HITRPS) obtained from reversed position specific BLAST (RPS-BLAST) search. Table 4 shows data stored in the ALIGN table 2222.

Column name Type name Length Nulls SUBJECT_LEN INT 10 YES EVALUE DOUBLE YES SCORE FLOAT YES QUERY_START INT 10 YES SUBJECT_START INT 10 YES FRAME ENUM NO IDENTITY INT 5 YES POSITIVE INT 5 YES NGAP INT 5 YES QUE Blob YES MAT Blob YES SBJ Blob YES HSP INT YES ACC_ID VARCHAR 50 YES ALIGN_ID VARCHAR 60 NO STRAND VARCHAR 20 YES

Referring to [Table 4], the ALIGN table 2222 includes the length of the BLAST HSP (SUBJECT_LEN), the E-value value (EVALUE) of the HSP ALIGNMENT, the SCORE value of the HSP ALIGNMENT (SCORE), and the starting position of the query (QUERY). QUERY_START), the starting position of the HSP ALIGNMENT (SUBJECT_START), the frame value (FRAME) of the BLASTx search result, the IDENTITY number of the HSP, the POSITIVE number of the HSP, the number of gaps of the HSP (NGAP), and the ALIGNMENT of the HSP. Query sequence of the part (QUE), ALIGNMENT MATCH content of the HSP (MAT), SUBJECT sequence of the ALIGNMENTed part of the HSP (SBJ), HSP length (HSP), BLAST HIT unique number (ACC_ID), BLAST ALIGNMENT unique number (ALIGN_ID) , ALIGNMENTSTRAND (STRAND) of the BLASTN result. Table 5 shows data stored in the PATTERN table 2224 which stores the pattern information obtained as a result of the protein domain regular expression search.

Column name Type name Length Nulls PATTERN_ID VARCHAR 60 NO NAME VARCHAR 50 YES DESCRIPTION TEXT YES MATCH_NO INT 5 YES SEQ_LEN INT 10 YES CLONE_ID VARCHAR 40 NO FULL MEDIUMTEXT YES

Referring to [Table 5], the PATTERN table 2224 includes a regular expression pattern unique number (PATTERN), a PROSITE name (NAME), a PROSITE detailed description (DESCRIPTION), the number of motifs included in the PROSITE pattern (MATCH_NO), and a searched protein. Sequence length (SEQ_LEN), EST sequence unique number (CLONE_ID), and full description (FULL) of the entire PROSITE pattern of the searched protein are included. Table 6 shows data stored in the MOTIF table 2225 for storing a plurality of motif information included in one regular expression search result.

Column name Type name Length Nulls MOTIF_ID VARCHAR 70 NO START_MATCH INT 10 YES END_MATCH INT 10 YES MOTIF_LEN INT 10 YES MOTIF_CON TINYTEXT YES PATTERN_ID VARCHAR 60 NO

Referring to [Table 6], the MOTIF table 2225 includes a motif unique number (MOTIF_ID), motif start position (START_MATCH), motif end position (END_MATCH), motif length (MOTIF_LEN), motif content (MOTIF_CON), and regular expression pattern. The unique number (PATTERN_ID) is stored. Table 7 shows data stored in the PRINTS table 2226 where the protein domain fingerprint results are stored.

Column name Type name Length Nulls PRINT_ID VARCHAR 60 NO PRINT_ACC VARCHAR 10 YES PRINT_NAME VARCHAR 50 YES PRINT_DESC VARCHAR 250 YES FULL MEDIUMTEXT YES CLONE_ID VARCHAR 40 NO

Referring to [Table 7], the PRINTS table 2226 includes a protein domain fingerprint identification number (PRINT_ID), a fingerprint access number (PRINT_ACC), a fingerprint name (PRINT_NAME), a detailed description of fingerprint classes (PRINT_DESC), and a finger. The full description of the print (FULL) and the EST sequence unique number (CLONE_ID) are stored.

In addition, the REFERENCE table 2227 includes a reference database 230 associated with the EST sequence database 221, an annotation database 222, and a management database 223 (eg, a unique number of a sequence-related document). REF_ID), gene title (TITLE, etc.) are stored.

Referring to FIG. 3, the management database 223 includes a project management information table (2231, hereinafter referred to as PROJECT table), a user management information table (2232, hereinafter referred to as USER table), and a history management information table (2233, hereinafter referred to as HISTORY). A table). The project management information is stored in the PROJECT table 2223, the project name PROJECTNAME is stored in the USER table 2232, and the user information and history information for each project are stored in the USER table 2232 and the HISTORY table 2233, respectively. Stored. The USER table 2232 stores a user ID USERID, a password for each user PASSWD, a project name PROJECTNAME, and database access permission information PERMISSION. In addition, the HISTORY table 2233 includes a name (DBNAME), a project name (PROJECTNAME), a data input (DBINPUT), a BLAST search (BLAST), a translation (TRANSLATION), and a PROSITE search (PROSITE). ), Whether to search for PRINTS (PRINTS), whether to search for RPS-BLAST (RPSBLAST), whether to generate a function category file (CATEGORY), and whether to generate a Remarkable hit file (REMARK). As described above, the EST analysis server 200 according to the present invention configures and manages a separate database for management for each project and management for each researcher in the project.

4 is a diagram illustrating a menu on a client interface for executing an EST sequence analysis program executed in the EST sequence analysis server 200 illustrated in FIG. 1, and submenus thereof. Referring to FIG. 4, the functions performed in the EST sequence analysis server 200 according to the present invention are largely divided into a sequence / protein annotation analysis function, a search function, an overall result viewing function, and a data management function.

In order to perform the annotation analysis function, first, an EST sequence database 221 in which EST sequence data is stored is generated, and sequence data obtained by sequencing is input. Details on performing annotation analysis are as follows.

5 is a diagram illustrating a database creation screen executed when the database creation menu illustrated in FIG. 4 is selected, and FIG. 6 is a data input screen executed when the data input menu illustrated in FIG. 4 is selected. Referring to FIG. 5, when a user inputs a desired name on the database creation screen, an EST sequence database 221 having a name designated by the user is generated. When the EST sequence database 221 is created, the user selects a database into which data is to be input from among a plurality of EST sequence databases already generated, and inputs an ABI file or a FASTA file into the selected database, as shown in FIG. 6. Done. When an ABI file or a FASTA file is input from the user, the sequence input unit 250 provided in the EST analyzer 210 converts the file into a predetermined format and stores the file in the EST sequence database 221.

Referring back to FIG. 4, the EST sequence analysis server 200 according to the present invention takes sequences stored in the EST sequence database 221 one by one, performs sequence similarity (BLAST) search and translation, and searches for a protein domain regular expression ( PROSITE), protein domain fingerprint search (PRINTS), and protein domain profile search (RPS-BLAST). Such EST sequence analysis and protein domain analysis are organized by analysis module so that the user can selectively perform the desired analysis. Details of this are as follows.

FIG. 7 is a diagram illustrating a BLAST search screen executed when the BLAST search menu illustrated in FIG. 4 is selected, and FIGS. 8 and 9 illustrate a BLAST search result performed by FIG. 7 and an alignment result thereof. Each figure shows. 7 to 9, when the user selects the EST sequence database 221 to be used for the search, the type of BLAST search database and the E-value on the screen of FIG. 7, the EST sequence analysis server 200 determines the BLAST database. A BLAST search using 231 is performed to obtain a BLAST search result as shown in FIGS. 8 and 9. Here, FIG. 8 is a search result in which the E-values are sorted in ascending order, and shows the matched place graphically. At this time, when the user clicks on arbitrary data, detailed information about the corresponding data is retrieved and shown as shown in FIG. 9.

FIG. 10 is a diagram illustrating a translation result performed when the translation menu illustrated in FIG. 4 is selected. The sequence data input by the user is translated into a predetermined format as shown in FIG. 10, and each of the translated data is analyzed by the protein domain search as follows.

11 and 12 are diagrams showing the results of a PROSITE search performed when the PROSITE menu shown in FIG. 4 is selected and detailed information thereof, and FIG. 13 is a PRINTS performed when the PRINTS menu shown in FIG. 4 is selected. A diagram showing the results of a search. Referring to FIG. 11, when the PROSITE menu is selected in FIG. 4, a protein domain regular expression search is performed on data identified as similar genes, thereby obtaining a result as illustrated in FIG. 11. The results of the PROSITE search may be displayed per translation frame of the EST sequence, or may be graphically depicted for domain match sites. As a result, the function of the new protein sequence can be predicted through the PROSITE search. Subsequently, when the PRINTS menu is selected in FIG. 4, the protein domain fingerprint search is performed on the data found to be similar genes. As shown in FIG. 13, the PRINTS search results for the translation frame are listed by class. Given. At this time, when the user clicks on any data obtained as a result of the search, detailed information about the data is retrieved and displayed.

FIG. 14 is a view showing an RPS-BLAST search screen performed when the RPS-BLAST menu shown in FIG. 4 is selected, and FIGS. 15 and 16 show an RPS-BLAST search result performed by FIG. 14 and its alignment ( alignment) results respectively. RPS-BLAST search results are shown by the translation frame of the EST sequence, the protein domain profile can be searched by this RPS-BLAST search.

After both the sequence similarity search and the protein domain search for the EST sequence described above are performed, the EST analysis server 200 based on the sequence similarity search result and the protein domain search result for any EST sequence, and thus, the EST sequence. The EST sequence of the reference database 230 is determined. As a result of the determination, when the EST sequence is identified, necessary information is analyzed in the gene contents of the reference database 230 corresponding to the EST sequence, and the information is stored in the annotation database 222 of the EST sequence and the analysis result database 220. A summary of the annotation analysis function performed by the EST analysis server 200 shown in FIG. 4 is as follows.

17 is a flow chart showing a method for constructing an EST sequence analysis and annotation database 222 in accordance with a preferred embodiment of the present invention. Referring to FIG. 17, the construction of the EST sequence analysis and annotation database 222 according to the present invention is largely performed by sequence similarity search and protein domain search.

In order to construct the annotation database 222 through the sequence similarity search, the EST sequence database 221 is constructed by first generating the EST sequence database 221 and inputting sequence data obtained by the sequencing method (step 2500). Subsequently, the sequences stored in the EST sequence database 221 are taken one by one, and then sequence similarity search (BLAST) is performed using the reference database 230 (step 2600). Then, based on the sequence similarity search result for any gene sequence, it is determined whether the EST sequence is identified with the gene sequence stored in the reference database 230 (step 2900). As a result of the determination in step 2900, if the EST sequence is identified with the gene sequence stored in the reference database 230, after analyzing the sequence similarity search result identified with the EST sequence (step 3100), the analysis result is annotated database Stored at 222.

In order to construct the annotation database 222 through protein domain search, first, after the sequences stored in the EST sequence database 221 are translated, the translation result is stored in the EST sequence database 221 (step 2700). . After the translation is performed in step 2700, the protein domain search is performed (step 2710). The protein domain search is largely performed by the protein domain regular expression search (PROSITE, step 2720), the protein domain fingerprint search (PRINTS, step 2730), and the protein domain. Profile search (RPS-BLAST, step 2740).

After the protein domain search is performed in step 2710, it is determined whether the corresponding EST sequence is identified with the protein domain sequence stored in the reference database 230 based on the result of the protein domain search performed (step 3000). As a result of the determination in step 3000, if the EST sequence has been identified, the protein domain sequence search result identified with the EST sequence is analyzed (step 3100), and the result is stored in the annotation database 222 (step 3300).

The EST sequence database 221 and the annotation database 222 constructed by such a method are characterized by showing the user by using the information when retrieving the EST sequence data and providing a web link for detailed information. The search using these databases 221 and 222 is as follows.

Referring back to FIG. 4, the EST analysis client 100 according to the present invention performs an ID search menu and a keyword to perform a multi-faceted search on the EST sequence and analysis result database 220 provided by the EST analysis server 200. A search menu, a function category keyword search menu, and a Remarkable Hit search menu.

18 to 23 are diagrams illustrating a search screen and a search result of the EST sequence database 221 and the annotation database 222 performed for each search menu shown in FIG. 4. First, FIGS. 18 and 19 show an annotation data search screen executed when the annotation data search menu, which is a submenu of the ID search menu shown in FIG. 4, is selected and the search results thereof are respectively shown. In FIG. 18, when a user selects a database to be searched and inputs an ID of an EST sequence to be searched, more detailed sequence information including a sequence similarity search result is searched and shown as shown in FIG. 19.

20 and 21 are diagrams illustrating a keyword search screen executed when the keyword search menu shown in FIG. 4 is selected, and a search result thereof. In FIG. 20, when a user selects a database to be searched and inputs a keyword such as a gene title and an E-value, as shown in FIG. 21, unique IDs and gene titles of similar genes based on the corresponding EST sequence ID are shown. Is searched and shown. At this time, if you click the unique ID of the gene, you can see the sequence information for the gene.

22 and 23 are diagrams illustrating a function category keyword search screen executed when the function category keyword search menu shown in FIG. 4 is selected, and a search result thereof. In FIG. 22, when a user selects a database to be searched and performs a search, as shown in FIG. 23, genes are searched and displayed for each functional category. The function category keyword search is one of the advanced search functions, and the gene information for each function is extracted by searching a category to which the gene belongs.

FIG. 24 is a diagram illustrating a Remarkable Hit search screen executed when the Remarkable Hit search menu shown in FIG. 4 is selected. Referring to FIG. 25, the remarkable hit search function is a function of searching and showing only the top result of the searched results, and belongs to the advanced search function together with the function category keyword search shown in FIG. 4.

As described above, the EST analysis server 200 according to the present invention performs analysis data search in various ways according to the search method selected by the user, and the EST analysis client 100 displays the search results performed by various methods on the screen. Is shown in. To this end, the EST analysis client 100 according to the present invention provides various overall result view menus such as a hit list view and a history map view.

FIG. 25 illustrates a hit list screen executed when the hit list search menu illustrated in FIG. 4 is selected. Referring to FIG. 25, the search results for the EST are shown in a tabular hit list. Here, the horizontal axis of the hit list indicates the type of the reference database, and the vertical axis of the hit list indicates the EST sequence ID, respectively. Each search result is indicated by a check mark depending on whether or not the database for which the search has been performed.

FIG. 26 illustrates a history map screen executed when the history map menu illustrated in FIG. 4 is selected. Referring to FIG. 26, the history map function is a function of displaying all analysis processes as one map and differentiating the completed analysis process. The analysis progress status of the entire EST sequence is displayed for each sequence database input by the user. The completion of the search is represented by different colors (for example, blue) displayed on the screen. This is a drawing generated using the performance information stored in the history table of the management database 223 after each analysis is completed, the user can check the status of the EST analysis already performed through this function, and determine whether to continue the analysis You can do it. The search function and the result viewing function of the EST analysis server 200 according to the present invention as described above are as follows.

27 is a flowchart showing a sequence retrieval method according to a preferred embodiment of the present invention. Referring to Figure 27, the sequence search method according to the present invention first selects a search method (step 2810). The sequence search method divided by step 2810 is largely divided into general search and advanced search. General search is divided into ID search and keyword search, and advanced search is divided into Remarkable Hit search and function category keyword search.

For example, when ID or keyword search is selected as a search method in step 2810, first, a gene ID or keyword search term to be used for search is input from the user (step 2820). The EST sequence and annotation data are retrieved from the EST sequence database 221 and the annotation database 222 (step 2830) in response to the search word input in operation 2820, and detailed information about the gene corresponding to the retrieved EST sequence data is obtained. Protein domain information is extracted (step 2840). The information extracted by this process is shown as a search result to the client 100 (step 2880).

If advanced search is selected as the search method in step 2810, the advanced search is further classified into a remarkable hit search and a function category keyword search (step 2850). If the Remarkable Hit search function is selected in step 2850, the search results of the highest level are extracted from the annotation database 222 to generate a Remarkable Hit file (step 2860). The Remarkable Hit file generated in step 2860 is shown to the client 100 as an advanced search result (step 2880). If a function category keyword search is selected in step 2850, a search for each function category is performed from the annotation database 222 (step 2870). The searched data in step 2870 is shown to the client 100 as an advanced search result (step 2880).

As described above, the EST sequence analysis system 200 according to the present invention is an EST sequence through EST sequence similarity search, protein domain regular expression search, domain fingerprint search, and domain profile search using a biological species and tissue-specific reference gene database. And it is possible to establish the analysis result database, extract detailed information of similar genes and predict domain related gene function through multiple search of the constructed EST sequence and analysis result database.

In the above, as an embodiment of the present invention, a client / server based EST sequence analysis system capable of EST sequence analysis and retrieval through UniGene, StackDB, RefSeq, and TIGR databases having gene sequence information and gene function information is specifically described. Although illustrated, various other reference gene and protein domain databases can be applied to the present invention, and the present invention can be applied both online and offline.

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 client / server-based EST analysis system according to the present invention, the database for the mass production of EST sequence results, the comparison of information in the existing database, and the storage and retrieval function of the search results can be efficiently Can be integrated. Therefore, the database of experimental EST data and the analysis of EST sequence search results can be easily performed by integrated analysis solutions, and the integrated results can be comprehensively extracted and analyzed through one interface.

Claims (27)

An input / output manager that receives an EST (Expressed Sequence Tag) sequence data calculated by an experiment from a user; A sequence input unit which converts the EST sequence data into a predetermined format and stores it in a first database; Perform a similarity search and a protein domain search between the EST sequence data stored in the first database and the sequence data stored in a second database in which verified large amounts of gene and protein sequence data are stored, and the search results are stored in the first database. An annotation analysis unit for storing; And And an analysis result search unit configured to perform a search on data stored in the first database in response to a search clue input from a user. The method of claim 1, The input / output manager receives project and user management information, the EST sequence information, and the search clue from at least one client connected through a network, and provides the search result performed by the analysis result search unit to the client through the network. EST sequence analysis system. The method of claim 2, wherein the first database is An EST sequence database for storing the EST sequence data input from a user; An annotation database for storing the similarity search and the domain search results performed by the annotation analyzer; And And a management database for storing the project management information and the user management information related to the EST analysis. The method of claim 1, wherein the second database is A BLAST database for performing the similarity search; And EST sequence analysis system comprising a domain search database for performing the protein domain search. The method of claim 4, wherein the domain search database is A first domain search database for performing a protein domain regular expression search for the EST sequence; A second domain search database for performing a protein domain fingerprint pattern search for the EST sequence; And And a third domain search database for performing a protein profile search for said EST sequence. The method of claim 1, And the EST sequence data input through the input / output manager comprises an ABI format file and a FASTA format file. The method according to claim 3 or 6, wherein The sequence input unit reads the ABI file, converts the sequence into a sequence, converts the converted sequence or the FASTA sequence into a predetermined data format, and stores the converted sequence information in the EST sequence database, and stores the project management information and the user management information. EST sequence analysis system, characterized in that stored in the management database. The method of claim 4, wherein the annotation analysis unit Performing a BLAST search on the EST sequence data using the BLAST database to identify which gene sequence is similar to that stored in the BLAST database, and storing the identified results in the annotation database; Annotation analyzer; And A second annotation analyzer configured to perform a protein domain regular expression search, a protein domain fingerprint pattern search, and a protein profile search for the EST sequence data using the domain search database, and store the search results in the annotation database; EST sequence analysis system, characterized in that. The method of claim 1, In response to the search clue input from the user, the analysis result search unit performs one of a general search including an ID search and a keyword search, and an advanced search including a function category keyword search and a Remarkable Hit search. EST sequence analysis system characterized in that the display of the search results in either of the form of hit list and history map. The method of claim 9, The Remarkable Hit search EST sequence analysis method characterized in that for extracting the top result from the general search results. The method of claim 9, The history map is EST sequence analysis system, characterized in that indicating the progress of the analysis of the entire EST sequence. (a) accepting Expressed Sequence Tag (EST) sequence data produced by an experiment from a user; (b) converting the EST sequence data into a predetermined format and storing it in a first database; (c) perform a similarity search and a protein domain search between the EST sequence data stored in the first database and data stored in a second database in which verified large amounts of gene and protein sequence data are stored; Storing in a database; And and (d) performing a search for data stored in the first database in response to a search clue input from a user. The method of claim 12, In step (a), the project and user management information, the EST sequence information and the search clue from the at least one client connected via a network, EST sequence analysis method. The method of claim 13, wherein the first database is An EST sequence database for storing the EST sequence data input from a user; An annotation database for storing the similarity search and the domain search results performed by the annotation analyzer; And And a management database for storing the project management information and the user management information related to the EST analysis. The method of claim 12, wherein the second database is A BLAST database for performing the similarity search; And EST sequence analysis method comprising a domain search database for performing the protein domain search. 16. The system of claim 15, wherein the domain search database is A first domain search database for performing a protein domain regular expression search for the EST sequence; A second domain search database for performing a protein domain fingerprint pattern search for the EST sequence; And EST sequence analysis method comprising a third domain search database for performing a protein profile search for the EST sequence. The method of claim 12, The EST sequence data input in the step (a), EST sequence analysis method characterized in that it comprises an ABI format file and FASTA format file. The method according to claim 14 or 17, In step (a), the ABI file is read and converted into a sequence, and the converted sequence or the FASTA sequence is converted into a predetermined data format and stored in the EST sequence database. The method of claim 14, The step (a) of the EST sequence analysis method further comprises the step of storing the project management information and the user management information in the management database. The method of claim 15, wherein step (c) (c-1) performing a BLAST search on the EST sequence data using the BLAST database to determine which gene sequence is similar to the EST sequence stored in the BLAST database, and the result of the identification to the annotation database Storing in; And (c-2) performing a protein domain regular expression search, a protein domain fingerprint pattern search, and a protein profile search on the EST sequence data using the domain search database, and storing the search results in the annotation database; EST sequence analysis method comprising the. The method of claim 12, wherein step (d) (d-1) selecting whether to perform a general search or an advanced search on the data stored in the first database; (d-2) when a general search is selected in the step (d-1), performing one of an ID search and a keyword search in response to the search clue input from a user; (d-3) when the advanced search is selected in the step (d-1), performing one of a function category keyword search and a remarkable hit search in response to the search clue input from the user; And (d-4) EST sequence analysis method comprising the step of displaying the search results performed in the step (d-2) or (d-3) in the form of a hit list and history map form . The method of claim 21, The Remarkable Hit search EST sequence analysis method characterized in that for extracting the most significant result from the search results performed in step (d-2). The method of claim 21, The history map is EST sequence analysis method characterized in that the analysis of the progress of the entire EST sequence. (a) receiving an EST sequence data generated by an experiment from a user and constructing a first database; (b) performing a similarity search between the EST sequence data stored in the first database and data stored in a second database in which verified large amounts of gene and protein sequence data are stored and a protein domain search for the EST sequence; (c) determining whether the EST sequence is identified with any gene sequence stored in the second database based on the sequence similarity search result and the protein domain search result performed in step (b). ; (d) analyzing the necessary information in the gene contents of the second database corresponding to the EST sequence when the EST sequence is identified, and storing the analysis result in the first database; And (e) storing whether the steps (a) and (b) are performed in a history table of the first database. The method of claim 24, wherein step (b) comprises: (b-1) performing a protein domain regular expression search on the EST sequence; (b-2) performing a protein domain fingerprint search on the EST sequence; And (b-3) EST sequence analysis and database construction method comprising the step of performing a protein domain profile search for the EST sequence. (a) In response to a search clue input from a user, one of an ID search and a keyword-specific search is performed on the first database in which the EST sequence analysis result is stored, and the genetic information and protein domain information corresponding to the retrieved EST sequence data are performed. Extracting; (b) selecting one of the Remarkable Hit function and the function category keyword search function by an advanced search method; (c) extracting and displaying a top result from the results extracted in step (a) when the remarkable hit function is selected as the advanced search method in step (b); And (d) If the function category keyword search function is selected as the advanced search function in step (b), perform a function-specific search for the category to which the result extracted in step (a) belongs, and display the search result. EST sequence search method comprising the step of. A computer-readable recording medium having recorded thereon a program for executing the method of any one of claims 12 to 26 on a computer.